HK1154405A - Methods of diagnosing and treating parp-mediated diseases - Google Patents

Description

Methods of diagnosing and treating PARP-mediated diseases

Cross Reference to Related Applications

The present application claims priority of U.S. provisional application 61/026,077, entitled "method of diagnosing and treating PARP-mediated diseases," filed on 4.2.2008, which is incorporated herein by reference in its entirety.

Background

The etiology of cancer and other diseases involves complex interactions between cytokines, including receptors for cellular enzymes and other downstream intracellular factors that signal through intracellular signaling networks. Growth factor receptors are thought to be important factors in cancer physiology, playing an important role in the progression and maintenance of the malignant phenotype (Jones et al, 2006, Endocrine-Rel. cancer, 13: S45-S51). For example, expression of Epidermal Growth Factor Receptor (EGFR), a tyrosine kinase receptor, has been shown to be essential in the formation of adenomas and tumors in intestinal tumors, as well as in the subsequent expansion of primary tumors (Roberts et al, 2002, PNAS, 99: 1521-. Overexpression of EGFR also plays a role in neoplasia, particularly in tumors of epithelial origin (Kari et al, 2003, Cancer Res., 63: 1-5). EGFR is a member of the ErbB family of receptors, which includes HER2c/neu, HER2, and HER3 receptor tyrosine kinases. The molecular signaling pathway of EGFR activation has been mapped experimentally and in silico, involving interactions of over 200 reactions and 300 chemicals (see Oda et al, Epub 2005, mol.sys.biol., 1: 2005.0010).

Another key cellular pathway, which is overexpressed by tumors, including regulation of cancer cell proliferation, is the insulin-like growth factor (IGF) signaling pathway (Khandwala et al, 2000, endo. Rev., 21: 215-) -244; Moschos and Mantzoros, 2002, Oncology 63: 317-. This signaling involves the action of two ligands, IGF1 and IGF2, three cell surface receptors, at least six high affinity binding proteins and a binding protein protease (Basearga et al, 2006, Endocrine-rel. cancer, 13: S33-S43; Pollak et al, 2004, Nature rev. cancer 4: 505-. Insulin-like growth factor receptor (IGF1R) is a transmembrane receptor tyrosine kinase that regulates IGF bioactivity and signaling through several key cellular molecular networks, including RAS0RAF-ERK and PI3-AKT-mTOR pathways. Functionalized IGF1R is required for conversion and has been shown to promote tumor cell growth and survival (Riedemann and macaula, 2006, endocr. Several genes that have been shown to promote cell proliferation in the IGF1R pathway in response to IGF-1/IGF-2 binding include Shc, IRS, Grb2, SOS, Ras, Raf, MEK and ERK. Genes involved in the cell proliferation, viability and survival functions of IGF1R signaling include IRS, PI3-K, PIP2, PTEN, PTP-2, PDK and Akt.

IGF signaling, the signaling interaction between IGF1 receptor and EGFR, is important in the modulation of EGFR-mediated-pathways, and can contribute to resistance to EGFR antagonist therapy (Jones et al, 2006, Endocrine-rel. cancer, 13: S45-S51).

Another pathway important in the control of proliferation and cell growth and development includes the Ets family of transcription factors. Ets family domain proteins (defined based on the conserved essential sequence of their DNA-binding domain) have functions as transcriptional activators or repressors, and their activity is often regulated by signal transduction pathways, including the MAP kinase pathway (Sharrocks, et al, 1997, int.j. biochem. cell biol.29: 1371-1387). ETS transcription factors (such as ETS1) regulate many genes and are involved in stem cell development, cell aging and death, and tumorigenesis. The conserved ETS domain within these proteins is a winged helix-turn-helix DNA-binding domain that recognizes the core consensus DNA sequence GGAA/T of the target gene (Dwyer et al, 2007, Ann. New York Acad. Sci. 1114: 36-47). There is increasing evidence that Ets1 proteins have oncogenic potential due to their key role in obtaining invasive behavior of oncogenic cells. Genes belonging to the Ets1 pathway for their oncogenic function include the interstitial metalloproteinases MMP-1, MMP-3, MMP-9, and urokinase-type plasminogen activator (uPA) (Sementchenko and Watson, 2000, Oncogne, 19: 6533-. These proteases are known to be involved in extracellular matrix (ECM) degradation, a key event in invasion. In angiosarcoma of the skin, Ets1 is co-expressed with MMP-1 (Naito et al, 2000, Pathol. Res. practice.196: 103-109). Ovarian cancer cells and mediator fibroblasts in breast and ovarian cancer produce MMP-1 and MMP-9 with Ets1 (Behrens et al, 2001, J.Pathol.194: 43-50; Behrens et al, 2001, int.J.mol.Med.8: 149-. In lung and brain tumors, Ets expression correlates with uPA expression (Kitage et al, 1999, Lab. Invest.79: 407-416; Takanami et al, 2001, Tumour biol.22: 205-210; Nakada et al, 1999, J.Neurophothol.exp.Neurol.58: 329-334). Ets1 was shown to induce the production of MMP-1, MMP-3 plus MMP-9, or MMP-1, MMP-9 plus uPA, respectively, when overexpressed in endothelial or hepatoma cells (Oda et al, 1999, J.cell physiol.178: 121-132; Sato et al, 2000, adv.exp.Med.biol.476: 109-115; Jiang et al, 2001, biochem.Biophys.Res.Commun.286: 1123-1130). The regulation of MMP1, MMP3, MMP9, and uPA, as well as VEGF and VEGF receptor gene expression have been attributed to Ets 1. Furthermore, Ets1 expression in tumors is indicative of a poor clinical prognosis. Table I summarizes the expression pattern of Ets1 in tumors.

Table I: ets 1 expression in different types of tumors

TMD ═ tumor microvascular density; LNM ═ lymph node metastasis; DCIS ═ ductal carcinoma in situ; LCIS ═ in situ lobular carcinoma (Ditmmer, 2003, mol. cancer 2: 29)

poly-ADP-ribose polymerase (PARP1) has been designated as a recognized downstream signaling molecule for EGFR activation or interference. EGFR stimulates PARP activation (through its signaling cascade pathway) leading to downstream cellular activity mediated through the PARP pathway (Hagan et al, 2007, j.cell. biochem., 101: 1384-. PARP1 signaling remains a variety of DNA-related functions including cell proliferation, differentiation, apoptosis, and DNA repair, and also affects telomere length and chromosome stability (d' Adda di Fagagna et al, 1999, Nature Gen., 23 (1): 76-80). PARP has been shown to be involved in maintaining genomic integrity-in asynchronous programsInhibition or deletion of PARP in PARP-/-mice compared to wild type siblings increases genomic instability in cell-to-cell expression of primary fibroblasts (Simbulan-Rosenthal et al, PNAS, 97 (21): 11274-11279(2000)) in divided oligonucleotide biochip assays. PARP deficient mice have also been shown to be protected from septic shock, type I diabetes, stroke and inflammation. It has been shown that direct protein-protein interaction between PARP-1 and two subunits of NF-. kappa.B requires its co-activator function (Hassa et al, J.biol.chem., 276 (49): 45588-45597 (2001)). Oxidative stress-induced transient activation of PARP1 consumes NAD + and eventually ATP, culminating in cellular dysfunction or necrosis. Vimentin expression in lung cancer cells has been shown to be regulated at the transcriptional level; PARP-1 binds to and activates the vimentin promoter (independent of its catalytic region) and is present in H ₂O₂-inhibition of induced vimentin expression. (Chu et al, am.J.Physiol.Lung cell.mol.Physiol., 293: L1127-L1134 (2007)).

The pathological mechanisms of cancer, stroke, myocardial ischemia, diabetes-related cardiovascular dysfunction, shock, traumatic central nervous system injury, arthritis, colitis, allergic encephalomyelitis and various other forms of inflammation involve this mechanism of cellular suicide through PARP activation. PARP1 has also been shown to be associated with and regulate the function of several transcription factors. The multiple functions of the PARP1 pathway make it a target for a variety of serious conditions, including various types of cancer and neurodegenerative diseases.

As can be seen, there are many molecular targets for cancer therapy that, when perturbed, can inhibit the growth or proliferation of cancerous tissue. Treatment of cancerous states may involve treatment that targets the above-mentioned molecular Cancer targets (e.g., EGFR), as well as traditional chemotherapy or other Cancer treatment approaches (Rocha-Lima et al, 2007, Cancer Control, 14: 295-. EGFR overexpression has been implicated in colorectal, pancreatic, glioma, small cell lung and other carcinomas (Karamouzis et al) Human, 2007, JAMA 298: 70-82; toschi et al, 2007, Oncologist, 12: 211-220; sequist et al, 2007, Oncologist, 12: 325-; hatake et al, 2007, Breast Cancer, 14: 132-149). Cetuximab, panitumumab, matuzumab, MDX-446, nimotuzumab, mAb 806, erbitux (IMC-C2225),(ZD1839), erlotinib, gefitinib, EKB-569, lapatinib (GW572016), PKI-166 and kalatinib are some EGFR inhibitors that have been used in clinical settings (Rocha-Lima et al, 2007, Cancer Control, 14: 295-. EGFR inhibitors have been tested alone, as well as in combination with chemotherapeutic agents.

However, studies to date have not successfully delineated the interaction of different known molecular pathways in cancer formation. Furthermore, despite the substantial resources devoted to monotherapy and other combination therapies directed to a large number of cancer targets, the incidence of resistance to these therapies and their prevention has not been fully investigated. For example, although EGFR inhibitors have shown efficacy in treating cancer patients, only a small fraction of patients have proven to be fully responsive to EGFR inhibitor treatment (Hutcheson et al, 2006, Endocrine-rel. cancer, 13: S89-S97). In contrast, a large number of patients have shown neogenetic or acquired resistance to EGFR inhibitors in recent studies. This resistance to anti-EGFR therapy is unknown, but may originate from the complex cellular signaling cascade of EGFR, including the mutual modulation of co-signaling between other surface receptors, such as IGR 1-receptor therapy (Jones et al, 2006, Endocrine-rel. cancer, 13: S45-S51). Therapeutic regimens that reduce resistance to currently available cancer therapies (e.g., chemotherapeutic drugs or chemotoxic drugs), or that reduce resistance to other targets, are needed as potential new therapeutic regimens.

In addition, cancer detection, prognosis and classification are changing with the current early detection strategies (when they are highly treatable). However, such screening procedures are not available for all cancers, including breast cancer. More effective and powerful strategies for early diagnosis of cancer would be of great benefit for prevention and more effective treatment of cancer. The screening step may also provide the attending physician with expression information, which may be advantageous for effective treatment of cancer patients.

Summary of The Invention

In one aspect, provided herein is a method of identifying a disease or disease state in a patient treatable by a combination of at least one PARP modulator and at least one modulator of a co-regulated gene (e.g., a differentially co-expressed gene), by measuring PARP expression and other gene levels in the patient, and if the PARP and at least one other gene levels are differentially expressed in the patient, treating the patient with a modulator of PARP and other differentially expressed genes.

In one embodiment, the commonly regulated expressed gene may be IGF1R, IGF2, or IGF 1. In another embodiment, the co-regulated gene of expression may be EGFR. In another embodiment, the co-regulated expression gene may be IGF1, IGF2, IGF1R, EGFR, mdm2, or Bcl 2. In some embodiments, the at least one co-regulated gene of expression may be selected from IGF1, IGF2, IGFR, EGFR, mdm2, Bcl2, ETS1, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK1, VAV3, AURKA, ERBB3, MIF, VEGF, VEGFR2, CDK1, CDK2, CDK9, farnesyl transferase (farnesyl transferase), UBE2A, UBE2D2, UBE2G1, USP28, or UBE 2S. In another embodiment, the at least one co-regulated gene may be selected from the group consisting of IGF, IGFR, EGFR, mdm, Bcl, ETS, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK, VAV, AURKA, ERBB, MIF, VEGFR, VEGF, UBE2, ABCC, ABCD, ACADM, ACLSL, ACY1L, ADM, ADRM, AGPAT, AHCY, AK3L, AKIIP, AKR1B, AKR1C, ALDH18A, ALDOA, ALOX, ALPL, ANP32, BGF, APG5, FGAREF, ARL, ARPP-19, PH, ATF7, ATIC, ATP11, ACAT 11, ATP, ACAT 1A, ATP, ACAT 5, CDC, CDP, CDC, CDSC, ATP, CDSC, ACAT, ACSL, ACAD 1L, ACSR 3L, ACAD 5, ACAD, CDBC, CDSC, ACAT, BC5, CDK, ACSL, ACSR 3L, CKLFSF6, CKS1B, CMKOR1, CNDP2, CPD, CPE, CPSF3, CPSF5, CPSF6, CPT1B, CRR B, CSH B, CSK, CSNK2A B, CSPG B, CTPSCTSB, CTSD, CXADR, CXCR B, CX B, CXSF B, CX B, DAAM B, DCK, DD3672, DDIT B, DDR B, DDX B, DHTKD B, DLAT, DNAFAD B, DNAJB B, DNAJC 36JC B, DNAJD B, DUSP B, DVL B, HSPOVL B, HSP B, HSP B, HSP B, HSP B, HSP B, HSP B, 36, MAGED1, MAK 1, MALAT1, MAP2K 1, MAP3K1, MAP4K 1, MAPK1, MARCKS, MBTPS 1, MCM 1, MCTS1, MDH1, ME1, METAP 1, METTL 1, MGAT 41, MKNK 1, MLPH, MOBK 11, MOBKL 11, MSH 1, MTHFD 1, MUC1, MX1, CBCP 1, NAJD1, NAT1, NBS1, NDFIP 1, RFC 1, NET1, NME QOPP 1, NPNNN 1, NRAS, NSE 1, PSNFCKS, PGN-1, NY-1, PSPMPAP 1, PSMP-PSNPPEPCP 1, PSNPPHP 1, PSP 1, PSNPPHP 1, PSNPPDN 1, PSNP 72, PSNPPDN 1, PSNP 72, PSPEPTCP 1, PSNP 1, PSNPPDN 1, PSNP 72, PSNP 1, PSNPPHP 1, PSPEPTCP 1, PSNP 1, PSP, RRAS, SART, SAT, SCAP, SCD, SDC, SEMA3, SERPINE, SFI, SGPL, SGPP, SH3GLB, SHC, SMARCC, SMC4L, SMS, SNRPD, SORD, SORL, SPP, SQLE, SRD5A2, SRM, SRPK, SS, SSBP, SSR, ST3GAL, ST6 GALNC, STX, SULF, SWAP, TA-KRP, TALA, TBL1XR, TFRC, TIAM, TKT, TMPO, TNFAIP, TNFSF, TOX, TPD, TPI, TPP, TRA, TRIP, TRPS, TXP, TSTA, TXN, TXNL, TXNRD, UBAP2, UBE2D, UBE2V, WHV, UGC, USP, YAB, USP, YNAP, SRPA, SRPP, SRPL, SRP, SRPA, SRK, SRP, SRN, SRK, TK, TXNL, TK, TXOL.

In one aspect, provided herein is a method of identifying a disease in a patient that is treatable by a PARP inhibitor in combination with an inhibitor or activator of at least one co-regulated expressed gene, by measuring the level of PARP and other co-regulated expressed genes in the patient, and further providing treatment of the patient using the PARP inhibitor itself in combination with an inhibitor of one or more other co-regulated expressed genes if the level of PARP and/or other co-regulated expressed genes in the patient is up-regulated.

One aspect relates to a method of identifying a disease or condition treatable by PARP and a modulator of other co-regulated expressed genes comprising identifying the level of co-regulated expressed genes (including PARP) and making a decision in a patient sample regarding identifying a disease treatable by a modulator of co-regulated expressed genes (including at least PARP), wherein the decision is made based on the expression level of said co-regulated expressed genes (including at least PARP). In some embodiments, the level of the co-regulated expressed gene (including at least PARP) is up-regulated.

In some embodiments, the disease is selected from the group consisting of cancer, inflammation, metabolic disease, CVS disease, CNS disease, lymphohematopoietic disease, endocrine and neuroendocrine disease, urinary tract disease, respiratory disease, female reproductive disease, and male reproductive disease. In some embodiments, the cancer is selected from colon adenocarcinoma, esophageal adenocarcinoma, and hepatocellular carcinoma (liver hepatocellular carcinoma), squamous cell carcinoma, pancreatic adenocarcinoma, islet cell tumor, rectal adenocarcinoma, gastrointestinal stromal tumor, gastric adenocarcinoma, adrenal cortical cell carcinoma, follicular carcinoma, papillary carcinoma, breast cancer, ductal carcinoma, lobular carcinoma, intraductal carcinoma, mucinous carcinoma, phyllodes tumor, ovarian adenocarcinoma, endometrial adenocarcinoma, granulosa cell tumor, mucinous cystadenocarcinoma, cervical adenocarcinoma, vulval squamous cell carcinoma, basal cell carcinoma, prostate adenocarcinoma, giant cell tumor of bone, osteosarcoma (bone ostearcoma), larynx carcinoma, lung adenocarcinoma, kidney carcinoma, bladder carcinoma, wilms' tumor, and lymphoma.

In some embodiments, the inflammation is selected from wegener's granulomatosis, hashimoto's thyroiditis, hepatocellular carcinoma, chronic pancreatitis, rheumatoid arthritis, reactive lymphoid hyperplasia, osteoarthritis, ulcerative colitis, and papillary carcinoma. In other embodiments, the metabolic disease is diabetes or obesity. In other embodiments, the CVS disease is selected from the group consisting of atherosclerosis, coronary artery disease, granulomatous myocarditis, chronic myocarditis, myocardial infarction, and primary hypertrophic cardiomyopathy. In some embodiments, the CNS disease is selected from alzheimer's disease, cocaine abuse, schizophrenia, and parkinson's disease. In some embodiments, the lymphohematopoietic disease is selected from the group consisting of non-hodgkin's lymphoma, chronic lymphocytic leukemia, and reactive lymphoid hyperplasia.

In some embodiments, the endocrine and neuroendocrine disease is selected from nodular hyperplasia, hashimoto's thyroiditis, islet cell tumor of pancreas, and papillary carcinoma. In some embodiments, the urinary tract disease is selected from renal cell carcinoma, transitional cell carcinoma, and wilms' tumor. In some embodiments, the respiratory disease is selected from the group consisting of adenocarcinoma, adenosquamous carcinoma, squamous cell carcinoma, and large cell carcinoma. In some embodiments, the female reproductive system disorder is selected from adenocarcinoma, leiomyoma, mucinous cystadenocarcinoma, and serous cystadenocarcinoma. In some embodiments, the male reproductive system disease is selected from prostate cancer, benign nodular hyperplasia, and seminoma.

In some embodiments, the identification of the level of genes (including at least PARP) that are co-regulated in expression includes testing techniques. In some embodiments, the test technique measures the expression level of genes (including at least PARP) whose expression is commonly regulated. In some embodiments, the sample is selected from the group consisting of a human normal sample, a tumor sample, hair, blood, cells, tissue, organ, brain tissue, blood, serum, sputum, saliva, plasma, nipple aspirate, synovial fluid, cerebrospinal fluid, sweat, urine, fecal matter, pancreatic fluid, trabecular fluid, cerebrospinal fluid, tears, bronchial lavage, swabbing, bronchial aspirate, semen, prostatic fluid, pre-cervical fluid, vaginal fluid, and pre-ejaculate. In some embodiments, the level of genes (including at least PARP) that are co-regulated in expression is up-regulated. In some embodiments, the level of genes (including at least PARP) that are co-regulated in expression is down-regulated. In some embodiments, the PARP modulator is a PARP inhibitor or antagonist. In some embodiments, the PARP inhibitor or antagonist is selected from the group consisting of a benzamide, a quinolone, an isoquinolone, a benzopyrone, a cyclic benzamide, a benzimidazole, and an indole, or a metabolite of said PARP inhibitor or antagonist.

In some embodiments, the method further comprises providing a conclusion regarding the disease to the patient, a health care provider, or a health care manager, the conclusion being made based on the decision. In some embodiments, the treatment is selected from the group consisting of oral administration, transmucosal administration, buccal administration, nasal administration, inhalation administration, parenteral administration, intravenous administration, subcutaneous administration, intramuscular administration, sublingual administration, transdermal administration, and rectal administration.

Another aspect relates to a computer readable medium adapted to transmit results of an analysis of a sample, wherein the medium comprises disease information of a patient treatable by a modulator of a co-regulated expressed gene in said patient, the co-regulated expressed gene comprising at least PARP, the information obtained by: identifying in a sample of the patient the expression level of genes of co-regulated expression, including at least PARP, and making a decision based on the expression level of genes of co-regulated expression, including at least PARP, to consider treating the disease by a modulator of the genes of co-regulated expression. In some embodiments, at least one step of the method is computer implemented.

Another aspect is a method of identifying a gene useful in treating a patient for a disease susceptible to treatment with a PARP inhibitor, said method comprising identifying a disease treatable with at least one PARP modulator, wherein the expression level of PARP is modulated in a plurality of samples from a population as compared to a control sample; determining the expression levels of a set of genes in the plurality of samples; and identifying a common regulated gene with said PARP regulation, wherein the expression level of said common regulated gene in a plurality of samples is increased or decreased as compared to a control sample; wherein modulation of said gene, which is co-modulated with PARP modulation, is useful in the treatment of diseases susceptible to PARP modulator treatment.

Other aspects include a method of treating a patient having a disease susceptible to treatment with a PARP modulator, the method comprising identifying a disease treatable with at least one PARP modulator, wherein the expression level of PARP in a sample from a patient having the disease is modulated as compared to a reference sample; identifying at least one co-regulated gene in said sample as compared to a reference sample, and treating said patient with PARP and an inhibitor of said co-regulated gene.

Another embodiment disclosed herein is a method of treating a disease, comprising providing a sample from a patient having the disease; identifying in each sample at least one gene that is modulated as compared to a reference sample, and treating a patient having the disease with a modulator of the identified modulated gene and a PARP modulator.

Another aspect is a method of treating a disease susceptible to treatment with a PARP modulator, said method comprising identifying a disease treatable with at least one PARP modulator, wherein the expression level of PARP in a plurality of samples is modulated as compared to a reference sample; identifying at least one co-regulated gene in the plurality of samples as compared to a reference sample; and treating the disease with an inhibitor of PARP and the co-regulated gene.

Another aspect is a method of treating a cancer susceptible to treatment with a PARP inhibitor, said method comprising identifying a cancer treatable with at least one PARP inhibitor, wherein the expression level of PARP is up-regulated in a plurality of cancer samples, identifying at least one gene in said plurality of samples that is up-regulated in common; and treating a patient having said cancer with an inhibitor of PARP and the co-regulated gene.

Also disclosed is a method of treating breast cancer susceptible to treatment with a PARP inhibitor, said method comprising identifying breast cancer treatable with at least one PARP inhibitor, wherein the expression level of PARP is up-regulated in a plurality of breast cancer samples, identifying at least one co-up-regulated gene in said plurality of samples, and treating a patient having said breast cancer with an inhibitor of PARP and the co-regulated gene. One embodiment is the treatment of triple negative breast cancer.

Further, disclosed herein is a method of treating lung cancer susceptible to treatment with a PARP inhibitor, said method comprising identifying lung cancer treatable with at least one PARP inhibitor, wherein the expression level of PARP is up-regulated in a plurality of lung cancer samples, identifying at least one gene that is co-up-regulated in said plurality of samples, and treating a patient having said lung cancer with an inhibitor of PARP and said co-regulated gene.

Another embodiment disclosed herein is a method of treating endometrial cancer susceptible to treatment with a PARP inhibitor, said method comprising identifying endometrial cancer that is treatable with at least one PARP inhibitor, wherein the expression level of PARP is up-regulated in a plurality of endometrial cancer samples, identifying said at least one co-up-regulated gene in said plurality of samples, and treating said patient with an inhibitor of PARP and said co-regulated gene. Further, a method of treating ovarian cancer susceptible to treatment with a PARP inhibitor, said method comprising identifying an ovarian cancer that is treatable with at least one PARP inhibitor, wherein the expression level of PARP is up-regulated in a plurality of ovarian cancer samples, identifying at least one gene that is co-up-regulated in said plurality of samples, and treating said patient with an inhibitor of PARP and said co-regulated gene.

Also provided herein is a kit for diagnosing or classifying a disease, the kit comprising means for measuring the expression level of PARP in a tissue sample, means for measuring the expression level of that previously identified gene which is co-regulated with PARP; and comparing said expression levels of PARP and co-regulated genes to expression levels of a reference sample, wherein expression levels compared to the reference sample are indicative of the presence of a disease or disease stage. Also included are kits for treating a disease susceptible to a PARP inhibitor, the kit comprising a means for measuring the expression level of PARP in a tissue sample, wherein an increase in the expression level of PARP compared to a reference sample is indicative of a disease susceptible to a PARP inhibitor; means for measuring the expression level of a previously identified gene that is co-regulated with PARP, wherein an increase in the expression of said co-regulated gene is indicative of an inhibitor of said co-regulated gene for use in treating said disease; and inhibitors of PARP and said co-regulated genes for use in treating said diseases.

Reference to a reference

All publications and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication or patent application was specifically and individually indicated to be so incorporated.

Drawings

The novel features of the invention are set forth with particularity in the appended claims. A better understanding of the features and advantages of the present invention will be obtained by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the invention are utilized, and the accompanying drawings of which:

FIG. 1 is a diagram showing the steps of one embodiment of the process disclosed herein.

FIG. 2 illustrates a computer configured to perform selected operations related to the methods disclosed herein.

Figure 3 shows PARP expression in human healthy tissue.

Figure 4 shows PARP expression in malignant and normal tissues.

Figure 5 shows PARP expression in human primary tumors.

FIG. 6 shows the correlation of high expression of PARP1 (FIG. 6A) with lower expression of BRCA1 (FIG. 6B) in primary ovarian tumors.

FIG. 7 shows the upregulation of PARP expression in ER-, PR-and Her-2 negative tissue samples. Figure 7A provides a normal breast tissue sample stained with hemolysin and eosin (H & E) or for markers ER, PR, HER2 or PARP 1. Figure 7B provides breast adenocarcinoma tissue samples stained with H & E or for markers ER, PR, HER2 or PARP 1.

Fig. 8 exemplarily shows a physical interaction network of genes selected to have a 2-fold change cutoff (cutoff) and common in three tissues: ovary, endometrium and breast.

FIG. 9 shows the regulatory interaction network from selected genes with a cut-off of 2-fold change and common in three tissues: ovarian, endometrial and breast tissue.

FIG. 10 shows mRNA expression in lung normal and tumor tissues. FIG. 10A shows Ki-67; FIG. 10B shows PARP 1; figure 10C shows PARP2, and figure 10D shows RAD51mRNA expression.

FIG. 11 shows the expression of PARP in human lung normal and tumor homologous samples.

Figure 12 shows PARP expression in lung human normal and tumor homologous samples.

Figure 13 shows PARP expression in lung human normal and tumor homologous samples.

Figure 14 shows PARP expression in human normal and tumor tissues of the breast. Fig. 14A shows Ki-67, fig. 14B shows PARP1, fig. 14C shows PARP2, and fig. 14D shows RAD51mRNA expression.

Figure 15 shows PARP expression in human normal and tumor homologous samples of breast.

Figure 16 shows PARP expression in human normal and tumor homologous samples of breast.

Figure 17 shows PARP expression in human normal and tumor homologous samples of breast.

Figure 18 shows the effect of PARP1 inhibition (compound III) on tumor growth and improvement in survival in mice, in a human ovarian adenocarcinoma OVCAR-3 xenograft model of cancer.

FIG. 19: compound III potentiates the activity of the IGF-1R inhibitor picropodophyllin (PPP) in triple negative breast cancer cells MDA-MB-468.

FIG. 20: the HCC827NSCLC cell line is a well characterized model for the analysis of EGFR inhibitors.

Detailed Description

The term "inhibit" or grammatical synonyms thereof, such as "inhibitor", is not intended to require a complete reduction in PARP activity. The reduction may be a reduction in the activity of the molecule in the absence of inhibition (e.g., in the absence of an inhibitor such as the PARP inhibitor disclosed herein) of at least about 50%, at least about 75%, at least about 90%, or at least about 95%. The term refers to an observable or detectable decrease in activity. In a treatment regimen, the inhibition may be sufficient to provide a therapeutic and/or prophylactic benefit in the condition being treated.

As used herein, the terms "specimen," "biological specimen," or grammatical equivalents thereof refer to a substance that is known or suspected to express PARP levels. The test sample may be used directly from the source or after pretreatment to alter the properties of the sample. The sample may be derived from any biological source, such as tissue or extracts, including cells, and physiological solutions, such as whole blood, plasma, serum, saliva, ocular lens fluid (oculars fluid), cerebrospinal fluid, sweat, urine, milk, ascites fluid, synovial fluid, peritoneal fluid, and the like. The sample may be obtained from a non-human animal or a human. In one embodiment, the sample is obtained from a human. The sample may need to be processed before use, such as preparing plasma from blood, diluting various fluids, etc. Methods of processing samples may involve filtration, distillation, extraction, concentration, inactivation of interfering components, addition of reagents, and the like.

The terms "subject", "patient" or "individual" as used herein refer to an individual or the like, including mammals and non-mammals, suffering from a disorder. Examples of mammals include, but are not limited to, any member of the mammalian class: human, non-human primates such as chimpanzees, and other apes and monkey species; farm animals such as cattle, horses, sheep, goats, pigs; domestic animals such as rabbits, dogs, and cats; the experimental animals include rodents such as rats, mice and guinea pigs, etc. Examples of non-mammals include, but are not limited to, birds, fish, and the like. In some embodiments, in the methods and compositions provided herein, the mammal is a human.

The term "treatment" or grammatical synonyms thereof as used herein refers to obtaining a therapeutic benefit and/or a prophylactic benefit. Therapeutic benefit refers to the elimination or alleviation of the underlying disease being treated. Likewise, a therapeutic benefit is achieved with elimination or alleviation of one or more physiological symptoms associated with the underlying disease, such that an improvement is observed in the patient, although the patient may still be afflicted with the underlying disease. For prophylactic benefit, the composition can be administered to a patient at risk of developing a particular disease or a patient reporting physiological symptoms of one or more diseases, although a diagnosis of the disease has not yet been made.

The term "expression level" or grammatical synonyms thereof as used herein refers to a measure of the amount of a nucleotide, such as RNA or mRNA, or protein of a gene in a patient, or alternatively, the level of activity of a gene or protein in the patient.

The term "differential expressed" or grammatical equivalents thereof as used herein refers to a change in expression level or a difference from a reference level (which may include a normal or average level of expression measured in a patient or patient population). The expression level may be increased or decreased compared to a reference expression level, and its effect may be transient or long-term. The relative term "co-regulated" or grammatical synonyms thereof as used herein means that the level of expression is altered or varied with another gene (here PARP1) or in tandem with another gene (here PARP 1). In some embodiments, the expression level of a gene, e.g., IGF1, IGF2, IGFR, EGFR, mdm2, Bcl2, ETS1, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK1, VAV3, AURKA, ERBB3, MIF, VEGF, VEGFR2, CDK1, CDK2, CDK9, farnesyl transferase, UBE2A, UBE2D2, UBE2G1, USP28, or UBE2S varies with the expression level of PARP 1. In some embodiments, the co-regulated gene is at least one of the following: IGF1, IGF2, IGFR, EGFR, mdm2, Bcl2, ETS1, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK1, VAV3, AURKA, ERBB3, MIF, VEGF, VEGFR2, CDK1, CDK2, CDK9, farnesyltransferase, UBE2A, UBE2D2, UBE2G1, USP28, UBE2S, ABCC S, ABCD S, ACADM, ACLSL S, ACY1L S, ADM, ADCC S, AGPAT S, AHCYCY, AK3L S, AK 36IIP, AK S, ACAK 1B S, ACAK 1L S, ACAK S, CAATP S, CALCDP S, CACKCD S, CAATP S, CALCDP S, CALCDP S, CALCGALCDP S, 363672, S, CALCAK S, CALCDP S, CALCAK S, CALCAK 363672, CALCK S, CALCK 363672, CALCK S, CALCK 363636363672, CALCK S, CALCK 363636363636363672, CALCK S, CALCK 36, CNDP2, CPD, CPE, CPSF3, CPSF5, CPSF6, CPT1B, CRR9, CSH2, CSK, CSNK2A1, CSPG 1, CTPSCTSB, CTSD, CXADR, CXCR 1, CXXC 1, DAAM1, DCK, DDAH1, DDIT 1, DDDDR 1, DDX 1, DHTKD1, DLAT, DNAXO 1, DNJB 1, JC 36JC 1, DNAFAD 1, DNAJD1, DUSP1, DVL 1, ELOVL 1, EME1, ENO1, ENPP 1, EPS ETNK1, 36V 1, GCSF 11, GCSF 2, HSP 8272, HSP-GFAGP 1, HSP-1, HSP-GFAGG 1, HSP 1, FLX 1, HSP 1, FLXK 1, HSP 1, HSP 36GFAGG 1, FLXK 1, 36GFDG 1, HSP 1, 36GFAGG 1, HSP 1, FLXK 36GFAGG 1, HSP 1, HSP 1, 36GFAGG 1, 3636363672, 36GFAGG 1, 363636363636363636GFAGG 36GFAGG 1, HSP 1, 36, MAP2K3, MAP2K6, MAP3K 6, MAP4K 6, MAPK 6, MARCKS, MBTPS 6, MCM 6, MCTS 6, MDH 6, ME 6, METAP 6, METTL 6, MGAT4 6, MKNK 6, MLPH, MOBK1 6, MOBKL1 6, MSH 6, MTHFD 6, MUC 6, MX 6, MYCBP, NAJD 6, NBNAT 6, NBS 6, NDFIP 6, NEK6, NET 6, NME 6, NNT, NQO 6, NRAS, NSE 6, NUCKS 6, NY-REN-41, ODC 6, OLR 6, P6, PABP 6, PADDP 6, PSPMSPP 6, PSRPP 6, PSNPPEPCP 6, PSNPPDN 6, PSP 6, PSNPPDN 6, PSEPR 6, PSNPPDN 6, PSEPR 6, PSNPPDN 6, PSEPR 6, PSP 6, PSEPR 6, PSEP, SCAP, SCD, SDC, SEMA3, SERPINE, SFI, SGPL, SGPP, SH3GLB, SHC, SMARCC, SMC4L, SMS, SNRPD, SORD, SORL, SPP, SQLE, SRD5A2, SRM, SRPK, SS, SSBP, SSR, ST3GAL, ST6 NAC, STX, SULF, SWAP, TA-KRP, TALA, TBL1XR, TFRC, TIAM, TKT, TMPO, TNFAIP, TNFR, TOX, TPD, TPI, TPP, TRA, TRIP, TRPS, TSPAN, TSTA, TXN, TXNL, TXNRAE, UBAP2, UBE2D, UBE2G, UBE2V, WHHL, WHDH, UGC, USP, WI, YUC, YAB 14, YAB.

Method for identifying diseases or disease stages treatable by modulators of differentially expressed genes, including at least PARP

In one aspect, the method comprises identifying a disease treatable by a modulator of a regulated gene (including at least PARP), comprising identifying the expression level of the regulated gene in a sample from the patient, and making a decision regarding identifying a disease treatable by a modulator of the regulated gene (including at least PARP), wherein the decision is made based on the expression level of the regulated gene. In another aspect, the method comprises treating a disease in a patient with a modulator of a regulated gene, comprising identifying the expression level of the regulated gene in a sample from the patient, making a determination that the disease is treatable by the modulator of the regulated gene based on the expression level of the regulated gene (including at least PARP), and treating the disease with the modulator of the regulated gene. In another aspect, the method comprises identifying the expression level of a modulated gene in a sample from the patient and treating the disease with a modulator of the identified gene and a PARP modulator. In another aspect, the method further comprises providing a conclusion regarding the disease to the patient, a healthcare provider, or a healthcare manager, wherein the conclusion is based on the decision. In some embodiments, the disease is breast cancer. In some embodiments, the level of the modulated gene (including at least PARP) is up-regulated. In some embodiments, the level of the modulated gene (including at least PARP) is down-regulated.

The present embodiments identify diseases, e.g., cancer, inflammation, metabolic disease, CVS disease, CNS disease, lymphohematopoietic disease, endocrine and neuroendocrine disease, urinary tract disease, respiratory disease, female reproductive disease, and male reproductive disease, wherein the level of the modulated gene (including at least PARP) is up-regulated. Accordingly, the present embodiments identify those diseases that can be treated by the identified modulators of the regulated genes. Modulation of PARP gene expression, at least, along with other regulated genes identified by the methods described herein, is useful in the treatment of these identified diseases. In some embodiments, the co-regulated gene, at least together with PARP, may be a protein expressed in the pathway of PARP, EGFR and/or IGF 1R. In other embodiments, the co-regulated gene may comprise IGF, IGFR, EGFR, mdm, Bcl, ETS, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK, VAV, AURKA, ERBB, MIF, VEGF, VEGFR, CDK, farnesyltransferase, UBE2D, UBE2G, USP, UBE2, ABCC, ABCD, ACADLD, ACSL, ACY1L, ADDM, AGPAT, AHCY, AK3L, AKIIP, AKR1B, AKR1C, ALDH18A, ALOX, ALPL, ANP32, GAF, APG5, FG, BACF 19, ATP-5, ATP, CDC, CDB, CDC, CDB, CDK, CABCAK 2G, CDK, BCB, CDK 2D, ACOCK, ACRB, CDC, ACRB, CFLAR, CGI-90, CHST6, CHSY1, CKLFSF4, CKLFSF6, CKS1B, CMKOR1, CNDP2, CPD, CPE, CPSF3, CPT 13, CRR 3, CSH 3, CSK, CSNK2A 3, CSPG 3, CTPSCTSB, CTSD, CXADR, CX3672, CXCX3672, CX 3, DCAM 3, DDAH 36K, DDAH 3, FADD 3, DDX3, DHTKD 3, DLAT, DNAJD 3, HSPJB JB 3, DNJC 3, 36JC 3, 36DG 3, HSP 36GFAGN 3, HSP GFAGGFAGGFAGN 3, HSP GFAGG 3, HSP 3, HSP 3, 36GFAGG 3, HSP 3, 36GFAGG 3, HSP 3, 36GFAGG 3, 36GFAGG 3, HSP 3, 36GFAGG 3, 36GFAGG 3, 36GFAGG 3, 3, LPGAT1, LTB4DH, LYN, MAD2L1, MADP-1, MAGED1, MAK 1, MALAT1, MAP2K 1, MAP3K1, MAP4K 1, MAPK1, MARCKS, MBTPS 1, MCM 1, MCTS1, MDH1, MDME 1, ME1, METAP 1, METTL 1, MGAT 41, MKNK 1, MLPH, MOBK 11, MOBKL 11, MOBK1, PHFH 1, MTHFMSD 1, MUC1, MX1, MYCBP, NAJD1, PSNPS 1, NBP1, NDFIP 1, NEK 1, PGM 1, NME1, NNT 1, NYPP 1, PSVPNSP 1, PSNPPSNPPSCP 1, PSNPPSNPPSNP 72, PSNPPSCP 1, PSCP 1, PSNPPSCP 1, PSCP 1, PSNPPSCP 1, PSP 1, PSCP 1, PSNPPSNP 1, PSP 1, PSCP 1, PSP 1, PSCP 1, PSP 1, PSNPPSP 1, PSP 1, PS, RFC, RGS19IP, RHOTB, RNASEH2, RNGTT, RNPEP, ROBO, RRAS, SART, SAT, SCAP, SCD, SDC, SEMA3, SERPINE, SFI, SGPL, SGPP, SH3GLB, SHC, SMARCC, SMC4L, SMS, SNRPD, SORD, SORL, SPP, SQLE, SRD5A2, SRM, SRPK, SS, SSBP, SSR, ST3GAL, ST6 NAC, STX, SUAP, TA-KRP, TALA, TBL1XR, TFRC, TIAM, AIT, TMPO, TNFSP, TNFSF, TOX, TPD, TPI, TPP, TRA, TRIP, TRPS, WHNL, TSNL, TXET, TXRB 2, TXUBC, UTP, USP, UBAB 2, USP, UB, USP, UBAB 2, UB, USP, UBAL, UB, USP, UBE, UB, UBE, UB 2, UBE, UB, USP, UBE, UB, UBE, UB. In other embodiments, the co-regulated gene may comprise IGF1, IGF2, IGFR, EGFR, mdm2, Bcl2, ETS1, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK1, VAV3, aua, ERBB3, MIF, VEGF, VEGFR2, CDK1, CKD2, CDK9, farnesyl transferase, UBE2A, UBE2D2, UBE2G1, USP28, UBE2S, or a combination thereof.

In one embodiment, the PARP inhibitor in combination with a modulator of other regulated genes is a PARP-1 inhibitor. PARP inhibitors used in the methods disclosed herein may act by interacting directly or indirectly with PARP (e.g., PARP-1). PARP inhibitors used herein may modulate PARP or may modulate one or more entities in the PARP pathway. In some embodiments the PARP inhibitor inhibits PARP activity.

The methods disclosed herein may be particularly useful for treating cancer of the female reproductive system. Breast tumors develop in women who are genetically deficient in either BRCA1 or BRCA2 genes because the tumor cells have lost specific mechanisms for repairing damaged DNA. BRCA1 and BRCA2 are important for DNA double strand break repair by homologous recombination and for mutations in these genes that cause breast and other cancers. PARP is involved in base excision repair (which is one pathway in repairing DNA double strand breaks). BRCA1 or BRCA2 dysfunction sensitizes cells to inhibition of PARP enzyme activity, resulting in chromosomal instability, cell cycle arrest and subsequent apoptosis.

Thus, PARP inhibitors can kill cells (where this form of DNA repair is absent) and are therefore effective in killing BRCA-deficient tumor cells and other similar tumor cells. Normal cells may not be affected by the drug because they may still have this DNA repair mechanism. Accordingly, PARP inhibitors, in combination with modulators of other modulated genes identified by the methods described herein, are useful for treating breast cancer patients deficient in BRCA1 or BRCA 2. The treatment may also be applied to other forms of breast cancer (behaving similarly to BRCA deficient cancers). Typically, breast cancer patients are treated with drugs that kill tumor cells but also damage normal cells. It is this damage to normal cells that causes distressing side effects such as nausea and hair loss. In some embodiments, an advantage of treatment with PARP inhibitors is that they are targeted: tumor cells were killed while normal cells were shown to be unaffected. This is because PARP inhibitors exploit certain gene-complementing phenotypes of some tumor cells.

It has been previously shown that the level of PARP in patients with the BRCA gene has been upregulated. See, for example, example 2 and U.S. application No.11/818,210, which are expressly incorporated herein by reference in their entirety. FIGS. 3-5 show differential regulation of PARP in certain primary tumors, as compared to a reference normal sample. FIG. 6 shows the correlation of high expression of PARP-1 (FIG. 6A) with lower expression of BRCA1 (FIG. 6B) in primary human ovarian tumors. In addition, figure 7 shows the upregulation of PARP expression in triple negative breast cancer (figure 7B), compared to normal breast tissue (figure 7A). PARP upregulation can be an indicator of defects in other defective DNA-repair pathways and unidentified BRCA-like genes. The evaluation of PARP-1 gene expression is an indicator of the sensitivity of tumors to PARP inhibitors. If PARP is up-regulated, BRCA deficient patients that can be treated by PARP inhibitors can be identified. In addition, such BRCA deficient patients may be treated with PARP inhibitors.

IGF1-R overexpression may be the result of BRCA1 loss (Werner and Roberts, 2003, Genes, Chromo. cancer 36: 113-120; Riedemann and Macaulay, 2006, Endocr. Rel. cancer, 13: Suppl 1: S33-S43). It has previously been shown that BRCA1 inhibits the IGF1-R promoter, and it was taught that inactivation of BRCA1 may lead to activation of IGF1-R expression due to the de-inhibitory effect of IGF 1-R.

Activation of EGFR triggers mitotic signaling in Gastrointestinal (GI) tumors, where prostaglandin E2(PGE2) rapidly phosphorylates EGFR and triggers extracellular signal-regulated kinase 2(ERK2) mitotic signaling in GI cells and tumors. PARP1 can be activated by direct interaction with ERK2, which in turn can enhance growth, proliferation and differentiation (regulated by the RAF-MEK-EREK signaling pathway) promoted by ERK-signaling (Cohen-Armon, 2007, Trends pharmacol. sci.28: 556-60 Epub).

Although both IGF1-R overexpression and PARP1 upregulation can be observed in BRCA1 deficient breast cancers, previous studies have not suggested or taught the interrelationship of the two pathways in breast cancer therapy. The studies described herein detail the co-upregulation of PARP1 and IGFR-1 in a variety of tumors, including breast, endometrial mullerian hybridomas, papillary serous ovarian adenocarcinoma, ovarian mullerian hybridomas, and skin tumors (see tables II-XVIII). Furthermore, it has been previously shown that the small molecule inhibitor NVP-AEW541 inhibits cell growth in ovarian adenocarcinoma cell lines OVCAR-3 and OVCAR-4 (Gotlieb et al, 2006, Gynecol. Oncol.100: 389-96). Accordingly, from previous observations of expression correlation tables and the role of IGF-1R in tumor growth and proliferation, treatment with PARP1 and IGF1R modulators may also increase the sensitivity of tumors (treated by a combination of PARP and IGF1R inhibitors) to chemotherapy.

Similarly, PARP1 upregulation was also observed in tumors of the same subclass, with EGFR upregulation also being observed (see tables II-XVIII, XXI). For example, co-upregulation of PARP1 and EGFR expression is observed in skin, uterine, breast and lung cancers, etc. (II-XVIII, XXI). Accordingly, treatment with PARP1 and EGFR may also increase the sensitivity of tumors (treated by the combination of PARP1 and EGFR inhibitors) to chemotherapy.

The steps of some embodiments are depicted in figure 1. Without limiting the scope of this embodiment, the steps may be performed independently of each other or sequentially. One or more steps may be skipped in the methods described herein. A sample is collected in step 101 from a patient suffering from a disease. In one embodiment, the samples are human normal and tumor samples, hair, blood, and other biological fluids. The level of PARP is analyzed by techniques well known in the art at step 102 and based on the PARP level, for example when PARP is up-regulated, diseases are identified at step 103 that can be treated by PARP inhibitors. Identifying other co-regulated expressed genes at step 104, wherein the modulation of the identified co-regulated expressed genes at step 105 is useful for treating a patient suffering from the disease identified using a combination of at least one PARP inhibitor and the identified co-regulated expressed gene modulator. It should be understood that other methods not explicitly described herein are also included. Without limiting the scope of this embodiment, collection of samples, analysis of PARP and co-regulated expressed genes in samples, and other techniques for treating diseases using a combination of at least one PARP inhibitor and an identified modulator of a co-regulated expressed gene are known in the art and are included within the scope of this embodiment.

Sample collection, preparation and separation

Biological samples may be obtained from individuals having an altered phenotypic state, such as various states of cancer or other diseases. Examples of phenotypic states also include the phenotype of normal patients, which can be used for comparison with diseased patients. In some embodiments, a patient with a disease is matched to a control sample (obtained from an individual who does not exhibit the disease). In other embodiments, a patient with a disease may be provided with a control sample, for example, from a tissue or organ that is not affected by the disease.

Samples can be collected from a variety of sources in a mammal (e.g., a human), including a bodily fluid sample or a tissue sample. The collected sample may be human normal and tumor samples, hair, blood, other biological fluids, cells, tissues, organs, or body fluids such as, but not limited to, brain tissue, blood, serum, sputum including saliva, plasma, nipple aspirate, synovial fluid, cerebrospinal fluid, sweat, urine, fecal matter, pancreatic fluid, trabecular fluid, cerebrospinal fluid, tears, bronchial lavage, swabbing, bronchial aspirate, semen, glandular fluid, pre-cervical fluid, vaginal fluid, pre-ejaculatory semen, etc. Suitable tissue samples include various types of tumor or cancer tissue, or organ tissue, such as those taken in a biopsy.

Samples can be collected repeatedly from an individual over an extended period of time (e.g., about once per day, once per week, once per month, once per half year, or once per year). Multiple samples obtained from an individual over a period of time can be used to corroborate earlier detected conclusions and/or to identify changes in biological patterns, leading to conclusions such as disease progression, drug treatment, etc.

Sample preparation and isolation may involve any steps, depending on the type of sample collected and/or the analysis of co-differentially expressed genes. Such steps include, by way of example only, concentration, dilution, pH adjustment, removal of high abundance polypeptides (e.g., albumin, gamma globulin, and transferrin, etc.), addition of preservatives and calibrators, addition of protease inhibitors, addition of denaturants, desalting of the sample, concentration of sample proteins, extraction and purification of liquids.

Sample preparation can also isolate molecules that bind to other proteins (e.g., carrier proteins) in a non-covalent complex. The method may isolate those molecules that bind to a particular carrier protein (e.g., albumin protein), or use a more general method, such as releasing the binding molecules from all carrier proteins by protein denaturation, e.g., using an acid, followed by removal of the carrier protein.

Removal of unwanted proteins (e.g., abundant, uninformative, or undetectable proteins) from a sample can be accomplished using high affinity reagents, high molecular weight filters, ultracentrifugation, and/or electrodialysis. High affinity reagents include antibodies or other reagents (e.g., aptamers) that selectively bind to high abundance proteins. Sample separation may include ion exchange chromatography, metal ion affinity chromatography, gel chromatography, hydrophobic chromatography, chromatofocusing, adsorption chromatography, isoelectric focusing and related techniques. The molecular weight filter includes a membrane that separates molecules based on size and molecular weight. Such filters may further use reverse osmosis, nanofiltration, ultrafiltration and microfiltration.

Ultracentrifugation represents one method for removing unwanted polypeptides from a sample. The ultracentrifugation method centrifuges the sample at about 15,000-60,000rpm while detecting the precipitation of particles (or the absence thereof) using an optical system. Electrodialysis is a process in which an electromembrane or semipermeable membrane is used in a process in which ions are transferred from one solution to another through the semipermeable membrane under the influence of a potential gradient. As the membranes used in electrodialysis may have the ability to selectively transport ions of positive or negative charge, repel ions of opposite charge, or allow species to migrate through the semi-permeable membrane based on size and charge, this allows electrodialysis to be used for concentration, removal, or separation of electrolytes.

Separation and purification may include any method known in the art, such as capillary electrophoresis (e.g., in a capillary or on a chip) or chromatography (e.g., in a capillary, column, or on a chip). Electrophoresis is a method that can be used to separate ionic molecules under the influence of an electric field. Electrophoresis may be performed in a gel, capillary or in a microchannel of a chip. Examples of gels for electrophoresis include starch, acrylamide, polyethylene oxide, agarose, or combinations thereof. Gels can be modified by their cross-linking, the addition of detergents or denaturants, the immobilization of enzymes or antibodies (affinity electrophoresis) or substrates (zymography), and the incorporation of pH gradient solutions. Examples of capillaries for electrophoresis include capillaries interfaced with electrospray.

Capillary Electrophoresis (CE) represents a class of methods for separating complex hydrophilic molecules from highly charged solutes. CE technology can also be implemented on microfluidic chips. Depending on the type of capillary and buffer used, the CE may further distinguish between separation techniques such as Capillary Zone Electrophoresis (CZE), capillary isoelectric focusing (CIEF), capillary isotachophoresis (ctipp), and Capillary Electrochromatography (CEC). One embodiment of CE technology coupled with electrospray ionization involves the use of a volatile solution, e.g., an aqueous mixture containing a volatile acid and/or base and an organic such as an alcohol or acetonitrile.

Capillary isotachophoresis (cITP) represents a technique in which analytes are separated at a constant rate through a capillary, but by their respective mobilities. Capillary Zone Electrophoresis (CZE), also known as free solution ce (fsce), is based on differences in the electrophoretic mobility of substances (determined by the charge on the molecules), and the frictional resistance of molecular collisions during migration (which is generally proportional to the size of the molecules). Capillary isoelectric focusing (CIEF) allows weakly ionized amphipathic molecules to be separated by electrophoresis in a pH gradient. CEC is a hybridization technique between traditional High Performance Liquid Chromatography (HPLC) and CE.

The separation and purification techniques used in this embodiment include any chromatographic method known in the art. Chromatography may be based on differential adsorption and elution of certain analytes or on the partitioning of analytes between a mobile phase and a stationary phase. Different examples of chromatography include, but are not limited to, Liquid Chromatography (LC), Gas Chromatography (GC), High Performance Liquid Chromatography (HPLC), and the like.

Measurement of expression levels of regulated genes

The level of genes whose expression is modulated, including at least PARP, can be measured by assays that detect and quantify the expression level of nucleotides, proteins in patient samples, or, alternatively, the level of activity of genes or proteins whose expression is commonly modulated in patient samples. For example, the operator can measure the expression level of a gene whose expression is regulated by mRNA quantitation. The most commonly used methods known in the art for quantifying mRNA in a sample include Northern blotting and in situ hybridization; a ribonuclease protection assay; and PCR-based methods, such as reverse transcription polymerase chain reaction (RT-PCR). Alternatively, antibodies that recognize specific duplexes, including DNA duplexes, RNA duplexes, and DNA-RNA heteroduplexes or DNA-protein duplexes may be used.

Representative methods for sequence-based Gene Expression Analysis include Serial Analysis of Gene Expression (SAGE), and Gene Expression Analysis by massively parallel sequencing (MPSS), Comparative Genomic Hybridization (CGH), chromatin immunoprecipitation (ChIP), Single Nucleotide Polymorphism (SNP) and SNP testing, Fluorescence In Situ Hybridization (FISH), protein binding testing, DNA microarrays (also commonly known as Gene or genomic chips, DNA chips or Gene arrays), and RNA microarrays. As described above, co-regulated levels of protein expression or protein activity may also be monitored and compared relative to reference levels.

In some embodiments, the level of genes (including at least PARP) that are modulated for expression in a sample from a patient is compared to a predetermined standard sample. The sample from the patient is obtained from diseased tissue, such as cancer cells or tissue. The standard sample may be from the same patient or from a different patient. The standard sample is typically a normal, disease-free sample. However, in some embodiments, the standard sample is from diseased tissue, for example, for disease staging or to assess the efficacy of treatment. The standard sample may be a combination of samples from several different patients. In some embodiments, the level of a co-regulated expressed gene (including at least PARP) from the patient is compared to a predetermined level. The predetermined level is typically obtained from a normal sample. As described herein, a "predetermined expression level" may be an expression level of a set of genes (including at least PARP) that are used, by way of example only, to evaluate a patient that may be selected for treatment, to evaluate a response to treatment with a PARP inhibitor, to evaluate a response to a combination treatment with a PARP inhibitor and a second therapeutic agent (e.g., a modulator of a gene whose expression is collectively modulated), and/or to diagnose cancer, inflammation, pain, and/or an associated condition in a patient. In other embodiments, the predetermined levels of expression of a set of genes (including at least PARP) may be determined in a population of patients with or without cancer. The predetermined expression level for each individual gene (including at least PARP) may be a single number, equally applied to each patient, or the predetermined expression level for each gene in the set may vary depending on the particular subpopulation of patients. For example, a male may have a different predetermined expression level than a female; non-smokers may have a different predetermined expression level than smokers. The age, weight and height of the patient may affect the predetermined expression level of the individual or of a given patient population or subpopulation. Further, the predetermined expression level may be a level determined individually for each patient. The predetermined expression level can be any suitable standard. For example, the predetermined expression level may be obtained from the same or a different person for whom the patient selection is being evaluated. In one embodiment, the predetermined expression level may be obtained from a previous evaluation of the same patient. In this way, the progress of the patient's selection may be monitored over time. Similarly, the predetermined expression levels of a set of gene targets (including at least PARP) may be from a specific patient population or subpopulation. Accordingly, the criteria may be obtained from an evaluation of another person or persons (e.g., a selected group of persons). In this way, the degree of selection of the person (whose selection is being evaluated) can be compared to other persons as appropriate, e.g., other persons of interest in similar circumstances, such as those suffering from similar or the same conditions.

In some embodiments, the expression level of each gene in the identified set of gene targets varies from a predetermined level by about 0.5 fold, about 1.0 fold, about 1.5 fold, about 2.0 fold, about 2.5 fold, about 3.0 fold, about 3.5 fold, about 4.0 fold, about 4.5 fold, or about 5.0 fold. In some embodiments, the fold change is less than about 1, less than about 5, less than about 10, less than about 20, less than about 30, less than about 40, or less than about 50. In other embodiments, the fold change in expression level is greater than about 1, greater than about 5, greater than about 10, greater than about 20, greater than about 30, greater than about 40, or greater than about 50 compared to the predetermined level. Fold changes from the predetermined level also include about 0.5, about 1.0, about 1.5, about 2.0, about 2.5, and about 3.0.

Tables I to XVII shown below illustrate differential gene expression data, including PARP1 and other gene expression profiles, in patients with the following diseases: cancer, metabolic disorders, diseases of the endocrine and neuroendocrine systems, cardiovascular diseases (CVS), diseases of the Central Nervous System (CNS), diseases of the male reproductive system, diseases of the female reproductive system, diseases of the respiratory system, diseases of the urinary tract, inflammation, diseases of the lymphohematopoietic system and diseases of the digestive system. The minimal fold change in expression represented in tables I to XVII is at least a 2-fold change.

Disclosed herein is a method of monitoring wherein the expression level of each of the identified co-regulated genes (including at least PARP) in a cancer patient or patient population can be monitored during cancer or during anti-tumor therapy, and in some cases, prior to and at the start of treatment. Determination of a decrease or increase in the expression level of each identified gene target of a predetermined group of commonly regulated genes in a cancer patient or patient population, as compared to the expression level of the same predetermined group of commonly regulated genes in normal individuals without cancer, yields the following assessment regarding patient progression and/or outcome: (i) more severe stages or levels of cancer; (ii) (ii) a shorter period of disease progression, and/or (iii) a lack of positive, i.e., effective response of the patient to cancer treatment. For example, a determination can be made as to whether the treatment regimen should be changed, i.e., changed to be more aggressive or less aggressive, based on monitoring the patient's expression levels over time, or in addition to or alternatively with reference to the patient's own previously determined levels, relative to normal levels of the same set of gene targets; to determine whether the patient is responding positively to his or her treatment; and/or to determine the disease state, e.g., the advanced stage or stage of cancer, or the improvement (remission), reduction (regression), or regression (regression) of a cancer or neoplastic disease. This embodiment allows determination of clinical benefit, Time To Progression (TTP), and length of survival, based on up-or down-regulating co-regulated gene expression levels in a predetermined group, as compared to levels in normal individuals.

Analysis of the expression levels of genes and their pathways in individual patients or patient populations is particularly valuable and informative, allowing physicians to more effectively select the optimal treatment and to utilize more robust treatments and treatment protocols based on the up-or down-regulated levels of the identified co-regulated gene targets. More aggressive treatments, or combination therapies and regimens, may serve to offset the poor patient prognosis and overall survival time. The healthcare practitioner provided with this information can choose to provide certain types of treatment, such as treatment with PARP inhibitors and/or other modulators of genes whose expression is commonly regulated, and/or more aggressive treatment.

When monitoring the expression level of a co-regulated gene (including at least PARP) in an individual patient or patient population over a period of time, which may be several minutes, hours, days, weeks, months, and in some cases years, or intervals thereof, a body fluid sample (e.g., serum or plasma) of the patient or patient population may be collected at regular intervals, as determined by an operator (e.g., a physician or clinician teacher) to determine the expression level of each identified co-regulated target gene (including at least PARP) with progression or treatment or disease, and compared to the level in a normal individual or population. For example, patient samples may be taken and monitored monthly, every two months, or a combination of one, two, or three month intervals. Furthermore, the obtained expression levels of genes (including at least PARP) that are commonly regulated by each identified target of the patient over time can conveniently be compared individually to each other and to normal controls during monitoring, thereby providing the patient's own expression level value as an intrinsic or personal control for long-term expression monitoring. Similarly, expression levels from a patient population may also be compared to other patient populations (including normal control populations), providing a convenient way to compare the results of the patient population for the monitoring period.

Table II: PARP1 upregulate-Diff/X (human); name: primary skin basal cell carcinoma upregulation (minimal fold change: 2.0); experiment: skin, basal cell carcinoma, primary; comparison: normal skin.

Table III: PARP1 upregulate-Diff/X (human); name: up-regulating primary cutaneous malignant melanoma (minimal fold change: 2.0); experiment: skin, malignant melanoma, primary; comparison: normal skin.

Table IV: PARP1 upregulate-Diff/X (human); name: upregulated primary papillary thyroid carcinoma follicular variation (minimal fold change: 2.0); experiment: thyroid, papillary carcinoma, follicular variant, primary; comparison: normal thyroid gland.

Table V: PARP1 upregulate-Diff/X (human); name: up-regulating primary testicular seminoma (minimal fold change: 2.0); experiment: testis, seminoma, primary; comparison: normal testis.

Table VI: PARP1 upregulate-Diff/X (human); name: up-regulated primary lung adenocarcinoma (minimal fold change: 2.0); experiment: lung, adenocarcinoma, primary; comparison: normal lung.

Table VII: PARP1 upregulate-Diff/X (human); name: up-regulated primary squamous cell carcinoma of the lung (minimal fold change: 2.0); experiment: lung, squamous cell carcinoma, primary; comparison: normal lung.

Table VIII: PARP1 upregulate-Diff/X (human); name: up-regulated primary endometrioid ovarian adenocarcinoma (minimal fold change: 2.0); experiment: ovary, adenocarcinoma, endometrioid type, primary; comparison: normal ovaries.

Table IX: PARP1 upregulate-Diff/X (human); name: up-regulated primary ovarian serous cystadenocarcinoma (minimal fold change: 2.0); experiment: ovary, serous cystadenocarcinoma, primary; comparison: normal ovaries.

Table X: PARP1 upregulate-Diff/X (human); name: breast invasive lobular carcinoma with a history of up-regulated primary no-smoking vs. normal (minimal fold change: 2.0); experiment: breast, invasive lobular carcinoma, primary; history of non-smoking; comparison: normal breast, no smoking history.

Table XI: PARP1 upregulate-Diff/X (human); name: up-regulated primary endometrial Mullerian hybridomas (minimal fold change: 2.0); experiment: endometrium, mullerian mixed tumor, primary; comparison: normal endometrium.

Table XII: PARP1 upregulate-Diff/X (human); name: up-regulated hepatocellular carcinoma (minimal fold change: 2.0); experiment: liver, hepatocellular carcinoma; comparison: liver, nodular hyperplasia of lesions.

Table XIII: PARP1 upregulate-Diff/X (human); name: up-regulated primary endometrioid endometrial adenocarcinoma (minimal fold change: 2.0); experiment: endometrium, adenocarcinoma, endometrioid type, primary; comparison: normal endometrium.

Table XIV: PARP1 upregulate-Diff/X (human); name: up-regulated primary lung large cell carcinoma (minimal fold change: 2.0); experiment: lung, large cell carcinoma, primary; comparison: normal lung.

Table XV: PARP1 upregulate-Diff/X (human); name: all types of lymph node non-Hodgkin lymphoma upregulated (minimal fold change: 2.0); experiment: lymph nodes, non-hodgkin lymphoma, all types; comparison: normal lymph nodes.

Table XVI: PARP1 upregulate-Diff/X (human); name: up-regulated diffuse large B-cell lymph node non-Hodgkin lymphoma (minimal fold change: 2.0); experiment: lymph nodes, non-hodgkin's lymphoma, diffuse large B-cell type; comparison: normal lymph nodes.

Table XVII: PARP1 upregulate-Diff/X (human); name: up-regulated primary ovarian mullerian hybridomas (minimal fold change: 2.0); experiment: ovary, mullerian hybridoma, primary; comparison: normal ovaries.

Table XVIII: PARP1 upregulate-Diff/X (human); name: up-regulated breast invasive ductal carcinoma (minimal fold change: 2.0); experiment: breast, invasive ductal carcinoma, primary; comparison: normal mammary gland.

Techniques for analyzing differentially expressed genes

Analysis of genes that are commonly regulated includes analysis of PARP gene expression, as well as all genes differentially expressed in human tumor tissue, including IGF1, IGF2, IGFR, EGFR, mdm2, Bcl2, ETS1, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK1, VAV3, AURKA, ERBB3, MIF, VEGF, CDK1, CDK2, CDK9, farnesyl transferase, UBE2A, UBE2D2, UBE2G1, USP28, or UBE2S, which may include analysis of DNA, RNA, analysis of the level of commonly regulated genes and/or analysis of the activity of protein products of commonly regulated genes, e.g., measurement of the level of mono-and poly-ADP-ribosylation for PARP gene expression, or other commonly regulated gene encoding enzyme activity. Other genes differentially expressed may also include, but are not limited to, IGF, IGFR, EGFR, mdm, Bcl, ETS, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK, VAV, AURKA, ERBB, MIF, VEGF, CDK, farnesyltransferase, UBE2D, UBE2G, USP, UBE2, ABCC, ABCD, ACADM, ACLSL, ACAY 1L, ADM, AGPAT, AHCY, AK3L, AKIIP, AKR1B, AKR1C, ALDH18A, ALDA, ALPL, ANP32, GAFF, APG5, ARFGEF, ARFGL, ARPP-19, BACP 7, ATP5, ATP, CABCA, ATP-5, CDC, CDB, CDC, CDK, ATP-5, CDK, ATP-3L, AK 2G, UBC, UBCC, ABC 2, ABCC, ABC 2, ABCC, ABC 2, ABC, ABCC, ABCD, ABC, ACCDK, ABCD, ACCDK, ACDH, ACCDK 2, ACCDK, AC, CHST6, CHSY1, CKLFSF4, CKLFSF6, CKS1B, CMKOR B, CNDP B, CPD, CPE, CPSF B, CPT1B, CRR B, CSH B, CSK, CSNK2A B, CSPG B, CTPSCTSB, CTSD, CXADR, CXCR B, CXXC B, DAXC B, DCK, DDAH B, DDIT B, DDX B, DHTKD B, DLAT, DNAJA B, DNJB B, DNJC B, HSPDNADN B, HSPFALG B, HSPGFAGN B, HSPGFAGGFAGN B, HSPGFAGFLAGFLEXP B, HSPGFAGFLX B, HSPGFAGGFAGGFAGFLX B, HSPGFAGGFAGFLD B, HSPGFAGFLD B, HSPGFAG3672, HSPGFAGFLXC B, HSPGFAGFLX B, HSPGFAGGFAGGFAG3672, B, HSPGFAGGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGFAGGFDG B, HSPGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGF3672, B, HSPGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGFDG B, HSPGFAGGFX B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFX B, HSPGFDG B, HSPGFX B, HSPGFAGGFAGGF3672, HSPGFX B, HSPGFAGGFAGGFAGGFAGGF3672, HSPGFX B, HSPGFAGGFAGGFAGGF, MADP-1, MAGED1, MAK3, MALAT 3, MAP2K3, MAP3K 3, MAP4K 3, MAPK 3, MARCKS, MBTPS 3, MCM 3, MDH 3, ME 3, METAP 3, METTL 3, MGAT4 3, MKNK 3, MLPH, MOBKL 13, MSH 3, MTHFD 3, MUC 3, MX 3, MYCBP, NAJD 3, NAT 3, NBS 3, NDP 3, NEK 3, QO 3, NMP 3, NNT 3, NNFP 3, NRAS, NSE 3, PGS 36SAP 3, PSPMSPP 3, PSWPP 3, PSMP 3, PSNPPEPCP 3, PSNPPEPTCP 3, PSNPCP 3, PSNPPEPTCP 3, PSP 3, PSCP 3, PSP 3, PSNPPEPTCP 3, PSP 3, PSNPPEPTCP 3, PSPEPTCP 3, PSP 3, PS, RNGTT, RNPEP, ROBO, RRAS, SART, SAT, SCAP, SCD, SDC, SEMA3, SERPINE, SFI, SGPL, SGPP, SH3GLB, SHC, SMARCC, SMC4L, SMS, SNRPD, SORD, SORL, SPP, SQLE, SRD5A2, SRM, SRPK, SS, SSBP, SSR, ST3GAL, ST6 GALNC, STX, SULF, SWAP, TA-KRP, TALA, TBL1XR, TFRC, TIAM, TKT, TMPO, TNFAIP, TNFSF, TOX, TPD, TPI, TPP, TRA, TRIP, TRPS, TSPAN, TSTA, TXN, NL, NRD, UBAP2, WHE 2, TXDH, WUBV, USP, YUBB, YUBV, USP, YUBA, USP, TXUBA, USP, TXUBN, USP, YUBA, TXUBV, USP, and YUBV. Without limiting the scope of this embodiment, any technique known in the art may be used to analyze the co-regulated genes and they all fall within the scope of this embodiment. Some examples of such detection techniques are given below, but these examples do not limit in any way the variety of detection techniques used in this embodiment.

Gene expression profiling: gene expression analysis methods include polynucleotide hybridization analysis based methods, polynucleotide sequencing based polynucleotide nucleotide methods, and polynucleotide nucleotide and proteomics based methods. The most commonly used Methods for quantifying mRNA expression in samples known in the art include northern blotting and in situ hybridization (Parker & Barnes, Methods in Molecular Biology 106: 247-283 (1999)); RNase protection assays (Hod, Biotechnicques 13: 852-854(1992)) and PCR-based methods such as reverse transcription-polymerase chain reaction (RT-PCR) technology (Weis et al, Trends in Genetics 8: 263-264 (1992)). Alternatively, antibodies that recognize specific duplexes including DNA duplexes, RNA duplexes, and DNA-RNA hybrid duplexes or DNA-protein duplexes may be used. Representative sequencing-based gene expression analysis methods include gene expression Sequencing (SAGE), Massively Parallel Signal Sequencing (MPSS) -based gene expression analysis, comparative genomic hybridization techniques (CGH), chromatin immunoprecipitation (ChIP), Single Nucleotide Polymorphisms (SNPs) and SNP arrays, Fluorescence In Situ Hybridization (FISH), protein binding arrays and DNA microarrays (also commonly referred to as gene or genomic chips, DNA chips, or gene microarrays), and RNA microarrays.

Reverse transcriptase PCR (RT-PCR): one of the most sensitive and flexible methods of gene expression analysis based on quantitative PCR technology is RT-PCR, which can be used to compare mRNA levels in different sample populations, normal tissues and tumor tissues (treated or not) to characterize gene expression patterns, to distinguish closely related mrnas, and to analyze RNA structure.

The first step is to isolate mRNA from the target sample. For example, the starting material can typically be total RNA isolated from a human tumor or tumor cell line, and the corresponding normal tissue or cell line, respectively. Thus, RNA can be isolated from a wide variety of normal and diseased cells and tissues, such as tumors, including breast, lung, colon, prostate, brain, liver, kidney, pancreas, spleen, thymus, testis, ovary, uterus, and the like, or tumor cell lines. If the mRNA source is a primary tumor, mRNA can be extracted from frozen or sequestered fixed tissue, such as paraffin-embedded and fixed (e.g., formalin-fixed) tissue samples. General methods for extracting mRNA are well known in the art and are disclosed in standard textbooks of Molecular Biology, including Ausube et al, Current Protocols of Molecular Biology, John Wileyand Sons (1997).

In particular, RNA isolation can be performed using the purification kit, the buffer kit and the protease provided by the manufacturer according to the manufacturer's instructions. For example, RNA prepared from tumors can be isolated by cesium chloride density gradient centrifugation. Since RNA cannot be used as a template for PCR, the first step in gene expression analysis using RT-PCR is to reverse transcribe the RNA template into cDNA, which is then exponentially amplified in a PCR reaction. The two most commonly used reverse transcriptases are the avilo myeloblastic leukemia virus reverse transcriptase (AMV-RT) and the Moloney murine leukemia virus reverse transcriptase (MMLV-RT). The reverse transcription step is usually primed with specific primers, random hexamers, or oligo dT primers, depending on the context and goal of the expression assay. The derived cDNA can then be used as a template in subsequent PCR reactions.

In order to minimize the effect of errors and variations between different samples, RT-PCR is usually performed using internal standards. The ideal internal standard is expressed at a constant level between different tissues and is not affected by experimental treatments. The most commonly used RNAs for gene expression pattern normalization are the mRNA for the housekeeping genes glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and β -actin.

A recent variation of RT-PCR technology is real-time quantitative PCR, which measures PCR product accumulation by means of a double-labeled fluorescent probe. The real-time quantitative PCR technique is compatible with both quantitative competitive PCR and quantitative comparative PCR. In quantitative competitive PCR, the internal competitor for each target sequence was used for normalization. Quantitative comparative PCR uses either a normalization gene contained in the sample, or a housekeeping gene of RT-PCR.

Fluorescence microscopy: some embodiments include fluorescence microscopy for analyzing differentially expressed genes, including at least one PARP. For example, fluorescence microscopy enables the observed structural molecular composition to be identified with highly chemically specific fluorescently labeled probes, such as antibodies. This can be achieved by conjugating the fluorophore directly to the protein and introducing it back into the cell. Fluorescent analogs can function like the native protein and thus can be used to reveal the intracellular distribution and expression of the protein. Along with NMR, infrared spectroscopy, circular dichroism and other techniques, the intrinsic fluorescence decay of proteins and their associated fluorescence anisotropy observations, collision quenching and resonance energy transfer are all techniques for protein detection. The natural fluorescent protein can be used as a fluorescent probe. Aequorin produces a naturally occurring fluorescent protein known as Green Fluorescent Protein (GFP). The fusion of these fluorescent probes to the target protein enables visualization by fluorescence microscopy and quantification by flow cytometry.

By way of example only, some probes are labels such as fluorescein and its derivatives, carboxyfluorescein, rhodamine and its derivatives, atropic labels, fluorescent red, fluorescent orange: cy3/cy5 alternatives, long-lived lanthanide complexes, long wavelength (up to 800nm) labels, DY anthocyanidin labels, and phycobiliproteins. By way of example only, some probes are conjugates, such as isothiocyanate conjugates, biotin protein conjugates, and biotin conjugates. By way of example only, some probes are enzyme substrates, such as fluorescent and chromogenic substrates. By way of example only, some probes are fluorescent dyes, such as FITC (green fluorescence, excitation/emission wavelength of 506/529nm), rhodamine B (orange fluorescence, excitation/emission wavelength of 560/584nm), and nile blue a (red fluorescence, excitation/emission of 636/686 nm). Fluorescent nanoparticles can be used in various types of immunoassays. Fluorescent nanoparticles are based on different materials such as polyacrylonitrile, polystyrene, etc. Fluorescent molecular rotors are microenvironment-limited sensors that fluoresce when their rotation is limited. Several examples of molecular limitations include increasing dye (aggregation), binding to antibodies, or limitation by actin polymerization. IEF (isoelectric focusing) is an analytical tool for the separation of ampholytes, mainly proteins. An advantage of using fluorescent IEF-labeled IEF-gel electrophoresis is that it is possible to directly observe the formation of the gradient. Fluorescent IEF-labels can also be detected by UV absorption at 280nm (20 ℃).

Libraries of peptides can be synthesized on solid supports and the solid supports individually selected for subsequent staining by use of a colored acceptor. If the receptors do not show any color, their bound antibodies can be stained. The method can be used not only for protein receptors, but also for screening binding ligands for synthetic artificial receptors and for screening novel metal binding ligands. Automated methods of HTS and FACS (fluorescence activated cell sorting system) can also be used. The FACS machine first passes the cells through a capillary tube and separates the cells by detecting their fluorescence intensity.

And (3) immunoassay: some embodiments include immunoassays that analyze differentially expressed genes. In western blot assays, such as electrophoretic separation of proteins, individual proteins can be identified by their antibodies. The immunoassay may be a competitive binding immunoassay in which the analyte competes with the labeled antigen for a limited number of antibody molecules (e.g., radioimmunoassay, EMIT). The immunoassay may also be noncompetitive, in which antibodies are present in excess and labeled. As the analyte-antigen complex increases, the amount of labeled antibody-antigen complex may also increase (e.g., ELISA). If they are produced by injecting an antigen into an experimental animal, or monoclonal antibodies, if they are produced by cell fusion and cell culture techniques, the antibodies may be polyclonal antibodies. In immunoassays, antibodies can be used as reagents specific for analyte antigens.

Without limiting the scope and content of embodiments of the invention, some types of immunoassays are, by way of example only, RIA (radioimmunoassay), enzyme immunoassays such as ELISA (enzyme-linked immunosorbent assay), EMIT (enzyme-enhanced immunoassay), Microparticle Enzyme Immunoassay (MEIA), LIA (luminescence immunoassay), and FIA (fluorescence immunoassay). These techniques can be used to detect biological substances in nasal samples. The antibody can be used as a primary antibody or a secondary antibody. They may be labelled with a radioisotope (e.g. 125I), a fluorescent dye (e.g. FITC) or an enzyme that catalyses a fluorescent or luminescent reaction (e.g. HRP or AP).

Biotin or vitamin H is a coenzyme that inherits specific affinity for avidin and streptavidin. This interaction makes biotinylated peptides a useful tool for qualitative and quantitative testing in various biotechnological assays. In order to improve biotin/streptavidin recognition by minimizing steric hindrance, it may be necessary to enlarge the distance between biotin and the peptide itself. This can be achieved by coupling a spacer molecule (such as 6-nitrohexanoic acid) between the biotin and the peptide.

Biotin quantification of biotinylated proteins provides a sensitive fluorescence assay to accurately determine the number of biotin labels on the protein. Biotinylated peptides are widely used in a variety of biomedical screening systems that require immobilization of at least one of the interacting substances on streptavidin-coated beads, membranes, slides, or microtiter plates. This assay is based on the displacement of a ligand labeled with a quencher dye from the biotin binding site of an agent. To expose any biotin groups in the multi-labeled protein that are sterically limited and inaccessible to the reagent, the protein may be treated with a protease to digest the protein.

EMIT is a competitive binding immunoassay, avoiding the usual separation steps. This is an immunoassay in which the protein is enzyme-labeled, and the enzyme-protein-antibody complex is enzyme-inactive, enabling quantification of label-free protein. Some embodiments include ELISA assays to analyze differentially expressed genes, including at least PARP. ELISA is based on selective antibodies attached to a solid support and combined with enzyme reactions to produce a system capable of detecting low levels of protein. It is also known as enzyme immunoassay or EIA. The protein is detected by an antibody against the protein, in other words, it is an antigen of the antibody. Monoclonal antibodies are often used.

Such tests may require the antibody to be immobilized on a solid surface, such as the inner surface of a test tube, and the same antibody to be conjugated to an enzyme to be prepared. The enzyme may be an enzyme that produces a colored product from a colorless substrate (e.g., beta-galactosidase). Such testing can be accomplished, for example, by filling a tube with a solution of the antigen to be detected (e.g., protein). Any antigen molecule present may bind to the immobilized antibody molecule. Antibody-enzyme conjugates may be added to the reaction mixture. The antibody portion of the conjugate binds to any antigen molecule previously bound, creating an antibody-antigen-antibody "sandwich". After washing off any unbound conjugate, a substrate solution may be added. After a certain time, the reaction is terminated (for example by adding 1N NaOH) and the concentration of the coloured product formed is measured spectrophotometrically. The intensity of the color is directly proportional to the concentration of the bound antigen.

ELISA methods can also be used to measure antibody concentrations, in which case the culture wells are coated with the corresponding antigen. A solution containing the antibody (e.g., serum) may be added. After it has had sufficient time to bind to the immobilized antigen, an enzyme-conjugated anti-immunoglobulin consisting of the antibody being tested may be added. After washing away unreacted reagents, a substrate may be added. The intensity of the color produced is directly proportional to the amount of enzyme-labeled antibody bound (and thus the concentration of antibody detected).

Some embodiments include radioimmunoassays to analyze the level of differentially expressed genes, including at least PARP. Isotopes can be used to study metabolism, distribution and binding of ligands to target proteins in vivo. Using in vivo¹H、¹²C、¹³C、³¹P、³²S and¹²⁷isotopes of I, e.g.³H、¹⁴C、³²P、³⁵S and¹²⁵I. in the receptor immobilization method on a 96-well plate, a receptor is immobilized in each well by an antibody or a chemical method, and a radiolabeled ligand is added to each well to induce binding. Unbound ligand can be washed away and then quantitated by radioactivity bound ligand or washed out ligandAnalyzed to determine the criteria. Then, the addition of the screening target compound induces a competitive binding reaction with the receptor. If the compound exhibits a higher affinity for the receptor than a standard radioligand, then most of the radioligand will not bind to the receptor and can remain in solution. Thus, by analyzing the amount of bound radioligand (or washed-off ligand), the affinity of the test compound for the receptor can be demonstrated.

When receptors cannot be immobilized on 96-well plates or when ligand binding needs to be performed in solution phase, a membrane filtration method may need to be employed. In other words, after the ligand-receptor binding reaction in solution, if the reaction solution is filtered through nitrocellulose filter paper, small molecules including the ligand may pass through it, and only the protein receptor may remain on the paper. Only the ligand that binds strongly to the receptor may remain on the filter paper and the relative affinity of the added compound can be determined by quantitative analysis of standard radioligands.

Some embodiments include a fluorescence immunoassay for analyzing differentially expressed genes, including at least PARP. Fluorescence-based immunological methods are based on competitive binding between labeled and unlabeled ligands on highly specific receptor binding sites. Fluorescence techniques can be used in immunoassays based on the change in fluorescence lifetime as a function of analyte concentration. This technique can be used in conjunction with a short-lived dye such as Fluorescein Isothiocyanate (FITC) (the donor), whose fluorescence can be quenched by energy transferred to eosin (the acceptor). A wide variety of photoluminescent compounds can be used, such as cyanine,Oxazine, thiazine, porphyrin, phthalocyanine, fluorescent infrared-luminescent polynuclear arene, phycobiliprotein, squarylium compound and organometallic complex, hydrocarbon and azo dye.

Fluorescence-based immunological methods can be, for example, heterogeneous or homogeneous. Heterogeneous immunoassays involve physical separation between bound and free labeled analytes. The analyte or antibody may be attached to a solid surface. This technique may be competitive (for higher selectivity) or non-competitive (for higher sensitivity). Detection may be direct (using only one antibody) or indirect (using a second antibody). Homogeneous immunoassays do not involve physical separation. The dual antibody fluorophore-labeled antigen participates in an equilibrium reaction with an antibody directed to both the antigen and the fluorophore. Labeled and unlabeled antigens may compete with limited anti-antigen antibodies.

Some fluoroimmunoassay methods include simple fluorescent labeling, Fluorescence Resonance Energy Transfer (FRET), Time Resolved Fluorescence (TRF), and Scanning Probe Microscopy (SPM). Simple fluorescent labeling methods can be used to determine receptor-ligand binding and enzyme activity by using the associated fluorescence and as a fluorescent indicator of various physiological changes in vivo, such as pH, ionic concentration and voltage. TRF is a method of selectively measuring lanthanide fluorescence after the emission of other fluorescent molecules has ended. TRF can be used with FRET and the lanthanide series can be either a donor or an acceptor. In scanning probe microscopy, at least one monoclonal antibody is attached to the solid surface, for example during the capture phase, and scanning probe microscopy is used to detect antigen/antibody complexes that may be present on the solid surface. The use of scanning tunneling microscopy eliminates the need for labels that are commonly used in many immunoassay systems to detect antigen/antibody complexes.

The protein identification method comprises the following steps: by way of example only, protein identification methods include low-throughput sequencing by Edman degradation, mass spectrometry techniques, peptide mass fingerprinting, resequencing, and antibody-based analysis. The protein quantitative analysis method comprises fluorescent dye gel staining, labeling or chemical modification methods (i.e. isotope-coded affinity tags (ICATS), binding fraction diagonal chromatography (cofardic)). The purified protein can also be used for the determination of three-dimensional crystal structures, and the method can be used for simulating intermolecular interactions. Common methods for determining three-dimensional crystal structure include X-ray crystallography and nuclear magnetic resonance spectroscopy. Characteristic indications of the three-dimensional structure of proteins can be probed with mass spectrometry. By coupling those portions of the protein that are spatially close but are far apart in sequence by chemical cross-linking, information about the overall structure can be inferred. By tracking the exchange of amide protons with deuterium in the solvent, it is possible to probe the likelihood of the solvent approaching various parts of the protein.

In one embodiment, a fluorescence activated cell sorting system (FACS) is used to identify cells that differentially express the expression of the identified genes, including at least PARP. FACS is a special type of flow cytometry. It provides a method of sorting heterogeneous mixtures of biological cells into two or more containers, one cell at a time, based on the specific light scattering and fluorescence characteristics of each cell. It provides a means of quantitatively recording fluorescent signals from individual cells and physically separating cells of particular interest. In another embodiment, the expression of the identified differentially regulated genes is assessed using a microfluidic-based device.

Mass spectrometry can also be used to characterize the expression of differentially regulated genes (including at least PARP) from patient samples. Two methods of whole protein ionization are electrospray ionization (ESI) and matrix-assisted laser desorption/ionization (MALDI). First, intact proteins are ionized by either of the two methods described above and then introduced into a mass spectrometer. Second, the protease is digested into smaller peptides with reagents such as trypsin or pepsin. Other proteolytic digestants may also be used. The collected peptide product is then introduced into a mass spectrometer. This method is commonly referred to as a "bottom-up" protein analysis mode.

Whole protein mass spectrometry is performed using time of flight (TOF) mass spectrometry or fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry. The instrument used for peptide mass spectrometry is quadrupole ion trap mass spectrometry. Multi-stage quadrupole-time-of-flight and MALDI time-of-flight instruments can also be used for this application.

There are two methods for isolating proteins or their enzymatically digested peptide products. The first method separates whole proteins and is called two-dimensional gel electrophoresis. The second method, high performance liquid chromatography, was used to separate the peptide product after enzymatic digestion. In some cases, it may be necessary to combine these two techniques.

Mass spectrometers can be used to identify proteins in two ways. Peptide mass spectrometry uses the mass of a proteolytic peptide, which is generated as a result of digestion of a series of known proteins, as input to search a database of predicted masses. If a protein sequence in the reference series matches a significant number of predicted masses to the experimental values, there is some evidence that this protein is present in the original sample.

Tandem mass spectrometry is also a method for identifying proteins. Collision induced dissociation is used in most applications to generate a set of fragments from a particular peptide ion. This cleavage process mainly results in cleavage products that break along peptide bonds.

Many different algorithms for identifying peptides and proteins have been described for tandem mass spectrometry (MS/MS), peptide sequencing from new sequences and sequence tag-based searches. One option that integrates the features of comprehensive data analysis is PEAKS. Other existing mass spectrometry software includes: peptide fragment fingerprints SEQUEST, Mascot, OMSSA and X! Tandem).

Proteins can also be quantitatively analyzed by mass spectrometry. Generally, the stable (e.g. non-radioactive) heavier carbon (C) will be¹³) Or nitrogen (N)¹⁵) Isotopes are added to one sample, while the other sample is supplied with a lighter isotope (e.g. C)¹²And N¹⁴) And (4) marking. The two samples were mixed prior to analysis. Due to their differences in mass, peptides derived from different species can be distinguished. The peak intensity ratio corresponds to the relative abundance ratio of the peptide (and protein). Isotopic labeling is carried out by SILAC (stable isotopic labeling with amino acids during cell culture), trypsin catalyzed O¹⁸Label, ICAT (isotope-coded affinity label), ITRAQ (isotope label for relative and absolute quantification). "semi-quantitative" mass spectrometry can be performed with the sample unlabeled. Typically, this is done using MALDI analysis (using linear mode). The peak intensity, or peak area, of each molecule (typically a protein) is related to the amount of protein in the sample. However, the individual signals depend on the major structure of the protein, the complexity of the sample, and the set-up of the instrument 。

N-terminal sequencing facilitates identification of unknown proteins, confirmation of recombinant protein identity and fidelity (reading frame, translation starting point, etc.), interpretation of NMR and crystal structure data, display of degree of identity between proteins, or provide data for design of synthetic peptides for antibody production, etc. N-terminal sequencing utilizes Edman degradation chemistry to remove amino acid residues from the N-terminus of a protein in order and identify them by reverse phase HPLC. Sensitivity can reach the level of hundreds of femtomoles, and long sequence reads (20-40 residues) can often be obtained from tens of picomoles of starting material. Pure proteins (> 90%) can yield data that is easily interpretable, but less pure protein mixtures can also provide useful data, depending on the exact interpretation of the data. N-terminally modified (in particular acetylated) proteins cannot be sequenced directly, since the absence of free primary amino groups hampers edman chemistry. However, limited hydrolysis of the blocking protein (e.g., with cyanogen bromide) may allow the production of amino acid mixtures in each instrumental cycle, and database analysis can be performed to interpret meaningful sequence information. C-terminal sequencing is a post-translational modification that affects the structure and activity of proteins. A wide variety of conditions can be associated with impaired protein processing, and C-terminal sequencing provides another means to study protein structure and processing mechanisms.

Identification of diseases treatable by modulators of differentially regulated genes

Some embodiments relate to diseases treatable by modulators of co-regulated genes, comprising identifying in a sample from a patient the expression level of a co-regulated gene (including at least PARP), making a decision regarding identifying the disease treatable by a modulator of a co-regulated gene, wherein the decision is made based on the expression level of a co-regulated gene (including at least PARP). The identification of the level of a co-regulated gene includes analysis of RNA, analysis of the level of a protein expressed by the regulated gene and/or analysis of the activity of said protein. When the level of a regulated gene is up-regulated in a disease, the disease can be treated with an inhibitor of the co-regulated gene.

In other embodiments, the level of the modulated gene is determined in a sample from a patient population and compared to a sample from a normal population to correlate any change in the expression level of the modulated genes (including at least PARP) with the presence of disease. Identification and analysis of the levels of these regulated genes may also include analysis of RNA, analysis of the levels of proteins expressed by the regulated genes, and analysis of the activity of these proteins. When the expression level of the regulated gene is increased in a plurality of samples from a patient population (as compared to samples from a normal population), the disease can be treated with an inhibitor of the regulated gene. In some embodiments, an increase of at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, or more may indicate that the upregulation of the co-regulated genes is sufficiently relevant for a particular disease or group of diseases.

In one embodiment, up-regulation of the identified regulated genes serves as an embodiment of BRCA-deficient cancer, in particular PARP up-regulation. Accordingly, the methods can be used to identify, for example, BRCA-mediated cancers that can be treated by modulators of the identified regulated genes, including PARP inhibitors and modulators of co-regulated expressed genes including IGF1, IGF2, IGFR, EGFR, mdm2, Bcl2, ETS1, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK1, VAV3, AURKA, ERBB3, MIF, VEGF, CDK1, 2, CDK9, farnesyl transferase, UBE2A, UBE2D2, UBE2G1, USP28, or UBE 2S. The identification of the expression level of the co-regulated gene may comprise one or more comparisons with a reference sample. The reference sample may be obtained from the same patient or a different patient (who is either unaffected by the disease (e.g., a normal patient) or a patient). The reference sample may be obtained from one patient, multiple patients, or generated synthetically. The authentication may also include a comparison of the authentication data to a database. One embodiment relates to identifying the level of regulated genes (including at least PARP) in a patient afflicted with a disease and correlating the expression levels of the same group of co-regulated expressed genes in normal patients. In some embodiments, the correlating step of the levels of genes whose expression is commonly regulated is performed by a software algorithm. The data generated may be converted to computer readable form; and performing an algorithm for classifying the data based on the user-entered parameters for monitoring signals representative of the expression level of the regulated gene in the diseased patient or patient population and corresponding signals representative of the expression level in the normal patient or patient population.

The identification and analysis of the expression levels of regulated genes (including at least PARP), identified by the methods described herein, has a number of therapeutic and diagnostic applications. Clinical applications include, for example, monitoring of disease, differentiating disease stages to know prognosis, selection of therapies, such as treatment with PARP inhibitors and modulators of genes whose expression is commonly modulated, and/or predicting treatment response, disease stage, identification of disease progression, prediction of treatment efficacy, monitoring of patient course (e.g., prior to disease onset), prediction of adverse response, monitoring of treatment-related efficacy and toxicity, and detection of relapse.

The identification of the expression levels of regulated genes, including at least PARP, in a patient or patient population, and the identification of diseases that can be subsequently treated by PARP inhibitors and modulators of the regulated genes, as disclosed herein, can be used to enable or aid in the drug development of therapeutic drugs. Identification of the expression level of a gene whose expression is modulated, for example, can be used to diagnose disease in patients enrolled in a clinical trial (e.g., in a patient population). Identification of the expression level of genes whose expression is modulated, including at least PARP, may indicate a disease state in a patient undergoing treatment in a clinical trial and indicate a change in state during treatment. Identification of the expression level of a gene whose expression is modulated can demonstrate the efficacy of treatment with a modulator of that modulated expressed gene and can be used to satisfy patients according to their response to various treatments.

The methods described herein can be used to identify a disease state in a patient or patient population. In one embodiment, the method is used to detect early stages of disease. In other embodiments, the method is used to stratify the identified disease. In certain embodiments, the patient, a health care provider, such as a physician or nurse, or a health care manager, uses the expression levels of identified genes whose expression is modulated (including at least PARP) in the patient to make a diagnosis, prognosis, and/or select treatment options, such as treatment with PARP inhibitors. In other embodiments, the health care provider and the patient can use the expression levels of each identified regulated gene obtained from the patient population, and can also make diagnostic, prognostic, and/or selection treatment options, such as combination treatment using a PARP inhibitor and a modulator of a co-regulated expressed gene.

In other embodiments, the methods described herein can be used to predict the likelihood of any individual or patient population responding to a particular treatment, to select a treatment, or to foreknowledge of possible side effects of treatment on a particular individual. Also, the method can be used to assess the efficacy of a treatment over time. For example, a biological sample may be obtained from a patient over a period of time while undergoing treatment. The expression levels of each identified gene in a set of gene targets in different samples can be compared to each other to determine the efficacy of the treatment. Likewise, the methods described herein can be used to compare the efficacy of different disease treatments and/or responses to one or more treatments in different populations (e.g., race, family history, etc.).

In some embodiments, at least one step of the methods described herein is performed using a computer as shown in fig. 2. FIG. 2 illustrates and is a computer for performing selected operations associated with the methods described herein. The computer 200 includes a central processor 201 connected to an input/output device 202 via a common bus 203. The input/output devices 202 may include a keyboard, mouse, scanner, data port, television monitor, liquid crystal display, printer, and the like. Storage 204 in the form of primary and/or secondary storage is also connected to the common bus 203. These components of fig. 2 represent features of a standard computer. The standard computer was programmed according to the methods described herein. In particular, the computer 200 may be programmed to perform the operations of the various methods described herein.

The memory 204 of the computer 200 may store an authentication module 205. In other words, the authentication module 205 may perform the operations associated with steps 102, 103, and 104 of FIG. 1. The term "identification module" as used herein includes, but is not limited to, analyzing the expression level of regulated genes (including at least PARP) in a patient sample; optionally, comparing the expression level in the test sample to the expression level in the reference sample; identifying the expression level of each identified gene whose expression is commonly regulated in the sample; and further identifying diseases treatable by the combination of a PARP inhibitor and a modulator of a gene whose expression is co-regulated. The identification module can also include a decision module, wherein the decision module includes instructions executable to make a decision regarding identifying a disease treatable by a modulator of a gene whose expression is commonly modulated and/or to provide a conclusion regarding the disease to a patient, a health care provider, or a health care manager. The execution code of the authentication module 205 may utilize any digital technique to perform the comparison and diagnosis.

Some embodiments include a computer readable medium using information about a disease treated by a modulator of an identified co-regulated expressed gene (including at least PARP) in a patient, the information obtained by: identifying the expression level of each identified co-regulated expressed gene (including at least PARP) in the patient sample and making a decision regarding treatment of the disease with the identified modulator of the co-regulated expressed gene based on the expression level of each identified co-regulated expressed gene. The medium may comprise a reference pattern of one or more expression levels of each identified gene in the sample that together regulate expression. The reference pattern may be used for comparison with a pattern obtained from a test patient, and an analysis of the disease may be made based on the comparison. The reference pattern may be obtained from normal patients, i.e. individuals without disease, patients with non-constant levels of disease, patients with diseases of varying severity. These reference patterns can be used for diagnosis, prognosis, assessing the efficacy of treatment, and/or determining the severity of a disease state in a patient. The methods described herein also include sending, between one or more computers, information about the expression levels of each identified co-regulated expressed gene in a patient sample and/or a decision to identify a disease that can be treated by a modulator or inhibitor described herein, such as co-internet use.

Disease and disorder

A variety of diseases include, but are not limited to, cancer types including adrenocortical carcinoma, anal carcinoma, aplastic anemia, bile duct carcinoma, bladder carcinoma, bone metastases, adult CNS brain tumors, childhood CNS brain tumors, breast carcinoma, giant lymph node hyperplasia, cervical carcinoma, childhood non-Hodgkin's lymphoma, colon and rectal cancer, endometrial carcinoma, esophageal carcinoma, familial Ewing's tumor, eye cancer, gall bladder cancer, gastrointestinal carcinoid tumors, gastrointestinal stromal tumors, gestational trophoblastic disease, Hodgkin's disease, Kaposi's sarcoma, kidney carcinoma, laryngeal carcinoma and hypopharynx cancer, acute lymphocytic leukemia, acute myelocytic leukemia, childhood leukemia, chronic lymphocytic leukemia, chronic myelocytic leukemia, liver carcinoma, lung carcinoid tumor, non-Hodgkin's lymphoma, male breast carcinoma, malignant mesothelioma, multiple myeloma, and leukemia, Myelodysplastic syndrome, cancer of the nasal cavity and sinuses, nasopharyngeal carcinoma, neuroblastoma, cancer of the oral cavity and oropharynx, osteosarcoma, ovarian cancer, pancreatic cancer, penile cancer, pituitary tumor, prostate cancer, retinoblastoma, rhabdomyosarcoma, salivary gland carcinoma, sarcoma (adult soft tissue carcinoma), melanoma skin cancer, non-melanoma skin cancer, gastric cancer, testicular cancer, thymus cancer, thyroid cancer, uterine sarcoma, vaginal cancer, vulval cancer, waldenstrom's macroglobulinemia, chronic lymphocytic leukemia and reactive lymphoid hyperplasia.

Diseases include angiogenesis in cancer, inflammation, cardiovascular diseases, degenerative diseases, CNS diseases, autoimmune diseases and viral diseases, including HIV. The compounds described herein are also efficacious in the cellular regulation of pathogens. Some viral diseases are, but are not limited to, Human Immunodeficiency Virus (HIV), herpes simplex virus types 1 and 2, and Cytomegalovirus (CMV), a co-infectious virus of dangerous HIV.

Some examples of diseases are illustrated herein, but are not intended to limit the scope of the embodiments of the invention, and other diseases known in the art may exist and are also included within the scope of the embodiments of the invention.

Examples of cancer

Examples of cancer include, but are not limited to, lymphoma, carcinoma, and hormone-dependent tumors (e.g., breast, prostate, or ovarian cancer). Abnormal cell proliferative diseases or cancers that can be treated in adults or children include solid/malignant tumors, tumors of local progression, human soft tissue sarcomas, metastatic cancers including lymphatic metastases, hematological malignancies including multiple myeloma, acute and chronic leukemias and lymphomas, head and neck cancers including oral, laryngeal and thyroid cancers, lung cancers including small cell and non-small cell cancers, breast cancers including small cell and ductal cancers, gastrointestinal cancers including esophageal, gastric, colon, colorectal cancers and polyps associated with colorectal neoplasias, pancreatic, liver, urinary tract, including bladder and prostate cancers, malignancies of the female reproductive tract including ovarian, uterine (including endometrial) and solid tumors in follicles, renal cancers including renal cell carcinoma, brain cancers including endogenous brain tumors (intrinsic brain tumors), Neuroblastoma, astrocytoma, glioma, metastatic tumor that invades the central nervous system, bone cancer including osteoma, skin cancer including malignant melanoma, human skin keratinocyte progressive tumor, squamous cell carcinoma, basal cell carcinoma, hemangiopericyte tumor, and kaposi's sarcoma.

In some embodiments, the cancer comprises colon adenocarcinoma, esophageal adenocarcinoma, hepatocellular carcinoma, squamous cell carcinoma, pancreatic adenocarcinoma, islet cell carcinoma, rectal adenocarcinoma, gastrointestinal stromal tumor, gastric adenocarcinoma, adrenal cortical cell carcinoma, follicular carcinoma, papillary carcinoma, breast carcinoma, ductal carcinoma, lobular carcinoma, intraductal carcinoma, mucinous carcinoma, phyllodes tumor, ovarian adenocarcinoma, endometrial adenocarcinoma, granulosa cell tumor, mucinous cystadenocarcinoma, cervical adenocarcinoma, vulval squamous cell carcinoma, basal cell carcinoma, prostate adenocarcinoma, giant cell tumor of bone, osteosarcoma, laryngeal carcinoma tumor, lung adenocarcinoma, kidney adenocarcinoma, bladder carcinoma, and wilms' tumor.

In another embodiment, the cancer comprises a mullerian mixed tumor of the endometrium, a mixed infiltrative tumor of the lactiferous duct and lobule, wilms' tumor, mullerian mixed tumor of the ovary, serous cystadenocarcinoma, ovarian adenocarcinoma (papillary serous type), ovarian adenocarcinoma (endometrioid type), breast infiltrative lobular carcinoma metastasis, testicular seminoma, benign nodular hyperplasia of the prostate, squamous cell carcinoma of the lung, large cell carcinoma of the lung, adenocarcinoma of the endometrium (endometrioid type), ductal carcinoma of the endometrium, basal cell carcinoma of the skin, infiltrative lobular carcinoma of the breast, fibrocystic disease, fibroadenoma, glioma, chronic myeloid leukemia, hepatocellular carcinoma, mucinous carcinoma, schwannoma, transitional cell carcinoma of the kidney, hashimoto thyroiditis, metastatic ductal infiltrative carcinoma of the breast, esophageal adenocarcinoma, thymoma, phyllodes tumor, rectal adenocarcinoma, metastasis of the endometrium, carcinoma of the breast, testicular cancer, melanoma, Osteosarcoma, colon adenocarcinoma, papillary thyroid carcinoma, leiomyoma, and gastric adenocarcinoma.

Invasive ductal carcinoma of the breast:

it has previously been shown that expression of PARP1 is increased in breast Invasive Ductal Carcinoma (IDC) compared to controls. See example 2 and fig. 5 herein, and U.S. application 11/818,210. For example, in more than two-thirds of IDC cases, PARP1 expression exceeds the 95% upper confidence limit ("overexpression") for the species of the control non-diseased matched normal population. IDC of the Estrogen Receptor (ER) -negative and Her 2-neu-negative subclasses has PARP1 overexpression in approximately 90% of tumors.

In addition, breast cancer patients also have increased levels of commonly regulated genes, including IGF 1-receptor, IGF-1 and EGFR. Other co-regulated genes whose expression is up-regulated by a minimum of 2-fold compared to controls include CEACAM6, CTSD, DHTKD1, DNAJC1, FADS2, GLUL, HSPB1, HMGB3, G1P2, IFI27, KPNA2, MMP9, MCM4, MALAT1, MUC1, MX1, NAT1, NUCKS, NUSAP1, OLR1, PSENEN, RAB31, SPP1, SORD, SQLE, TSPAN13, TSTA3, TPD52, and UBE 2S.

Thus, in one aspect, IDC breast cancer patients are treated with a combination of a PARP modulator and modulators of other co-modulated genes including IFG 1-receptor, IGF-1, EGFR, CEACAM6, CTSD, DHTKD1, DNAJC1, FADS2, GLUL, HSPB1, HMGB3, G1P2, IFI27, KPNA2, MMP9, MCM4, MALAT1, MUC1, MX1, NAT1, NUCKS, NUSAP1, OLR1, PSENEN, RAB31, SPP1, SORD, SQLE, TSPAN13, TSTA3, TPD52, and UBE 2S. The combination therapy includes at least one PARP inhibitor. In addition, the combination therapy includes a modulator of at least one co-regulated gene. In one embodiment, PARP expression and ER and/or Progesterone Receptor (PR) and/or Her2-neu status are assessed prior to administration of a combination treatment of a PARP inhibitor and a modulator of a co-regulated gene. In one embodiment, the combination therapy is used to treat IDC of the estrogen receptor-negative and Her 2-neu-negative subclasses. In another embodiment, the combination therapy is used to treat cancers for which anti-hormonal agent is not effective (e.g., anti-estrogen or anti-progesterone) or anti-Her 2-neu treatment. In another embodiment, the combination therapy is used to treat triple negative breast cancer, such as triple negative invasive ductal carcinoma.

Lobular cancer of mammary gland infiltration

Breast invasive lobular cancer patients show increased levels of PARP expression and co-regulated expressed genes, including genes of the IGF 1-receptor pathway (including IGF1, IGF2 and EGFR). Other co-regulated genes whose expression is up-regulated by at least 2-fold compared to controls include the BGN, BASP1, CAP2, DDX39, KHSRP, LASS2, MLPH, NUSAP1, OLR1, GART, PYGB, PPP2R4, RAB31, SEMA3F, SFI1, SH3GLB2, SORD, TRPS1, B4GALT2, and vav3 oncogenes.

Thus, in one aspect, breast invasive lobular cancer patients are treated with a combination of a PARP modulator and a modulator of other co-modulated genes including IFG 1-receptor, IGF1, IGF2, EGFR, BGN, BASP1, CAP2, DDX39, KHSRP, las 2, MLPH, NUSAP1, OLR1, GART, PYGB, PPP2R4, RAB31, SEMA3F, SFI1, SH3GLB2, SORD, TRPS1, B4GALT2, and vav3 oncogenes. The combination therapy includes at least one PARP inhibitor. In addition, the combination therapy includes a modulator of at least one co-regulated gene.

Cancer of three yin

In one embodiment, triple negative cancer is treated with a combination therapy of a PARP modulator and a modulator of a co-regulated gene. The level of PARP and other identified co-regulated genes is assessed in triple negative cancers and if overexpression of the identified co-regulated genes is observed, the cancer is treated with a combination of a PARP inhibitor and a modulator of at least one co-regulated gene of expression. "triple negative" breast cancer refers to tumors that lack receptors for the hormones estrogen (ER-negative) and progesterone (PR-negative) and for the protein HER 2. This makes them resistant to some potent anticancer drugs such as tamoxifen, aromatase inhibitors and herceptin. Surgery and chemotherapy are standard treatment options for most forms of triple negative cancer. In one embodiment, standard treatment for triple negative cancers is combined with a combination therapy of a PARP modulator and a modulator of a co-regulated gene to treat these cancers.

Ovarian adenocarcinoma

Ovarian adenocarcinoma patients show increased levels of PARP expression and co-regulated genes of the IGF 1-receptor pathway (e.g., IGF1, IGF2, and EGFR). Other commonly regulated genes that are up-regulated by at least 2 fold as compared to a control include ACLSL1, ACSL3, AK3L1, ARFGEF1, ADM, AOF1, ALOX5, ATP5G 5, ATP5J 5, ATP2A 5, ATP11 5, ATP6V0 5, AKIIP, BCL2L 5, BACE 5, NSE 5, CELSR 5, CHST 5, CPD, CPT1 5, CTSB, CD5, CDS 5, CTS 5, LFSF 5, CSPG 5, CRR 5, CBMYP, CN3672, CXXC5, DDGF 5, DDP 5, PGNFSF 5, PGNFP 5, PGNFDGP 5, PGNFP 5, PGNFT 5, PG3672, PGNFP 5, PGNFT 5, PG3672, PGNFT 5, PG3672, PGNFDE 5, PG3672, PGNFP 5, PGNFDE 5, PG3672, PGNFDE 5, PG3672, PGNFDE 5, PG3672, SRD5A2L, SDC4, STX18, TSPAN13, TYMS, TPI1, TNFAIP2, YWHAB, YWHAZ, UBE2S, B3GNT1, GALNT4, GALNT7, VEGF, VAV3, ERBB3, VDAC1, or LYN.

Thus, in one aspect, ovarian adenocarcinoma cancer patients are treated with a combination of a PARP modulator and modulators of other co-modulated genes including IFG 1-receptor, IGF1, IGF2, EGFR, ACLSL1, ACSL3, AK3L1, ARFGEF1, ADM, AOF1, ALOX5, ATP5G3, ATP5J2, ATP2a2, ATP11A, ATP6V0B, AKIIP, BCL2L1, BACE2, NSE2, CELSR2, CHST6, CPD, CPT1B, CTSB, CD B, CDs B, CXCR B, cksfsf B, CSPG 72, 36r B, pcdfnpt B, pgp B, pgpdnpddp B, pgt B, pgpdt B, pgt B, pgt B, pgt B, 36, P4HB, PTGS1, PSMD14, PSMB3, PPP1CA, PDXK, PP, PKM2, RAB10, RAB11FIP1, RAB3IP, RACGAP1, RANBP1, RAN, RGS19IP1, RDH10, SRPK1, SORD, SAT, SGPL1, SGPP2, ST6GAL1, SRD5A2L, SDC4, STX18, TS 13, TYMS, TPI1, TNFAIP2, YWHAB, YAZGALVWH, UBE2S, B3GNT1, GALNT4, GALNT7, VEGF, VAV3, ERBB3, VDAC1, or LYN. The combination therapy includes at least one PARP inhibitor. In addition, the combination therapy includes a modulator of at least one co-regulated gene.

Endometrium Mullerian mixed tumor

Endometrial mullerian mixed tumors show increased levels of PARP expression and co-regulated genes that are up-regulated by at least 2-fold compared to controls and include ATF5, ADRM1, ALDH18a1 AKR1B1, BACH, CKS1B, CSH2, CRR9CXXC5, DNAJA1, ENO1, EME1, FBXO45, FTL, FTLL1, GGH, GPI, GMPS, ILF2, MAD2L1, MCM4, MAGED 4, MAP4K4, psmh 4, MARCKS, NRAS, NNT, NY-REN-41, PNK 4, PRCC, PCTK 4, PGD, PGK 4, PLD 4, plpl 4, PSMD4, PSMA-r 4, psm 4, psnrap 4, psrp 4, srubb 4, vsrp 4, srubb 4, or vdr 4.

Thus, in another aspect, endometrial mullerian mixed tumor patients are treated with a combination of a PARP modulator and a modulator of other co-modulated genes including ATF5, ADRM1, ALDH18a1 AKR1B1, BACH, CKS1B, CSH2, CRR9CXXC5, DNAJA1, ENO1, EME1, FBXO45, FTL, FTLL1, GGH, GPI, GMPS, ILF2, MAD2L1, MCM4, MAGED1, MAP4K4, psmh 2, MARCKS, NRAS, NNT, NY-REN-41, PNK 2, PRCC, PCTK 2, PGD, PGK 2, PLD 2, plplplp 2, PSMD 2, PSMA-rat 2, psm 2, psnrb 2, psrp 2, srubb 2, psrp 2, psf 2, srubb 2, vsr 2, vsrp 2, tfr 2, or vdr 2.

Seminoma of testis

Testicular seminoma patients show increased levels of PARP expression and co-regulated genes that are up-regulated by at least 2-fold compared to controls, and include ARL5, ALPL, APG5L, RNPEP, ATP11C, ABCD4, CACNB3, CD109, CDC14B, CXXC6, ELOVL6, GRB10, HSPCB, inp 5F, KLF4, MOBKL1A, MSH2, PLOD1, PTPN12, ST6GALNAC2, SDC2, TIAM1, TSPAN13, or ERBB 3.

Thus, in another aspect, testicular seminoma patients are treated with a combination of a PARP modulator and a modulator of other co-modulated genes including ARL5, ALPL, APG5L, RNPEP, ATP11C, ABCD4, CACNB3, CD109, CDC14B, CXXC6, ELOVL6, GRB10, HSPCB, inp 5F, KLF4, MOBKL1A, MSH2, PLOD1, PTPN12, ST6GALNAC2, SDC2, TIAM1, TSPAN13, or ERBB 3.

Squamous cell carcinoma of lung

Lung squamous cell carcinoma shows increased levels of PARP expression and co-regulated genes that are up-regulated by at least 2-fold compared to controls and includes PTS, AK3L2, AKR1C1, AKR1C2, AKR1C3, ATP2 A3, ABCC 3 CSNK2 A3, CKS 13, CDW 3, CMKOR 3, CSPG 3, CDK 3, DVL3, DUSP 3, ELOVL 3, GGH, GPI, GCLC, GSR, GMPS, HSPB 3, HSPD 3, HPRT 3, HIG 3, IGFBP3, RFC gap 3, MIF, ME 3, MMP 3, MCM 3, MAP3K 3, NQO 3, ODC 3, PPIF, pfif, pfkpd, pgp 3, ahracs, psrat, pst 3, pstxp 3, tptxp 3, tptfr 3, pgr 3, tptfp 3, tptfr 3, tp3672, tptfp 3, pstxp 3, tptfp 3, tp3672, tptfr 3, tp3672, tpr 3, tp3672, tpr 3, tpr 36.

Thus, in another aspect, lung squamous cell carcinoma patients are treated with a combination of a PARP modulator and a modulator of other co-modulated genes including PTS, AK3L2, AKR1C1, AKR1C2, AKR1C3, ATP2 A3, ABCC 3 CSNK2 A3, CKS 13, CDW 3, CMKOR 3, CSPG 3, CDK 3, DVL3, DUSP 3, acell 3, GGH, GPI, GCLC, gsgmpr, HSPB 3, HSPD 3, HPRT 3, HIG 3, IGFBP3, IDH 3, MIF, 3, MCM 3, MAP3K 3, NQO 3, PPIF, pfpt, pgcd, gapp 3, tpsms 3, txp 3, tpp 3, tp.

Adenocarcinoma of lung

Lung adenocarcinomas show increased levels of PARP expression and co-regulated genes that are up-regulated by at least 2 fold compared to controls and include ALDH18a1, AKR1C1, AKR1C2, AKR1C3, ATP2A2, ATP1B1, CPE, CD24, CKS1B, FA2H, GCLC, GFPT1, IGFBP3, IDH2, KMO, LGR4, MIF, MCM4, MTHFD2, NQO1, ODC1, PFKP, PLA2G4A, PSAT1, PLOD2, PDIA4, PDIA6, PDK1, SRD5A2L, SRD5a1, srtyms, UBE2S, UGDH, 7, or UNC5 59 5 CL.

Thus, in another aspect, a lung adenocarcinoma patient is treated with a combination of a PARP modulator and a modulator of other co-regulated genes, including ALDH18a1, AKR1C1, AKR1C2, AKR1C3, ATP2A2, ATP1B1, CPE, CD24, CKS1B, FA2H, GCLC, GFPT1, IGFBP3, IDH2, KMO, LGR4, MIF, MCM4, MTHFD2, NQO1, ODC1, PFKP, PLA2G4A, cs, PSAT1, PLOD2, PDIA4, PDIA6, PDK1, SRD5A2L, SRD5a1, TYMS, UBE2S, UGDH, GALNT7, or UNC5 CL.

Large cell carcinoma of lung

Lung large cell carcinoma patients show increased levels of PARP expression and co-regulated genes that are up-regulated by at least 2-fold compared to controls and include PTS, ATF7IP, AK3L1, AK3L2, ALDH18a1, ATP2a2, DNAJC9, GPR89, HSPD1, HYOU1, LDHA, MIF, MMP9, MBTPS2, MALAT1, MTHFD2, NRAS, PCTK1, PPIF, PFKP, PAICS, PLOD2, PSMB4, PDK1, PKM2, RACGAP1, bp1, RAN, RFC5, SRPK1, SRD5a1, TPI1, or UBE 2S.

Thus, in another aspect, a lung large cell carcinoma patient is treated with a combination of a PARP modulator and a modulator of other co-modulated genes including PTS, ATF7IP, AK3L1, AK3L2, ALDH18a1, ATP2a2, DNAJC9, GPR89, HSPD1, HYOU1, LDHA, MIF, MMP9, MBTPS2, MALAT1, MTHFD2, NRAS, PCTK1, PPIF, PFKP, PAICS, PLOD2, PSMB4, PDK1, PKM2, rac 1, RANBP1, RAN, RFC5, SRPK1, SRD5a1, TPI1, or UBE 2S.

Lymph node non-hodgkin lymphoma

Lymph node non-hodgkin lymphomas show increased levels of PARP expression and co-regulated genes that are up-regulated by at least 2-fold compared to controls and include ANP32E, BCAT1, CD83, CGI-90, CSK, ARPP-19, DDX21, DCK, DHFR, DAAM1, DUSP10, GRHPR, GGA2, GCHFR, HSPA 2, HS2ST 2, HDAC 2, HPRT 2, KPNA2, MAD2L 2, MCM 2, MOBK1 2, MSH2, NUSAP 2, ODC 2, PFTK 2, pl3672, prrt 2, PMS2L 2, PCNA, PTPN 2, RACGAP 2, RNGTT, SNRPD 2, SMS, SGPP 2, scpp 2, scap 2, swss 2, typ-2, TNFSF 2, tmsf 2L 2, tnfp 2, tfn 2, or tfe 2.

Thus, in another aspect, a lymph node non-hodgkin lymphoma patient is treated with a combination of a PARP modulator and a modulator of other co-modulated genes including ANP32E, BCAT1, CD83, CGI-90, CSK, ARPP-19, DDX21, DCK, DHFR, DAAM1, DUSP10, GRHPR, GGA2, GCHFR, HSPA 2, HS2ST 2, HDAC 2, HPRT 2, KPNA2, MAD2L 2, MCM 2, mopsap 361 2, mskrh 2, NUSAP 2, ODC 2, PFTK 2, PLCG2, prgap 2, PMS2L 2, PCNA, PTPN 2, rac3672, rnt 2, SNRPD 2, SMS, SGPP 2, scpp 2, SWAP 2, ssap 2, tpp 2, tpf 2, TNFSF 2, tmsf 2L 2, tmsf 2, or TNFSF 2.

Diffuse large B-cell type of lymph node non-Hodgkin lymphoma

Lymph node non-Hodgkin lymphoma diffuse large B-cell type patients show an increased level of PARP expression and co-regulated expressed genes, which are up-regulated by at least 2 fold compared to a control, and include BPNT, ATIC, ATF, ACADM, ACY1L, BCL, BAG, BCAT, CFLAR, CD, CKS1, CDC5, CPSF, C1QBP, PCIA, CSK, ARPP-19, CDK, DHFR, DLAT, JDA, DUSP, ENO, GSPT, GMNN, GPI, GRHPR, GTPBP, GCHFR, HSPH, HSPE, HSPD, HSPA, HSPCA, RFC, GAP 2ST, HDAC, HRNYMT 1L, HPRT, HIG, INSHA, MADP 2L, MCM-1, MAK, MDH, MDME, RACK, AHBP, PRMBK, ACK, ACY1L, PSRP, PSNK, PSRP, PSNK, PSMP, PSAP, PSCP, PSAP, PSN-41, PSAP, PSN-PCMCAP, PSAP, PSABC, SMS, SGPP1, SCAP2, SWAP70, SMARCC1, SS18, TXNL2, TYMS, TOX, TRIP13, TBL1XR1, TFRC, TKT, TPI1, TNFSF9, YWHAE, UCHL5, USP28, UBE2A, UBE2D2, UBE2G1, UBE2S, UTP14A, TALA, LYN.

Thus, in another aspect, lymph node non-Hodgkin lymphoma diffuse large B-cell type patients are treated with a combination of a PARP modulator and a modulator of other co-regulated genes including BPNT, ATIC, ATF, ACADM, ACY1L, BCL, BAG, BCAT, CFLAR, CD, CKS1, CDC5, CPSF, C1QBP, PCIA, CSK, ARPP-19, CDK, DHFR, DAAT, DNAD, DUSP, ENO, GSPT, GMNN, GPI, GRHPR, GTPBP, GCHFR, HSPH, HSPE, HSPD, HSPA, HSPCA, HSPCB, HS2ST, RFC, HRMT1L, HPLDRT, HIPG, INSIG, HAH, MAD, MADD 2L, MADP-1, MCM, MDH, MCTM, MCTS, MBK, MTKPBP, AHAP, PHAKBP, PRACK 1L, PRLDRT, PRPSAP, PRBK, PRNCK, PRPSAP, RBPCK, PRPSAP, PRNCK, PRPSAP, RPSAP, PSAP, SGPP1, SCAP2, SWAP70, SMARCC1, SS18, TXNL2, TYMS, TOX, TRIP13, TBL1XR1, TFRC, TKT, TPI1, TNFSF9, YWHAE, UCHL5, USP28, UBE2A, UBE2D2, UBE2G1, UBE2S, UTP14A, TALA, LYN.

Hepatocellular carcinoma

Hepatocellular carcinomas show increased PARP expression and levels of co-regulated genes that are up-regulated by at least 2-fold compared to controls and include AGPAT5, ACSL3, ALDOA, ASPH, ATP1a1, CPD, FZD6, GBAS, HTATIP2, IRAK1, KMO, LPGAT1, MMP9, MCM4, ODC1, PTGFRN, RACGAP1, ROBO1, SPP1, SHC1, TSPAN13, nrtxd 1, TKT, or UBE 2S.

Thus, in one aspect, hepatocellular carcinoma patients are treated with a combination of PARP modulators and modulators of other co-regulated genes, including AGPAT5, ACSL3, ALDOA, ASPH, ATP1a1, CPD, FZD6, GBAS, HTATIP2, IRAK1, KMO, LPGAT1, MMP9, MCM4, ODC1, PTGFRN, RACGAP1, ROBO1, SPP1, SHC1, TSPAN13, TXNRD1, TKT, or UBE 2S.

Papillary thyroid carcinoma follicular variant

Papillary thyroid carcinoma follicular variant patients show also increased levels of PARP expression and co-regulated genes that are up-regulated by at least 2-fold compared to controls and include CAMK2D, CTSB, DUSP6, EPS8, FAS, MGAT4B, WIG1, PERP, PLD3, RAB14, SSR3, ST3GAL5, or TPP 1.

Thus, in another aspect, papillary thyroid cancer follicular variant patients are treated with a combination of PARP modulators and modulators of other co-regulated genes, including CAMK2D, CTSB, DUSP6, EPS8, FAS, MGAT4B, WIG1, PERP, PLD3, RAB14, SSR3, ST3GAL5, or TPP 1.

Malignant melanoma of skin

Malignant melanoma of the skin shows increased expression of PARP and levels of co-regulated genes that are up-regulated by at least 2-fold compared to controls and includes EME1, FBXO7, GPR89, GANAB, HSPD1, HSPA8, HPS5, LDHB, MAD2L1, MLPH, NBS1, NEK6, NME1, sap1, PAICS, PSMA5, RFC3, AHCY, nunu, SMC4L1, SAT, TYMS, TKT, or TRA 1.

Thus, in another aspect, a patient with malignant melanoma on the skin is treated with a combination of a PARP modulator and a modulator of other co-regulated genes including EME1, FBXO7, GPR89, GANAB, HSPD1, HSPA8, HPS5, LDHB, MAD2L1, MLPH, NBS1, NEK6, NME1, NUSAP1, PAICS, PSMA5, RFC3, AHCY, SMC4L1, SAT, TYMS, TKT, or TRA 1.

Basal cell carcinoma of skin

Basal cell carcinoma of the skin shows increased expression of PARP and levels of co-regulated genes that are up-regulated by at least 2-fold compared to controls and include ACY1L2, CHSY1, CDC42EP4, CCAR1, CSPG2, CXADR, CXXC6, CDK6, DDIT4, GPR56, HSPCA, HSPCAL3, HS2ST1, IGSF4, KTN1, KMO, MARCKS, NNT, PHCA, PAFAH1B1, FLJ23091, RFC3, RBBP4, SORL1, yhrae, USP47, or UBE 2S.

Thus, in another aspect, a skin basal cell carcinoma patient is treated with a combination of a PARP modulator and a modulator of other co-modulated genes including ACY1L2, CHSY1, CDC42EP4, CCAR1, CSPG2, CXADR, CXXC6, CDK6, DDIT4, GPR56, HSPCA, HSPCAL3, HS2ST1, IGSF4, KTN1, KMO, MARCKS, NNT, PHCA, PAFAH1B1, FLJ23091, RFC3, RBBP4, SORL1, yhwheel, USP47, or UBE 2S.

Examples of inflammation

Examples of inflammation include, but are not limited to, systemic inflammatory disorders and disorders associated locally with the migration and attraction of monocytes, leukocytes and/or neutrophils. Inflammation may result from infection by pathogenic organisms (including gram-positive bacteria, gram-negative bacteria, viruses, fungi, and parasites such as protozoa and helminths), graft rejection (including rejection of solid organs such as kidney, liver, heart, lung, or stratum corneum, and rejection of bone marrow transplants, including Graft Versus Host Disease (GVHD)), or from localized chronic or acute autoimmune reactions or allergies. Autoimmune diseases include acute glomerulonephritis; rheumatoid arthritis or reactive arthritis; chronic glomerulonephritis; inflammatory bowel diseases such as Crohn's disease, ulcerative colitis and necrotizing enterocolitis; syndrome associated with granulocyte infusion; inflammatory dermatoses such as contact dermatitis, atopic dermatitis, psoriasis; systemic Lupus Erythematosus (SLE), autoimmune thyroiditis, multiple sclerosis, and some forms of diabetes, or any other autoimmune state in which the pathology caused by the patient's own immune system challenge prevents destruction. Allergies include allergic asthma, chronic bronchitis, acute and delayed hypersensitivity reactions. Systemic inflammatory disease states include inflammation associated with trauma, burns, reperfusion following an ischemic event (e.g., an embolic event in the heart, brain, intestine or peripheral blood vessels, including myocardial infarction and stroke), sepsis, ARDS or multiple organ dysfunction syndrome. Inflammatory cell replenisher is present in atherosclerotic plaques.

In one embodiment, provided herein is a method of treating inflammation using a modulator of PARP and a modulator of another co-regulated gene of inflammation. Inflammation includes, but is not limited to, non-hodgkin's lymphoma, wegener's granulomatosis, hashimoto's thyroiditis, hepatocellular carcinoma, thymus atrophy, chronic pancreatitis, rheumatoid arthritis, reactive lymphoid hyperplasia, osteoarthritis, ulcerative colitis, papillary carcinoma, crohn's disease, ulcerative colitis, acute cholecystitis, chronic cholecystitis, cirrhosis, chronic sialadenitis, peritonitis, acute pancreatitis, chronic gastritis, endometriosis, acute cervicitis, chronic cervicitis, lymphoid hyperplasia, multiple sclerosis, secondary to idiopathic thrombocytopenic purpura hypertrophy, primary IgA nephropathy, systemic lupus erythematosus, psoriasis, emphysema, chronic pyelonephritis, and chronic cystitis.

Examples of endocrine and neuroendocrine disorders

Examples of endocrine disorders include diseases of the adrenal gland, breast, gonads, pancreas, parathyroid, pituitary, thyroid, dwarfism, and the like. Adrenal disorders include, but are not limited to, addison's disease, hirsutism (hirsutism), cancer, multiple endocrine neoplasia, congenital adrenal hyperplasia, and pheochromocytoma. Breast diseases include, but are not limited to, breast cancer, fibrocystic breast disease, and gynecomastia. Gonadal disorders include, but are not limited to, congenital adrenal hyperplasia, polycystic ovary syndrome, and turner's syndrome. Pancreatic disorders include, but are not limited to, diabetes (type I and type II), hypoglycemia, and insulin resistance. Parathyroid disorders include, but are not limited to, hyperparathyroidism and hypoparathyroidism. Pituitary diseases include, but are not limited to, acromegaly, Cushing's syndrome, diabetes insipidus, Anematolite's syndrome, hypopituitarism and prolactinoma. Thyroid disorders include, but are not limited to, cancer, goiter, hyperthyroidism, hypothyroidism, nodules, thyroiditis, and Wilson's syndrome. Examples of neuroendocrine disorders include, but are not limited to, depression and anxiety disorders associated with hormonal imbalance, menstrual epilepsy, menopause, menstrual migraine, genitourinary disorders, gastrointestinal disorders such as, enteroendocrine tumors including carcinoids, gastrinomas, and somatostatin tumors, achalasia, and Hischronson's disease. In some embodiments, the endocrine and neuroendocrine diseases include nodular hyperplasia, hashimoto's thyroiditis, islet cell tumor, and papillary carcinoma.

Endocrine and neuroendocrine disorders in children include developmental disorders and diabetes insipidus. Developmental delay with congenital ectopic growth or dysplasia/hypoplasia of the pituitary gland is commonly observed in anaplasia of the forebrain, hyaline septal-optic nerve dysplasia and basal hernia of the brain. Acquired diseases such as craniopharyngioma, optic nerve/hypothalamic glioma are often associated with clinical short stature and diencephalon syndrome. Precocious puberty and hyperplasia are observed in the following diseases: arachnoid cyst, hydrocephalus, hypothalamic hamartoma, and germ cell tumor. Excessive secretion of growth hormone and corticotropin from pituitary adenomas may lead to pathologic stature and obesity in children. Diabetes insipidus can be secondary to the infiltration process of behemorrhizus langerhans cell histiocytosis, tuberculosis, germ cell tumor, post-pituitary-stem trauma/surgical injury and hypoxic-ischemic encephalopathy.

In one embodiment, provided herein is a method of treating endocrine and neuroendocrine diseases using modulators of PARP and modulators of other co-regulated genes of endocrine and neuroendocrine diseases.

Examples of nutritional and metabolic disorders

Examples of nutritional and metabolic diseases include, but are not limited to, aspartylglucamine urosis (aspartylgluminaria), biotinidase deficiency, carbohydrate-deficient glycoprotein syndrome (CDGS), crigler-najal syndrome, cystinosis, diabetes insipidus, fabry disease (fabry), disorders of fatty acid metabolism, galactosemia, gaucher disease (gaucher), glucose-6-phosphate dehydrogenase (G6PD), glutaruria, hurler disease (hurler), hurler-scheie disease (hurler-scheie), hunter disease (hunter), hypophosphatemia, I-cell disease (I-cell), krabbe disease (krabbe), lactic acidosis, long-chain 3 dehydrogenase CoA deficiency (LCHAD), lysosomal storage disease, mannoside disease, maple diabetes, malto larmi disease (mareaux-lamy white matter dystrophy), metachromatic leukodystrophy, mitochondrial disease, Morchella (morquio), mucopolysaccharidosis, neuro-metabolic disease, niemann-pick disease (niemann-pick), organic acidemia, purinosis (purine), Phenylketonuria (PKU), pompe disease (pompe), pseudohuler disease (pseudo-hurler), pyruvate dehydrogenase deficiency, sandhoff disease (sandhoff), sanfilippo disease (sanfilippo), sayis disease (scheie), sly disease, tay-saxophone disease (tay-sachs), trimethyosis (trimethyosmus) (fish-malonor syndrome), urea cycle disorders, vitamin D deficiency rickets, muscle metabolic diseases, genetic metabolic diseases, acid-base balance disorders, acidosis, alkali poisoning, melanogastic disease, α -mannosidosis, amyloidosis, anemia, iron deficiency, ascorbic acid deficiency, vitamin deficiency, foot odor deficiency, leg deficiency, and leg deficiency, Biological enzyme deficiency, glycoprotein deficiency syndrome, carnitine disease, cystinosis, cystinuria, fabry's disease, fatty acid oxidation disorder, fucoside accumulation disease, galactosemia, gaucher's disease, gilbert's disease, glucose phosphate dehydrogenase deficiency, glutaremia, glycogen storage disease, hart naph's disease, hemochromatosis, hemosiderosis, hepatolenticular degeneration, histidinemia, homocystinuria, hyperbilirubinemia, hypercalcemia, hyperinsulinemia, hyperkalemia, hyperlipidemia, hyperoxaluria, vitamin a hyperemia, hypocalcemia, hypoglycemia, hypokalemia, hyponatremia, hypophosphatase disease, insulin resistance, iodine deficiency, iron overload, jaundice, chronic idiopathic diseases, liinergic disease, lewy-nedoch's syndrome, leucine metabolic disorder, lysosomal storage disease, lysosomal disease, and other diseases, Magnesium deficiency, maple syrup urine disease, MELAS syndrome, menkes curly hair syndrome, metabolic syndrome X, mucolipid accumulation, mucopolysaccharide storage disorders, niemann pick disease, obesity, ornithine carbamoyltransferase deficiency, osteomalacia, pellagra, peroxisome disorders, porphyria, erythropoiesis abnormalities, porphyria formation, geford's syndrome, pseudogaucher disease, refsum disease, leie's syndrome, englery disease, sandhoff disease, dangill disease, tay-saxophone disease, tetrahydrobiopterin deficiency, trimethylamine urine disease (fish odor syndrome), tyrosinemia, urea cycle disorders, water electrolyte imbalance, weieck encephalopathy, vitamin a deficiency, vitamin B12 deficiency, vitamin B deficiency, volman disease, and zeweger syndrome.

In one embodiment, provided herein is a method of treating a nutritional disorder or metabolic disease using a modulator of PARP and a modulator of other co-regulated genes of the nutritional disorder or metabolic disease. In some embodiments, the metabolic disease comprises diabetes and obesity.

Examples of lymphohematopoietic disorders

Lymphohematopoietic diseases include hematologic and lymphatic diseases. Hematologic diseases include diseases, disorders or conditions that affect hematopoietic cells or tissues. Hematologic diseases include diseases, disorders or conditions associated with abnormal blood volume and function. Examples of hematological disorders include those resulting from radiation therapy or chemotherapy of the bone marrow due to cancer, and also include pernicious anemia, hemorrhagic anemia, hemolytic anemia, aplastic anemia, sickle cell anemia, sideroblastic anemia, anemia associated with chronic infections such as malaria, trypanosomiasis, HIV, hepatitis virus or other viral infections, myelopathic anemia due to bone marrow deficiency, renal failure anemia, polycythemia, Infectious Mononucleosis (IM), acute nonlymphocytic leukemia (ANLL), Acute Myeloid Leukemia (AML), Acute Promyelocytic Leukemia (APL), acute myelomonocytic leukemia (AMMoL), polycythemia vera, lymphoma, Acute Lymphocytic Leukemia (ALL), chronic lymphocytic leukemia, Wilms' tumor, Ewing's sarcoma, retinoblastoma, hemophilia, diseases associated with increased risk of thrombosis, herpes, thalassemia, antibody-mediated diseases such as transfusion reactions and erythroblastosis, mechanical trauma to erythrocytes such as microangiopathic hemolytic anemia, thrombotic thrombocytopenic purpura and disseminated intravascular coagulation, infections caused by parasites such as plasmodium infections, chemical burns such as lead poisoning, hyperfunction of the spleen.

Lymphatic system diseases include, but are not limited to, lymphadenitis, lymphangitis, lymphedema, lymphocysts, lymphoproliferative disorders, mucocutaneous lymph node syndrome, reticuloendotheliosis, spleen disease, thymic hyperplasia, thymic tumor, tuberculosis, lymph nodes, pseudolymphoma, and lymphatic malformations.

In one embodiment, provided herein is a method of treating a hematologic disease using a modulator of PARP and a modulator of another co-regulated gene of the hematologic disease. Lymphohematopoietic diseases include, but are not limited to, non-hodgkin's lymphoma, chronic lymphocytic leukemia, and reactive lymphoid hyperplasia.

Examples of CNS disorders

Examples of CNS disorders include, but are not limited to, neurodegenerative disorders, drug abuse such as cocaine abuse, multiple sclerosis, schizophrenia, acute disseminated encephalomyelitis, transverse myelitis, hereditary demyelinating diseases, spinal cord injury, virus-induced demyelinating diseases, progressive multiple leukoencephalopathy, human T-lymphocyte leukemia virus-associated myelopathy, and nutrient-metabolic disorders.

In one embodiment, provided herein is a method of treating a CNS disease using a modulator of PARP and a modulator of another co-regulated gene of the CNS disease. In some embodiments, the CNS disease comprises parkinson's disease, alzheimer's disease, cocaine abuse, and schizophrenia.

Examples of neurodegenerative diseases

Neurodegenerative diseases include, but are not limited to, Alzheimer's disease, pick's disease, diffuse lewy body disease, progressive supranuclear palsy (Steyr-Richardson syndrome), multiple system degeneration (Charey-Delerg syndrome), motor neuron disease including amyotrophic lateral sclerosis, degenerative ataxia, corticobasal degeneration, ALS-Guam parkinsonism dementia complex, subacute sclerosing panencephalitis, Huntington's disease, Parkinson's disease, synucleinopathies, primary progressive aphasia, striatal degeneration, equine-joseph disease/spinocerebellar ataxia type 3 and olivopontocerebellar degeneration, Gilles de Tourette's disease, bulbar and pseudobulbar palsy, spinal and bulbar muscular atrophy (Kennedy's disease), primary lateral sclerosis, familial spastic paraparesis, paresis, and paradoxicasis, Wedney-Hoffmann disease, Kurgery-Welan disease, Tay-saxophone disease, sandhoff disease, familial ankylosing disease, Wo-Ku-Wer disease, spastic paraplegia, progressive multifocal leukoencephalopathy, and prion diseases (including Creutzfeldt-Jakob disease, Jaczmann-Straussler-Scheinker disease, Kuru and fatal familial insomnia), Alexander disease, Alepper disease, amyotrophic lateral sclerosis, dyskinetic telangiectasia, Batten disease, Canavan disease, Kenzey syndrome, corticobasal degeneration, Creutzfeldt-Jakob disease, Huntington disease, Kennedy disease, Berry disease, Lewy body dementia, Mare-Johnson disease, spinocerebellar ataxia type 3, multiple sclerosis, multiple atrophy, Parkinson's disease, Pelizaeus-Merzbacher disease, Leffermum's disease, Sheerd's disease, Spi-Walgt-Schlenk-Barcane disease, Steire-Richardson-Oldershawski disease, and tabes dorsi.

In one embodiment, provided herein is a method of treating neurodegenerative diseases using modulators of PARP and modulators of other genes that are co-modulated with neurodegenerative diseases.

Examples of urinary tract diseases

Urinary tract disorders include, but are not limited to, disorders of the kidney, ureter, bladder, and urinary tract. For example, urethritis, cystitis, pyelonephritis, renal defects, hydronephrosis, polycystic kidney disease, polycystic kidney, lower urinary tract obstruction, bladder eversion and urethral cleavage, hypospadiae, bacteriuria, prostatitis, intrarenal and peripheral abscesses, benign prostatic hypertrophy, renal cell carcinoma, transitional cell carcinoma, Wilms' tumor, uremia and glomerulonephritis.

In one embodiment, provided herein is a method of treating a urinary tract disorder using a modulator of PARP and a modulator of another co-regulated gene of the urinary tract disorder.

Examples of respiratory diseases

Respiratory diseases and conditions include, but are not limited to, asthma, Chronic Obstructive Pulmonary Disease (COPD), adenocarcinoma, adenosquamous carcinoma, squamous cell carcinoma, large cell carcinoma, Cystic Fibrosis (CF), dyspnea, emphysema, wheezing, pulmonary hypertension, pulmonary fibrosis, hyperreactive airways, elevated adenosine or adenosine receptor levels, pulmonary bronchoconstriction, pulmonary inflammation and allergy, lung surfactant depletion, chronic bronchitis, bronchoconstriction, dyspnea, pulmonary airway obstruction and obstruction, adenosine tests to detect cardiac function, pulmonary vasoconstriction, obstructive breathing, Acute Respiratory Distress Syndrome (ARDS), specific drug administration such as drugs that result in elevated adenosine and adenosine receptor levels, other drugs such as administration to treat supraventricular tachycardia (SVT) and adenosine loading tests, infant Respiratory Distress Syndrome (RDS), RDS, Pain, allergic rhinitis, decreased lung surfactant, decreased coenzyme Q levels, or chronic bronchitis, among others.

In one embodiment, provided herein is a method of treating respiratory diseases and disorders using modulators of PARP and modulators of other co-regulated genes of respiratory diseases and disorders.

Examples of diseases of the female reproductive system

Female reproductive system disorders include disorders of the vulva, vagina, cervix, uterus, fallopian tubes and ovaries. Some examples include diseases of the uterine adnexa such as, for example, fallopian tube disease, ovarian disease, leiomyoma, mucinous cystadenocarcinoma, serous cystadenocarcinoma, ovarian crown cyst, and pelvic inflammatory disease; endometriosis; tumors of the reproductive system such as, for example, tumors of the fallopian tubes, uterus, vagina, vulva and ovary; vaginal atresia; genital herpes; sterile; sexual dysfunction such as dyspareunia and impotence; tuberculosis; uterine diseases such as cervical diseases, endometrial hyperplasia, endometritis, hematuria, uterine bleeding, uterine tumors, uterine prolapse, uterine rupture and uterine inversion; vaginal disorders such as dyspareunia, colporrhagia, vaginal fistulas, vaginal tumors, vaginitis, vaginal discharge and candidiasis or vulvovaginitis; vulvar diseases such as vulvar trunk, pruritus, vulvar tumor, vulvitis, and candidiasis; and genitourinary disorders such as genitourinary abnormalities and genitourinary tumors.

In one embodiment, provided herein is a method of treating a female reproductive system disease using a modulator of PARP and a modulator of another co-modulated gene of the female reproductive system disease.

Examples of diseases of the male reproductive system

Male reproductive system diseases include, but are not limited to, epididymitis; reproductive system tumors such as penile tumors, prostate tumors, and testicular tumors; coleal hematocele; genital herpes; hydrocele of tunica vaginalis; sterile; penile diseases such as balanitis, hypospadias, fibrospongitis of the penis, penile tumors, phimosis, and priapism of the penis; prostate diseases such as prostatic hypertrophy, prostate tumors and prostatitis; sexual dysfunction such as dyspareunia and impotence; twisting a spermatic cord; a cyst of sperm; testicular diseases such as cryptorchidism, orchitis, and testicular tumors; tuberculosis; varicocele; urogenital diseases such as, for example, urogenital abnormalities and urogenital tumors; and gangrene.

In one embodiment, provided herein is a method of treating male reproductive disorders using modulators of PARP and modulators of other co-modulated genes of male reproductive disorders.

Examples of cardiovascular disorders (CVS)

Cardiovascular disorders include those diseases that can cause ischemia or be caused by reperfusion of the heart. Examples include, but are not limited to, atherosclerosis, coronary artery disease, granulomatous myocarditis, chronic myocarditis (non-granulomatous), primary hypertrophic cardiomyopathy, Peripheral Artery Disease (PAD), stroke, angina pectoris, myocardial infarction, cardiovascular tissue damage due to cardiac arrest, cardiovascular tissue damage due to cardiac bypass, cardiogenic shock, and related diseases known to those skilled in the art or related to dysfunction of the heart or vasculature or tissue damage (particularly, but not limited to, tissue damage related to PARP activation).

In one embodiment, provided herein is a method of treating a cardiovascular disorder using a modulator of PARP and a modulator of another co-regulated gene of the cardiovascular disorder. In some embodiments, CVS diseases include, but are not limited to, atherosclerosis, granulomatous myocarditis, myocardial infarction, myocardial fibrosis secondary to valvular heart disease, myocardial fibrosis without infarction, primary hypertrophic cardiomyopathy, and chronic myocarditis (non-granuloma).

Examples of viral diseases

Viral diseases include, but are not limited to, diseases caused by viral infection and subsequent replication. Examples of viral diseases include, but are not limited to, infections caused by the following viruses: human immunodeficiency virus, hepatitis C virus, hepatitis B virus, herpes virus, varicella-zoster, adenovirus, cytomegalovirus, enterovirus, rhinovirus, rubella virus, influenza virus and encephalitis virus. In some embodiments, HIV infection and replication are treated by the combination therapies described herein. In one embodiment, provided herein is a method of treating a viral disease using a modulator of PARP of the viral disease and a modulator of an additional co-regulated gene.

PARP and disease pathways

Poly (ADP-ribose) polymerase (PARP) is known as poly (ADP-ribose) synthase and poly ADP-ribosyltransferase. PARP catalyzes the formation of poly (ADP-ribose) polymers that can be linked to intranuclear proteins (as well as to themselves) and thereby alter the activity of those proteins. This enzyme plays a role in enhancing DNA repair, but also in regulating chromatin in the nucleus (for a review see: D.D' animals et al "Poly (ADP-ribosylation interactions in the regulation of nuclear functions," biochem. J.342: 249-268 (1999)).

PARP-1 comprises an N-terminal DNA binding domain, a self-modifying domain and a C-terminal catalytic domain; a variety of cellular proteins interact with PARP-1. The N-terminal DNA binding domain comprises two zinc finger motifs. Transcription enhancer factor-1 (TEF-1), retinoid X receptor alpha, DNA polymerase alpha, X-ray repair cross-complementing factor-1 (XRCC1), and PARP-1 itself interact with PARP-1 in this region. The auto-repair region contains the BRCT motif (one of the protein-protein interacting molecules). This motif was originally found at the C-terminus of BRCA1 (breast cancer susceptibility protein 1) and is present in a variety of proteins involved in DNA repair, recombination and cell cycle checkpoint regulation. POU-homeodomain-contains octameric transcription factor-1 (Oct-1), Yin Yang (YY)1 and ubiquitin conjugating enzyme 9(ubc9) capable of interacting with the BRCT motif in PARP-1.

More than 15 members of the PARP family of genes are present in the mammalian genome. PARP family proteins and poly (ADP-ribose) polysaccharide hydrolases (PARG), which degrade poly (ADP-ribose) to ADP-ribose, can be involved in a variety of cell regulatory functions including DNA damage response and transcriptional regulation, and are in many ways associated with carcinogenesis and cancer biology.

Several PARP family proteins have been identified. Tankyrase has been found to be an interacting protein of telomere regulatory factor 1(TRF-1) and is involved in telomere regulation. Vault parp (vault parp) (vparp) is a component of the vault complex (vault complex) which acts as a nuclear-cytoplasmic carrier. PARP-2, PARP-3 and 2, 3, 7, 8-tetrachlorodibenzo-p-bis have been identified British inducible PARP (TiPARP). Thus, poly (ADP-ribose) metabolism can be associated with a variety of cellular regulatory functions.

One member of this gene family is PARP-1. The PARP-1 gene product is expressed at high levels in the nucleus of cells and is dependent on DNA damage activation. Without being bound by any theory, it is believed that PARP-1 binds to DNA single or double strand breaks through the amino-terminal DNA binding domain. This binding activates the carboxy-terminal catalytic domain and results in the formation of a polymer of ADP-ribose on the targeting molecule. PARP-1 is itself a target for poly ADP-ribosylation due to the auto-correcting domain of the central position. This nuclear glycosylation of PARP-1 results in the isolation of the PARP-1 molecule from the DNA. The entire process of binding, ribosylation and isolation occurs very rapidly. It has been proposed that this transient binding of PARP-1 to the site of DNA damage results in the restoration of the DNA repair system or may act to inhibit recombination long enough to restore the repair system.

The source of ADP-ribose used for the PARP reaction is Nicotinamide Adenine Dinucleotide (NAD). NAD is synthesized in cells of the cellular ATP pool, and thus high levels of activated PARP activity can rapidly lead to depletion of cellular energy stores. It has been demonstrated that induction of PARP activity can lead to cell death (which is associated with depletion of cellular NAD and ATP pools). PARP activity is induced in many cases of oxidative stress or during inflammation. For example, during reperfusion of ischemic tissue, reactive nitric oxide is produced, and nitric oxide leads to the production of other reactive oxygen species, including hydrogen peroxide, peroxynitrite, and hydroxyl radicals. The latter can directly damage DNA, and the resulting damage induces activation of PARP activity. In general, it appears that sufficient activation of PARP activity occurs, thereby depleting cellular energy storage and cell death. It is believed that a similar mechanism may be applied during inflammation when endothelial cells and pro-inflammatory cells synthesize nitric oxide, which causes oxidative DNA damage around the cells, and subsequent activation of PARP activity. Cell death due to PARP activation is believed to be an important contributor to the extent of tissue damage caused by ischemia-reperfusion injury or by inflammation.

Inhibition of PARP activity could potentially be used to treat cancer. De-inhibition of dnase (by PARP-1 inhibition) can trigger DNA fragmentation, which is specific for cancer cells and induces apoptosis only in cancer cells. PARP small molecule inhibitors can make treated tumor cell lines more susceptible to killing by ionizing radiation as well as by some DNA damaging chemotherapeutic drugs. Treatment with PARP inhibitors may be effective either as monotherapy or in combination with chemotherapy or radiation therapy. Combination therapy with chemotherapy can induce tumor regression at concentrations at which chemotherapy is effective by itself. In addition, PARP-1 mutant mice and PARP-1 mutant cell lines are sensitive to radiation and similar types of chemotherapeutic drugs.

The level of PARP and co-regulated gene expression may be indicative of the disease state, stage or diagnosis of an individual patient. For example, the relevant levels of PARP-1 expression are upregulated in patients with prostate and breast cancer as compared to normal patients. Similarly, the relevant levels of PARP-1 expression are up-regulated in patients with ovarian and endometrial cancer as compared to normal patients. In different cancers, the upregulation levels exhibited by the individual cancer types are not the same as one another. For example, different breast cancers show up-regulation to varying degrees. Similarly, different ovarian cancers show up-regulation to varying degrees. This suggests that not only does PARP-1 upregulation help identify PARP-1 mediated diseases that can be treated by PARP-1 inhibitors, but it also helps predict/determine the efficacy of treatment with PARP-1 inhibitors based on the degree of upregulation of PARP-1 in the patient. Thus, the assessment of PARP and co-regulated gene expression may be an indicator of tumor sensitivity to PARP-1 inhibitors and co-regulated genes. This may also facilitate personalized dosing regimens for the patient.

PARP related pathways

As discussed above, other genes that are co-regulated along with PARP expression may also be used to identify and treat diseases that may be treated by a combination of PARP and co-regulated gene modulators. For example, the relative levels of PARP-1 expression in tumor tissue samples, as well as the indicated upregulation of IGF1R and EGFR expression, may indicate a cancer that may be treated by a combination of PARP inhibitor and IGF1R and EGFR inhibitor, as compared to normal patients. Furthermore, the relative levels of PARP-1, IGF1R, and EGFR expression in patients with inflammatory disease, as compared to normal patients, may indicate inflammatory disease that may be treated by a combination of a P ARP inhibitor and IGF1R, and an EGFR inhibitor.

Co-regulation of other identified genes can be detected independently of the analysis of PARP level expression. For example, the practitioner, based on the teachings provided herein, would apply PARP inhibitors in combination with IGF1R inhibitors to breast cancer tissues, since a co-regulated relationship between PARP-1 and IGF1R expression was demonstrated. Accordingly, one embodiment comprises administering co-regulated gene modulators, such as IGF1R and EGFR inhibitors, for the treatment of diseases (including cancer) regardless of the measurement of PARP level expression. Administration of such co-regulated gene modulators may occur before or after administration of the PARP modulator, or independently of administration of the PARP modulator.

Thus, one embodiment disclosed herein is to demonstrate the correlation of multiple pathways with PARP modulation to identify potential targets for co-modulated therapy. The following gene targets are exemplary (and not exclusive of others) genes whose expression is co-regulated with PARP expression in disease states.

Insulin-like growth factor receptor 1

Insulin-like growth factor receptor (IGF1R) is a transmembrane receptor tyrosine kinase that mediates IGF biological activity and signaling through several key cellular molecular networks, including the RAS0RAF-ERK and PI3-AKT-mTOR pathways. Functional IGF1R is required for transformation and has been shown to promote tumor cell growth and survival. Some genes that have been shown to promote cell proliferation in the IGF1R pathway in response to IGF-1/IGF-2 binding include Shc, IRS, Grb2, SOS, Ras, Raf, MEK and ERK. Genes involved in cell proliferation, motility and survival functions of IGF1R signaling include IRS, PI3-K, PIP2, PTEN, PTP-2, PDK and Akt.

IGF1R is often overexpressed in human tumors, including melanoma, colon, pancreas, prostate, and kidney cancers. Overexpression of IGF1R can be as an oncogene, where such overexpression of IGF1R can be the result of loss of tumor suppressor genes (including wild-type p53, BRCA1, and VHL). Activation of IGF1R protects cells from a variety of apoptosis-inducing drugs, including osmotic stress, hypoxia, and anticancer drugs. Expression of functional IGF1R seems to be a key determinant of resistance to apoptosis in vitro and in vivo. IGF is known to protect tumor cells from cytotoxic drugs. This effect can be attributed to the well-recognized ability of the IGF axis to inhibit apoptosis, and also to the apparent ability to influence aspects of DNA damage response. In line with this, sensitivity to chemotherapy can be increased by various methods of blocking the IGF axis. The IGF axis can potentially be blocked in several different contexts, including interfering with the expression and function of ligands, binding proteins, and receptors. Small molecule inhibitors, antibodies, IGF1R dominant negative, antisense, and siRNA represent examples of inhibitors that can increase sensitivity to chemotherapy through the IGF axis.

Experiments were performed in multiple tissue samples to determine whether there was a correlation between PARP and IGF-1R expression. Table XIX shows expression levels in a number of tissues, including adrenal, bone, breast tumor tissue, including IDC, invasive lobular carcinoma, and the like. As can be seen, upregulation of IGF1-R (among which PARP1 upregulation) can be observed in the same tissues, for example in breast, ovarian and skin cancers. Accordingly, one embodiment is the treatment of a disease susceptible to the combination of PARP and an IGF1R modulator. In addition, IGF 1R-regulated genes, including genes that are commonly regulated along the IGF1R pathway, are also included herein.

Table XIX: expression of IGF1R (insulin-like growth factor 1 receptor) in human primary tumors tested on test hg133a compared to normal tissue.

Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Adrenal, adrenal cortex cell carcinoma, primary	3	65.828	35.85	75.958
Adrenal gland, normal	13	85.341	37.713	92.31
					Bone, giant cell tumor of bone, primary	10	57.201	25.847	45.959
Bone, normal	8	46.953	14.046	43.164
					Bone, osteosarcoma, primary	4	64.269	20.188	60.848
Mixed invasive carcinoma of the breast, ductus lactis and lobule, primary	8	112.111	69.247	99
					Breast, invasive ductal carcinoma, primary	169	124.036	95.462	97.339
Breast, invasive lobular carcinoma, primary	17	114.33	66.461	99.947
					Breast, ductal carcinoma	3	214.121	100.275	208.348
Breast, mucinous carcinoma, primary	4	163.719	127.018	146.328
					Mammary gland, Normal	68	87.822	58.73	70.932
Breast, phyllodes tumor (phyllocystic sarcoma), primary	5	99.977	33.553	117.663
					Colon, adenocarcinoma (excluding mucinous types), primary	77	47.25	24.702	41.896
Colon, adenocarcinoma, mucoid, primary	7	54.155	32.766	48.534

Colon, Normal	180	41.474	19.577	38.744
					Endometrium, adenocarcinoma, endometrioid type, primary	50	77.703	34.7	70.791
Endometrium, Mullerian mixed tumor, primary	7	103.11	112.968	58.225
					Endometrium, normal	23	109.476	61.449	86.356
Esophagus, adenocarcinoma, primary	3	76.404	89.219	33.085
					Esophagus, normal	22	54.934	22.855	46.997
Kidney, cancer, chromophobe type, primary	3	79.838	38.577	98.029
					Kidney, normal	81	94.875	39.237	90.24
Renal, renal cell carcinoma, clear cell type, primary	45	69.441	44.919	57.36
					Renal, renal cell carcinoma, non-clear cell type, primary	15	86.186	50.4	70.631
Renal, transitional cell carcinoma, primary	4	41	20.564	42.229
					Kidney, Wilms' tumor, primary	8	104.733	47.828	89.439
Larynx, normal	4	54.531	7.301	54.091
					Larynx, squamous cell carcinoma, primary	4	111.113	89.014	97.039
Liver, hepatocellular carcinoma	16	22.266	7.512	21.544
					Liver, normal	42	27.576	25.82	22.895
Lung, adenocarcinoma, primary	46	65.452	47.363	55.441
					Lung, adenosquamous carcinoma, primary	3	56.079	34.038	47.214
Lung, large cell carcinoma, primary	7	61.764	46.439	31.328
					Lung, neuroendocrine carcinoma (non-small cell type), primary	3	37.427	24.31	27.517
Lung, normal	126	57.277	29.69	52.18
					Lung, small cell carcinoma, primary	3	57.647	23.035	62.91
Lung, squamous cell carcinoma, primary	39	81.713	50.819	66.414
					Oral cavity, squamous cell carcinoma, primary	3	136.372	93.9	93.936
Ovary, adenocarcinoma, clear cell type, primary	6	93.691	43.793	75.009

Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Ovary, adenocarcinoma, endometrioid, primary	22	73.115	32.45	75.949
Ovary, adenocarcinoma, papillary serous type, primary	36	126.618	261.068	75.962
					Ovary, granulomatous tumor, primary	3	169.841	60.705	169.927
Ovary, mucinous cystadenocarcinoma, Primary	7	75.393	66.713	50.779
					Ovary, Mullerian mixed tumor, Primary	5	126.91	121.824	79.955
Ovary, Normal	89	115.666	53.302	108.304
					Pancreas, adenocarcinoma, primary	23	63.885	16.923	60.04
Pancreas, islet cell tumor, malignant, Primary	7	56.924	63.772	30.551
					Pancreas, Normal	46	93.076	37.674	89.188
Prostate, adenocarcinoma, primary	86	119.495	53.987	114.899
					Prostate, normal	57	108.233	58.456	93.388
Rectum, adenocarcinoma (excluding mucinous type), primary	29	59.204	19.34	65.388
					Rectum, adenocarcinoma, mucoid, primary	3	62.573	31.476	57.951
Rectum, normal	44	50.965	19.969	48.972
					Skin, basal cell carcinoma, primary	4	179.37	85.237	202.634
Skin, malignant melanoma, primary	7	87.475	42.005	86.499
					Skin, normal	61	55.948	23.541	49.106
Skin, squamous cell carcinoma, primary	4	66.185	17.746	69.936
					Small intestine, gastrointestinal stromal tumor (GIST), primary	4	10.347	3.768	10.282
Small intestine, normal	97	36.769	20.176	32.341
					Stomach, adenocarcinoma (excluding finger ring cell types), primary	27	44.607	29.077	37.317
Stomach, adenocarcinoma, finger print cell type, primary	9	50.232	16.902	52.252
					Stomach, gastrointestinal stromal tumor (GIST), primary	9	36.869	61.155	15.828
Stomach being normal	52	58.767	28.497	47.439

Thyroid, follicular carcinoma, primary	3	120.042	41.591	130.814
					Thyroid, normal	24	81.333	49.295	71.732
Thyroid, papillary carcinoma, primary; all variants	29	83.359	51.903	63.894
					Bladder, normal	9	62.521	20.653	55.34
Bladder, transitional cell carcinoma, primary	4	64.6	12.927	59.941
					Cervix, adenocarcinoma, primary	3	103.944	95.785	55.348
Uterine cervixIs normal and normal	115	71.105	24.883	66.647
					Vulva, normal of vulva	4	63.062	21.067	69.51
Vulvar, squamous cell carcinoma, primary	5	141.052	129.493	84.436

Insulin-like growth factor 2(IGF2)

As discussed above, overexpression of IGF1R may function as an oncogene, where such overexpression of IGF1R may be the result of deletion of tumor suppressor Genes, including wild-type p53, BRCA1 and VHL (Werner and Roberts, 2003, Genes, Chromo and Cancer, 36: 112-120; Riedemann and Macaulay, 2006, Endocr. Relat. Cancer, 13: S33-43). Consistent with the role of IGF1R in cancer progression, blockade of the IGF axis has previously been shown to increase sensitivity to chemotherapy. The IGF axis can potentially be blocked at several different levels, including interfering with the expression and function of ligands including IGF 2. Thus, the function of IGF ligand (e.g., IGF2) inhibitors may also play a role in cancer progression.

Experiments were performed in multiple tissue samples to determine if there was a correlation between PARP and IGF2 expression. Table XX shows expression in a number of tissues including adrenal glands, bone, breast tumor tissue, including IDC and invasive lobular carcinoma, among others. It can be seen that IGF2 was shown to be upregulated in the same tissues (among which PARP1 is upregulated), for example in breast, liver, lung and ovarian cancers. Accordingly, one embodiment is the treatment of a disease susceptible to a combination of PARP and IGF2 modulators. In addition, IGF2 related genes (including IGF1, IGF3, IGF4, IGF5, IGF6, and other insulin-like growth factor receptor ligands) are also included herein.

Table XX: expression of IGF2 (insulin-like growth factor 2) in human primary tumors compared to normal tissues

Sample set	Number of samples	Mean value of	Standard deviation of
				Adrenal, adrenal cortex cell carcinoma, primary	3	1848.834	3090.534
Adrenal gland, normal	13	529.291	547.211
				Bone, giant cell tumor of bone, primary	10	92.575	46.504
Bone, normal	8	541.963	363.888

Bone, osteosarcoma, primary	4	563.184	570.075
				Mixed invasive carcinoma of the breast, ductus lactis and lobule, primary	8	266.772	222.345
Breast, invasive ductal carcinoma, primary	169	302.565	404.769
				Breast, invasive lobular carcinoma, primary	17	427.307	267.766
Breast, ductal carcinoma	3	309.277	169.406
				Breast, mucinous carcinoma, primary	4	323.68	104.134
Mammary gland, Normal	68	625.371	391.936
				Breast, phyllodes tumor (phyllocystic sarcoma), primary	5	4635.806	758.39
Colon, adenocarcinoma (excluding mucinous types), primary	77	404.074	990.572
				Colon, adenocarcinoma, mucoid, primary	7	142.852	115.826
Colon, Normal	180	124.294	164.11
				Endometrium, adenocarcinoma, endometrioid type, primary	50	262.408	261.542
Endometrium, Mullerian mixed tumor, primary	7	4298.005	3973.436
				Endometrium, normal	23	962.379	568.949
Esophagus, adenocarcinoma, primary	3	88.334	23.213
				Esophagus, normal	22	147.307	93.47
Kidney, cancer, chromophobe type, primary	3	98.284	49.051
				Kidney, normal	81	180.318	173.522
Renal, renal cell carcinoma, clear cell type, primary	45	172.314	293.9
				Renal, renal cell carcinoma, non-clear cell type, primary	15	81.293	74.054
Renal, transitional cell carcinoma, primary	4	5620.705	4310.083
				Kidney, Wilms' tumor, primary	8	5461.075	2837.742
Sample set	Number of samples	Mean value of	Standard deviation of

Larynx, normal	4	501.856	381.37
				Larynx, squamous cell carcinoma, primary	4	309.574	200.901
Liver, hepatocellular carcinoma	16	1912.226	3539.841
				Liver, normal	42	1505.288	632.644
Lung, adenocarcinoma, primary	46	81.16	86.841
				Lung, adenosquamous carcinoma, primary	3	202.216	248.096
Lung, large cell carcinoma, primary	7	1233.22	1890.947
				Lung, neuroendocrine carcinoma (non-small cell type), primary	3	22.408	8.574
Lung, normal	126	116.73	221.406
				Lung, small cell carcinoma, primary	3	307.962	315.514
Lung, squamous cell carcinoma, primary	39	81.715	74.222
				Oral cavity, squamous cell carcinoma, primary	3	341.49	278.662
Ovary, adenocarcinoma, clear cell type, primary	6	211.816	243.491
				Ovary, adenocarcinoma, endometrioid, primary	22	229.471	416.059
Ovary, adenocarcinoma, papillary serous type, primary	36	1154.231	1834.815
				Ovary, granulomatous tumor, primary	3	77.318	59.672
Ovary, mucinous cystadenocarcinoma, Primary	7	97.436	32.315
				Ovary, Mullerian mixed tumor, Primary	5	2463.327	3493.894
Ovary, Normal	89	416.275	283.767
				Pancreas, adenocarcinoma, primary	23	917.465	3230.5
Pancreas, islet cell tumor, malignant, Primary	7	1209.737	2927.581
				Pancreas, Normal	46	199.883	170.572
Prostate, adenocarcinoma, primary	86	66.905	51.16

Prostate, normal	57	172.881	141.803
				Rectum, adenocarcinoma (excluding mucinous type), primary	29	1360.42	1973.822
Rectum, adenocarcinoma, mucoid, primary	3	140.862	95.539
				Rectum, normal	44	122.072	76.08
Skin, basal cell carcinoma, primary	4	519.235	445.788
				Skin, malignant melanoma, primary	7	78.738	30.463
Skin, normal	61	238.046	254.135
				Skin, squamous cellsCancer of primary origin	4	414.236	175.126
Small intestine, gastrointestinal stromal tumor (GIST), primary	4	5792.309	2849.492
				Small intestine, normal	97	100.364	82.367
Stomach, adenocarcinoma (excluding finger ring cell types), primary	27	424.297	1312.845
				Stomach, adenocarcinoma, finger print cell type, primary	9	189.732	95.09
Stomach, gastrointestinal stromal tumor (GIST), primary	9	6297.024	3314.963
				Stomach being normal	52	100.862	49.616
Thyroid, follicular carcinoma, primary	3	105.778	110.206
				Thyroid, normal	24	123.019	67.385
Thyroid, papillary carcinoma, primary; all variants	29	53.051	33.209
				Bladder, normal	9	589.553	501.207
Bladder, transitional cell carcinoma, primary	4	148.173	100.896
				Cervix, adenocarcinoma, primary	3	1137.023	593.279
Cervix, normal	115	608.103	352.223
				Vulva, normal of vulva	4	283.469	232.196
Sample set	Number of samples	Mean value of	Standard deviation of

Vulvar, squamous cell carcinoma, primary

5

398.101

277.493

Epidermal growth factor receptor

It has been shown that the expression of Epidermal Growth Factor Receptor (EGFR), a tyrosine kinase receptor, is essential in the progression of adenomas and carcinomas of intestinal tumors, as well as the subsequent expansion of neoplastic tumors (Roberts et al, 2002, PNAS, 99: 1521-. Overexpression of EGFR also plays a role in neoplasia, especially in tumors of epithelial origin (Kari et al, 2003, Cancer Res., 63: 1-5). Overexpression of EGFR has also been implicated in colorectal, pancreatic, glioma progression, small cell lung, and other carcinomas (Karamouzis et al, 2007, JAMA 298: 70-82; Toschi et al, 2007, Oncoloist, 12: 211-220; Sequist et al, 2007, Oncoloist, 12: 325-330; Hatake et al, 2007, Breast Cancer, 14: 132-149). EGFR is a member of the ErbB family of receptors, which includes HER2c/neu, HER2, and HER3 receptor tyrosine kinases. The molecular signaling pathway of EGFR activation has been characterized experimentally and in silico, involving about 200 reactions and 300 chemical species interactions (see Oda et al, Epub 2005, mol.sys.biol., 1: 2005.0010). In addition, EGFR stimulates PARP activation (through its signaling cascade pathway) and downstream cellular events mediated by the PARP pathway have been triggered (Hagan et al, 2007, j.cell. biochem., 101: 1384-1393).

Experiments were performed in multiple tissue samples to determine if there was a correlation between PARP and EGFR expression. Table XXI shows expression levels in a number of tissues, including adrenal, bone, breast tumor tissue, including IDC, and invasive lobular carcinoma, among others. As can be seen, up-regulation of EGFR (in which PARP1 is up-regulated) can be observed in the same tissue, for example in breast, ovarian and lung cancer. Accordingly, one embodiment is the treatment of diseases susceptible to a combination of PARP and EGFR modulators. In addition, EGFR-related genes, including genes that are co-regulated in the EGFR pathway, are also included herein.

Table XXI: EGFR (epidermal growth factor receptor; erythroblastic leukemia virus (v-erb-b) oncogene homolog, avian) tested in test hg133a was expressed in human primary tumors compared to normal tissues.

Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Adrenal, adrenal cortex cell carcinoma, primary	3	129.704	68.212	98.678
Adrenal gland, normal	13	206.012	141.491	218.327
					Bone, giant cell tumor of bone, primary	10	75.665	48.088	65.433
Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Bone, normal	8	56.238	60.711	37.849
Bone, osteosarcoma, primary	4	120.054	48.685	105.045
					Mixed invasive carcinoma of the breast, ductus lactis and lobule, primary	8	41.399	47.671	22.832
Breast, invasive ductal carcinoma, primary	169	99.864	205.802	61.254
					Breast, invasive lobular carcinoma, primary	17	95.073	86.523	74.745
Breast, ductal carcinoma	3	76.167	20.435	78.839
					Breast, mucinous carcinoma, primary	4	53.4	53.594	40.467
Mammary gland, Normal	68	245.198	215.156	205.936
					Breast, phyllodes tumor (phyllocystic sarcoma), primary	5	393.825	154.773	467.458

Colon, adenocarcinoma (excluding mucinous types), primary	77	120.497	94.693	103.941
					Colon, adenocarcinoma, mucoid, primary	7	93.805	74.634	83.1
Colon, Normal	180	171.561	111.035	183.725
					Endometrium, adenocarcinoma, endometrioid type, primary	50	159.77	123.307	141.211
Endometrium, Mullerian mixed tumor, primary	7	279.821	425.216	71.541
					Endometrium, normal	23	247.392	190.703	207.384
Esophagus, adenocarcinoma, primary	3	65.199	53.315	70.837
					Esophagus, normal	22	284.301	195.112	296.05
Kidney, cancer, chromophobe type, primary	3	199.572	175.321	149.855
					Kidney, normal	81	167.833	111.603	166.218
Renal, renal cell carcinoma, clear cell type, primary	45	475.552	460.868	363.274
					Renal, renal cell carcinoma, non-clear cell type, primary	15	438.275	312.272	363.517
Renal, transitional cell carcinoma, primary	4	128.624	102.806	127.813
					Kidney, Wilms' tumor, primary	8	71.286	82.021	28.815

Larynx, normal	4	370.959	186.229	396.688
					Larynx, squamous cell carcinoma, primary	4	1310.153	1353.765	967.125
Liver, hepatocellular carcinoma	16	220.168	276.906	183.839
					Liver, normal	42	283.048	211.77	213.125
Lung, adenocarcinoma, primary	46	297.437	489.456	155.995
					Lung, adenosquamous carcinoma, primary	3	128.766	91.833	100.892
Lung, large cell carcinoma, primary	7	145.19	174.142	58.306
					Lung, neuroendocrine carcinoma (non-small cell type), primary	3	24.308	17.541	24.732
Lung, normal	126	214.472	136.084	199.47
					Lung, small cell carcinoma, primary	3	38.594	44.361	17.537
Lung, squamous cell carcinoma, primary	39	234.471	241.841	175.944
					Oral cavity, squamous cell carcinoma, primary	3	710.2	417.391	487.112
Ovary, adenocarcinoma, clear cell type, primary	6	110.201	69.532	80.94
					Ovary, adenocarcinoma, endometrioid, primary	22	106.113	76.106	108.206

Ovary, adenocarcinoma, papillary serous type, primary	36	125.456	131.366	91.677
					Ovary, granulomatous tumor, primary	3	330.038	171.65	304.702
Ovary, mucinous cystadenocarcinoma, Primary	7	256.915	196.875	201.768
					Ovary, Mullerian mixed tumor, Primary	5	173.476	217.763	128.913
Ovary, Normal	89	226.521	106.329	232.277
					Pancreas, adenocarcinoma, primary	23	159.08	123.238	94.418
Pancreas, islet cell tumor, malignant, Primary	7	55.68	51.943	48.9
					Pancreas, Normal	46	137.569	117.347	117.425
Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Prostate, adenocarcinoma, primary	86	170.831	100.727	158.375
Prostate, normal	57	194.519	129.737	179.636
					Rectum, adenocarcinoma (excluding mucinous type), primary	29	170.452	87.615	174.248
Rectum, adenocarcinoma, mucoid, primary	3	195.563	149.368	111.354
					Rectum, normal	44	202.086	106.159	233.46

Skin, basal cell carcinoma, primary	4	510.675	294.101	465.462
					Skin, malignant melanoma, primary	7	77.052	102.515	28.869
Skin, normal	61	296.749	214.128	265.763
					Skin, squamous cell carcinoma, primary	4	205.607	109.906	165.561
Small intestine, gastrointestinal stromal tumor (GIST), primary	4	87.92	60.244	91.574
					Small intestine, normal	97	112.607	75.33	110.804
Stomach, adenocarcinoma (excluding finger ring cell types), primary	27	159.547	90.62	141.751
					Stomach, adenocarcinoma, finger print cell type, primary	9	156.941	66.185	156.444
Stomach, gastrointestinal stromal tumor (GIST), primary	9	79.845	49.667	73.449
					Stomach being normal	52	130.321	87.634	120.267
Thyroid, follicular carcinoma, primary	3	128.064	21.149	127.098
					Thyroid, normal	24	181.933	105.446	166.104
Thyroid, papillary carcinoma, primary; all variants	29	242.517	160.473	192.848
					Bladder, normal	9	155.559	151.518	131.99

Bladder, transitional cell carcinoma, primary	4	223.719	200.354	167.709
					Cervix, adenocarcinoma, primary	3	86.934	98.416	30.427
Cervix, normal	115	205.156	149.735	173.903
					Vulva, normal of vulva	4	352.591	203.2	276.016
Vulvar, squamous cell carcinoma, primary	5	863.035	591.738	558.964

Thymine nucleotide synthase

Thymidylate synthase (TYMS) utilizes 5, 10-methylenetetrahydrofolate (methylene-THF) as a cofactor to maintain a library of dtmps (thymidine-5' monophosphates) that are critical for DNA replication and repair. It is of interest that this enzyme acts as a target for cancer chemotherapeutic agents. It is believed to be the primary site of action of 5-fluorouracil, 5-fluoro-2' -deoxyuridine, and some folic acid analogs. Resistance to chemotherapy is a major factor in the death of patients with advanced cancer.

Wang et al (2004) utilized digital karyotyping to look for genomic changes in liver metastatic cancer that is clinically resistant to 5-fluorouracil (5-FU). Of the 4 patients, 2, it was of particular interest to identify their amplification of the region of approximately 100kb on chromosome 18p11.32, since it contains the TYMS gene (a molecular target of 5-FU). TYMS analysis by FISH identified 7 TYMS gene amplifications (23%) in 5-FU-treated cancer at 31, whereas no amplification was observed in metastatic cancers in patients not treated with 5-FU. Patients with metastatic cancer containing TYMS amplification had significantly shorter median survival times (329 days) than those without amplification (1,021 days, P less than 0.01). These data indicate that gene amplification of TYMS is the primary mechanism of 5-FU resistance in vivo and may be of great significance for the management of colorectal cancer patients with recurrent disease.

One of the 5-FU resistance mechanisms is the activation of DNA repair, in which 5-FU is efficiently removed from DNA by base excision and mismatch repair systems (Fisher et al, 2007). Because PARP1 is a key enzyme in base excision DNA repair, the combination of PARP1 inhibitors with 5-FU is advantageous in anticancer therapy, especially for tumors that are clinically resistant to 5-fluorouracil. However, treatment of cancer cells with PARP1 inhibitor in combination with 5-FU can also increase the intracellular concentration of 5-FU and thus exacerbate cytotoxicity. Reduction of 5-FU volume or concomitant treatment with PARP1 inhibitors and modulators of TYMS can be used to reduce side effects (which can occur with increased cytotoxicity) while maintaining the efficacy of 5-FU as a cancer chemotherapeutic agent.

Experiments were performed in multiple tissue samples to determine if there was a correlation between PARP and TYMS expression. Table XXII shows expression levels in a number of tissues, including adrenal, bone, breast tumor tissue, including IDC, and invasive lobular carcinoma, among others. It can be seen that TYMS is upregulated and co-regulated with PARP1 in primary human tumors of the same subtype, such as tumors of the skin, breast, lung, ovary, esophagus, endometrium, and lymphomas and sarcomas. Accordingly, one embodiment is the treatment of a disease susceptible to a combination of PARP and TYMS modulators. In addition, TYMS-related genes (including along co-regulated genes) are also included herein.

Table XXII: expression of TYMS (thymidylate synthase) in human primary tumors, compared to normal tissues.

Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Adrenal, adrenal cortex cell carcinoma, primary	3	132.055	80.029	94.132
Adrenal gland, normal	13	112.2	125.033	69.718
					Bone, giant cell tumor of bone, primary	10	442.203	142.143	426.813
Bone, normal	8	694.953	431.602	790.188
					Bone, osteosarcoma, primary	4	1437.891	682.273	1471.017
Mixed invasive carcinoma of the breast, ductus lactis and lobule, primary	8	421.25	115.564	405.456
					Breast, invasive ductal carcinoma, primary	169	378.192	296.349	289.609
Breast, invasive lobular carcinoma, primary	17	304.073	198.812	236.622

Breast, ductal carcinoma	3	155.269	125.42	112.061
					Breast, mucinous carcinoma, primary	4	389.638	269.167	268.04
Mammary gland, Normal	68	211.465	208.685	137.409
					Breast, phyllodes tumor (phyllocystic sarcoma), primary	5	382.787	240.871	325.51
Colon, adenocarcinoma (excluding mucinous types), primary	77	548.493	382.288	403.87
					Colon, adenocarcinoma, mucoid, primary	7	512.226	272.655	390.405
Colon, Normal	180	372.032	164.29	344.596
					Sample set	Number of samples	Mean value of	Standard deviation of	Median value
Endometrium, adenocarcinoma, endometrioid type, primary	50	436.551	317.309	345.238
					Endometrium, Mullerian mixed tumor, primary	7	964.617	562.444	791.133
Endometrium, normal	23	153.952	87.587	125.089
					Esophagus, adenocarcinoma, primary	3	381.495	152.442	385.147
Esophagus, normal	22	276.286	81.626	251.979
					Kidney, cancer, chromophobe type, primary	3	72.47	18.244	73.02
Kidney, normal	81	141.763	57.283	136.178
					Renal, renal cell carcinoma, clear cell type, primary	45	382.754	189.427	363.738
Renal, renal cell carcinoma, non-clear cell type, primary	15	303.375	176.847	307.655
					Renal, transitional cell carcinoma, primary	4	412.684	93.512	427.31
Kidney, Wilms' tumor, primary	8	1476.481	439.652	1525.669
					Larynx, normal	4	223.235	153.725	225.307
Larynx, squamous cell carcinoma, primary	4	438.591	147.061	444.474
					Liver, hepatocellular carcinoma	16	339.718	312.097	186.297
Liver, normal	42	97.609	55.053	76.779
					Lung, adenocarcinoma, primary	46	395.333	277.394	321.811
Lung, adenosquamous carcinoma, primary	3	289.903	126.881	288.952

Lung, large cell carcinoma, primary	7	711.327	689.444	461.744
					Lung, neuroendocrine carcinoma (non-small cell type), primary	3	774.576	1219.221	84.446
Lung, normal	126	148.916	221.609	87.398
					Lung, small cell carcinoma, primary	3	2588.806	571.104	2303.79
Lung, squamous cell carcinoma, primary	39	474.506	215.236	411.88
					Oral cavity, squamous cell carcinoma, primary	3	487.365	162.008	451.582
Ovary, adenocarcinoma, clear cell type, primary	6	311.964	130.948	347.086
					Ovary, adenocarcinoma, endometrioid, primary	22	416.111	270.493	350.067
Ovary, adenocarcinoma, papillary serous type, primary	36	455.821	264.365	437.236
					Ovary, granule finenessCytoma, primary	3	418.185	134.782	444.559
Ovary, mucinous cystadenocarcinoma, Primary	7	240.015	98.597	206.486
					Ovary, Mullerian mixed tumor, Primary	5	893.972	723.698	759.005
Ovary, Normal	89	94.871	64.692	72.971
					Pancreas, adenocarcinoma, primary	23	225.254	85.825	226.028
Pancreas, islet cell tumor, malignant, Primary	7	135.288	67.946	157.649
					Pancreas, Normal	46	142.844	58.552	127.242
Prostate, adenocarcinoma, primary	86	86.485	31.51	80.935
					Prostate, normal	57	114.079	54.25	99.422
Rectum, adenocarcinoma (excluding mucinous type), primary	29	494.755	246.677	458.696
					Rectum, adenocarcinoma, mucoid, primary	3	735.218	490.808	880.833
Rectum, normal	44	370.889	136.132	367.675
					Skin, basal cell carcinoma, primary	4	330.685	104.388	299.771
Skin, malignant melanoma, primary	7	689.139	197.955	693.518
					Skin, normal	61	150.4	70.711	140.82
Skin, squamous cell carcinoma, primary	4	487.68	411.122	359.363

Small intestine, gastrointestinal stromal tumor (GIST), primary	4	141.255	100.778	140.167
					Small intestine, normal	97	303.491	125.797	290.568
Stomach, adenocarcinoma (excluding finger ring cell types), primary	27	510.892	294.791	463.295
					Sample set	Number of samples	Mean value of	Standard deviation of	Median value
Stomach, adenocarcinoma, finger print cell type, primary	9	395.57	185.806	327.718
					Stomach, gastrointestinal stromal tumor (GIST), primary	9	280.21	203.266	248.372
Stomach being normal	52	233.257	147.033	184.606
					Thyroid, follicular carcinoma, primary	3	165.154	166.032	71.214
Thyroid, normal	24	75.569	58.227	54.852
					Thyroid, papillary carcinoma, primary; all variants	29	199.353	100.226	208.498
Bladder, normal	9	122.017	41.588	121.504
					Bladder, transitional cell carcinoma, primary	4	929.875	676.766	763.497
Cervix, adenocarcinoma, primary	3	396.607	320.83	492.964
					Cervix, normal	115	139.799	168.179	96.579
Vulva, normal of vulva	4	219.039	93.687	174.65
					Vulvar, squamous cell carcinoma, primary	5	514.322	465.291	319.74

Dihydrofolate reductase

Folate plays an important role in one-carbon unit metabolism, which is critical for purine, thymidylate biosynthesis and thus DNA replication. The antifolate methotrexate was rationally designed 60 years ago for a potent blockade of the folate-dependent enzyme dihydrofolate reductase (DHFR) to achieve temporary remission in childhood acute leukemia. Dihydrofolate reductase converts dihydrofolate to tetrahydrofolate, and de novo synthesis of purines, thymidylate and certain amino acids requires a methyl group shuttle. Whereas the functional dihydrofolate reductase gene has been depicted as chromosome 5, multiple intron-free processed pseudogenes or dihydrofolate reductase-like genes have been identified on separate chromosomes. DNA sequence amplification is one of the most common manifestations of genomic instability in human tumors. However, resistance to folic acid is a major obstacle to cure cancer chemotherapy. The mechanism of antifolate resistance is often associated with alterations in the reflux/reflux transporter of the antifolate, as well as the regulation of folate-dependent enzymes such as DHFR.

Experiments were performed in multiple tissue samples to determine if there was a correlation between ARP and DHFR expression. Table XXIII shows DHFR expression levels in various tissues. It can be seen that DHFR is co-regulated with PARP1 in ovarian, breast, endometrial, skin, lung, kidney, lymphoma sarcoma and kidney, wilms' tumor and other primary human tumor tissues. Accordingly, one embodiment is the treatment of a disease susceptible to a combination of PARP and DHFR modulators. In addition, DHFR-associated genes (including along co-regulated genes) are also included herein.

Table XXIII: DHFR (dihydrofolate reductase) expression in human primary tumors, compared to normal tissues.

Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Adrenal, adrenal cortex cell carcinoma, primary	3	53.061	37.548	57.399
Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Adrenal gland, normal	13	22.945	16.408	19.555
Bone, giant cell tumor of bone, primary	10	38.484	9.626	41.785
					Bone, normal	8	82.832	44.371	74.682
Bone, osteosarcoma, primary	4	87.758	29.643	78.453
					Mixed invasive carcinoma of the breast, ductus lactis and lobule, primary	8	58.62	32.781	49.355
Breast, invasive ductal carcinoma, primary	169	52.827	29.75	44.657
					Breast, invasive lobular carcinoma, primary	17	58.29	53.061	38.56
Breast, ductal carcinoma	3	44.978	22.862	57.325
					Breast, mucinous carcinoma, primary	4	40.964	16.635	47.057
Mammary gland, Normal	68	38.129	15.455	35.202
					Breast, phyllodes tumor (phyllocystic sarcoma), primary	5	51.482	17.856	44.299
Colon, adenocarcinoma (excluding mucinous types), primary	77	70.123	41.505	59.975
					Colon, adenocarcinoma, mucoid, primary	7	81.11	57.656	58.015
Colon, Normal	180	56.486	21.806	54.762
					Endometrium, adenocarcinoma, endometrioid type, primary	50	70.055	34.502	70.361
Endometrium, Mullerian mixed tumor, primary	7	85.451	61.922	77.752
					Endometrium, normal	23	28.606	11.427	27.791
Esophagus, adenocarcinoma, primary	3	45.832	23.407	47.507
					Esophagus, normal	22	37.982	11.676	37.601
Kidney, cancer, chromophobe type, primary	3	17.625	11.558	23.875

Kidney, normal	81	39.648	13.897	38.936
					Renal, renal cell carcinoma, clear cell type, primary	45	37.43	22.148	32.293
Renal, renal cell carcinoma, non-clear cell type, primary	15	33.744	17.337	32.808
					Renal, transitional cell carcinoma, primary	4	41.028	22.893	45.222
Kidney, Wilms' tumor, primary	8	174.762	79.335	176.578
					Larynx, normal	4	46.161	13.723	44.058
Larynx, squamous cell carcinoma, primary	4	46.204	34.758	32.263
					Liver, hepatocellular carcinoma	16	78.036	43.038	74.708
Liver, normal	42	86.709	31.903	89.705
					Lung, adenocarcinoma, primary	46	45.462	19.855	41.378
Lung, adenosquamous carcinoma, primary	3	32.97	6.387	30.038
					Lung, large cell carcinoma, primary	7	50.102	13.56	51.152
Lung, neuroendocrine carcinoma (non-small cell type), primary	3	39.58	22.283	32.609
					Lung, normal	126	30.627	18.138	27.496
Lung, small cell carcinoma, primary	3	207.21	116.1	172.329
					Lung, squamous cell carcinoma, primary	39	44.442	20.418	38.266
Oral cavity, squamous cell carcinoma, primary	3	50.591	48.384	22.788
					Ovary, adenocarcinoma, clear cell type, primary	6	52.468	11.372	50.238
Ovary, adenocarcinoma, endometrioid, primary	22	63.741	28.237	56.181
					Ovary, adenocarcinoma, papillary serous type, primary	36	70.085	42.998	53.931
Ovary, granulomatous tumor, primary	3	66.06	17.895	58.1
					Ovary, mucinous cystadenocarcinoma, Primary	7	59.345	17.46	58.75
Ovary, Mullerian mixed tumor, Primary	5	51.93	11.264	55.106
					Ovary, Normal	89	29.295	13.071	27.128
Pancreas, adenocarcinoma, primary	23	31.801	18.707	28.935

Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Pancreas, islet cell tumor, malignant, Primary	7	32.128	14.69	25.704
Pancreas, Normal	46	20.131	10.056	19.465
					Prostate, adenocarcinoma, primary	86	44.128	22.422	39.503
Prostate, normal	57	32.561	9.798	31.657
					Rectum, adenocarcinoma (excluding mucinous type), primary	29	79.861	39.471	72.342
Rectum, adenocarcinoma, mucoid, primary	3	65.662	30.635	69.424
					Rectum, normal	44	48.55	17.727	45.586
Skin, basal cell carcinoma, primary	4	71.724	31.055	69.857
					Skin, malignant melanoma, primary	7	76.207	40.33	63.72
Skin, normal	61	34.889	12.719	32.547
					Skin, squamous cell carcinoma, primary	4	59.489	33.534	48.304
Small intestine, gastrointestinal stromal tumor (GIST), primary	4	35.594	9.378	34.778
					Small intestine, normal	97	73.068	29.842	71.135
Stomach, adenocarcinoma (excluding finger ring cell types), primary	27	61.852	33.329	51.711
					Stomach, adenocarcinoma, finger ring Cell type, primary	9	58.447	26.841	54.011
Stomach, gastrointestinal stromal tumor (GIST), primary	9	45.187	44.147	27.267
					Stomach being normal	52	35.652	22.821	31.295
Thyroid, follicular carcinoma, primary	3	35.569	12.886	29.585
					Thyroid, normal	24	32.666	11.093	32.857
Thyroid, papillary carcinoma, primary; all variants	29	37.14	14.107	34.082
					Bladder, normal	9	22.458	7.004	21.109
Bladder, transitional cell carcinoma, primary	4	89.141	107.591	38.967
					Cervix, adenocarcinoma, primary	3	30.539	8.38	35.371
Cervix, normal	115	31.69	19.096	28.354

Vulva, normal of vulva	4	37.254	7.095	35.127
					Vulvar, squamous cell carcinoma, primary	5	65.844	39.414	55.885

NFκB

Nfkb has been detected in many cell types expressing cytokines, inflammatory chemokines, growth factors, cell adhesion molecules and some acute phase proteins for health, as well as in many disease states. NF-. kappa.B is activated by a wide variety of stimuli, such as cytokines, free-oxide radicals (oxidant-free radials), inhaled particles, ultraviolet radiation, and bacterial or viral products. Nuclear factor- κ B (NF- κ B) is a common name for a family of dimers formed from several proteins: NF-. kappa.B 1 (also known as p50/p105), NF-. kappa.B 2 (also known as p52/p100), REL, RELA (also known as p 65/NF-. kappa.B 3) and RELB. These different heterodimers bind to specific promoters to initiate transcription of a wide range of genes, which affects inflammatory responses as well as cell death and survival and tissue repair. NF-. kappa.B is active in the nucleus and is inhibited by kappa.B inhibitors (I.kappa.B) in the cytoplasm by their sequestration. I κ B binds to NF- κ B and is important for the maintenance of NF- κ B in the cytoplasm. NF-. kappa.B becomes active once it is released from I.kappa.B (FIG. 1). I κ B is a well-characterized target of several kinase cascades that activate the I κ B enzyme (IKK). The IKK α and IKK β subunits preferentially form heterodimers, and both directly phosphorylate I κ B, which leads to its ubiquitination and degradation by the proteosome. The IKK subunit IKK γ has structural and regulatory functions and is thought to mediate interactions with upstream kinases in response to cellular activation signals. Growth factors, cytokines such as interleukin-1 (IL-1) and tumor-necrosis factor (TNF), hormones, and other signals activate NF- κ B through phosphorylation of I κ B.

Important evidence suggests that NF-. kappa.B regulates tumor formation and tumor progression. Two mouse models of inflammation-associated cancer further support a link between NF- κ B activity and cancer formation and progression. For example, in a study of Mdr 2-knockout mice, it spontaneously developed an inflammatory disorder known as cholangiocytic hepatitis, suggesting that these mice develop hepatocellular carcinoma. The survival of hepatocytes and their progression to malignancy is regulated by NF- κ B7. Furthermore, in mouse models of colitis-associated cancer, deletion of IKK β in intestinal epithelial cells results in a significant reduction in tumor incidence. All these results indicate that NF- κ B activation, which is associated with increased incidence of cancer by being seen in inflammatory-based diseases.

Although chemotherapeutic agents have been successfully used to treat patients with many different types of cancer, the emergence of resistance to the cytotoxic effects of chemotherapy is a major impediment to effective cancer treatment. Most chemotherapeutic drugs cause the cell-death program through activation of the tumor-suppressor protein p 53. However, NF- κ B is also activated in response to treatment with cytotoxic drugs, such as taxane, vinca alkaloids, and topoisomerase inhibitors. The NF-. kappa.B pathway affects cell growth and apoptosis in many ways. For example, in HeLa cells, the topoisomerase I inhibitor SN38 (7-ethyl-10-hydroxycamptothecin), which is an active metabolite of irinotecan, and the topoisomerase II inhibitor doxorubicin, both induce NF- κ B nuclear transport, and activation of NF- κ B targets the genes directly through mobilization and stimulation of the IKK complex, rather than through secondary production of NF- κ B activators such as cytokines, allowing the cells to survive.

In vivo models of ovarian, colorectal and pancreatic Cancer have shown that NF-kB inhibition increases the efficacy of anti-Cancer drugs (Mabuchi et al, 2004, J.biol. chem.279: 23477-23485; Cusack et al, 2001, Cancer Res.61: 3535-3540; Shah et al, 2001, J.cell biochem.82: 110-122; Bold et al, 2001, J.Surg. Res.100: 11-17). NF- κ B inhibition is thought to prevent tumors from fighting chemotherapeutic agents. Thus, the development of NF- κ B inhibitors can increase the efficacy of many anticancer drugs.

Recent studies have shown that synthesis of protein-bound ADP-ribose polymers catalyzed by poly (ADP-ribose) polymerase-1 (PARP-1) modulates NF-. kappa.B-dependent pathways. NF-. kappa.B-p 50DNA binding is protein-poly (ADP-ribosyl) -dependent. Co-immunoprecipitation and immunoblot analysis revealed that PARP-1 physically interacts with NF-. kappa.B-p 50 with high specificity (Chang WJ, Alvarez-Gonzalez R., J biol. chem.2001 Dec 14; 276 (50): 47664-70. the sequence-specific binding of NF-. kappa.B is reversibly regulated by auto-correction reaction of poly (ADP-ribose) polymerase 1). In addition to direct interaction with PARP1, the NF- κ B pathway is co-regulated in several tumor types, with PARP1 upregulation also being observed (see tables I-XVIII). Furthermore, NF-. kappa.B is a ubiquitous transcription factor and promotes transcription of 150 genes (Mori et al, 2002, Blood 100: 1828-234; Mori et al, 1999, Blood 93: 2360-2368). The NF-. kappa.B molecular pathway comprises several key cellular proteins (involved in the regulation of inflammation, apoptosis, cell proliferation and differentiation), such as IRAK1, Bcl-2(Yang et al, 2006, Clin Cancer Res.12: 950-60), Bcl-6(Li et al, 2005, JImmunol.174 (1): 205-14), VEGF (Tong et al, 2006, Respir Res.2: 7: 37), Aurora kinase and VAV3 oncogenes.

Accordingly, one embodiment is the treatment of a disease susceptible to a combination of PARP and NFKB modulators. In addition, NFKB related genes, IRAK1, Bcl-2, Bcl-6, Aurora kinase, VAV3 oncogene and other genes commonly regulated in the NFKB pathway are also included herein.

Endothelial cytokine/VEGF

Endothelial cells provide nutrients and oxygen and remove catabolites and produce multiple growth factors that promote tumor growth, invasion and survival. Thus, angiogenesis provides both perfusion and paracrine effects on growing tumors and tumor cells, and endothelial cells can drive each to expand the malignant phenotype. Ovarian cancer is a major cause of cancer morbidity and mortality, despite advances in modern surgical and chemotherapeutic control. The molecular pathways controlling angiogenesis are critical to the pathogenesis of ovarian cancer and have been shown to be prognostic. The understanding of molecular pathways involved in regulating angiogenesis has led to the identification of many targets for anti-angiogenic therapy. Anti-angiogenic agents are currently in clinical trials, some of which have been approved or are being approved for clinical use in the treatment of cancer and other angiogenesis-dependent diseases. One target of angiogenesis is VEGF and its receptors. VEGF, initially known as VPF due to its increased vascular permeability, stimulates the proliferation and migration of endothelial cells and plays a key role in angiogenesis, and endothelial integrity and survival. VEGF plays important roles in other biological signaling functions, including tumor cell survival and motility, hematopoiesis, immune function, liver integrity, and nervous system function. The multiple functions of VEGF are regulated by several different receptors, including the tyrosine kinase receptors VEGFR1(flt-1), VEGFR2(KDR, flk-1), and VEGFR3(flt4), with different binding specificities for each form of VEGF.

Experiments were performed in multiple tumor tissue samples to determine if there was a correlation between PARP and VEGF expression. Table XXIV shows expression levels in various tissues. It can be seen that VEGF is upregulated with PARP1 and is regulated in and in co-regulation with tumors of the same subtype, such as breast, ovarian and skin tumors and sarcomas. Accordingly, one embodiment is the treatment of a disease susceptible to a combination of PARP and VEGF modulators. In addition, VEGF related genes, including those co-regulated in the VEGF pathway, are also included herein.

Table XXIV: VEGF (vascular endothelial growth factor) expression in human primary tumors, compared to normal tissues.

Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Adrenal, adrenal cortex cell carcinoma, primary	3	386.427	220.704	275.803

Adrenal gland, normal	13	534.83	424.117	485.418
					Bone, giant cell tumor of bone, primary	10	325.043	304.973	215.554
Bone, normal	8	195.529	73.331	187.259
					Bone, osteosarcoma, primary	4	602.198	578.869	452.353
Mixed invasive carcinoma of the breast, ductus lactis and lobule, primary	8	191.214	66.208	171.42
					Breast, invasive ductal carcinoma, primary	169	307.37	185.757	255.532
Breast, invasive lobular carcinoma, primary	17	305.927	201.926	241.604
					Breast, ductal carcinoma	3	252.557	113.835	305.515
Breast, mucinous carcinoma, primary	4	207.89	79.708	202.417
					Mammary gland, Normal	68	225.756	177.612	190.945
Breast, phyllodes tumor (phyllocystic sarcoma), primary	5	379.044	247.428	340.865
					Colon, adenocarcinoma (excluding mucinous types), primary	77	403.428	291.03	331.978
Colon, adenocarcinoma, mucoid, primary	7	343.139	227.791	363.118
					Colon, Normal	180	193.049	123.726	162.853
Endometrium, adenocarcinoma, endometrioid type, primary	50	429.783	250.521	368.132
					Endometrium, Mullerian mixed tumor, primary	7	376.359	163.596	382.885
Endometrium, normal	23	575.093	382.852	476.946
					Esophagus, adenocarcinoma, primary	3	464.866	319.11	455.746
Esophagus, normal	22	294.149	150.077	282.678
					Kidney, cancer, chromophobe type, primary	3	455.21	63.48	467.21
Kidney, normal	81	494.861	235.446	464.756
					Renal, renal cell carcinoma, clear cell type, primary	45	2068.059	1272.634	2000.188
Renal, renal cell carcinoma, non-clear cell type, primary	15	937.413	931.299	654.782
					Renal, transitional cell carcinoma, primary	4	975.47	808.737	754.803
Kidney, Wilms' tumor, primary	8	239.096	134.285	190.813

Larynx, normal	4	256.177	200.315	177.084
					Larynx, squamous cell carcinoma, primary	4	253.816	104.837	217.95
Liver, hepatocellular carcinoma	16	471.428	322.779	382.127
					Liver, normal	42	498.101	210.551	497.388
Lung, adenocarcinoma, primary	46	565.451	310.102	490.923
					Lung, adenosquamous carcinoma, primary	3	579.793	730.484	222.619
Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Lung, large cell carcinoma, primary	7	514.945	302.189	452.012
Lung, neuroendocrine carcinoma (non-small cell type), primary	3	180.059	54.684	189.478
					Lung, normal	126	473.02	210.329	446.044
Lung, small cell carcinoma, primary	3	341.097	216.97	383.485
					Lung, squamous cell carcinoma, primary	39	426.689	273.396	389.508
Oral cavity, squamous cell carcinoma, primary	3	336.828	172.021	272.722
					Ovary, adenocarcinoma, clear cell type, primary	6	189.693	85.656	161.422
Ovary, adenocarcinoma, endometrioid, primary	22	475.62	316.071	419.278
					Ovary, adenocarcinoma, papillary serous type, primary	36	529.555	283.552	476.174
Ovary, granulomatous tumor, primary	3	235.513	64.065	228.599
					Ovary, mucinous cystadenocarcinoma, Primary	7	282.313	120.574	298.024
Ovary, Mullerian mixed tumor, Primary	5	421.141	195.681	308.7
					Ovary, Normal	89	100.699	72.854	86.687
Pancreas, adenocarcinoma, primary	23	524.075	227.812	478.653
					Pancreas, islet cell tumor, malignant, Primary	7	639.243	499.434	530.466
Pancreas, Normal	46	407.617	115.931	425.551
					Prostate, adenocarcinoma, primary	86	547.601	377.291	460.667
Prostate, normal	57	805.882	540.435	715.723

Rectum, adenocarcinoma (excluding mucinous type), primary	29	371.234	162.844	344.84
					Rectum, adenocarcinoma, mucoid, primary	3	262.932	88.046	215.869
Rectum, normal	44	182.564	103.8	164.297
					Skin, basal cell carcinoma, primary	4	300.302	270.286	240.215
Skin, malignant melanoma, primary	7	127.179	84.561	97.95
					Skin, normal	61	123.011	59.089	119.897
Skin, squamous cell carcinoma, primary	4	212.813	94.938	192.998
					Small intestine, gastrointestinal stromal tumor (GIST), primary	4	265.372	271.901	203.655
Small intestine, normal	97	257.186	170.574	215.101
					Stomach, adenocarcinoma (excluding finger ring cell types), primary	27	413.359	296.365	317.794
Stomach, adenocarcinoma, finger print cell type, primary	9	288.769	80.831	288.931
					Stomach, gastrointestinal stromal tumor (GIsT), Primary	9	242.777	381.025	102.627
Stomach being normal	52	362.303	159.695	328.802
					Thyroid, follicular carcinoma, primary	3	841.322	697.265	925.178
The thyroid gland is provided with a plurality of thyroid glands,is normal	24	1134.377	286.605	1134.341
					Thyroid, papillary carcinoma, primary; all variants	29	836.596	350.532	873.247
Bladder, normal	9	262.966	166.1	173.303
					Bladder, transitional cell carcinoma, primary	4	719.789	248.426	735.062
Cervix, adenocarcinoma, primary	3	428.006	164.593	467.605
					Cervix, normal	115	259.71	271.623	197.708
Vulva, normal of vulva	4	203.085	146.444	154.186
					Vulvar, squamous cell carcinoma, primary	5	329.278	108.746	291.862

Matrix metalloproteinases family

Matrix metalloproteinase-9 (matrix metallopeptidase-9; MMP9), also known as 92-kD gelatinase or type V collagenase, is a 92-kD type IV collagenase that degrades collagen in the extracellular matrix. MMP9 expression plays a role in enabling angiogenesis and invasion through different types of pituitary tumors, with MMP9 expression being present in some invasive and recurrent pituitary adenomas as well as in most pituitary carcinomas. Furthermore, aggressive megaprolactinoma is more likely to express MMP9 than non-aggressive megaprolactioma. Aggressive megaprolactinoma showed higher-density MMP9 staining compared to non-aggressive tumors and normal pituitary glands, or between prolactinoma of different sizes. MMP9 expression was also associated with aggressive tumor behavior. MMP-9 also belongs to the molecular network of the transcription factor nuclear-factor kappa B (NF-. kappa.B), which is a marker of many highly malignant tumors (St-Pierre et al, 2004, Expert opin. therp. targets 8: 473-.

Concentrations of MMP9 were also increased in bronchoalveolar lavage (BAL), sputum, bronchi, and serum of asthmatic patients, compared to normal individuals. Using a segmented bronchial challenge (SBP) for BAL and ELISA assays (Kelly et al, 2000, am.J.Resp.Crit.CareMed.162: 1157-1161) from allergic patients, increased MMP9 was detected in antigen-challenged patients compared to saline-challenged patients. The same study also concluded that MMP9 can be attributed not only to inflammation but also to eventual airway remodeling in asthma.

The link between MMP9 expression and tumor recurrence and tumor invasion, and its association with angiogenesis, suggests that administration of MMP9 inhibitors is a potential therapeutic strategy. Overexpression of MMP-9 in cancer and a variety of inflammatory conditions points to a molecular mechanism controlling its expression as a potential target for eventual rational therapeutic intervention.

Experiments were performed in multiple tumor tissue samples to determine if there was a correlation between PARP and MMP9 expression. Table XXV shows the expression levels in various tissues. As can be seen, MMP9 is regulated and co-regulated with PARP1 in tumors of the same subtype, such as breast, endometrial, lung, ovarian and skin tumors and sarcomas. Accordingly, one embodiment is the treatment of a disease susceptible to a combination of PARP and MMP9 modulators. In addition, genes associated with MMP9, including genes co-regulated in the MMP9 pathway, are also included herein.

Table XXV: MMP9 (matrix metalloproteinase 9; gelatinase B, 92kDa gelatinase, 92kDa collagenase type IV) was expressed in human primary tumors compared to normal tissues.

Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Adrenal, adrenal cortex cell carcinoma, primary	3	309.003	363.776	111.922
Adrenal gland, normal	13	252.092	641.203	78.986
					Bone, giant cell tumor of bone, primary	10	8416.738	2667.464	7897.901
Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Bone, normal	8	2879.804	1459.135	3104.17
Bone, osteosarcoma, primary	4	4257.056	4017.873	3840.443
					Mixed invasive carcinoma of the breast, ductus lactis and lobule, primary	8	365.875	238.051	297.772
Breast, invasive ductal carcinoma, primary	169	458.281	676.915	312.815
					Breast, invasive lobular carcinoma, primary	17	242.394	186.712	184.418
Breast, ductal carcinoma	3	174.671	131.922	118.519
					Breast, mucinous carcinoma, primary	4	554.482	474.424	531.033
Mammary gland, Normal	68	212.419	532.284	109.432

Breast, phyllodes tumor (phyllocystic sarcoma), primary	5	152.665	73.258	173.198
					Colon, adenocarcinoma (excluding mucinous types), primary	77	281.312	182.492	243.195
Colon, adenocarcinoma, mucoid, primaryProperty of (2)	7	506.083	504.14	208.984
					Colon, Normal	180	146.424	76.77	125.097
Endometrium, adenocarcinoma, endometrioid type, primary	50	280.906	226.62	184.995
					Endometrium, Mullerian mixed tumor, primary	7	2130.553	4421.419	152.861
Endometrium, normal	23	74.372	81.725	52.858
					Esophagus, adenocarcinoma, primary	3	162.76	119.022	126.363
Esophagus, normal	22	99.099	43.267	87.497
					Kidney, cancer, chromophobe type, primary	3	74.455	12.548	74.468
Kidney, normal	81	65.316	29.326	53.621
					Renal, renal cell carcinoma, clear cell type, primary	45	207.592	264.124	118.489
Renal, renal cell carcinoma, non-clear cell type, primary	15	132.558	168.005	83.409
					Renal, transitional cell carcinoma, primary	4	111.546	77.957	85.9
Kidney, Wilms' tumor, primary	8	100.97	58.478	88.166
					Larynx, normal	4	162.638	197.338	77.062
Larynx, squamous cell carcinoma, primary	4	675.211	526.673	461.672
					Liver, hepatocellular carcinoma	16	182.726	121.648	140.502
Liver, normal	42	91.165	56.079	78.537
					Lung, adenocarcinoma, primary	46	382.767	295.098	269.92
Lung, adenosquamous carcinoma, primary	3	157.601	24.124	169.713
					Lung, large cell carcinoma, primary	7	513.391	243.603	389.392
Lung, neuroendocrine carcinoma (non-small cell type), primary	3	169.638	135.354	144.106
					Lung, normal	126	199.713	537.561	113.429
Lung, small cell carcinoma, primary	3	116.438	20.137	123.616
					Lung, squamous cell carcinoma, primary	39	458.118	327.988	389.82
Oral cavity, squamous cell carcinoma, primary	3	888.299	613.909	784.061
					Ovary, adenocarcinoma, clear cell type, primary	6	84.894	28.076	97

Ovary, adenocarcinoma, endometrioid, primary	22	240.36	248.189	132.824
					Ovary, adenocarcinoma, papillary serous type, primary	36	306.398	377.337	200.176
Ovary, granulomatous tumor, primary	3	54.976	11.932	60.659
					Ovary, mucinous cystadenocarcinoma, Primary	7	141.805	147.638	75.617
Ovary, Mullerian mixed tumor, Primary	5	173.381	132.143	87.017
					Ovary, Normal	89	79.258	34.05	74.142
Pancreas glandAdenocarcinoma, primary	23	771.454	2575.291	170.842
					Pancreas, islet cell tumor, malignant, Primary	7	94.33	64.615	78.529
Pancreas, Normal	46	114.647	45.476	107.669
					Sample set	Number of samples	Mean value of	Standard deviation of	Median value
Prostate, adenocarcinoma, primary	86	97.399	54.502	89.814
					Prostate, normal	57	88.492	62.469	76.093
Rectum, adenocarcinoma (excluding mucinous type), primary	29	263.49	137.758	225.801
					Rectum, adenocarcinoma, mucoid, primary	3	243.039	77.917	261.742
Rectum, normal	44	138.354	57.909	134.267
					Skin, basal cell carcinoma, primary	4	310.963	41.044	316.027
Skin, malignant melanoma, primary	7	438.656	524.74	226.982
					Skin, normal	61	178.343	140.519	131.711
Skin, squamous cell carcinoma, primary	4	623.436	372.054	519.425
					Small intestine, gastrointestinal stromal tumor (GIST), primary	4	123.403	136.145	71.538
Small intestine, normal	97	159.231	138.833	115.218
					Stomach, adenocarcinoma (excluding finger ring cell types), primary	27	278.681	198.698	199.374
Stomach, adenocarcinoma, finger print cell type, primary	9	248.745	135.248	190.314
					Stomach, gastrointestinal stromal tumor (GIST), primary	9	92.783	24.101	86.242
Stomach being normal	52	111.717	50.627	99.757
					Thyroid, follicular carcinoma, primary	3	107.466	29.565	123.712
Thyroid, normal	24	109.347	67.108	93.531
					Thyroid, papillary carcinoma, primary; all variants	29	219.295	167.203	143.996

Bladder, normal	9	96.898	51.823	93.024
					Bladder, transitional cell carcinoma, primary	4	318.932	441.905	120.076
Cervix, adenocarcinoma, primary	3	98.137	20.265	93.975
					Cervix, normal	115	118.874	156.193	81.22
Vulva, normal of vulva	4	174.167	131.037	134.115
					Vulvar, squamous cell carcinoma, primary	5	361.991	143.537	284.436

Vascular Endothelial Growth Factor Receptor (VEGFR)

As discussed above, molecular pathways controlling angiogenesis are critical to the pathogenesis of cancer, including ovarian cancer, and have been shown to be prognostic. The understanding of molecular pathways involved in regulating angiogenesis has led to the identification of many targets for anti-angiogenic therapies. Anti-angiogenic agents are currently used in clinical trials, and some have been approved or are being approved clinically for use in the treatment of cancer and other angiogenesis-dependent diseases. One of the most abundant targets of angiogenesis is VEGF and its receptors. The multiple functions of VEGF are regulated by several different receptors, including the tyrosine kinase receptors VEGFR1(flt-1), VEGFR2(KDR, flk-1), and VEGFR3(flt4), which have different binding specificities for various forms of VEGF.

Experiments were performed in multiple tumor tissue samples to determine if there was a correlation between PARP and VEGFR expression. Table XXVI shows the expression levels in various tissues. It can be seen that VEGFR is up-regulated with PARP1 in the same subtype of tumors and is co-regulated, such as breast, ovarian and skin tumors and sarcomas. Accordingly, one embodiment is the treatment of diseases susceptible to a combination of PARP and VEGFR modulators. Furthermore, VEGFR related genes, including genes that are commonly regulated in the VEGFR pathway, are also included herein.

Table XXVI: VEGFR (vascular endothelial growth factor receptor; fms-related tyrosine kinase 1; vascular permeability factor receptor) expression in human primary tumors, as compared to normal tissues.

Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Adrenal, adrenal cortex cell carcinoma, primary	3	164.936	4.48	166.572
Adrenal gland, normal	13	152.418	86.102	125.14
					Bone, giant cell tumor of bone, primary	10	208.978	82.892	212.244
Bone, normal	8	124.117	48.471	120.579
					Bone, osteosarcoma, primary	4	172.903	40.099	187.677
Mixed invasive carcinoma of the breast, ductus lactis and lobule, primary	8	108.947	17.335	108.756
					Breast, invasive ductal carcinoma, primary	169	139.716	54.83	131.223

Breast, invasive lobular carcinoma, primary	17	140.044	71.903	132.439
					Breast, ductal carcinoma	3	127.712	66.629	138.567
Breast, mucinous carcinoma, primary	4	177.408	128.251	162.643
					Mammary gland, Normal	68	144.957	49.448	139.707
Breast, phyllodes tumor (phyllocystic sarcoma), primary	5	194.148	80.426	143.412
					Colon, adenocarcinoma (excluding mucinous types), primary	77	147.279	80.655	130.934
Colon, adenocarcinoma, mucoid, primary	7	129.576	76.123	117.097
					Colon, Normal	180	109.609	50.48	107.287
Endometrium, adenocarcinoma, endometrioid type, primary	50	162	71.111	142.101
					Endometrium, Mullerian mixed tumor, primary	7	155.66	62.996	134.38
Endometrium, normal	23	154.482	60.008	158.068
					Esophagus, adenocarcinoma, primary	3	158.602	117.853	104.145
Esophagus, normal	22	140.646	63.48	119.305
					Kidney, cancer, chromophobe type, primary	3	141.386	41.858	148.401
Kidney, normal	81	179.173	82.344	166.604
					Renal, renal cell carcinoma, clear cell type, primary	45	763.988	488.604	817.291
The kidney of the patient is in the state of kidney,renal cell carcinoma, non-clear cell type, primary	15	315.641	258.129	239.351
					Renal, transitional cell carcinoma, primary	4	137.1	70.462	139.443
Kidney, Wilms' tumor, primary	8	133.696	41.772	119.966
					Larynx, normal	4	134.412	62.546	118.376
Larynx, squamous cell carcinoma, primary	4	161.819	39.718	177.312
					Liver, hepatocellular carcinoma	16	211.309	113.676	202.537
Liver, normal	42	163.819	194.899	118.909
					Lung, adenocarcinoma, primary	46	190.999	63.168	186.342
Lung, adenosquamous carcinoma, primary	3	118.837	36.286	125.858

Lung, large cell carcinoma, primary	7	225.434	125.006	208.652
					Lung, neuroendocrine carcinoma (non-small cell type), primary	3	128.331	15.91	132.63
Lung, normal	126	206.081	103.97	186.79
					Lung, small cell carcinoma, primary	3	129.72	27.533	139.847
Lung, squamous cell carcinoma, primary	39	203.882	76.374	193.402
					Oral cavity, squamous cell carcinoma, primary	3	187.011	56.588	217.093
Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Ovary, adenocarcinoma, clear cell type, primary	6	117.336	30.027	124.267
Ovary, adenocarcinoma, endometrioid, primary	22	141.227	70.984	120.492
					Ovary, adenocarcinoma, papillary serous type, primary	36	127.796	60.599	120.385
Ovary, granulomatous tumor, primary	3	100.205	32.533	81.852
					Ovary, mucinous cystadenocarcinoma, Primary	7	130.879	33.579	146.784
Ovary, Mullerian mixed tumor, Primary	5	157.225	75.293	164.511
					Ovary, Normal	89	92.269	45.755	84.056
Pancreas, adenocarcinoma, primary	23	231.983	77.716	221.626
					Pancreas, islet cell tumor, malignant, Primary	7	250.136	96.966	195.835
Pancreas, Normal	46	143.642	55.219	132.551
					Prostate, adenocarcinoma, primary	86	129.853	91.797	108.61
Prostate, normal	57	167.226	71.922	169.295
					Rectum, adenocarcinoma (excluding mucinous type), primary	29	139.189	56.884	124.772
Rectum, adenocarcinoma, mucoid, primary	3	89.556	31.809	72.237
					Rectum, normal	44	117.38	49.095	109.924
Skin, basal cell carcinoma, primary	4	133.536	71.765	126.292
					Skin, malignantMelanoma, primary of origin	7	105.148	56.109	75.886
Skin, normal	61	127.806	44.362	118.749

Skin, squamous cell carcinoma, primary	4	173.046	30.208	174.057
					Small intestine, gastrointestinal stromal tumor (GIST), primary	4	212.338	88.898	177.183
Small intestine, normal	97	120.66	42.031	112.947
					Stomach, adenocarcinoma (excluding finger ring cell types), primary	27	151.819	53.342	138.801
Stomach, adenocarcinoma, finger print cell type, primary	9	181.654	47.637	181.526
					Stomach, gastrointestinal stromal tumor (GIST), primary	9	155.728	107.806	113.455
Stomach being normal	52	135.918	42.117	139.831
					Thyroid, follicular carcinoma, primary	3	222.44	128.368	277.516
Thyroid, normal	24	372.974	102.414	337.823
					Thyroid, papillary carcinoma, primary; all variants	29	297.717	136.673	247.497
Bladder, normal	9	190.26	93.234	152.274
					Bladder, transitional cell carcinoma, primary	4	273.824	262.168	161.156
Cervix, adenocarcinoma, primary	3	160.544	59.888	128.978
					Cervix, normal	115	183.173	96.843	170.376
Vulva, normal of vulva	4	190.585	45.15	188.274
					Vulvar, squamous cell carcinoma, primary	5	220.708	42.917	234.018

Vascular endothelial growth factor receptor 2(VEGFR2)

As discussed above, the tyrosine kinase receptor family of VEGFRs, which plays a role in angiogenesis, is a potential target for the development of anticancer therapeutics. Experiments were therefore performed to determine the correlation that existed between PARP and VEGFR2 expression in various tumor tissue samples. Table XXVII shows the expression levels in various tissues. It can be seen that VEGFR2 is upregulated and co-regulated with PARP1 in tumors of the same subtype, such as tumors of the breast, ovary, and skin and sarcoma. Accordingly, one embodiment is the treatment of diseases susceptible to PARP and VEGFR modulators. Furthermore, VEGFR2 related genes, including genes that are commonly regulated in the VEGFR2 pathway, are also included herein.

Table XXVII: expression of VEGFR2 (vascular endothelial growth factor receptor 2, kinase insert domain receptor (type III receptor tyrosine kinase)) in human primary tumors compared to normal tissues.

Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Adrenal, adrenal cortex cell carcinoma, primary	3	54.418	16.608	54.696

Adrenal gland, normal	13	111.67	121.562	66.839
					Bone, giant cell tumor of bone, primary	10	54.808	21.963	52.183
Bone, normal	8	72.551	29.122	64.245
					Bone, osteosarcoma, primary	4	55.346	17.552	55.116
Mixed invasive carcinoma of the breast, ductus lactis and lobule, primary	8	38.151	9.897	40.119
					Breast, invasive ductal carcinoma, primary	169	45.243	17.55	44.149
Breast, invasive lobular cancer,primary disease(s)	17	57.124	23.57	52.747
					Breast, ductal carcinoma	3	55.079	16.518	61.707
Breast, mucinous carcinoma, primary	4	49.099	33.814	40.821
					Mammary gland, Normal	68	72.812	29.255	66.472
Breast, phyllodes tumor (phyllocystic sarcoma), primary	5	88.855	36.644	73.775
					Colon, adenocarcinoma (excluding mucinous types), primary	77	33.293	16.994	30.262
Colon, adenocarcinoma, mucoid, primary	7	33.315	8.847	32.644
					Colon, Normal	180	31.22	15.867	27.868
Endometrium, adenocarcinoma, endometrioid type, primary	50	42.819	27.836	36.227
					Endometrium, Mullerian mixed tumor, primary	7	35.176	14.565	30.606
Endometrium, normal	23	118.847	90.297	105.117
					Esophagus, adenocarcinoma, primary	3	36.744	14.795	33.667
Esophagus, normal	22	34.456	10.861	33.479
					Kidney, cancer, chromophobe type, primary	3	45.755	28.875	32.784
Kidney, normal	81	78.391	29.358	75.001
					Renal, renal cell carcinoma, clear cell type, primary	45	178.44	145.319	142.553
Renal, renal cell carcinoma, non-clear cell type, primary	15	102.066	105.1	56.906
					Renal, transitional cell carcinoma, primary	4	28.451	12.694	24.175
Kidney, Wilms' tumor, primary	8	49.808	24.211	51.614

Larynx, normal	4	49.429	6.255	51.377
					Larynx, squamous cell carcinoma, primary	4	44.504	20.342	35.819
Liver, hepatocellular carcinoma	16	67.244	28.225	68.843
					Liver, normal	42	87.754	40.675	84.103
Lung, adenocarcinoma, primary	46	61.276	31.117	51.565
					Lung, adenosquamous carcinoma, primary	3	56.68	35.265	43.723
Lung, large cell carcinoma, primary	7	40.867	38.503	29.793
					Lung, neuroendocrine carcinoma (non-small cell type), primary	3	53.965	39.357	40.297
Lung, normal	126	111.651	47.136	107.643
					Lung, small cell carcinoma, primary	3	22.696	9.35	24.654
Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Lung, squamous cell carcinoma, primary	39	37.921	16.918	35.459
Oral cavity, squamous cell carcinoma, primary	3	27.326	5.753	24.035
					Ovary, adenocarcinoma, clear cell type, primary	6	35.485	19.253	30.079
Ovary, adenocarcinoma, endometrioid, primary	22	32.288	14.611	29.366
					Ovary, adenocarcinoma, papillary serous type, primary	36	29.226	11.714	25.12
Ovary, granulomatous tumor, primary	3	38.018	6.286	34.969
					Ovary, mucinous cystadenocarcinoma, Primary	7	34.894	7.065	34.569
Ovary, Mullerian mixed tumor, Primary	5	19.053	7.903	16.049
					Ovary, Normal	89	44.58	15.589	43.665
Pancreas, adenocarcinoma, primary	23	40.994	16.987	38.622
					Pancreas, islet cell tumor, malignant, Primary	7	76.18	45.816	68.714
Pancreas, Normal	46	43.239	15.192	40.642
					Prostate, adenocarcinoma, primary	86	37.848	16.065	32.759
Prostate, normal	57	52.378	22.855	50.076

Rectum, adenocarcinoma (excluding mucinous type), primary	29	35.377	12.352	35.386
					Rectum, adenocarcinoma, mucoid, primary	3	28.283	11.811	21.766
Rectum, normal	44	28.944	14.854	25.861
					Skin, basal cell carcinoma, primary	4	42.488	20.683	43.236
Skin, malignant melanoma, primary	7	39.168	10.039	40.545
					Skin, normal	61	59.014	24.546	54.485
Skin, squamous cell carcinoma, primary	4	50.418	15.958	54.986
					Small intestine, gastrointestinal stromal tumor (GIST), primary	4	31.127	12.326	31.387
Small intestine, normal	97	31.744	15.843	28.931
					Stomach adenocarcinoma (excluding finger ring)Cell type), primary	27	39.251	18.89	36.631
Stomach, adenocarcinoma, finger print cell type, primary	9	33.975	12.855	29.06
					Stomach, gastrointestinal stromal tumor (GIsT), Primary	9	70.241	131.243	23.443
Stomach being normal	52	38.534	13.998	35.883
					Thyroid, follicular carcinoma, primary	3	56.578	7.441	54.753
Thyroid, normal	24	137.266	40.699	137.41
					Thyroid, papillary carcinoma, primary; all variants	29	95.774	49.594	87
Bladder, normal	9	51.661	30.22	36.98
					Bladder, transitional cell carcinoma, primary	4	38.644	12.864	33.928
Cervix, adenocarcinoma, primary	3	59.629	5.755	59.743
					Cervix, normal	115	82.943	40.489	75.229
Vulva, normal of vulva	4	55.41	9.211	53.173
					Vulvar, squamous cell carcinoma, primary	5	53.617	25.435	47.715

Interleukin 1 receptor associated kinase 1(IRAK1)

Interleukin-1 is a proinflammatory cytokine that acts to produce a systemic and local response to infection, injury, and immune attack. IL1 (produced primarily by induced macrophages and monocytes) is involved in lymphocyte activation, fever, leukocyte trafficking, acute phase responses, and cartilage remodeling. The biological activity of IL1 is mediated by its type I receptor located on the plasma membrane of responder cells. Binding of IL1 to its receptor triggers activation of the nuclear factor kappa-B, a family of related transcription factors that regulate expression of genes with cognate DNA binding sites. NF-. kappa.B is retained in the cytoplasm of most cells by inhibitory kappa.B proteins. The inhibitory protein degrades in response to a variety of extracellular stimuli, including IL1, releasing NF- κ -B into the nucleus where it activates a number of genes. Interleukin-1 receptor activated kinases (IRAKs) are key regulators in the signaling pathway of the IL-1 receptor. IRAK1 is a key mechanism for NF- κ B activation, as found in experiments with IRAK-deficient mice (which showed reduced activation of NFKB).

Experiments were performed in multiple tumor tissue samples to determine whether there was a correlation between PARP and IRAK1 expression. Table XXVIII shows the expression levels in various tissues. As can be seen, IRAK1 is regulated and co-regulated with PARP1 in tumors of the same subtype, such as breast, endometrial, ovarian and lung tumors and sarcomas. Accordingly, one embodiment is the treatment of a disease susceptible to a combination of PARP and IRAK1 modulators. Additionally, IRAK 1-related genes, including genes that are commonly regulated in the VEGFR pathway, are also included herein.

Table XXVIII: expression of IRAK1 (interleukin 1 receptor-associated kinase 1) in human primary tumors compared to normal tissue.

Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Adrenal, adrenal cortex cell carcinoma, primary	3	673.561	474.546	500.804
Adrenal gland, normal	13	459.673	151.366	454.364
					Bone, giant cell tumor of bone, primary	10	391.207	133.291	371.409
Bone, normal	8	397.607	117.151	372.114
					Bone, osteosarcoma, primary	4	479.645	49.624	465.032
Mixed invasive carcinoma of the breast, ductus lactis and lobule, primary	8	636.321	642.372	413.28
					Breast, invasive ductal carcinoma, primary	169	456.616	211.377	401.965
Breast, invasive lobular carcinoma, primary	17	350.163	151.82	314.908
					Breast, ductal carcinoma	3	245.276	70.2	209.671
Breast, mucinous carcinoma, primary	4	335.537	79.055	316.279
					Mammary gland, Normal	68	323.839	107.498	301.842
Breast, phyllodes tumor (phyllocystic sarcoma), primary	5	292.625	53.779	286.932
					Colon, adenocarcinoma (excluding mucinous types), primary	77	621.857	244.1	569.836
Colon, adenocarcinoma, mucoid, primary	7	599.666	189.643	504.995
					Colon, Normal	180	388.56	124.057	365.397
Endometrium, adenocarcinoma, endometrioid type, primary	50	326.862	132.076	310.135

Endometrium, Mullerian mixed tumor, primary	7	442.289	171.683	475.694
					Endometrium, normal	23	237.621	106.731	219.986
Esophagus, adenocarcinoma, primary	3	1091.677	116.454	1149.642
					Esophagus, normal	22	376.737	120.868	360.387
Kidney, cancer, chromophobe type, primary	3	281.963	27.212	280.497
					Sample set	Number of samples	Mean value of	Standard deviation of	Median value
Kidney, normal	81	302.706	88.382	305.896
					Renal, renal cell carcinoma, clear cell type, primary	45	365.557	116.429	348.144
Renal, renal cell carcinoma, non-clear cell type, primary	15	469.698	204.005	385.459
					Renal, transitional cell carcinoma, primary	4	451.774	131.753	493.001
Kidney, Wilms' tumor, primary	8	306.802	105.516	307.513
					Larynx, normal	4	437.626	182.359	452.501
LarynxSquamous cell carcinoma, primary	4	535.586	192.651	499.768
					Liver, hepatocellular carcinoma	16	398.31	157.464	395.092
Liver, normal	42	177.604	62.495	168.052
					Lung, adenocarcinoma, primary	46	573.945	263.63	529.26
Lung, adenosquamous carcinoma, primary	3	422.739	45.237	425.833
					Lung, large cell carcinoma, primary	7	548.695	222.506	499.715
Lung, neuroendocrine carcinoma (non-small cell type), primary	3	362.296	228.291	283.294
					Lung, normal	126	299.378	105.865	281.969
Lung, small cell carcinoma, primary	3	302.829	71.079	274.84
					Lung, squamous cell carcinoma, primary	39	586.278	231.736	546.641
Oral cavity, squamous cell carcinoma, primary	3	652.55	484.533	377.583
					Ovary, adenocarcinoma, clear cell type, primary	6	403.469	165.346	345.298
Ovary, adenocarcinoma, endometrioid, primary	22	480.493	267.492	420.408

Ovary, adenocarcinoma, papillary serous type, primary	36	550.768	297.353	518.682
					Ovary, granulomatous tumor, primary	3	204.326	9.245	199.434
Ovary, mucinous cystadenocarcinoma, Primary	7	446.244	157.448	408.978
					Ovary, Mullerian mixed tumor, Primary	5	459.58	261.132	387.474
Ovary, Normal	89	193.631	70.936	183.31
					Pancreas, adenocarcinoma, primary	23	408.518	108.348	409.698
Pancreas, islet cell tumor, malignant, Primary	7	616.628	260.06	494.256
					Pancreas, Normal	46	337.27	109.44	306.728
Prostate, adenocarcinoma, primary	86	437.337	128.249	424.415
					Prostate, normal	57	337.15	75.629	324.359
Rectum, adenocarcinoma (excluding mucinous type), primary	29	667.234	209.823	644.219
					Rectum, adenocarcinoma, mucoid, primary	3	641.685	183.696	707.031
Rectum, normal	44	376.082	118.912	357.174
					Skin, basal cell carcinoma, primary	4	240.874	35.248	238.726
Skin, malignant melanoma, primary	7	358.732	136.687	357.463
					Skin, normal	61	405.686	109.659	389.601
Skin, squamous cell carcinoma, primary	4	417.131	49.109	410.967
					Small intestine, gastrointestinal stromal tumor (GIST), primary	4	207.223	71.481	192.011
Small intestine, normal	97	496.133	169.772	480.523
					Stomach, adenocarcinoma (excluding finger ring cell types), protogenHair property	27	616.382	262.711	548.388
Stomach, adenocarcinoma, finger print cell type, primary	9	783.841	628.775	572.466
					Stomach, gastrointestinal stromal tumor (GIST), primary	9	232.296	75.708	242.608
Stomach being normal	52	380.597	157.268	340.104
					Thyroid, follicular carcinoma, primary	3	257.712	97.865	292.424
Thyroid, normal	24	161.685	52.119	146.901

Thyroid, papillary carcinoma, primary; all variants	29	197.349	99.501	185.737
					Sample set	Number of samples	Mean value of	Standard deviation of	Median value
Bladder, normal	9	235.241	107.541	204.569
					Bladder, transitional cell carcinoma, primary	4	302.469	150.232	270.951
Cervix, adenocarcinoma, primary	3	309.646	106.687	289.85
					Cervix, normal	115	232.08	96.727	214.625
Vulva, normal of vulva	4	328.463	119.872	280.431
					Vulvar, squamous cell carcinoma, primary	5	363.919	110.84	399.783

V-ErbB2 erythroblastic leukemia virus oncogene homolog 3(ERBB3)

It has been shown that the expression of Epidermal Growth Factor Receptor (EGFR), a tyrosine kinase receptor, is essential in the formation of adenomas and carcinomas of intestinal tumors, and that subsequent tumor expansion has been initiated (Roberts et al, 2002, PNAS, 99: 1521-. Overexpression of EGFR also plays a role in neoplasia, especially tumors of epithelial origin (Kari et al, 2003, Cancer Res., 63: 1-5). EGFR is a member of the ErbB family of receptors, which includes HER2c/neu, HER2, and HER3 receptor tyrosine kinases.

One key EGFR pathway involves the oncogene ERBB3 (also known as HER23), which is a member of the HER-family of receptor tyrosine kinases, including HER1/EGFR/c-ERBB2, HER4/c-ERBB 4. The HER-family shares a high degree of structural and functional homology. HER signaling promotes tumor formation (primarily by activating the PI3K/Akt pathway) and is driven primarily by phosphorylation of the transactivation inactive member HER3, suggesting that HER3 functions significantly in the regulation of tumor cell proliferation. In addition, the HER-family constitutes a complex network of intracellular signal transduction pathways that bind multiple extracellular ligands, thereby causing receptor interactions and cross-activation of HER-family members. For example, the formation of HER2/HER3 heterodimers produces mitogenic and transforming receptor complexes within the HER (erbb) family.

Experiments were performed in multiple tissue samples to determine if there was a correlation between PARP and ERBB3 expression. Table XXIX shows expression levels in various tissues. It can be seen that ERBB3 is regulated and co-regulated with PARP1 in tumors of the same subtype, such as breast, ovarian and skin tumors and sarcomas. Accordingly, one embodiment is the treatment of a disease susceptible to a combination of PARP and ERBB3 modulators. In addition, ERBB3 related genes, including genes that are commonly regulated in the ERBB3 pathway, are also included herein.

Table XXIX: expression of ERBB3(v-erb-b2 erythroblastic leukemia virus oncogene homolog 3) in human primary tumors compared to normal tissues.

Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Adrenal, adrenal cortex cell carcinoma, primary	3	577.882	980.547	14.285

Adrenal gland, normal	13	125.524	343.556	18.187
					Bone, giant cell tumor of bone, primary	10	10.336	7.223	9.132
Bone, normal	8	37.284	57.615	14.053
					Bone, osteosarcoma, primary	4	20.579	17.253	18.759
Mixed invasive carcinoma of the breast, ductus lactis and lobule, primary	8	2280.914	1187.289	2134.499
					Breast, invasive ductal carcinoma, primary	169	1548.723	857.043	1416.273
Breast, invasive lobular carcinoma, primary	17	2063.404	1228.354	1905.583
					Breast, ductal carcinoma	3	2912.882	391.626	2915.354
Breast, mucinous carcinoma, primary	4	1540.657	647.821	1335.309
					Mammary gland, Normal	68	1113.455	580.417	1092.339
Breast, phyllodes tumor (phyllocystic sarcoma), primary	5	537.381	166.451	530.115
					Colon, adenocarcinoma (excluding mucinous types), primary	77	1971.768	746.859	1840.703
Colon, adenocarcinoma, mucoid, primary	7	1430.242	808.398	1351.427
					Colon, Normal	180	1458.433	515.98	1383.82
Endometrium, adenocarcinoma, endometrioid type, primary	50	758.705	441.307	671.915
					Endometrium, Mullerian mixed tumor, primary	7	391.366	552.712	92.314
Endometrium, normal	23	499.473	409.346	332.495
					Esophagus, adenocarcinoma, primary	3	1853.052	965.33	1968.129
Esophagus, normal	22	1013.875	393.124	1017.246
					Kidney, cancer, chromophobe type, primary	3	449.46	159.14	375.862
Kidney, normal	81	980.48	349.951	991.148
					Renal, renal cell carcinoma, clear cell type, primary	45	942.527	714.444	765.094
Renal, renal cell carcinoma, non-clear cell type, primary	15	1184.511	985.788	1181.861
					Renal, transitional cell carcinoma, primary	4	1881.073	1688.566	1149.255
Kidney, Wilms' tumor, primary	8	174.465	102.523	156.7

Larynx, normal	4	987.72	681.018	1184.756
					Larynx, squamous cell carcinoma, primary	4	399.736	136.302	449.028
Liver, hepatocellular carcinoma	16	1623.121	904.592	1607.987
					Liver, normal	42	963.955	470.103	837.661
Lung, adenocarcinoma, primary	46	1121.085	690.427	852.101
					Lung, adenosquamous carcinoma, primary	3	1110.685	512.485	1073.488
Lung, large cell carcinoma, primary	7	772.418	399.168	558.1
					Lung, neuroendocrine carcinoma (non-small cell type), primary	3	593.582	515.062	802.766
Lung, normal	126	664.625	297.552	607.42
					Lung, small cell carcinoma, primary	3	314.576	136.305	383.976
Lung, squamous cell carcinoma, primary	39	535.679	349.395	464.982
					Oral cavity, squamous cell carcinoma, primary	3	632.589	681.131	255.479
Ovary, adenocarcinoma, clear cell type, primary	6	1334.761	700.043	1133.209
					Ovary, adenocarcinoma, endometrioid, primary	22	880.946	425.324	770.453
Ovary, adenocarcinoma, papillary serous type, primary	36	982.248	604.01	779.513
					Ovary, granulomatous tumor, primary	3	12.718	5.99	13.055
Ovary, mucinous cystadenocarcinoma, Primary	7	1448.166	459.784	1443.369
					Ovary, Mullerian mixed tumor, Primary	5	537.117	543.134	496.456
Ovary, Normal	89	62.734	174.184	26.506
					Pancreas, adenocarcinoma, primary	23	1127.646	680.621	889.292
Pancreas, islet cell tumor, malignant, Primary	7	1230.09	1379.954	844.986
					Pancreas, Normal	46	466.353	163.486	426.184
Prostate, adenocarcinoma, primary	86	1655.44	477.053	1574.154
					Prostate, normal	57	992.882	394.393	1007.848
Rectum, adenocarcinoma (excluding mucinous type), primary	29	1844.5	734.105	1699.542

Rectum, adenocarcinoma, mucoid, primary	3	1159.982	1067.734	838.012
					Rectum, normal	44	1328.401	449.394	1237.417
Skin, basal cell carcinoma, primary	4	635.797	278.09	622.684
					Skin, malignant melanoma, primary	7	2547.3	2402.871	1875.538
Skin, normal	61	783.091	377.959	747.794
					Skin, squamous cell carcinoma, primary	4	301.374	121.643	335.271
Small intestine, gastrointestinal stromal tumor (GIST), primary	4	11.31	10.04	8.432
					Small intestine, normal	97	1790.03	773.198	1825.371
Stomach, adenocarcinoma (excluding finger ring cell types), primary	27	1411.513	670.095	1388.222
					Stomach, adenocarcinoma, finger print cell type, primary	9	1138.628	228.311	1053.921
Stomach, gastrointestinal stromal tumor (GIST), primary	9	13.944	11.315	7.565
					Stomach being normal	52	1148.508	506.496	1140.674
Thyroid, follicular carcinoma, primary	3	535.996	284.787	420.907
					Thyroid, normal	24	160.13	77.384	139.421
Thyroid, papillary carcinoma, primary; all variants	29	368.881	394.066	205.043
					Bladder, normal	9	304.776	186.305	250.217
Bladder, transitional cell carcinoma, primary	4	1698.328	860.141	1647.78
					Cervix, adenocarcinoma, primary	3	533.276	625.49	206.731
Cervix, normal	115	353.483	199.167	290.434
					Vulva, normal of vulva	4	671.006	249.678	757.337
Vulvar, squamous cell carcinoma, primary	5	345.409	144.583	390.85

Migration inhibitory factor

Tumor-associated macrophages can affect tumor progression, angiogenesis, and invasion. Migration Inhibitory Factor (MIF) is a pleiotropic cytokine that plays a key role in inflammatory and immune-mediated diseases, such as Rheumatoid Arthritis (RA) and atherosclerosis. MIF is secreted by T lymphocytes and macrophages on Lipopolysaccharide (LPS) -exposed portions and induces the secretion of tumor necrosis factor-alpha (TNF- α) (by mouse macrophages). MIF is highly expressed in macrophages, endothelial cells, Synovial Tissue (ST), fibroblasts, serum, and synovial fluid. MIF stimulates macrophages to release proinflammatory cytokines such as TNF- α, interleukin 1 β (IL-1 β), IL-6, and IL-8. MIF upregulates IL-1 β, Matrix Metalloproteinases (MMPs) MMP-1, MMP-3, MMP-9, and MMP-13 in RAST fibroblasts. In rodent arthritis models, administration of anti-MIF antibodies ameliorates arthritis with significant inhibition of clinical and histological features of the disease. anti-MIF treatment also improved the results of acute encephalomyelitis and experimental autoimmune myocarditis in mice. These studies suggest a key role for MIF in the pathogenesis of immune and inflammatory diseases. This also suggests that MIF is a potent angiogenic factor. MIF upregulates VCAM-1 and ICAM-1 via Src, PI3K, and NF κ B activation.

Due to the critical role of MIF in disease progression, modulation of MIF expression is considered as a possible therapeutic target. Accordingly, one embodiment is the treatment of a disease susceptible to a combination of PARP and MIF modulators. In addition, MIF-related genes, including genes that are co-regulated in the MIF pathway, are also included herein.

VAV3 oncogene

VAV proteins are guanine nucleotide exchange factors (GEFs) of the Rho family gtpases, which activate pathways that lead to actin backbone rearrangement and transcriptional changes. VAV3 preferentially acts as GEF on RhoG (ARHG), RhoA (ARHA, and, to a lesser extent, RAC1, and binds to the greatest extent these GTPases in the nucleotide free state. researchers have identified a splice variant of VAV3, which is called VAV3.1, but contains only the C-terminal SH3-SH2-SH3 region VAV3.1 appears to be down-regulated by EGF and transforming growth factor-beta (TGFB). VAV3 also appears to enhance nuclear factor kappa-B (NFKB) -dependent transcription.

Due to the critical role of VAV3 in disease progression, modulation of VAV3 expression is considered as a possible therapeutic target. Accordingly, one embodiment is the treatment of a disease susceptible to a combination of PARP and VAV3 modulators. In addition, VAV 3-related genes, including genes that are commonly regulated in the VAV3 pathway, are also included herein.

Aurora kinase

Aurora kinase A (AURKA) is a mitotic centromeric protein kinase (Kimura et al, 1997, J.biol.chem.272: 13766-13771). The major role of AURKA in tumor progression is to control chromosome segregation during mitosis (Bischoff and Plowman, 1999, Trends CellBiol.9: 454-459). AURKA is often amplified in cancer and induces phosphorylation of I κ Ba, thereby modulating its degradation. Loss of I κ Ba leads to activation of transcription of NF- κ B target genes. In human primary breast cancer, 13.6% of the samples showed AURKA gene amplification, all of which showed nuclear localization of NF- κ B, indicating that this particular subset of breast cancer patients may benefit from AURKA inhibition.

Furthermore, analysis of NF-. kappa.B activity by different human tumor cell types has shown a link between cell resistance to chemotherapeutic agents and NF-. kappa.B activation. For example, A549 human lung adenocarcinoma cells and SKOV3 human ovarian carcinoma cells have high levels of NF-. kappa.B and are resistant to cytotoxic drugs such as doxorubicin and VP-16 (etoposide). It also shows that NF- κ B, Bcl-XL and Bcl-2 activities are down-regulated with concomitant increases in cytotoxic drug potency in a549 and SKOV3 cells treated with small molecule inhibitors of Aurora kinase. These findings are of great significance for cancer chemotherapy. AURKA-inhibition increases the efficacy of chemotherapeutic agents and reverses acquired resistance caused by NF- κ B activation. As a result, blocking NF-. kappa.B activation by inhibition of AURKA may provide a valuable enhancement to specific chemotherapeutic regimens (Linardopoulos, 2007, J BUON.12(Suppl 1): S67-70).

Experiments were performed in multiple tissue samples to determine if there was a correlation between PARP and AURKA expression. Table XXX shows the expression levels in various tissues. It can be seen that AURKA is regulated and co-regulated with PARP1 in tumors of the same subtype, such as breast, endometrial, lung and ovarian tumors and sarcomas. Accordingly, one embodiment is the treatment of a disease susceptible to a combination of PARP and AURKA modulators. Furthermore, AURKA-associated genes, including genes that are co-regulated in the AURKA pathway, are also included herein.

Table XXX: expression of Aurora kinase a in human primary tumors compared to normal tissues.

Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					The adrenal gland,adrenocortical carcinoma, primary	3	44.754	8.862	43.392
Adrenal gland, normal	13	25.672	15.905	22.076
					Bone, giant cell tumor of bone, primary	10	51.061	18.222	48.306
Bone, normal	8	143.441	110.647	130.871
					Bone, osteosarcoma, primary	4	178.04	83.591	187.41
Mixed invasive carcinoma of the breast, ductus lactis and lobule, primary	8	95.51	47.454	86.491
					Breast, invasive ductal carcinoma, primary	169	89.343	82.104	73.288
Breast, invasive lobular carcinoma, primary	17	74.299	55.943	60.594
					Breast, ductal carcinoma	3	74.636	71.118	49.292
Breast, mucinous carcinoma, primary	4	51.741	45.158	34.593
					Mammary gland, Normal	68	28.743	42.088	18.843
Breast, phyllodes tumor (phyllocystic sarcoma), primary	5	34.084	14.567	29.148
					Colon, adenocarcinoma (excluding mucinous types), primary	77	162.923	85.18	142.004
Colon, adenocarcinoma, mucoid, primary	7	112.896	42.873	101.745
					Colon, Normal	180	70.295	38.393	63.784
Endometrium, adenocarcinoma, endometrioid type, primary	50	69.564	45.648	57.714
					Endometrium, Mullerian mixed tumor, primary	7	169.364	72.819	197.607
Endometrium, normal	23	36.878	56.805	20.135
					Esophagus, adenocarcinoma, primary	3	859.368	1198.639	203.561
Esophagus, normal	22	36.408	16.133	41.23
					Kidney, cancer, chromophobe type, primary	3	42.363	25.248	41.311
Kidney, normal	81	16.64	9.488	15.193
					Renal, renal cell carcinoma, clear cell type, primary	45	34.884	24.019	27.772

Renal, renal cell carcinoma, non-clear cell type, primary	15	36.489	24.565	30.32
					Renal, transitional cell carcinoma, primary	4	62.951	43.077	53.03
Kidney, Wilms' tumor, primary	8	134.715	48.472	137.996
					Sample set	Number of samples	Mean value of	Standard deviation of	Median value
Larynx, normal	4	38.267	7.859	40.105
					Larynx, squamous cell carcinoma, primary	4	106.771	33.873	100.127
Liver, hepatocellular carcinoma	16	80.374	59.267	64.87
					Liver, normal	42	19.333	13.529	17.57
Lung, adenocarcinoma, primary	46	92.449	68.175	72.573
					Lung, adenosquamous carcinoma, primary	3	43.065	23.707	38.673
Lung, large cell carcinoma, primary	7	110.99	39.237	113.89
					Lung, neuroendocrine carcinoma (non-small cell type), primary	3	93.442	119.109	44.063
Lung, normal	126	27.345	35.968	19.32
					Lung, small cell carcinoma, primary	3	147.378	13.136	154.126
Lung, squamous cell carcinoma, primary	39	111.537	50.622	106.782
					Oral cavity, squamous cell carcinoma, primary	3	122.089	70.313	159.159
Ovary, adenocarcinoma, clear cell type, primary	6	70.834	31.287	76.297
					Ovary, adenocarcinoma, endometrioid, primary	22	64.496	36.983	57.426
Ovary, adenocarcinoma, papillary serous type, primary	36	107.434	98.927	88.224
					Ovary, granulomatous tumor, primary	3	24.753	19.999	27.065
Ovary, mucinous cystadenocarcinoma, Primary	7	33.119	14.621	31.509
					Ovary, Mullerian mixed tumor, Primary	5	184.608	181.022	102.966
Ovary, Normal	89	70.168	68.424	46.725
					Pancreas, adenocarcinoma, primary	23	48.758	30.381	43.699
Pancreas, islet cell tumor, malignant, Primary	7	39.542	25.776	28.543

Pancreas, Normal	46	29.429	28.901	22.729
					Prostate, adenocarcinoma, primary	86	15.487	7.05	15.689
Prostate, normal	57	11.147	5.557	10.483
					Rectum, adenocarcinoma (excluding mucinous type), primary	29	158.666	66.032	153.322
Rectum, adenocarcinoma, mucoid, primary	3	109.484	70.156	126.287
					Rectum, normal	44	55.244	21.11	51.151
Skin, basal cell carcinoma, primary	4	50.118	8.463	52.27
					Skin, malignant melanoma, primary	7	111.153	57.768	111.744
Skin, normal	61	21.863	32.713	15.678
					Skin, squamous cell carcinoma, primary	4	91.039	80.277	67.971
Small intestine, gastrointestinal stromal tumor (GIST), primary	4	27.262	20.437	23.665
					Small intestine, normal	97	61.336	31.207	59.736
Stomach, adenocarcinoma (excluding finger ring cell types), primary	27	164.992	102.295	158.801
					Stomach, adenocarcinoma, finger print cell type, primary	9	106.468	45.98	128.174
Stomach, gastrointestinal stromal tumor (GIST), primary	9	21.34	13.545	15.836
					Stomach being normal	52	51.789	28.173	47.535
Thyroid gland, follicular fluid Sexual cancer, primary origin	3	36.25	50.475	12.917
					Thyroid, normal	24	15.556	7.707	14.658
Thyroid, papillary carcinoma, primary; all variants	29	23.949	13.406	21.053
					Bladder, normal	9	16.597	11.305	12.724
Bladder, transitional cell carcinoma, primary	4	108.368	60.835	92.147
					Cervix, adenocarcinoma, primary	3	107.466	96.964	115.821
Cervix, normal	115	18.21	32.776	11.183
					Vulva, normal of vulva	4	29.709	15.366	23.056
Sample set	Number of samples	Mean value of	Standard deviation of	Median value

Vulvar, squamous cell carcinoma, primary

5

94.718

13.914

104.197

Bcl-2

BCL-2 promotes lymphomatosis and affects the sensitivity of tumor cells to chemotherapy and radiation therapy. The Bcl-2 family of proteins is known to include more than 30 proteins in total, which have pro-apoptotic or anti-apoptotic functions, suggesting that they may also play a different role in carcinogenesis (Cory et al, 2003, Oncogene 22: 8590-8607). Pro-survival Bcl-2 family members act as oncogenes. Expression of Bcl-2 in transgenic mice demonstrates that inhibition of apoptosis can lead to cancer, as these mice develop B-cell lymphomas and leukemias. The life of B-lymphoid tumors was significantly prolonged by Bcl-2 transgene expression, indicating that Bcl-2 overexpression is predisposed to the formation of B-cell lymphomas.

Experiments were performed in multiple tissue samples to determine if there was a correlation between PARP and Bcl-2 expression. Table XXXI shows expression levels in various tissues. It can be seen that Bcl-2 is upregulated with PARP1 in tumors of the same subtype and is co-regulated, such as tumors of the breast, ovary, and skin and sarcoma. Accordingly, one embodiment is the treatment of a disease susceptible to the combination of PARP and Bcl-2 modulators. In addition, Bcl-2 related genes, including genes that are co-regulated in the Bcl-2 pathway, are also included herein.

Table XXXI: expression of BCL2 (B-cell CLL/lymphoma 2) in human primary tumors compared to normal tissue.

Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Adrenal, adrenal cortex cell carcinoma, primary	3	41.369	13.086	39.567
Adrenal gland, normal	13	76.565	79.915	57.591
					Bone, giant cell tumor of bone, primary	10	67.268	25.075	60.992
Bone, normal	8	93.551	37.089	101.793
					Bone, osteosarcoma, primary	4	86.148	46.86	87.134
Mixed invasive carcinoma of the breast, ductus lactis and lobule, primary	8	165.395	79.131	129.186
					Breast, invasive ductal carcinoma, primary	169	185.081	137.681	153.948
Breast, invasive lobular carcinoma, primary	17	253.721	170.271	188.582
					Breast, ductal carcinoma	3	304.094	82.093	320.92
Breast, mucinous carcinoma, primary	4	231.889	174.353	202.309
					Mammary gland, Normal	68	180.278	62.194	184.029
Breast, phyllodes tumor (phyllocystic sarcoma), primary	5	156.731	53.76	158.242

Colon, adenocarcinoma (excluding mucinous types), primary	77	58.51	25.967	52.622
					Colon, adenocarcinoma, mucoid, primary	7	78.225	59.629	58.656
Colon, Normal	180	99.747	38.155	94.906
					Endometrium, adenocarcinoma, endometrioid type, primary	50	118.084	82.562	91.368
Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Endometrium, Mullerian mixed tumor, primary	7	76.471	24.044	80.782
Endometrium, normal	23	243.099	126.075	215.948
					Esophagus, adenocarcinoma, primary	3	37.097	14.877	32.719
Esophagus, normal	22	76.845	21.677	71.56
					Kidney, cancer, chromophobe type, primary	3	291.793	82.103	264.825
Kidney, normal	81	160.415	44.839	158.151
					Renal, renal cell carcinoma, clear cell type, primary	45	213.18	109.86	185.721
Renal, renal cell carcinoma, non-clear cell type, primary	15	225.067	108.419	240.49
					Renal, transitional cell carcinoma, primary	4	23.076	9.024	20.267
Kidney, Wilms' tumor, primary	8	150.344	52.247	132.065
					Larynx, normal	4	108.966	91.936	68.871
Larynx, squamous cell carcinoma, primary	4	52.95	15.864	50.99
					Liver, hepatocellular carcinoma	16	61.05	32.886	54.112
Liver, normal	42	63.025	84.148	47.745
					Lung, adenocarcinoma, primary	46	73.211	70.81	56.933
Lung, adenosquamous carcinoma, primary	3	78.094	28.561	64.352
					Lung, large cell carcinoma, primary	7	64.283	28.099	68.291
Lung, neuroendocrine carcinoma (non-small cell type), primary	3	32.677	25.312	35.5
					Lung, normal	126	70.777	32.745	66.795
Lung, small cell carcinoma, primary	3	256.362	121.664	188.266

Lung, squamous cell carcinoma, primary	39	86.702	94.356	68.855
					Oral cavity, squamous cell carcinoma, primary	3	41.448	23.986	43.03
Ovary, adenocarcinoma, clear cell type, primary	6	143.916	160.188	76.602
					Ovary, adenocarcinoma, endometrioid, primary	22	116.538	91.275	85.27
Ovary, adenocarcinoma, papillary serous type, primary	36	64.043	39.388	52.971
					Ovary, granulomatous tumor, primary	3	291.661	18.052	295.117
Ovary, mucinous cystadenocarcinoma, Primary	7	96.739	102.705	67.26
					Ovary, Mullerian mixed tumor, Primary	5	138.111	123.538	86.269
Ovary, Normal	89	189.339	72.787	174.35
					Pancreas, adenocarcinoma, primary	23	70.77	33.311	61.929
Pancreas, islet cell tumor, malignant, Primary	7	44.424	16.346	42.696
					Pancreas, Normal	46	61.713	18.442	58.003
Prostate, adenocarcinoma, primary	86	80.779	30.717	76.884
					Prostate, normal	57	126.448	44.583	115.617
Rectum, adenocarcinoma (excluding mucinous type), primary	29	49.829	13.682	47.972
					Rectum, adenocarcinoma, mucoid, primary	3	53.416	27.606	45.316
Rectum, normal	44	99.686	25.97	101.939
					Skin, basal cell carcinoma, primary	4	136.707	30.101	123.82
Skin, malignant melanoma, primary	7	140.862	116.907	125.858
					Skin, normal	61	104.32	35.887	99.801
Skin, squamous cell carcinoma, primary	4	149.226	168.298	74.5
					Small intestine, gastrointestinal stromal tumor (GIST), primary	4	781.493	120.352	786.203
Small intestine, normal	97	98.346	51.187	92.945
					Stomach, adenocarcinoma (excluding finger ring cell types), primary	27	61.502	22.173	57.512
Stomach, adenocarcinoma, finger print cell type, primary	9	69.446	34.59	67.033

Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Stomach, gastrointestinal stromal tumor (GIST), primary	9	260.615	127.994	241.293
Stomach being normal	52	65.716	26.897	58.761
					Thyroid, follicular carcinoma, primary	3	315.749	209.219	435.183
Thyroid, normal	24	470.013	98.75	503.828
					Thyroid, papillary carcinoma, primary; all variants	29	209.72	107.891	214.138
Bladder, normal	9	104.859	39.085	88.841
					Bladder, transitional cell carcinoma, primary	4	42.722	14.206	46.577
Cervix, adenocarcinoma, primary	3	185.839	58.711	166.966
					Cervix, normal	115	169.441	50.511	167.885
Vulva, normal of vulva	4	104.927	25.708	103.02
					Vulvar, squamous cell carcinoma, primary	5	51.488	4.185	52.544

Ubiquitin proteasome pathway

The ubiquitin proteasome pathway is the major mechanism of cellular degradation. Proteasomes enable the rapid clearance of proteins important for cell cycle progression, including cyclins, cyclin-dependent kinase inhibitors and NF-. kappa.B. IkB is polyubiquinated (in response to its phosphorylation by IKK) and cleaved by the 26S proteasome. Inhibition of the ubiquitin proteasome pathway results in dysregulation of cellular proteins involved in cell cycle control, promotion of tumor growth, and induction of apoptosis. Recently, proteasome inhibitors (which have shown promising anti-cancer responses in vitro and in vivo) have been introduced into the treatment of malignancies. Proteasome inhibitors were initially considered as a therapeutic approach because they have potential protein targets (which are known to be dysregulated in tumor cells). Proteasome inhibitors have been reported to alter the levels of cyclin-dependent kinase inhibitors p21 and p27 (also known as WAF1 and KIP1, respectively) and some pro-and anti-apoptotic proteins, leading to cell cycle arrest and apoptosis in some tumor types. Malignant cells are more affected by certain proteasome inhibitors, and this can be explained (in part) by the interference of CDC25A, CDC25C, p27, and cyclins, which are typically activated in cancer cells. For sustained cell growth, ordered and transient degradation of these regulatory molecules is required. Thus, inhibition of proteasome-mediated degradation of these molecules can prevent or retard cell growth. P53 accumulates in response to cellular stress such as chemical-or radiation-induced DNA damage, oncogene activation and tissue hypoxia. MDM2 inhibits the activity of p53, in part by allowing p53 to export to the cytoplasm, where it can be degraded by the proteasome. p53 becomes stable upon proteasome inhibition, which stimulates p 53-mediated tumor-inhibiting activity. Other explanations for the anti-cancer activity of proteasome inhibitors include inhibition of IkB degradation, which allows NF κ B to be maintained in the cytoplasm. NF-. kappa.B is considered to be one of the molecules that plays a central role in regulating many of the actions of proteasome inhibition. An interesting study has demonstrated the degree of efficacy of proteasome inhibitors due to inhibition of NF- κ B. Using multiple myeloma cells, Hideshima et al compared the effects of an IKK inhibitor (PS-1145) and bortezomib, a proteasome inhibitor that inhibits the chymase activity of the proteasome in a potent, reversible and selective manner (Hideshima et al, 2002, J.biol. chem.277: 16639-16647). While both PS-1145 and bortezomib blocked NF κ B activation, mono bortezomib was more complete.

Experiments were performed in multiple tissue samples to determine if there was a correlation between PARP expression and ubiquitin proteasome pathway protein expression. Table XXXII shows the expression levels of UBE2S in various tissues. It can be seen that UBE2S is upregulated with PARP1 and is co-regulated in tumors of the same subtype, such as tumors of the breast, ovary, and skin and sarcoma. Accordingly, one embodiment is the treatment of a disease susceptible to a combination of PARP and UBE2S modulators. In addition, UBE 2S-related genes, including genes co-regulated in ubiquitin proteasome pathway proteins, are also included herein.

Table XXXII: UBE2S (ubiquitin conjugating enzyme E2S; similar to ubiquitin conjugating enzyme E2S (ubiquitin conjugating enzyme E2-24kDa) (ubiquitin-protein ligase) (ubiquitin carrier protein) (E2-EPF5)) was expressed in human primary tumors compared to normal tissues.

Sample set	Number of samples	Mean value of	Standard deviation of	Median value
					Adrenal, adrenal cortex cell carcinoma, primary	3	129.097	46.893	137.935
Adrenal gland, normal	13	82.156	34.849	82.309
					Bone, giant cell tumor of bone, primary	10	137.94	33.664	147.67
Bone, normal	8	145.715	104.824	122.049
					Bone, osteosarcoma, primary	4	623.943	421.543	591.478
Mixed invasive carcinoma of the breast, ductus lactis and lobule, primary	8	150.452	73.597	149.141
					Breast, invasive ductal carcinoma, primary	169	211.898	198.18	136.568
Breast, invasive lobular carcinoma, primary	17	121.074	102.75	98.11
					Breast, ductal carcinoma	3	88.188	37.496	107.824
Breast, mucinous carcinoma, primary	4	228.67	158.594	184.996
					Mammary gland, Normal	68	76.54	114.038	54.967
Breast, phyllodes tumor (phyllocystic sarcoma), primary	5	151.531	44.68	144.279
					Colon, adenocarcinoma (excluding mucinous types), primary	77	292.319	191.312	239.821
Colon, adenocarcinoma, mucoid, primary	7	233.435	124.977	212.778
					Colon, Normal	180	94.723	43.203	87.05
Endometrium, adenocarcinoma, endometrioid type, primary	50	189.219	143.485	151.341

Endometrium, Mullerian mixed tumor, primary	7	423.028	199.339	377.047
					Endometrium, normal	23	83.824	45.485	79.293
Esophagus, adenocarcinoma, primary	3	176.663	36.089	193.352
					Esophagus, normal	22	106.996	30.476	108.666
Kidney, cancer, chromophobe type, primary	3	108.286	24.187	97.844
					Kidney, normal	81	36.839	18.515	37.16
Renal, renal cell carcinoma, clear cell type, primary	45	66.31	43.833	55.188
					Sample set	Number of samples	Mean value of	Standard deviation of	Median value
Kidney essence and kidney essenceCell carcinoma, non-clear cell type, primary	15	64.572	27.295	64.618
					Renal, transitional cell carcinoma, primary	4	270.505	281.828	149.683
Kidney, Wilms' tumor, primary	8	412.566	188.967	427.328
					Larynx, normal	4	123.45	59.992	136.237
Larynx, squamous cell carcinoma, primary	4	330.967	173.065	276.574
					Liver, hepatocellular carcinoma	16	93.342	52.304	81.455
Liver, normal	42	44.982	30.912	44.236
					Lung, adenocarcinoma, primary	46	168.798	162.569	107.818
Lung, adenosquamous carcinoma, primary	3	79.825	12.277	78.251
					Lung, large cell carcinoma, primary	7	218.032	104.354	255.401
Lung, neuroendocrine carcinoma (non-small cell type), primary	3	543.348	731.846	141.593
					Lung, normal	126	79.129	155.169	57.522
Lung, small cell carcinoma, primary	3	1071.102	211.415	1060.096
					Lung, squamous cell carcinoma, primary	39	340.664	209.747	257.964
Oral cavity, squamous cell carcinoma, primary	3	280.816	167.057	318.621
					Ovary, adenocarcinoma, clear cell type, primary	6	103.755	36.619	99.987
Ovary, adenocarcinoma, endometrioid, primary	22	183.702	109.354	146.8

Ovary, adenocarcinoma, papillary serous type, primary	36	174.4	102.164	154.5
					Ovary, granulomatous tumor, primary	3	156.848	16.187	159.53
Ovary, mucinous cystadenocarcinoma, Primary	7	84.611	15.699	84.895
					Ovary, Mullerian mixed tumor, Primary	5	363.898	221.096	403.494
Ovary, Normal	89	87.552	46.998	79.653
					Pancreas, adenocarcinoma, primary	23	113.283	54.941	97.892
Pancreas, islet cell tumor, malignant, Primary	7	146.32	69.165	139.025
					Pancreas, Normal	46	41.189	32.682	39.683
Prostate, adenocarcinoma, primary	86	84.105	31.659	78.611
					Prostate, normal	57	62.336	21.869	62.386
Rectum, adenocarcinoma (excluding mucinous type), primary	29	243.362	136.269	203.98
					Rectum, adenocarcinoma, mucoid, primary	3	162.35	72.122	153.531
Rectum, normal	44	87.534	33.51	88.558
					Skin, basal cell carcinoma, primary	4	144.053	35.538	145.552
Skin, malignant melanoma, primary	7	413.489	334.748	233.006
					LeatherCutaneous normalization	61	54.469	80.562	44.588
Skin, squamous cell carcinoma, primary	4	318.382	401.815	147.191
					Small intestine, gastrointestinal stromal tumor (GIST), primary	4	159.986	44.725	151.947
Small intestine, normal	97	61.454	24.241	60.23
					Stomach, adenocarcinoma (excluding finger ring cell types), primary	27	186.598	113.859	146.447
Stomach, adenocarcinoma, finger print cell type, primary	9	164.955	74.288	170.523
					Stomach, gastrointestinal stromal tumor (GIST), primary	9	99.259	43.37	104.269
Stomach being normal	52	93.083	52.839	79.504
					Thyroid, follicular carcinoma, primary	3	129.16	95.772	83.155
Thyroid, normal	24	60.847	26.391	63.367

Thyroid, papillary carcinoma, primary; all variants	29	65.447	25.161	58.688
					Bladder, normal	9	56.905	21.981	48.891
Bladder, transitional cell carcinoma, primary	4	278.795	125.176	271.553
					Sample set	Number of samples	Mean value of	Standard deviation of	Median value
Cervix, adenocarcinoma, primary	3	293.178	270.738	213.411
					Cervix, normal	115	78.201	72.59	69.419
Vulva, normal of vulva	4	82.187	33.953	72.273
					Vulvar, squamous cell carcinoma, primary	5	201.097	75.24	216.477

Methods of treatment using PARP inhibitors

PARP inhibitors have potential therapeutic benefits when used alone to treat a variety of diseases such as myocardial ischemia, stroke, head trauma and neurodegenerative diseases, as well as with other agents chemotherapeutic agents, radiation, oligonucleotides or antibodies as adjunctive therapies in cancer therapy. Without limiting the embodiments of the present invention, it is understood that a variety of PARP inhibitors are known in the art and are included within the scope of the embodiments of the present invention. Disclosed herein are some examples of PARP inhibitors, but they do not limit the scope of the present specification in any way.

The great advantage of PARP inhibitors has been designed as analogs of benzamide that competitively bind with the natural substrate NAD at the catalytic site of PARP. PARP inhibitors include, but are not limited to, benzamides, cyclic benzamides, quinolones and isoquinolones and benzopyrones (US 5,464,871, US 5,670,518, US 6,004,978, US 6,169,104, US 5,922,775, US 6,017,958, US 5,736,576, and US 5,484,951, all of which are incorporated herein by reference). The PARP inhibitors include a variety of cyclic benzamide analogs (i.e., lactams) that are potent inhibitors at the NAD site. Other PARP inhibitors include, but are not limited to, benzimidazoles and indoles (EP 841924, EP1127052, US 6,100,283, US 6,310,082, US 2002/156050, US 2005/054631, WO 05/012305, WO 99/11628, and US 2002/028815). A number of small molecular weight inhibitors of PARP have been used to elucidate the functional role of poly ADP-ribosylation in DNA repair. Inhibition of PARP in cells treated with alkylating agents results in a significant increase in DNA-strand breaks and cell killing (Durkaccz et al, 1980, Nature 283: 593-. Since then, such inhibitors have been shown to enhance the effect of radiotherapy response by inhibiting the repair of potentially lethal lesions (Ben-Hur et al, 1984, British Journal of Cancer, 49 (suppl.VI): 34-42; and Schlicker et al, 1999, int.J. Radiat. Bio i., 75: 91-100). PARP inhibitors have been reported to be effective in radiosensitizing hypoxic tumor cells (US patents 5,032,617, 5,215,738 and 5,041,653). In addition, PARP knock-out (PARP-/-) animals show genomic instability towards alkylating agents and gamma-irradiation (Wang et al, 1995, Genes Dev., 9: 509-.

Oxygen free radical DNA damage (leading to DNA mid-chain breaks which are subsequently recognized by PARP) is a major contributing factor to such diseases, as shown by PARP inhibitor studies (Cosi et al, 1994, j. neurosci.res., 39: 38-46; and Said et al, 1996, proc. natl.acad.sci.u.s.a., 93: 4688-4). Potent retroviral infection of mammalian cells has also been shown to be blocked by inhibition of PARP activity. Inhibition of infection by such recombinant retroviral vectors has been shown to occur in a number of different cell types (Gaken et al, 1996, J.virology, 70 (6): 3992-. Thus, inhibitors of PARP have been developed for use in antiviral therapy and in the treatment of cancer (WO 91/18591). In addition, PARP inhibition has been proposed to delay the appearance of the aging trait in human fibroblasts (Rattan and Clark, 1994, biochem. Biophys. Res. Comm., 201 (2): 665-. This may be related to the role PARP plays in controlling telomere function (d' Adda di Fagagna et al, 1999, Nature Gen., 23 (1): 76-80).

PARP inhibitors may have the following structural features: 1) amide or lactam functionality; 2) the NH proton of the amide or lactam may be conserved for efficient binding; 3) the amide group is attached to the aromatic ring or the lactam group is fused to the aromatic ring; 4) optimized to the cis configuration of the amide on the aromatic plane; and 5) forcing the monoaryl carboxamide into the heteropolylactam structure (Costantino et al, 2001, J Med chem., 44: 3786-3794). Virag et al, 2002, Pharmacol rev, 54: 375-429, 2002 outline various PARP inhibitors. Some examples of PARP inhibitors include, but are not limited to, isoquinolinones and dihydroisoquinolinones (e.g., US6,664,269 and WO 99/11624), nicotinamide, 3-aminobenzamides, monoarylamides and bis-, tri-, or tetracyclic lactams, phenanthrenediones (Perkins et al, 2001, Cancer Res., 61: 4175) -4183), 3, 4-dihydro-5-methyl-isoquinolin-1 (2H) -one, and benzoxazole-4-carboxamides (Griffin et al, 1995, Anticancer Drug Des, 10: 507-514; Griffin et al, 1998, J Med Chem, 41: 5247-5256; and Griffin et al, 1996, Pharm Sci, 2: 43-48), dihydroisoquinolin-1 (2H) -one, 1, 6-naphthyridin-5 (6H) -one, Quinazolin-4 (3H) -one, thieno [3, 4-c ] pyridin-4 (5H) -one and thieno [3, 4-d ] pyridin-4 (3H) -one, 1, 5-dihydroxyisoquinoline and 2-methyl-quinazolin-4 [3H ] -one (Yoshida et al, 1991, J Antibiolt (Tokyo,) 44: 111-112; Watson et al, 1998, Bioorg Med Chem., 6: 721-734; and White et al, 2000, J Med Chem., 43: 4084-4097), 1, 8-naphthalimide derivative and (5H) phenanthridine-6-one (Banasik et al, 1992, J2001, J1569-Med Chem, 267: 1569-5; Watson et al, 1998, Bioorg Med Chem., 6: 721-734; Soriano et al, 108, Nat-7, Leork et al, 1577, Leork et al, Li et al, 1577, Leork et al, J Med Chem. 11: 1687-1690; and Jagtap et al, 2002, Crit Care med., 30: 1071-1082), tetracyclic lactams, 1, 11 b-dihydro- [2H ] benzopyrano [4, 3, 2-de ] isoquinolin-3-one, 1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine (MPTP) (Zhang et al, 2000, biochem biophysis Res commu., 278: 590-598; and Mazzon et al, 2001, Eur J Pharmacol, 415: 85-94). Other examples of PARP inhibitors include, but are not limited to, those described in the patents: US 5,719,151, US 5,756,510, US6,015,827, US6,100,283, US6,156,739, US6,310,082, US6,316,455, US6,121,278, US6,201,020, US6,235,748, 6,306,889, US6,346,536, US6,380,193, US6,387,902, US6,395,749, US6,426,415, US6,514,983, US6,723,733, US6,448,271, US6,495,541, US6,548,494, US6,500,823, US6,664,269, US6,677,333, US6,903,098, US6,924,284, US6,989,388, US6,277,990, US6,476,048 and US6,531,464. Other examples of PARP inhibitors include, but are not limited to, those described in the following patent applications: US 2004198693a1, US 2004034078a1, US 2004248879a1, US 2004249841a1, US 2006074073a1, US 2006100198a1, US2004077667a1, US 2005080096a1, US 2005171101a1, US 2005054631a1, WO 05054201a1, WO 05054209a1, WO 05054210a1, WO 05058843a1, WO 06003146a1, WO 06003147a1, WO 06003148a1, WO 06003150a1 and WO 05097750a 1.

In one embodiment, the PARP inhibitor is a compound of formula (Ia)

Wherein R is₁、R₂、R₃、R₄And R₅Each independently selected from hydrogen, hydroxyl, amino, nitro, iodine, (C)₁-C₆) Alkyl, (C)₁-C₆) Alkoxy group, (C)₃-C₇) Cycloalkyl and phenyl, wherein 5R₁、R₂、R₃、R₄And R₅At least two of the substituents are always hydrogen, at least one of the 5 substituents is always nitro, and at least one of the substituents ortho to the nitro group is always iodine, and pharmaceutically acceptable salts, solvates, isomers, tautomers, metabolites, analogs or prodrugs thereof. R₁、R₂、R₃、R₄And R₅It may also be a halogen, such as chlorine, fluorine or bromine. Additional details regarding formula Ia are provided in U.S. patent 5,464,871.

One compound of formula Ia is a compound of formula Ia:

wherein R is₂、R₃、R₄And R₅Independently of one another, from hydrogen, hydroxyl, amino, nitro, iodine, (C)₁-C₆) Alkyl, (C)₁-C₆) Alkoxy group, (C)₃-C₇) Cycloalkyl and phenyl, wherein 5R are₁、R₂、R₃、R₄And R₅At least two of the substituents are always hydrogen and at least one of the 5 substituents is always nitro.

Another compound of the formula Ia

Formula III

In some embodiments, the metabolites of formula I or Ia are used in the methods of the present invention. Some metabolites useful in the methods of the present invention are compounds of formula (Ib):

Wherein: (1) r₁、R₂、R₃、R₄And R₅At least one of the substituents is always a sulfur-containing substituent, and the remaining substituents R₁、R₂、R₃、R₄And R₅Independently selected from hydrogen, hydroxyl, amino, nitro, iodine, bromine, fluorine, chlorine, (C)₁-C₆) Alkyl, (C)₁-C₆) Alkoxy group, (C)₃-C₇) Cycloalkyl and phenyl, wherein 5R₁、R₂、R₃、R₄And R₅At least two of the substituents are always hydrogen; or (2) R₁、R₂、R₃、R₄And R₅At least one of the substituents being other than a sulfur-containing substituent, and 5 substituents R₁、R₂、R₃、R₄And R₅Always is iodine, and wherein said iodine is always located in R which is nitro, nitroso, hydroxyamino, hydroxy or amino₁、R₂、R₃、R₄Or R₅Ortho to the group; and pharmaceutically acceptable salts, solvates, isomers, tautomers, metabolites, analogs or prodrugs thereof. In some embodiments, the compound of (2) is such that the iodine group is always located at R, which is nitroso, hydroxyamino, hydroxy or amino₁、R₂、R₃、R₄Or R₅Ortho to the radical. In some embodiments, the compound of (2) is such that the iodine group is always located at R, which is nitroso, hydroxyamino or amino₁、R₂、R₃、R₄Or R₅Ortho to the radical.

The following compounds are metabolic compounds, each represented by the formula:

R₆selected from hydrogen, alkyl (C)₁-C₈) Alkoxy (C)₁-C₈) Isoquinolinones, indoles, thiazoles,Azole,Diazoles, thiophenes, or phenyls

Without being limited to any particular mechanism, provided below are examples of metabolites of MS292 via nitroreductase or glutathione conjugation mechanisms:

mechanism of nitroreductase

Compound III glutathione conjugation and metabolism:

in some embodiments, the benzopyranone compounds of formula II are used in the methods disclosed herein. The benzopyranone compound of the formula II is

Formula II

Wherein R is₁、R₂、R₃And R₄Independently selected from H, halogen, optionally substituted hydroxy, optionally substituted amine, optionally substituted lower alkyl, optionally substituted phenyl, optionally substituted C₄-C₁₀Heteroaryl and optionally substituted C₃-C₈Cycloalkyl groups or salts, solvates, isomers, tautomers, metabolites or prodrugs thereof (u.s patent 5,484,951 is incorporated herein by reference in its entirety).

Some embodiments use compounds having the following formula:

wherein R is₁、R₂、R₃Or R₄Each independently selected from hydrogen, hydroxy, amino, (C)₁-C₆) Alkyl, (C)₁-C₆) Alkoxy group, (C)₃-C₇) Cycloalkyl, halogen and phenyl and pharmaceutically acceptable salts thereof, wherein R₁、R₂、R₃Or R₄At least three of the four substituents are always hydrogen.

Some embodiments use compounds having the following formula:

wherein R is₁、R₂、R₃Or R₄Each independently selected from hydrogen, hydroxy, amino, (C) ₁-C₆) Alkyl, (C)₁-C₆) Alkoxy group, (C)₃-C₇) Cycloalkyl, halogen and phenyl and pharmaceutically acceptable salts thereof, wherein R₁、R₂、R₃Or R₄At least three of the four substituents are always hydrogen.

Some embodiments use compounds having the following formula:

wherein R is₁、R₂、R₃Or R₄Each independently selected from hydrogen, hydroxy, amino, (C)₁-C₆) Alkyl, (C)₁-C₆) Alkoxy group, (C)₃-C₇) Cycloalkyl, halogen and phenyl, wherein R₁、R₂、R₃Or R₄At least three of the four substituents are always hydrogen.

One embodiment uses a benzopyranone compound of the following formula II:

compound IV

In another embodiment, the compound used in the methods disclosed herein is

For additional details regarding benzopyranone compounds, reference is made to U.S. patent 5,484,951, which is incorporated herein by reference in its entirety.

It is likely that the most potent and effective PARP inhibitors (i.e., the most likely candidates for drug development) are not yet available in the scientific literature, but they are undergoing clinical trials or may ultimately appear in the various databases of published and pending patent applications. All such PARP inhibitors are within the scope of the present embodiments. In addition to the selective, potent enzyme inhibition of PARP, several other methods are available for inhibiting PARP cellular activity in cells or in experimental animals. Inhibition of intracellular calcium mobilization prevents oxide-induced PARP activation, NAD + depletion, and cellular necrosis, as demonstrated in thymocytes (Virag et al, 1999, Mol Pharmacol., 56: 824-833) and in intestinal epithelial cells (Karczewski et al, 1999, Biochem Pharmacol., 57: 19-26). Similar to calcium chelators, intracellular zinc chelators have been shown to prevent oxide-induced PARP activation and cellular necrosis (Virag et al, 1999, Br J Pharmacol., 126: 769-777). Intracellular purines (inosine, hypoxanthine), in addition to their multiple effects, also have biological effects as inhibitors of PARP (Virag et al, 2001, FASEB j., 15: 99-107).

The methods provided may include administering a PARP inhibitor by itself or in combination with other therapies. The choice of treatment, which may be co-administered with the compositions described herein, will depend (in part) on the condition being treated. For example, to treat acute myeloid leukemia, the compounds described herein can be used in combination with the following methods: radiation therapy, monoclonal antibody therapy, chemotherapy, bone marrow transplantation, or a combination thereof.

A therapeutically effective amount of a PARP inhibitor as disclosed herein is administered to a patient (e.g., a mammal such as a human) to affect a pharmacological activity involving inhibition of PARP enzyme or PARP activity. As such, PARP inhibitors are useful for treating or preventing a variety of diseases and disorders in animals, including nerve block injury caused by cell damage or death (due to necrosis or apoptosis), cerebral ischemia and reperfusion injury, or neurodegenerative diseases. In addition, the compounds may also be used to treat cardiovascular disorders in animals by administering an effective amount of a PARP inhibitor to the animal. Further, the compounds are useful in the treatment of cancer and in radiosensitizing or chemosensitizing tumor cells.

In some embodiments, the PARP inhibitors are useful for modulating damaged neurons, promoting neuronal regeneration, preventing neurodegeneration, and/or treating neurological disorders. The PARP inhibitors inhibit PARP activity and are therefore useful for treating neural tissue damage in animals, particularly damage caused by cancer, cardiovascular disease, cerebral ischemia and reperfusion injury, or neurodegenerative disease. The PARP inhibitors are useful for treating myocardial tissue damage, particularly damage caused by myocardial ischemia or by reperfusion injury, in a patient. The compounds are useful for treating cardiovascular disorders selected from the group consisting of: coronary artery disease, such as atherosclerosis; angina pectoris; myocardial infarction; myocardial ischemia and cardiac arrest; a cardiac bypass; and cardiogenic shock.

In another aspect, the PARP inhibitor is useful for treating cancer, or in combination with chemotherapy, radiation therapy or radiation. The PARP inhibitors described herein may be "anti-cancer agents", which term also includes "anti-tumor cell growth agents" and "anti-tumor agents". For example, the PARP inhibitors are useful for treating cancer, and radiosensitizing and/or chemosensitizing tumor cells in cancer.

Radiosensitizers are known to increase the sensitivity of cancerous cells to the toxic effects of electromagnetic radiation. Many current cancer treatment protocols use radiosensitizers activated by electromagnetic radiation of x-rays. Examples of x-ray activated radiosensitizers include, but are not limited to, the following: metronidazole, misonidazole, desmethol-nidazole, pimonidazole, mitomycin C, RSU 1069, SR 4233, EO9, RB 6145, niacinamide, 5-bromodeoxyuridine (BUdR), 5-iodo-deoxyuridine (IUdR), bromodeoxycytidine, fluorodeoxyuridine (FudR), hydroxyurea, cisplatin, and therapeutically effective analogs and derivatives thereof.

Photodynamic therapy (PDT) of cancer uses visible light as a radiation activator of sensitizers. Examples of photodynamic radiosensitizers include, but are not limited to, the following: hematoporphyrin derivatives, porfimer sodium, benzene-porphyrin derivatives, NPe6, tin protoporphyrin (tin ethoporphyrin) SnET2, pheoborbide-alpha, bacteriochlorophyll-alpha, naphthalocyanine, phthalocyanine, zinc phthalocyanine, and therapeutically effective analogs and derivatives thereof.

The radiosensitizer can be administered with a therapeutically effective amount of one or more other PARP inhibitors, including but not limited to: PARP inhibitors that promote the incorporation of radiosensitizers into target cells; PARP inhibitors that control the influx of therapeutic agents to nutrients and/or oxygen to target cells. Similarly, chemosensitizers are also known to increase the sensitivity of cancer cells to the toxic effects of chemotherapeutic compounds. Exemplary chemotherapeutic agents that may be used in combination with PARP inhibitors include, but are not limited to, doxorubicin, camptothecin, dacarbazine, carboplatin, cisplatin, daunorubicin, docetaxel, doxorubicin, interferons (α, β, γ), interleukin 2, irinotecan, paclitaxel, streptozotocin, temozolomide, topotecan, and therapeutically effective analogs and derivatives thereof. In addition, other therapeutic agents that may be used in combination with PARP inhibitors include, but are not limited to, 5-fluorouracil, calcium folinate, 5 '-amino-5' -deoxythymidine, oxygen, hyperoxia (carbogen), whole blood infusion (red cell transfusions), perfluorocarbons (e.g., Fluosol-DA), 2, 3-DPG, BW12C, calcium channel blockers, pentoxifylline (pentoxyfylline), anti-angiogenic compounds, hydralazine, and L-BSO.

In some embodiments, the therapeutic agent for treatment comprises an antibody or agent that binds to PARP and thereby reduces PARP levels in the patient. In other embodiments, expression may be modulated to affect the level and/or PARP activity of PARP in a patient. Therapeutic and/or prophylactic polynucleotide molecules can be delivered using gene transfer and gene therapy techniques. Other agents include small molecules that bind to or interfere with PARP and thus affect its function, as well as small molecules that bind to or interfere with the nucleotide sequence encoding PARP and thus affect PARP levels. These agents may be administered alone or in combination with other types of therapies for treating diseases known and available to those skilled in the art. In some embodiments, the PARP inhibitor for treatment may be therapeutic, prophylactic, or both. The PARP inhibitors may act directly on PARP or modulate other cellular components, which then have an effect on the level of PARP. In some embodiments, the PARP inhibitor inhibits PARP activity.

The method of treatment as described herein can be by oral, transmucosal, buccal, nasal, inhalation, parenteral, intravenous, subcutaneous, intramuscular, sublingual, transdermal, ocular, and rectal administration.

Pharmaceutical compositions suitable for identifying PARP inhibitors useful in the treatment of diseases treatable by PARP inhibitors in a patient include compositions wherein the active ingredient is contained in a therapeutically or prophylactically effective amount (i.e., an amount effective to obtain a therapeutic or prophylactic benefit). The actual effective amount for a particular application will depend, inter alia, on the condition being treated and the route of administration. Determination of an effective amount is within the ability of those skilled in the art. The pharmaceutical composition comprises a PARP inhibitor, one or more pharmaceutically acceptable carriers, diluents or excipients, and optionally other therapeutic agents. The composition may be formulated for sustained or delayed release.

The composition can be administered by injection, topically, orally, transdermally, rectally, or by inhalation. Therapeutic agents administered in oral form may include powders, tablets, capsules, solutions or emulsions. An effective amount may be administered in a single dose or in a series of doses separated by suitable time intervals, such as hours. Pharmaceutical compositions may be formulated in conventional manner using one or more physiologically acceptable carriers comprising excipients and auxiliaries which facilitate the formulation of the active compounds in pharmaceutically usable preparations. Suitable formulations depend on the chosen route of administration. Suitable techniques for preparing pharmaceutical compositions of therapeutic agents are well known in the art.

A preferred dose of Compound III is 4mg/kg IV over 1 hour, twice weekly, starting on day 1 (the doses of Compound III are preferably separated by at least 2 days). Compound III treatment is preferably administered twice weekly, IV infusion for three consecutive weeks, 28-day one cycle. Other preferred doses include 0.5, 1.0, 1.4, 2.8 and 4mg/kg as monotherapy or in combination therapy.

It will be appreciated that the dosage of the active compound, and compositions containing the active compound, will vary from patient to patient. Determining the ideal dosage will generally involve balancing the therapeutic benefit with the risk or deleterious side effects of any of the treatments described herein. The selected dosage level will depend on a variety of factors including, but not limited to, the activity of the particular PARP inhibitor, the route of administration, the time of administration, the rate of excretion of the compound, the duration of the treatment, the other drugs, compounds and/or substances used in combination, and the year, sex, body weight, condition, general condition, and prior medical history of the patient. The amount and route of administration of the compound is ultimately at the discretion of the physician, although typically the dose should result in a local concentration at the site of action (which concentration achieves the desired effect without causing substantial deleterious or toxic side effects).

In vivo administration may be effected in a single dose, continuously or intermittently (e.g., in separate small doses at appropriate intervals) during the course of treatment. Methods of determining the most effective mode and dosage to administer are well known to those skilled in the art and will vary with the formulation used in the treatment, the purpose of the treatment, the target cells being treated and the patient being treated. Single or multiple administrations can be carried out using dosage levels and patterns selected by the treating physician.

IGF1 receptor/IGF pathway and modulators

As noted above, IGF1 receptor, IGF-1 or IGF-2 modulators (including inhibitors) may also be administered as described herein. Podophyllotoxin extension, PPP, BMS554417, BMS536924, AG1024, NVP-AEW541, NVP-ADW742, and antibodies to IGF1 receptor or its ligand are examples of compounds useful in combination with the methods of the invention. In one non-limiting embodiment, the picropodophyllin can be administered in a dosage of 0.01-50 μ M. In one non-limiting embodiment, the picropodophyllin may be administered at a dosage of about 7 mg/kg/day or about 28 mg/kg/day. Other compounds that inhibit the IFR-1 receptor or its ligand are also specifically included herein. Provided herein is a method of treating triple negative breast cancer using a PARP inhibitor in combination with at least one anti-tumor agent. In one embodiment, the at least one antineoplastic agent is a picropodophyllin. Also described herein is a method of treating ER-negative, PR-negative, HER-2 negative metastatic breast cancer in a patient in need of such treatment comprising administering to the patient a PARP inhibitor and a picropodophyllin.

EGFR pathway and modulators

Similarly, EGFR modulators or inhibitors may also be administered as described above, including cetuximab, panitumumab, matuzumab, MDX-446, nimotuzumab, mAb 806, erbitux (IMC-C2225),(ZD1839), erlotinib, gefitinib, EKB-569, lapatinib (GW572016), PKI-166, and kalatinib (Rocha-Lima et al, 2007, Cancer Control, 14: 295-. In one non-limiting embodiment of the present invention,may be administered at a dose of 250 mg/day, 500 mg/day, 750 mg/day or 1250 mg/day. Other compounds that inhibit EGFR (including nucleotide expression or activity), or that inhibit other targets in the erbB tyrosine kinase receptor family, are included within the scope of the present application. Provided herein is a method of treating lung cancer using a PARP inhibitor in combination with at least one anti-tumor agent. In one embodiment, the at least one antineoplastic agent isAlso described herein is a method of treating lung adenocarcinoma, small cell carcinoma, non-small cell carcinoma, squamous cell carcinoma in a patient in need of such treatmentA method of squamous cell carcinoma or large cell carcinoma comprising administering to said patient a PARP inhibitor and

criteria for cancer site care

In another aspect, PARP inhibitors are used in combination with the primary standard of care treatment for the cancer being treated. Described herein are criteria for the care of a certain type of cancer. In some embodiments, the modulators and inhibitors disclosed herein are used in combination with standard of care as described herein.

Endometrium: there are four standard of care for endometrial cancer, including surgery (hysterectomy, bilateral fallopian tube, ovariectomy, and radical hysterectomy), radiation, chemotherapy, and hormone therapy. Adjuvant therapies involving such treatments are administered in some cases.

Mammary gland: current breast cancer treatments involve breast-conservative surgical treatment and radiation therapy with or without tamoxifen, radical hysterectomy with or without tamoxifen, breast-conservative surgical treatment without radiation therapy, bilateral prophylactic total breast resection without axillary lymph node sweeping, delivery of tamoxifen to reduce the incidence of subsequent breast cancer, and adjunctive treatments including such treatment.

Ovary: if the tumor is good-or moderately differentiated-a total abdominal hysterectomy and a bilateral salpingo-oophorectomy using a reticulectomy may be sufficient for patients with early stage disease. Patients diagnosed with stage III and IV disease are treated with surgery and chemotherapy.

Cervix: methods of treating exocervical lesions include Loop Electrosurgical Excision Procedure (LEEP), laser therapy, taper resection, and cryotherapy. For stage I and II tumors, treatment options include: loop electrosurgical resection procedures, taper resection and intracavitary radiotherapy alone, bilateral pelvic lymphadenectomy, postoperative total pelvic radiotherapy plus chemotherapy, and radiotherapy plus chemotherapy with cisplatin or cisplatin/5-FU. For stage III and IV tumors, the standard treatment for cervical cancer is radiation and/or chemotherapy with drugs, including cisplatin, ifosfamide-cisplatin, paclitaxel, irinotecan, paclitaxel/cisplatin, and cisplatin/gemcitabine.

Testis: standard treatments for seminomas are radical inguinal orchiectomy (with or without single dose carboplatin adjunctive therapy), removal of the testes by radical inguinal orchiectomy followed by radiation therapy, and radical inguinal orchiectomy followed by combined chemotherapy or radiation therapy of the abdominal and pelvic lymph nodes. For non-seminoma patients, treatment included testicular removal by inguinal followed by retroperitoneal lymph node sweeping, radical inguinal orchiectomy (with or without retroperitoneal lymph node removal (with or without retroperitoneal lymph node sweeping (with or without chemotherapy)) with or without preservation of fertility).

Lung: in non-small cell lung cancer (NSCLC), the results of standard therapy are poor, except for the majority of localized cancers. All patients newly diagnosed with NSCLC are potential candidates for the evaluation of new forms of therapeutic studies. Surgery is the most effective curative treatment option for the disease; radiation therapy can cure a small number of patients and can provide relief in most patients. Adjuvant chemotherapy may provide additional benefit to patients who resect NSCLC. In the advanced stages of the disease, chemotherapy is used.

Skin: traditional approaches to basal cell carcinoma treatment involve the use of cryosurgery, radiation therapy, electro-desiccation and curettage, and simple resection. Local squamous cell carcinoma of the skin is a highly curable disease. Traditional treatment methods involve the use of cryosurgery, radiation therapy, electro-desiccation and curettage, and simple resection.

Liver: hepatocellular carcinoma may be cured by surgical resection, but surgery is the treatment of choice for only a small fraction of patients with localized disease. Other treatments that are still in clinical research include systemic or perfusion chemotherapy, hepatic artery ligation or embolization, percutaneous ethanol injection, cryotherapy, and radiolabeled antibodies, often in combination with surgical resection and/or radiation therapy.

Thyroid gland: standard treatment options for thyroid cancer include total thyroidectomy, lobectomy, and combinations of the procedure with I131 removal, external radiation therapy, thyroid stimulating hormone inhibition with thyroxine, and chemotherapy.

Esophagus: the primary treatment modalities include surgery alone or chemotherapy in combination with radiation therapy. Effective relief can be obtained in individual cases with a combination of various surgeries, chemotherapies, radiation therapy, stents, photodynamic therapy, and endoscopic treatment with Nd: YAG laser.

Kidney: surgical resection is the primary method of treating the disease. Even in patients with disseminated tumors, topical forms of treatment may play an important role in alleviating the symptoms of primary tumors or ectopic hormone secretion. Systemic treatments have proven to have only limited efficacy.

In one embodiment, PARP inhibitors are combined with other chemotherapeutic agents, e.g., irinotecan, topotecan, cisplatin, or temozolomide, to improve the treatment of many cancers, such as colorectal and gastric cancers, and melanoma and glioma, respectively. In another embodiment, the PARP inhibitor is combined with irinotecan for the treatment of advanced colorectal cancer or with temozolomide for the treatment of malignant melanoma.

In cancer patients, in one embodiment, PARP inhibition is used to increase the therapeutic benefit of radiation and chemotherapy. In another embodiment, targeting PARP is used to prevent tumor cells from repairing DNA themselves and the development of drug resistance, which makes them more sensitive to cancer treatment. In another embodiment, PARP inhibitors are used to enhance the effects of various chemotherapeutic agents (e.g., methylating agents, DNA topoisomerase inhibitors, cisplatin, etc.) as well as radiation against spectroscopic tumors (e.g., glioma, melanoma, lymphoma, colorectal cancer, head and neck cancer).

Reagent kit

In another aspect, a kit for identifying a disease in a patient treatable by a PARP modulator is provided, wherein the kit is useful for detecting the level of PARP in a sample obtained from the patient. For example, the kit may be used to identify the level and/or activity of PARP in normal and diseased tissues as described herein, wherein PARP levels are differentially present in samples from diseased and normal patients. In one embodiment, the kit comprises a substance comprising an adsorbent thereon, wherein the adsorbent is adapted to bind PARP and/or RNA, and instructions directing the identification of the level of PARP and/or PAR (mono-and poly-ribose) by contacting the sample with the adsorbent and detecting PARP immobilized by the adsorbent. In another embodiment, a kit comprises (a) an agent that specifically binds to or interacts with PARP; and (b) a detection reagent. In some embodiments, the kit may further comprise instructions for appropriate operating parameters in the form of a label or separate insert. Optionally, the kit may further comprise standard or control information whereby the test sample may be compared to a control information standard to determine whether the test amount of PARP detected in the sample is a diagnostic amount.

The container means of the kit generally comprises at least one vial, test tube, flask, bottle, syringe and/or other solvent means in which the at least one polypeptide can be placed and/or, preferably, suitably aliquoted. The kit can include a means for containing at least one fusion protein, detectable moiety, reporter molecule, and/or any other commercially available closed structure reagent container. Such containers may comprise injection and/or blow-molded plastic containers that store the desired vials. The kit may also include printed material for the purpose of using the substances in the kit.

The packages and kits may further comprise buffering agents, preservatives and/or stabilizers in the pharmaceutical formulations. The individual components of the kit may be sealed in separate containers and all of the different containers may be in one package. The kit may be designed for frozen or room temperature storage.

In addition, the formulation may include a stabilizer, such as Bovine Serum Albumin (BSA), to increase the life of the kit. When the composition is lyophilized, the kit may include additional solution formulations to reconstitute the lyophilized formulation. Acceptable reconstitution solutions are well known in the art and include, for example, pharmaceutically acceptable Phosphate Buffered Saline (PBS).

In some embodiments, the therapeutic agent may also be provided as a separate component in a separate container within the kit for treatment. Suitable packaging and other articles for use (e.g., measuring cups for liquid formulations, foil wrappers to reduce exposure to air, etc.) are known in the art and may be included with the kit.

The packages and kits may further comprise labeling instructions, for example, product instructions, modes of administration, and/or therapeutic indications. The packages provided herein can include any of the compositions described herein for treating any of the indications described herein.

The term "packaging material" refers to the physical structure that contains the components of the kit. The packaging material can aseptically contain the ingredient, and can be made of materials commonly used for such purposes (e.g., paper, corrugated cardboard, glass, plastic, foil, ampoules, and the like). The label or package insert may include suitable written instructions. Thus, the kit can additionally include a label or instructions for using the kit components in any of the methods described herein. The kit may include the compound in a package or adapter and instructions for administering the compound in the methods described herein.

The kit may also include instructions teaching the use of the kit according to the various methods and means described herein. Such kits optionally include information, such as scientific literature references, package inserts, clinical laboratory results, and/or summaries of such information, etc., which indicate or establish the activity and/or advantages of the composition, and/or which describe dosages, administrations, side-effects, drug interactions, diseases for which the composition is administered, or other information useful to the health care provider. Such information may be based on the results of various studies, for example, studies involving in vivo models using experimental animals and studies based on human clinical trials. In various embodiments, the kits described herein can be provided to, sold to, and/or submitted to health providers, including consciousness, nurses, pharmacists, prescribing physicians, and the like. In some embodiments, the kit may be sold directly to the consumer. In certain embodiments, the packaging material can further comprise a container containing the composition, and optionally a label adhered to the container. The kit optionally includes other components, such as, but not limited to, a syringe for administering the composition.

The instructions may include instructions for performing any of the methods described herein, including methods of treatment. The indication may additionally include an indication of a satisfactory clinical endpoint or any adverse symptoms that may occur, or other information required by other regulatory bodies, such as the food and drug administration, for use on human patients.

The indication may be on "printed material", for example, on paper or cardboard within or adhered to the kit, or on a label adhered to the kit or packaging material, or on a label adhered to a vial or test tube containing the components of the kit. Indications may additionally be included in computer readable media such as magnetic disks (floppy disks or hard disks), optical CDs such as CD-or DVD-ROMs/RAMs, magnetic tapes, electrical storage media such as RAMs and ROMs, IC tips, and mixtures of these such as magnetic/optical storage media.

In some embodiments, the kit may include reagents for testing the level of DNA, RNA, or protein expression in a sample of tumor cells from a patient to be treated.

In some aspects, a kit can comprise reagents and materials to perform any of the assays described herein.

Examples

The present application may be better understood by reference to the following non-limiting examples, which are presented as exemplary embodiments of the present application. The following examples are intended to more fully illustrate the embodiments, but should not be construed as in any way limiting the broad scope of the present application. While specific embodiments of the present application have been shown and described herein, it will be obvious that such embodiments are provided by way of example only. Many modifications, changes, and substitutions will now occur to those skilled in the art; it should be understood that various alternatives to the embodiments described herein may be employed in practicing the embodiments described herein.

Example 1

Gene array testing has been widely used to monitor mRNA expression in many areas of biomedical research. High density oligonucleotide array technology allows researchers to monitor tens of thousands of genes in a single hybridization experiment because they express different genes in tissues and cells. The expression profile of the mRNA molecules of a gene is obtained by combining intensity information from probes in a probe set consisting of 11-20 probe pairs of oligonucleotides 25bp in length, interrogating the sequences of different parts of the gene.

Gene expression was evaluated using Affymetrix Human Genome genes (45,000 gene transcripts, covering 28,473 UniGene clusters). Approximately 5 μ g of total RNA from the sample was labeled using a high yield transcriptional labeling kit, and the labeled RNA was hybridized, washed, and scanned (according to the manufacturer's instructions) (Affymetrix, inc., Santa Clara, CA). The level of transcription signal was estimated from the scanned image using Affymetrix Microarraysuite 5.0 software (MAS5) (Affymetrix). The signals on each array were normalized to a modified mean value (trimmed mean value)500, excluding the lowest 2% and highest 2% signals. Hereinafter, for convenience, the Affymetrix probe set representing a unique GenBank sequence will be referred to as a probe or gene. To verify any errors in the representation due to image defects, the correlation coefficient of each array to an idealized distribution, which is the average of all arrays, was determined. Genes were filtered from the remaining arrays using the detection P values reported by MAS 5. Genes with P > 0.065 were removed in 95% of the arrays, while all other signals were included for class statistical comparisons.

Example 2

Upregulation of PARP1mRNA in normal and tumor tissues

Research design and materials and methods

Tissue sample: normal and cancer tissue samples were collected in the united states or uk. Samples were collected as part of a normal surgical procedure and snap frozen within 30 minutes of resection. The samples were transported at-80 ℃ and stored in the vapor phase of liquid nitrogen at-170 to-196 ℃ until processing. The samples to be analyzed are subjected to a medical pathology examination and validation. In conjunction with the initial diagnostic report, H & E-stained slides from adjacent sections of tissue were observed and samples were classified by diagnostic category. During the examination of the slides by the pathologist, the visually estimated percentage of tissue implicated by the tumor was recorded and the fraction of malignant nucleated cells was indicated. Auxiliary studies such as ER/PR and Her-2/neu expression studies are performed by methods including immunohistochemistry and fluorescence in situ hybridization. These results, along with accompanying pathological and clinical data, are annotated in the sample catalog and management databases (Ascenta, Bioexpress databases; Gene Logic, Gaithersburg, Md.).

RNA extraction, quality control and expression profiling: RNA was extracted from the samples as follows: according to the manufacturer's recommendations at Reagent (Invitrogen, Carlsbad, CA) followed by isolation using RNeasy kit (Qiagen, Valencia, CA). RNA quality and integrity (28 s/18s ratio and RNA integrity values obtained with an Agilent 2100 Bioanalyzer), purity (by the ratio of absorbance at A260/A280), and quantity (by absorbance at A260 or alternative tests) were evaluated. GeneExpression levels were assessed using Affymetrix Human Genome U133A and BGeneChips (45,000 probe sets representing more than 39000 transcripts from approximately 33000 well-documented genes). 2. mu.g (2. mu.g) of total RNA was collected and used for Superscript II^TM(Invitrogen, Carlsbad, Calif.) and T7 oligo dT primer (for cDNA Synthesis) and AffymetrixIVT Labeling Kit (Affymetrix, Santa Clara, Calif.) prepared cRNA. UV absorption was used to assess the amount and purity of the cRNA synthesis product. The quality of cRNA synthesis was assessed using an agilent bioanalyzer or MOPS agarose gel. The labeled cRNA was then fragmented and 10. mu.g was used for hybridization at 45 ℃ for 16-24 hours for each array. The arrays were washed, stained according to the manufacturer's recommendations, and scanned on Affymetrix GeneChip Scanners. Array data quality was evaluated using a dedicated high-throughput application that evaluated the data using a number of objective criteria, including 5 '/3' GAPDH ratio, signal/noise ratio, background, and other indicators that must be incorporated into the analysis by the back (e.g., outliers, vertical variations). The GeneChip analysis was performed using Microarray analysis Suite version 5.0, Data Mining Tool 2.0, and Microarray database software (www.affymetrix.com). All genes present on the GeneChip were globally normalized (globallel normalized) and scaled to a signal intensity of 100.

Quality control: RNA was evaluated for quality and integrity (28 s/18s ratio and RNA Integrity Number (RIN) obtained with an Agilent 2100 Bioanalyzer), purity (by the ratio of absorbance at A260/A280), and quantity (by absorbance at A260 or alternative tests (i.e., Ribogreen)). UV absorption was used to assess the amount and purity of cRNA synthesis product. The quality of the cRNA synthesis was evaluated using Agilent Bioanalyzer or MOPS agarose gels. Array data quality was assessed using proprietary high throughput applications that evaluated the data using several strict objective criteria, such as 5 '/3' GAPDH ratio, signal/noise ratio, background, and other more than thirty indicators that must be passed to incorporate the analysis process (e.g., outliers, vertical variation). The data generated in the whole process is controlled in a quality system to ensure the integrity of the data.

Statistical analysis: mean values and 90%, 95%, 99% and 99.9% Upper Confidence Limits (UCL) for individual predictors were calculated. Because we evaluate the likelihood that individual samples outside the normal set are within the baseline distribution, the prediction interval of the mean is chosen instead of the confidence interval to estimate the expected range of future individual measurements. Prediction interval of Definition of formula (I), whereinIs the average of normal breast samples; s is the standard deviation of the normal sample, n is the sample size of the normal sample, and A is the 100 th (1- (p/2)) percentile of the Student's t-distribution with n-1 degrees of freedom. The PARP1 gene was previously known to be elevated in tumor samples, suggesting that upregulation relative to baseline is a major concern. Therefore, the lower confidence limit is not calculated. According to recognized characteristics, including tumor stage, smoking status or age. The samples were assigned to different subgroups. Some samples belong to more than one subgroup, and some samples do not belong to any subgroup outside the basic cancer type. Individual cancer samples were identified as having greater than 90%, 95%, 99% or 99.9% UCL. Pearson correlation coefficients were calculated for 44,759 probe sets on the Affymetrix HG-U133A/B array set, compared to PARP 1. The correlation is based on the cancer sample set tested.

All analyses were performed using Windows SAS v8.2(www.sas.com) and were performed using AffymetrixMAS5 expression intensity calculated by Operating System (www.affymetrix.com). The PARP1 gene in the HG-U133A array is represented by a single probe set with the identifier "208644 _ at". Signaling of this probe set based on MAS5 The intensity produces a result.

A single normal and cancerous tissue from breast, ovarian, endometrial, lung and prostate tissues was selected. Any one cancerous sample may be represented in more than one subfraction class.

Breast cancer outcome: expression of PARP1 in Invasive Ductal Carcinoma (IDC) was significantly increased compared to normal, where about 70% of IDCs may have PARP1 expression above the 95% confidence limit of the normal population, supporting the findings previously observed by BiPar. As was frequently observed in the analysis, further analysis of different IDC sample subsets showed that the percentage of IDCs with increased PARP1 expression observed increased to 88% to 89% if ER status of IDCs was negative or if their Her2-neu status was negative. The percentage of PR negative samples that exceeded the normal 95% UCL was 79%, not as significant, but still improved. Furthermore, PARP1 expression tended to become slightly higher in the ER (-), PR (-), and Her2-neu (-) mammary IDC (invasive ductal carcinoma) classes compared to their respective (+) class. This phenomenon was not observed in the p53 category or in the tumor stage category. This conclusion may be influenced by the fact that a single sample in this analysis contributes to different classes. Examination of the supplementary data set showed that the highest expression of PARP1 in the ER (-) group was also a high expression in the PR (-) group and the Her2-neu (-) group. The same applies to the lowest expressor in the (+) group. This suggests that any treatment against PARP1 overexpression is more effective in ER, PR or Her2-neu negative cases.

Ovarian outcome: fromSystem selects normal ovarian and cancerous ovarian samples, which are defined forMembers of the sample set of the System. All ovarian cancers expressed a higher mean PARP1 compared to normal ovaries. The clear cell adenocarcinoma and mucinous cystadenocarcinoma samples expressed significantly less PARP1 than the other subtypes, TableThe degradation of the achievement is less. In individual sample evaluation, the majority of pathological subtypes of ovarian cancer showed that the vast majority of samples were above the 95% upper confidence limit: (a) the frequency of samples with confidence limits higher than 95% among papillary serous adenocarcinoma, serous cystadenocarcinoma, granulosa cell tumor and mullerian mixed tumor is similar and higher; (b) in endometrioid adenocarcinomas, about half of the samples were above the 95% upper confidence limit; (c) in clear cell adenocarcinoma and mucinous cystadenocarcinoma, the samples below 1/3 were above the upper 95% confidence limit.

Furthermore, a clinical subgroup comparison of PARP1 expression in ovarian cancer samples showed: (a) papillary serous stage I is similar to papillary serous stage III; and (b) papillary serous adenocarcinomas with elevated CA125 are similar to serous adenocarcinomas.

Accordingly, PARP1 expression was elevated in ovarian cancer samples compared to normal samples. Furthermore, despite this finding, not all ovarian cancer samples showed this overexpression. This broad distribution and propensity for higher expression (shift) in the ovarian cancer group indicates that 75% of ovarian cancers have PARP1 expression above the 95% upper confidence limit for normal ovarian expression. Further analysis of different subsets of ovarian cancer samples showed that if they were of the subtype papillary serous adenocarcinoma, serous cystadenocarcinoma, Mullerian mixed tumor or granulomatous carcinoma, an increase in the percentage of ovarian cancer samples with high PARP1 expression to-90% was observed. For clear cell adenocarcinoma and mucinous cystadenocarcinoma subtypes, an increase in PARP1 was indeed exhibited in the assessed specimens below 1/3.

Endometrial results: expression of PARP1 in endometrial cancer is generally elevated compared to normal. In addition, all endometrial cancers showed greater average PARP1 signal intensity than normal endometrium. PARP1 expression was much higher in Mullerian mixed tumor samples than in other subtypes. PARP1 expression exceeded the 95% highest confidence interval ("overexpression") in the normal population in about one-quarter of all endometrial cancer samples, about one-third of all lung cancer samples, and about one-eighth of all prostate cancer samples. Mullerian mixed tumors and lung squamous cell carcinomas showed the highest frequency of increased expression of PARP 1.

In addition, individual samples from all endometrial cancer subtypes were tested individually against a distribution of normal endometrial samples. Each defined as 90%, 95%, 99% and 99.9% above the upper bound of normal group confidence. Elevated PARP1 expression in cancerous endometrial samples relative to normal endometrial samples is evident. The variation in PARP1 expression was much greater (i.e. more spread) for cancerous endometrial samples than for normal endometrial samples. No outliers were observed within the normal endometrial sample set with respect to PARP1 expression. Most pathological subtypes of endometrial cancer show that the vast majority of specimens are above 90% UCL. Of particular note, samples with Mullerian hybridomas appearing above 95% UCL were most frequently (85.7%) and still higher at 99.9% UCL (71.4%).

Lung results: in both the normal and malignant lung sample classes, the mean PARP1 signal intensity was higher for all lung cancer expressions than for normal lungs. Individual samples from all lung cancer subtypes were tested individually against a normal lung sample distribution. Elevated expression of PARP1 in cancerous lung samples relative to normal lung samples is evident. PARP1 expression from cancerous lung samples showed a much greater variation (i.e., greater spread) than normal lung samples.

Prostate results: although the mean PARP1 signal intensity expressed in the prostate cancer group showed some increase compared to the normal prostate group, PARP1 expression was only slightly elevated in the cancerous prostate samples compared to the normal prostate samples. The cancerous prostate sample expression of PARP1 shows a similar degree of variation (i.e., the same spread) as that of the normal prostate sample.

Example 3

Co-expression of PARP1 Mrna and other targets in normal and cancer tissues

The PARP1 gene is represented by a single probe set with a "208644 _ at" identifier on the HG-U133A array. Other genes, such as BRCA1, BRCA2, RAD51, MRE11, p53, PARP2 and mucin 16 are represented in HG-U133A/B array set by their respective sets of information probes. The probe sets corresponding to the 7 genes in the ovarian cancer sample analysis are listed in table XXXIII.

Table XXXIII: comparing genes with their corresponding HG-U133A/B Probe set IDs

Gene symbol	Title	Segment names
			BRCA1	Breast cancer 1, early onset	204531_s_at
BRCA2	Breast cancer 2, early onset	214727_at
			MRE11A	MRE11 meiotic recombinant 11 homolog A (Saccharomyces cerevisiae)	205395_s_at，242456
MUC16	Mucin 16, cell surface association	220196_at
			PARP2	The family of poly (ADP-ribose) polymerases,member 7	204752x_at，214086_s_at，215773_x_at
RAD51	RAD51 homolog (RecA homolog, E.coli) (Saccharomyces cerevisiae)	205024_s_at
			TP53	Tumor protein p53 (Li Fu Lao Ming syndrome)	201746_at，211300_s_at

Comparison of PARP1 with selected genes in ovarian samples: PARP1 expression was correlated with the expression of other genes measured on the HG-U133A/B array set. The correlation is based on the full set of 194 samples selected for the analysis. Table XXXIV summarizes the results of this analysis. For MRE11A, PARP2 and TP53, more than one probe set was tiled (tile) over the HG-U133A/B array set.

Table XXXIV: pearson correlation of PARP1 expression to selected Probe sets

No negative correlation was found in all cases. A positive correlation indicates that the probe set changed in the same direction as PARP 1. When PARP1 has low expression, for example in normal samples, the expression of these related genes is expected to be low as well. When PARP1 expression is elevated, for example in malignant samples, the expression of these related genes is expected to be elevated as well. All of these genes, except PARP2, appear to be malignant markers in ovarian cancer and their response pattern is similar to PARP 2.

Other genes that are co-regulated with PARP1 in ovarian cancer are included in the following list XXXV:

table XXXV: genes and their pathways coexpressed with PARP1 in ovarian cancer

The association of PARP1 expression with genes BRCA1, BRCA2, RAD51, MRE11, p53, PARP2 and mucin 16 indicates significant association for all genes (except PARP 2). RAD51 had the highest correlation.

PARP1 expression was also tested for correlation with genes expressed in endometrial, lung and prostate tissue samples. By correlating PARP1 with all other genes, genes with up to 80% correlation with PARP1 were identified. In endometrial and lung samples, a highly correlated (i.e., top 40) set of normal genes associated with cell proliferation was identified in both tissues.

Comparison of PARP1 with selected genes-endometrial results: PARP1 expression was correlated with all other probe sets tested on HG-U133A/B array set. The gene symbol and gene name (if any) have been provided for each analyzed probe set. The correlation is based on the full set of 80 samples selected for the analysis. Table XXXVI summarizes the 40 most relevant probe sets (when compared to PARP 1).

Table XXXVI: pearson correlation of PARP1 expression with selected Probe sets

The most relevant gene for PARP1 expression was DTL with a pearson correlation of 0.765. The first 40 probe sets all had a positive correlation with PARP 1. Positive correlation represents a situation where the change in PARP1 expression is the same as the change in the positively correlated probe set. Negative correlations were also observed for the probe set, but none of those negative correlations ranked the first 40 bits of the absolute scale. The highest negative correlation probe set corresponds to the HOM-TES-103 gene (hypothetical protein LOC25900, isoform 3), with a correlation of-0.636.

Comparison of PARP1 with selected genes-lung results: PARP1 expression was correlated with all other probe sets determined on the HG-U133A/B array set. Each probe set analyzed has been provided with the gene symbol and gene name (if any). The correlation was based on a set of 347 samples selected for the analysis (excluding 4 outlier normal samples). Table XXXVII summarizes the 40 most highly correlated probe sets (when compared to PARP 1).

Table XXXVII: pearson correlation of PARP1 expression with selected Probe sets

The gene most correlated with PARP1 expression was UBE2T, which had a pearson correlation of 0.815. The first 40 probe sets all had a positive correlation with PARP 1. Positive correlation represents the same change in PARP1 expression as in the positively correlated probe set. Negative correlations were also observed for the probe set, but none of those negative correlations ranked the first 40 on the absolute scale. The probe set with the highest negative correlation corresponds to the TGFBR2 gene (transforming growth factor, beta receptor II) with a correlation of-0.670.

Comparison of PARP1 with selected genes-prostate results: PARP1 expression was correlated with all other probe sets measured on HG-U133A/B array set. Some probesets correspond to the same gene, while others have no known gene annotation available. The gene symbol and gene name (if any) have been provided for each analyzed probe set. The correlation is based on a set of 114 samples selected for the analysis. Table XXXVIII summarizes the 40 most relevant probe sets (compared to PARP 1).

Table XXXVIII: pearson correlation of PARP1 expression with selected Probe sets

The gene with the best correlation to PARP1 expression is MAPKAPK5, which has a Pearson correlation of 0.522. The first 40 probe sets were both positively and negatively correlated to PARP 1. Positive correlation represents the case where the expression of PARP1 and the positively correlated probe set changes in the same direction. The negatively correlated probe set represents the case where the expression of PARP1 was changed in the opposite direction. The probe set with the greatest degree of negative correlation corresponded to the GGTL3 gene (gamma-glutamyltransferase-like 3), with a degree of correlation of-0.515.

By correlating PARP1 expression with other genes on the HG-U133A/B array set, genes with up to 70% to 80% correlation in endometrium and lung were identified. Although the best correlated genes were different in each tissue, there was a consistent probe set in the top 40 list. Table XXXIX lists the top 40 7 probe sets in both the endometrium and lung and shows the relevant Gene Ontology Biological Process (Gene Ontology Biological Process) terminology. The genes indicated are associated with cell proliferation. None of these probe sets ranked top 5000 for the prostate samples selected for this analysis.

Table XXXIX: consistent probesets between the 40 most relevant probesets in lung and endometrium

PARP1 is involved in base-nick repair following DNA damage and appears to be an essential step in the lead detection/signaling pathway for DNA strand break repair. Thus, co-regulation of PARP1 with other genes critical to cell cycle, chromosome segregation, cell division and mitosis is of interest. The degree of correlation of the most relevant probe sets in the prostate is significantly lower than the most relevant probe sets in the endometrium or lung. If PARP1 is relatively unchanged in normal prostate compared to prostate adenocarcinoma (over 60 years old), then the low correlation of PARP1 expression in prostate for other probe sets on the array set is not surprising. Due to the lack of statistical significance in the cancer group, the most relevant prostate gene list was not compared to other tissues.

And (4) conclusion: PARP1 expression was generally increased in endometrial and lung cancer samples compared to normal samples. No similar increase in signal was observed in the prostate cancer samples evaluated. The figures show that, despite this finding, not all endometrial and lung cancer samples showed such overexpression. This broader distribution and higher tendency to expression in the endometrial and lung cancer groups indicates that PARP1 expression exceeds 95% of the confidence upper limits for their respective normal expression for 37% of endometrial cancers and 77% of lung cancers. Further analysis of the various subpopulations of endometrial cancer samples indicated that the percentage of cancer samples with increased PARP1 expression was observed to rise to-86% if the cancer samples were mullerian mixed tumor subtypes. Clear cell adenocarcinoma and mucinous cystadenocarcinoma showed an increase in PARP1 in one third or fewer of the samples evaluated, possibly indicating less sensitive cancer types. These findings should be further investigated and confirmed. In summary, (1) PARP1 is expressed more highly in endometrial and lung cancers than in their respective normal tissues; (2) certain subtypes of endometrial and lung cancer appear to show higher expression than other subtypes. Specifically, mullerian mixed tumor and lung squamous cell carcinoma samples showed a higher proportion of samples over normal UCL than other types; and (3) 7 genes were located simultaneously in the first 40 probesets most related to PARP1 in the endometrium and in the lung. These genes are associated with cell proliferation and mitosis.

Example 4

Monitoring PARP expression in tissue samples

Test description and method: XP^TMPCR is a multiplex RT-PCR methodology which makes it possible to analyze the expression of multiple genes in a single reaction (Quin-Rong Chenet al: Diagnosis of the Small Round Blue Cell turbines Using Mutliplex Polymerase Chain reaction. J. mol. diagnostics, Vol.9.No.1, February 2007). The use of a specific combination of gene specific primers and universal primers in the reaction resulted in a series of fluorescently labeled PCR products, whose size and number were measured using capillary electrophoresis equipment GeXP.

Sample treatment: briefly, freshly purified tissue samples were plated in 24-well plates at a density of 6X106 cells/well. Half of the samples were immediately lysed and the others were snap frozen in a dry ice and ethanol bath and stored at-80 ℃ for 24 hours. Total RNA from each sample was isolated according to Altha Technologies, Inc. SOP Total RNAI association Using Promega SV96 Kit (Cat. No. Z3505). The concentration of RNA obtained from each sample was determined Using 03-XP-008, RNA quantification Using the Quant-it Ribogreen RNAAssay Kit (Cat. No. R-11490). To be obtained from individual samples A portion of the RNA was adjusted to 5 ng/. mu.L, followed by XP^TM-PCR。

XP^TM-PCR: multiplex RT-PCR was performed Using 25ng of total RNA per sample Using the protocol previously described (Quin-Rong Chen et al: diagnostics of the Small Round Blue cell turbines Using Mutliplex Polymerase Chain reaction. J.mol.diagnostics, Vol.9.No.1, February 2007). RT reactions were carried out as described for SOP 11-XP-002(cDNA Production from RNA) using Applied Biosystems 9700. For each cDNA, the sequence was modified according to SOP11-XP-003 (XP)^TMPCR) PCR reactions were performed using Applied Biosystems 9700. To monitor the efficiency of the RT and PCR reactions, 0.24 attamoles (attamoles) of kanamycin RNA was incorporated into each RT reaction. Two types of positive control RNA were used. Other test controls include 'no template control' (NTC) (where water is added to the individual reactions instead of RNA) and 'reverse transcriptase negative' (RT-) control (where sample RNA is subjected to steps without reverse transcriptase).

Expression analysis and calculation: the PCR reaction was analyzed by capillary electrophoresis. The fluorescently labeled PCR reaction was diluted, mixed with Genome Lab size standard-400(Beckman-Coulter, Part Number608098), denatured, and loaded onto the Beckman Coulter using SOP 11-XP-004, Operation and Maintenance of the CEQ 8800 Genetic Analysis System. The data obtained from 8800 was analyzed using expression analysis software to generate relative expression values for each gene. The relative expression of each targeted gene for cyclophilin A, GAPDH or β -actin expression within the same response is shown as the average of duplicate experiments. The standard deviation and percent coefficient of variation (% CV) associated with these values are also reported, where appropriate.

The statistical analysis method comprises the following steps: the mathematical form of the analysis of variance model used for this analysis is as follows:

Y_ijkl＝μ+α_i+β_j+γ_k+ω_l(ijk)+ε_ijkl i＝1...5 j＝1...4 k＝1...3 l＝1...3

(1)Coυ(Y_ijkl，Y_ijkl)＝σ² _ω+σ² _τ Coυ(Y_ijkl，Y_ijkl’)＝σ² _ω Coυ(Y_ijkl，Y_ijk’l)＝0

wherein, Y_ijklNormalized Rfu ratio obtained for the ith time point, the ith replicate at the ith sample, the jth dose concentration. The parameter μ in the model is the ensemble average of normalized Rfu ratios, an unknown constant, α_iThe stationary effect due to sample i, β_jA fixed effect due to the dose concentration j, γ_kIs a fixed effect due to the time point k, and ω_l(ijk)Random effects from the ith time point, i-th replicate at the ith sample, assuming mean 0 obedience, variance σ² _ωNormal distribution of (e ∈)_ijklIs a random error term associated with the normalized Rfu ratio from the ith time point of the ith sample at the jth dose concentration, assuming that it obeys a mean of 0 and a variance of σ² _ωIs normally distributed.

For the above model, data was analyzed using a linear mixing effect function (lme function) in an R-encoded nonlinear mixing effect packet (nlme packet). Overall dose Effect (H) of each Gene₀：β₁＝β₂＝β₃＝β₄＝β₅＝0；H₁: at least one term of beta_iDifferent) will be analyzed using the F-test.

Example 5

Expression of PARP in syngeneic samples Using Q-RT-PCR

Test description and method: XP^TMPCR is a multiplex RT-PCR method that can enable expression analysis of multiple genes in a single reaction (Kahn et al, 2007). The use of specific combinations of gene-specific primers and universal primers in the reaction results in a series of fluorescently labeled PCR products, using capillariesThe electrophoresis apparatus GeXP measures their size and number.

XP^TM-PCR: multiplex RT-PCR was performed using 25ng of total RNA per sample using the previously described protocol (Khan et al, 2007). RT reactions were performed as described for SOP 11-XP-002(cDNAproduction from RNA) using Applied Biosystems 9700. For each cDNA, the sequence was based on SOP 11-XP-003 (XP)^TMPCR) PCR reactions were performed using Applied Biosystems 9700. To monitor the efficiency of the RT and PCR reactions, 0.24 attamoles (attamoles) of kanamycin RNA was incorporated into each RT reaction. A positive control RNA was used, which is described in detail in the "test assay" section below. Other test controls include 'no template control' (NTC) (where water is added to the individual reactions instead of RNA) and 'reverse transcriptase negative' (RT-) control (where steps are performed on sample RNA without the use of reverse transcriptase).

Expression analysis and calculation: the PCR reaction was analyzed by capillary electrophoresis. Fluorescently labeled PCR reactions were diluted, combined with Genome Lab size standard-400(Beckman-Coulter, Part Number608098), denatured, and loaded onto the Beckman Coulter using SOP 11-XP-004, Operation and Maintenance of the CEQ 8800 Genetic Analysis System. The data obtained from 8800 were analyzed using our proprietary expression analysis software to generate relative expression values for each gene. The expression of each targeted gene relative to the expression of glucuronidase β (GUSB) within the same reaction was reported as the average of duplicate experiments. Where appropriate, the standard deviation and percent coefficient of variation (% CV) associated with these values are also reported.

Sample description: frozen human breast and lung tissue was harvested intraoperatively and stored in isogenic paired form on dry ice. They consisted of tumor and normal samples from each individual studied.

Extracting sample RNA: using RiboPure^TMRNA isolation kit (Ambion Cat. #1924) extracted RNA from each sample. To ensure that the samples are thawed only under conditions where the ribonuclease is denatured, each will be thawed The frozen sample was placed on a new sample collection pan placed on dry ice. Approximately 100mg of lung tissue fragments and 200mg of breast tissue fragments were cut out for each sample using a new razor blade and immediately placed in a labeled test tube containing a TRI Reagent and two ceramic beads. The samples were then homogenized for 2 minutes at 20MHz using Qiagen Laboratory hybridization Mill Type MM 300. The direction of the mixer to grind the sample block was then reversed and the sample was re-homogenized for 2 minutes. Then according to the kit with the provision of RiboPure^TMProtocol RNA was isolated from the homogenate.

After isolation, each RNA sample was subjected to a DNase reaction (according to SOP 3-XP-001 DNaseI Treatment of RNA) to remove any residual sample DNA.

RNase-In (Ambion, Cat. No. AM2696) which is an RNase inhibitor was added to each sample immediately after the DNase heat inactivation step of the DNase reaction at a final concentration of 1U/. mu.L.

RNA quantification: the concentration of RNA was determined using a RiboGreen RNA quantification Kit (Invitrogen, Cat. No. R11490) and according to SOP 3-EQ-031 Wallac Victor 21420 MultilabelCounter.

Sample RNA quality: RNA samples obtained from each sample were analyzed on an Agilent Bioanalyzer according to the Altha Technology's SOP 11-XP-001 Operation of the Agilent 2100 Bioanalyzer.

Sample requirements: the samples were processed according to the following protocol: triplicate determinations (each RNA sample in three independent XPs)^TMTested in PCR reactions) and RT-PCR reaction sample requirements (25 ng total RNA was used per reaction).

XP^TM-PCR: RT-PCR controls were as follows: (1) reverse transcription controls (RT negative) for DNA contamination present in RNA are negative; and (2) a PCR control (non-template control) for DNA contamination in the reagents was negative. Positive control: the human positive control RNA used in the test was Ambion human Reference RNA (HUR), (Ambion, custom order).

PARP 1-pathway analysis of activated tumors

A data source: gene expression data sets obtained from BiPar Sciences were analyzed using the Reset 5.0Molecular Interaction Database (Yuryev et al, 2006, Bioinformatics, 7: 171). The published database was augmented with 2344 automatically established bioprocess pathways, 249 networks of cellular components and 129 metabolic pathways derived from KEGG (Daraselia et al, 2007, Bioinformatics, 8: 243).

Identification of samples with differential expression of PARP 1: analysis of PARP 1-activated tumors was performed using expression data provided by BiPar Sciences Inc. Samples obtained from four tumor tissues were analyzed: breast, endometrium, ovary and lung. Samples obtained from MAS5 normalization in each tissue were divided into two categories: tumors with low PARP1 expression and tumors with high PARP1 expression. The minimal difference in PARP1 expression between any sample pair of the two classes was a 2-fold change. The results of looking for samples with differential PARP1 expression are shown in table XL.

Table XL: results of selecting samples with differential expression of PARP1

All files using the selected samples had the following:

a column with gene identifiers derived from the original microarray file;

correlation pattern-absolute value of gene profile correlation with PARP1 gene;

relatedness-degree of gene profile relatedness to the PARP1 gene;

log2 ratio of the average expression of a gene in high/low log ratio-PARP 1 high expressing tumors to the average expression of the gene in PARP1 low expressing tumors;

samples with low PARP1 expression; and

samples with high PARP1 expression.

Identification of significant genes: for each gene, fold of expression change was calculated as log ratio between mean normalized signal intensity in samples with low PARP1 levels and mean in corresponding tumors with high PARP1 expression. For lung samples where data on normal tissue was available, the ratio was calculated as the difference between fold change in expression of PARP1 overexpressing tumors versus normal tissue and PARP1 underexpressing tumors versus normal tissue.

For breast, endometrial and ovarian samples, p-values indicating confidence in differential expression were calculated using unpaired t-tests. For lung samples, it is not possible to calculate p-values, since they have only one sample for each type of tumor.

Table XLI: and (4) identifying the significant genes. The table contains the actual number of genes, with duplicate probes removed, and probes that did not map proteins in ResNet5 not counted

All files using the selected samples had the following:

a column with the gene identifiers of the original gene microarray file;

correlation pattern-absolute value of the correlation with the gene profile of the PARP1 gene;

correlation-degree of gene profile correlation with PARP1 gene;

log2 ratio of the average expression of a gene in high/low log ratio-PARP 1 high expressing tumors to the average expression of the gene in PARP1 low expressing tumors;

p-value of differential expression calculated by unpaired t-test;

mean expression values in PARP1 low expressing tumors;

mean expression values in PARP1 highly expressed tumors;

samples with low PARP1 expression; and

samples with high PARP1 expression.

Comparative analysis of significant genes: for the three statistical cut-off values described in table XLI, the following comparative analyses were performed at three levels, respectively: (1) direct comparison of differentially expressed genes to find significant genes common to three or four tissues; (2) comparative gene ontology analysis was performed to find differentially expressed and common for three or four tissues GO populations that are common to the tissues; and (3) comparative pathway analysis was performed to find pathways that are differentially expressed/co-regulated and common to three or four tumor types (breast, ovary, endometrium and lung).

First in three tissues: significant genes, GO populations and pathways were identified in common in breast, endometrium and ovary. Significant genes that are common among all four tissues were additionally identified. This is done because the small number of lung tissue samples may cause a bias in the comparative analysis.

The "Find groups" and "Find paths" options in the path Studio are used for each organization to identify common GO groups and paths. The "Find clusters" and "Find pathways" options identify significant clusters and pathways by comparing differentially expressed genes to clusters and pathways in Pathway Studio databases using the Fisher's exact test.

The common clusters/paths of three or four tissues are found by calculating the intersection between the GO cluster lists or the intersection between the path lists. When finding clusters/pathways common to all tissues, only clusters/pathways with a Fisher's exact test p-value less than 0.001 were considered.

The results of the comparative analysis for each of the three statistical cut-off values are: 2 times of critical value; p-value 0.01 cut-off; and a 2-fold + p-value of 0.01 cut-off.

The results of comparing gene ontology and pathway analysis describe a list of significantly overexpressed GO populations and pathways for each tissue differentially expressing genes, and also describe GO populations and pathways that were overexpressed in all four tissues.

Ontology analysis of significant genes: ontology analysis of significant genes was performed using the Fisher exact test as described in the previous section. The analysis results obtained were as follows: 2 times of critical value; p-value 0.01 cut-off; and a 2-fold + p-value of 0.01 cut-off.

Network analysis: starting from the identified significant genes of each tissue, a physical network was established using the Build Pathway tool option (find direct interactions between selected entities), in which filters were set to contain only Binding interactions (Binding interactions). Networks were established for significant genes common to each tissue as well as all three tissues.

The Expression regulatory network is established with the establish pathway tool option "find direct interactions between selected entities" where the filter settings are set to contain Expression and Promoter Binding regulatory relationships.

The network is established by: significant genes per group, significant genes shared between each pair of tissues, and significant genes shared between 3 tissues and 4 tissues. Examples of two networks are also shown in fig. 8 and 9.

The networks were compared using pathway studio (ariadne genomics) to find proteins from significant genes selected at a 2-fold cut-off that appeared on the network. The results of the comparison may be obtained from a Network analysis folder. A list of proteins present in the physical and regulatory networks in all three tissues is available. The proteins with the greatest connectivity (connectivity) in all networks were EGFR, BCL2, IGF1, CAV1, LEP, IGF1R, ALB, MDM2, IGF2, FOXM1, CALR, PAX6, WT1, and PARP 1. See (Yuryev et al, 2006, BMC Bioinformatics, 7: 171; Daraselia et al, 2007, BMCBioinformatics 8: 243; Sivachenko et al, 2007, J.Bioinformam.Comput.biol.5 (2B): 429-56). Accordingly, this result demonstrates that EGFR, BCL2, IGF1, CAV1, LEP, IGF1R, ALB, MDM2, IGF2, FOXM1, CALR, PAX6, and WT1 are commonly regulated in all four tumor tissues as PARP1 expression is up-regulated in breast, endometrial, ovarian, and lung cancers.

The presence of PARP1 in all networks indicates that PARP1 is an important regulatory target in PARP1 activated tumors and shows the presence of a regulatory network targeted for PARP1 activation. Other proteins in the network may be used as biomarkers for selecting PARP 1-activated tumors for treatment with PARP1 inhibitors, or as targets in PARP1 inhibitor combination therapy.

WT1, FOXM1, CALR and PAX6 are transcription factors that may be responsible for the activation of PARP1 expression regulatory networks. FOXM1 was also found to be significant in the network enrichment analysis below.

The fact that IGF1, IGF2, and IGF1R are present in all networks indicates that PARP 1-activated tumors should be IGF sensitive. There is no consistent correlation between IGF pathway genes and PARP1 for all tissues. The association or lack of association between these two functional modules must be evaluated using a more sensitive technique than microarrays. Currently available data suggest that there is no direct causal relationship between PARP1 and the IGF pathway. It is more likely that they are under the control of a common set of transcription factors, and that the combined action of these factors appears different in different tissue contexts.

Network enrichment analysis: the log ratio between gene expression in low-PARP 1 tumors and PAPR1 overexpressing tumors was calculated as follows: log ratios between mean expression values in samples differentially expressed by PARP1 were calculated. The log-ratio obtained by this calculation was input to a Path Studio Enterprise for network enrichment analysis algorithm (Sivachenko et al, 2007, J.Bioinform.Compout.biol.5 (2B): 429-56), using the "Find significant regulators (Find significant regulators)" command. The first 500 significant regulators in the Expression or Promoter binding networks (Expression or Promoter binding networks) are available for each tissue. WT1 was found to be a significant regulator in the Promoter Binding network (Promoter Binding network) in all three tissues, and FOXM1 was found to be a significant regulator in the Expression network (Expression network) in all three tissues.

Example 6

To further investigate the correlation of co-regulated genes and PARP upregulation in tumors, IGF1R, IGF2, EGFR, TYMS, DHFR, VEGF, MMP9, VEGFR2, IRAK1, ERBB3, AURKA, BCL2, UBE2S mRNA levels were measured and compared to expression levels in normal tissues (as described above). The results are shown in tables XIX to XXXI below.

Materials and methods

Tissue sample: normal and cancer tissue samples were collected in the united states or uk. Samples were collected as part of a normal surgical procedure and snap frozen within 30 minutes of resection. The samples were transported at-80 ℃ and stored in the vapor phase of liquid nitrogen at-170 to-196 ℃ until processing. The samples to be analyzed are subjected to a medical pathology examination and validation. In conjunction with the initial diagnostic report, H & E-stained slides from adjacent sections of tissue were observed and samples were classified by diagnostic category. During the examination of the slides by the pathologist, the visually estimated percentage of tissue implicated by the tumor was recorded and the fraction of malignant nucleated cells was indicated. Auxiliary studies such as ER/PR and Her-2/neu expression studies are performed by methods including immunohistochemistry and fluorescence in situ hybridization. These results, along with accompanying pathological and clinical data, are annotated in the sample catalog and management databases (Ascenta, Bioexpress databases; GeneLogic, Gaithersburg, Md.).

RNA extraction, quality control and expression profiling: RNA was extracted from the samples as follows: according to the manufacturer's recommendations atReagent (Invitrogen, Carlsbad, CA) followed by isolation using RNeasy kit (Qiagen, Valencia, CA). RNA quality and integrity (28 s/18s ratio and RNA integrity values obtained with an Agilent 2100 Bioanalyzer), purity (by the ratio of absorbance at A260/A280), and quantity (by absorbance at A260 or alternative tests) were evaluated. Gene expression levels were assessed using Affymetrix Human Genome U133A and BGeneChips (45,000 probe sets representing more than 39000 transcripts from approximately 33000 well-documented genes). 2. mu.g (2. mu.g) of total RNA was collected and used for Superscript II^TM(Invitrogen, Carlsbad, Calif.) and T7 oligo dT primer (for cDNA Synthesis) and AffymetrixIVT Labeling Kit (Affymetrix, Santa Clara, Calif.) prepared cRNA. UV absorption was used to assess the amount and purity of the cRNA synthesis product. The quality of cRNA synthesis was assessed using an agilent bioanalyzer or MOPS agarose gel. The labeled cRNA was then fragmented and 10. mu.g was used for hybridization at 45 ℃ for 16-24 hours for each array. The arrays were washed, stained according to the manufacturer's recommendations, and scanned on Affymetrix GeneChip Scanners. Array data quality was evaluated using proprietary high throughput applications that evaluated the data using a number of objective criteria, including 5 '/3' GAPDH ratio, signal/noise ratio, background, and other indicators that must be incorporated into the analysis by the back (e.g., outliers, vertical variation). The GeneChip Analysis was performed using Microarray Analysis Suiterations 5.0, Data Mining Tool 2.0, and Microarray database software (www.affymetrix.com). All genes present on the GeneChip were globally normalized (globallel normalized) and scaled to a signal intensity of 100.

Quality comparison: RNA was evaluated for quality and integrity (28 s/18s ratio and RNA Integrity Number (RIN) obtained with an Agilent 2100 Bioanalyzer), purity (by the ratio of absorbance at A260/A280), and quantity (by absorbance at A260 or alternative tests (i.e., ribogreen)). UV absorption was used to assess the amount and purity of cRNA synthesis product. The quality of the cRNA synthesis was evaluated using Agilent Bioanalyzer or MOPS agarose gels. Array quality was assessed using proprietary high throughput applications that evaluated data using several strict objective criteria, such as 5 '/3' GAPDH ratio, signal/noise ratio, background, and other over thirty additional indicators (e.g., outliers, vertical variation). The data generated in the whole process is controlled in a quality system to ensure the integrity of the data.

Example 8

Cytotoxicity studies: to investigate the therapeutic role of PARP and co-regulated gene regulators in cancer growth and progression, cytotoxicity studies can be performed.

Different types of cancer cell lines or primary cells from different sources can be spotted onto 48 or 96 well plates. The cells may be cultured in a suitable medium. The culture can be incubated at 37 deg.C in 95% O ₂/5％CO₂Is maintained in a humid atmosphere. After spotting the plates (24 hours), the medium was removed and replaced with medium in the presence of different concentrations of: PARP1 with IGF1R and/or EGFR inhibitors, e.g. Compound III with Small molecule IGF1R kinase inhibitors NVP-AEW541 and/or erbitux(A monoclonal antibody against EGFR). Cell Viability was measured after 6 days of culture at 37 ℃ using Cell Titer-Blue, Cell Viability Assay (Promega) (see O' Brien et al, 2000, Eur. J. biochem., 267: 5421-5426; Gonzalez and Tarloff, 2001). The test incorporates a fluorescent/colorimetric growth indicator, which is detected based on a reduction in vital dye. Cytotoxicity was measured as growth inhibition.

Cytotoxicity can also be assessed by counting the number of surviving cells. The cells were harvested by washing the monolayers with PBS followed by brief incubation in 0.25% trypsin and 0.02% EDTA. Cells were then harvested, washed twice by centrifugation and resuspended in PBS. The cell number and viability were then determined by staining a small cell suspension with 0.2% trypan blue saline solution and measuring the cells in a hemocytometer. Cell number and viability can be assessed by staining cells with annexin-FITC or/and with propidium iodide and analyzing by flow cytometry.

Example 9

Cell proliferation study: to investigate the role of PARP and co-regulated gene regulators in the treatment of cancer growth and progression, cell proliferation studies can be performed.

The cultured cells can be cultured in the presence of various concentrations of a test substance, such as compound III and the small molecule IGF1R kinase inhibitor NVP-AEW541 and/or erbitux(A monoclonal antibody against EGFR). The cultured cells were spotted in a black 96-well Multiplate (tissue culture grade; clear flat bottom) at 37 ℃ in a moist atmosphere to a final volume of 100 ul/well. To the cells, 10 ul/well of BrdU labeling solution (final concentration of BrdU: 10uM) was added, and the cells were further cultured at 37 ℃ for another 2-25 hours. MP was centrifuged at 300Xg for 10 min and the labeled medium was removed by aspiration using a catheter. Cells were dried using a hair dryer for about 15 minutes, or at 60 ℃ for 1 hour. 200 ul/well of FixDenat was added to the cells and incubated at 15-25 ℃ for 30 minutes. The FixDenat solution was completely removed by flicking and tapping. 100 ul/well of Anti-BrdU-POD working solution was added and incubated at 15-25 ℃ for about 90 minutes. The antibody conjugate was removed by flicking and the wells were rinsed three times with 200-300 ul/well wash solution. The wash solution was removed by flicking. Then 100 ul/well substrate solution was added to each well. The light emission of the sample can be measured using a microplate photometric plate with a photomultiplier tube.

Example 10

The role of PARP and co-regulated gene regulators in the treatment of cancer growth and progression can be measured using a xenograft cancer model.

For example, it has been revealed in the human ovarian adenocarcinoma OVCAR-3 xenograft model that the inhibitory effect of compound III on PARP1 inhibits tumor growth and improves survival in mice. See fig. 18. Furthermore, ovarian adenocarcinoma OVCAR-3 cells produce IGF-I and IGF-II and express IGF1R, evidence that supports the presence of autocrine loops. Previous studies have shown that treatment with NVP-AEW541, a small molecular weight inhibitor of IGF-IR kinase, inhibits the growth of OVCAR-3 tumors (Gotlieb et al, 2006, Gynecol Oncol.100 (2): 389-96). Importantly, neither treatment with compound III nor NVP-AEW541 completely inhibited tumor growth. Accordingly, it is expected from this data that the combination of a PARP inhibitor (e.g., compound III) and an IGF1R inhibitor (e.g., NVP-AEW541) can further inhibit tumor growth.

Example 11

The effect of PARP1 and IGF1 receptor inhibitors in combination with chemotherapeutic agents in the treatment of IDC breast cancer can be determined.

A multicenter, open label, randomized study will be performed to demonstrate the therapeutic effectiveness of treatment of PARP1 inhibitor (compound III), IGF1R (NVP-AEW541) inhibitor, and chemotherapeutic agents (e.g., gemcitabine, carboplatin, cisplatin) for IDC breast cancer. The therapeutic efficacy of the combination therapy will be compared to the therapeutic efficacy of the chemotherapeutic agent alone.

Research and design: open 2-group randomized safety and efficacy study, in which up to 90 patients, 45 in each group, were randomized as follows: study group 1: chemotherapeutic agent alone, e.g. gemcitabine (1000 mg/m)²(ii) a 30 minutes, IV infusion) or carboplatin (AUC 2; 60 minutes, IV infusion), administered on days 1 and 8 of a 21 day cycle; or study group 2: chemotherapeutic Agents + IGF1R and PARP 1 inhibitors, e.g. Gemcitabine (1000 mg/m)²(ii) a 30 minutes, IV infusion) or carboplatin (AUC 2; 60 minutes, IV infusion), on days 1 and 8 of a 21-day cycle, and compound III (4mg/kg 1 hour, IV infusion) and NVP-AEW541(25 mg/kg; bid).

Evaluation: tumors are evaluated by standard methods (e.g., CT) at baseline and then every 6-8 weeks (in the absence of clinically significant disease progression).

Example 12

The effect of compound III and its nitroso metabolites in combination with a second agent on the cell cycle was determined in cancer cell lines.

Compound III and compound III-1 compounds were tested in the presence of a second reagent according to the protocol shown in the table below.

Reagent	Compound III	Cell lines
			IGF1R inhibitors	+/-	MDA-MB-468
EGFR inhibitors	+/-	HCC827

Materials and methods

Cell culture: triple negative (triple negative) MDA-MB-468 human breast cancer, U251 human glioblastoma, and lung adenocarcinoma HCC827 cells were cultured in Dulbecco Modified Eagle Medium (containing 10% fetal bovine serum). The cells were treated with 10⁵[ solution ]/P100 or 10⁴Seeding Density of/P60 in growth Medium and at 37 ℃ with 5% CO₂Culturing for 12-18 hours. Compound was added in a single dose with (or without) a second reagent (see table 1) over 72 hours. DMSO was used as a control. After treatment, cells were analyzed using BrdUELISA assay (Roche Applied Science), FACS-based cell cycle assay or TUNEL.

A compound: compound III was used for each independent experiment directly from dry powder dissolved in DMSO (cat #472301, Sigma-Aldrich) and then working concentrations of 111nM, 313nM and 1 μ M in cell culture medium were prepared using the entire volume of stock solution to avoid any possible precipitation and corresponding loss of compound. Control experiments were performed using vehicle (DMSO) at matched volumes/concentrations; in these controls, the growth or cell cycle distribution of the cells showed no change.

PI excretion, cell cycle and TUNEL assay (FACS): after drug addition and incubation, cells were removed for counting and PI (propidium iodide) drainage tests. An aliquot of the cells was centrifuged and resuspended in 0.5ml ice-cold PBS (containing 5. mu.g/ml PI). Another portion of the cells was fixed in ice cold 70% ethanol and stored in the refrigerator overnight. For cell cycle analysis, cells were stained with Propidium Iodide (PI) using standard methods. Cellular DNA content was determined by flow cytometry using BD LSRII FACS and the percentage of cells in the G1, S or G2/M phase was determined using ModFit software.

To detect apoptosis, cells were labeled using the "In Situ Cell Death Detection Kit, Fluoroescein" (Roche diagnostics Corporation, Roche Applied Science, Indianapolis, Ind.). Briefly, the fixed cells were centrifuged and washed once in phosphate-buffered saline (PBS) containing 1% Bovine Serum Albumin (BSA), then resuspended in 2ml of permeabilization buffer (0.1% Triton X-100 and 0.1% sodium citrate in PBS) for 25 minutes at room temperature and washed twice in 0.2ml PBS/1% BSA. The cells were resuspended in 50. mu.l of TUNEL reaction mix (TdT enzyme and labeling solution) and incubated in an incubator at 37 ℃ in a humidified dark atmosphere for 60 minutes. The labeled cells were washed once in PBS/1% BSA and resuspended in 0.5ml ice-cold PBS containing 1. mu.g/ml 4', 6-diamidino-2-phenylindole (DAPI)) for at least 30 minutes. All cell samples were analyzed using BD LSRII (BD Biosciences, San Jose, CA). All flow cytometry analyses were performed using triplicate samples (each containing at least 30,000 cells) (shown as typical results for independent experiments). The coefficient of variation was equal to or less than 0.01 in all experiments.

Bromodeoxyuridine (BrdU) labeling assay and FACS-based cell cycle analysis: 50 μ l of BrdU (Sigma Chemical Co., St. Louis, Mo.) stock solution (1mM) was added to give a final concentration of 10 μ M BrdU. The cells were then incubated at 37 ℃ for 30 minutes, fixed in ice-cold 70% ethanol and stored at 4 ℃ overnight. The fixed cells were centrifuged and washed once in 2ml PBS, then resuspended in 0.7ml denaturing solution (0.2mg/ml pepsin in 2N HCl), at 37 ℃ in the dark for 15 minutes, then 1.04ml 1M Tris buffer (Trizma base, Sigma chemical Co.) was added to stop the hydrolysis. Cells were washed in 2ml PBS and resuspended in 100- μ l (1: 100 dilution) TBFP permeation buffer (PBS containing 0.5% Tween-20, 1% bovine serum albumin and 1% fetal bovine serum) containing anti-BrdU antibody (DakoCytomation, Carpinteria, Calif.), incubated in the dark at room temperature for 25 minutes and washed in 2ml PBS. Primary anti-labeled cells were resuspended in 100. mu.l of ALEXA-containing cells Goat anti-mouse IgG (H + L) F (ab')₂Fragments (1: 200 dilution, 2mg/mL, Molecular Probes, Eugene, OR) in TBFP buffer and incubated in the dark at room temperature for 25 minutes, washed in 2mL PBS and resuspended in 0.5mL ice-cold PBS containing 1. mu.g/mL 4', 6-diamidino-2-phenylindole (DAPI) for at least 30 minutes. All cellsSamples were analyzed using BD LSR II (BD Biosciences, San Jose, CA). All flow cytometry analyses were performed using triplicate samples (containing at least 30,000 cells per duplicate) (shown as typical results for independent experiments). The coefficient of variation was equal to or less than 0.01 in all experiments.

Results

Compounds were dissolved in 100% DMSO as 10mM stock solutions at the start of the experiment.

The MDA-MB-468 human breast cancer cells and the lung cancer adenocarcinoma cell line HCC827 cells were tested for suitability for FACS-based cell cycle analysis.

FACS analysis based on DNA content and BrdU assay

Based on preliminary results of proliferation and survival assays, two different dose concentrations of compound III were selected.

The effect of the active dose combination on cell survival, cell cycle distribution and BrdU incorporation was tested by FACS analysis.

Concentration confirmation and stability. Triplicate cell samples were taken within 5 and 15 minutes post-dose, collected by centrifugation, washed with PBS, and stored at-70 ℃. The samples were transported to the host-specified unit for further analysis (Alta Analytical Laboratory).

Representative results are shown in the following table and in fig. 19.

Response of triple negative breast cancer cells MDA-MB-468 to Compound III in combination with IGF-R inhibitor Podophyllotoxin (PPP)

	Sub-G1	G1	S	G2/M	TUNEL(+)	BrdU(-)S	Living cell
								PPP 0nM+201uM
0	0.81	50.96	30.37	16.04	0.7	1.82	100
								50	1.01	50.20	31.34	15.21	0.9	2.23	82
100	1.12	40.63	34.52	20.16	1.6	3.56	61
								PPP 200nM+201uM
0	1.22	51.42	30.22	15.01	0.9	2.13	89
								50	1.32	49.75	31.41	15.10	2.7	2.43	77
100	1.63	37.51	35.58	21.30	2.1	3.98	59
								PPP 400nM+201uM
0	7.77	37.29	25.32	20.17	4.1	9.45	60
								50	7.25	32.88	28.47	22.37	4.2	9.03	42
100	5.93	23.62	31.78	29.98	6.9	8.69	32

In HCC827 cell line, Compound III was shown to potentiate EGF-R inhibitor(see FIGS. 19A and 19B).

HCC827 non-small cell lung cancer (NSCLC) cell line has been established and used as a model for EGFR inhibitor analysis. See also fig. 20.

Lung cancer cell HCC827 and Compound IIIThe responses of the combinations of (a) are summarized in the following list:

example 13

To further investigate co-regulatory gene and PARP upregulation in tumors, mRNA levels were measured as described above and compared to expression levels in normal tissues for IGF1, IGF2, IGFR, EGFR, mdm2, Bcl2, ETS1, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK1, VAV3, AURKA, ERBB3, MIF, VEGF, VEGFR2, CDK1, CKD2, CDK9, farnesyltransferase, UBE2A, UBE2D2, UBE2G1, USP28, UBE2S, or combinations thereof.

Materials and methods

Tissue sample: normal and cancer tissue samples were collected in the united states or uk. Samples were collected as part of a normal surgical procedure and snap frozen within 30 minutes of resection. The samples were transported at-80 ℃ and stored in the vapor phase of liquid nitrogen at-170 to-196 ℃ until processing. The samples to be analyzed are subjected to a medical pathology examination and validation. In conjunction with the initial diagnostic report, H & E-stained slides from adjacent sections of tissue were observed and samples were classified by diagnostic category. During the examination of the slides by the pathologist, the visually estimated percentage of tissue implicated by the tumor was recorded and the fraction of malignant nucleated cells was indicated. Auxiliary studies such as ER/PR and Her-2/neu expression studies are performed by methods including immunohistochemistry and fluorescence in situ hybridization. These results, along with accompanying pathological and clinical data, are annotated in the sample catalog and management databases (Ascenta, Bioexpress databases; GeneLogic, Gaithersburg, Md.).

RNA extraction, quality control and expression profiling: RNA was extracted from the samples as follows: according to the systemRecommended by the manufacturer inReagent (Invitrogen, Carlsbad, CA) followed by isolation using RNeasy kit (Qiagen, Valencia, CA). RNA quality and integrity (28 s/18s ratio and RNA integrity values obtained with an Agilent 2100 Bioanalyzer), purity (by the ratio of absorbance at A260/A280), and quantity (by absorbance at A260 or alternative tests) were evaluated. Gene expression levels were assessed using Affymetrix Human Genome U133A and BGeneChips (45,000 probe sets representing more than 39000 transcripts from approximately 33000 well-documented genes). 2. mu.g (2. mu.g) of total RNA was collected and used for Superscript II^TM(Invitrogen, Carlsbad, Calif.) and T7 oligo dT primer (for cDNA Synthesis) and AffymetrixIVT Labeling Kit (Affymetrix, Santa Clara, Calif.) prepared cRNA. UV absorption was used to assess the amount and purity of the cRNA synthesis product. The quality of cRNA synthesis was assessed using an agilent bioanalyzer or MOPS agarose gel. The labeled cRNA was then fragmented and 10. mu.g was used for hybridization at 45 ℃ for 16-24 hours for each array. The arrays were washed, stained according to the manufacturer's recommendations, and scanned on Affymetrix GeneChip Scanners. Array data quality was evaluated using proprietary high throughput applications that evaluated the data using a number of objective criteria, including 5 '/3' GAPDH ratio, signal/noise ratio, background, and other indicators that must be incorporated into the analysis by the back (e.g., outliers, vertical variation). The GeneChip Analysis was performed using Microarray Analysis Suiterations 5.0, Data Mining Tool 2.0, and Microarray database software (www.affymetrix.com). All genes present on the GeneChip were globally normalized (globallel normalized) and scaled to a signal intensity of 100.

Quality comparison: RNA was evaluated for quality and integrity (28 s/18s ratio and RNA Integrity Number (RIN) obtained with an Agilent 2100 Bioanalyzer), purity (by the ratio of absorbance at A260/A280), and quantity (by absorbance at A260 or alternative tests (i.e., ribogreen)). UV absorption was used to assess the amount and purity of the cRNA synthesis product. The quality of the cRNA synthesis was evaluated using Agilent Bioanalyzer or MOPS agarose gels. Array quality was assessed using proprietary high throughput applications that evaluated data using several strict objective criteria, such as 5 '/3' GAPDH ratio, signal/noise ratio, background, and over thirty additional indicators (e.g., outliers, vertical variation). The data generated in the whole process is controlled in a quality system to ensure the data integrity of the data.

PARP1 inhibitors and inhibitors of co-regulated genes can be administered to patients as described in example 11.

Example 14

To further study co-regulated genes and PARP upregulation in breast tumors, mRNA levels were measured as described above for BRCA1, BRCA2, or a combination thereof and compared to expression levels in normal tissues.

Materials and methods

Tissue sample: samples of normal tissue and cancerous breast tissue are collected in the united states or uk. Samples were collected as part of a normal surgical procedure and snap frozen within 30 minutes of resection. The samples were transported at-80 ℃ and stored in the vapor phase of liquid nitrogen at-170 to-196 ℃ until processing. The samples to be analyzed are subjected to a medical pathology examination and validation. In conjunction with the initial diagnostic report, H & E-stained slides from adjacent sections of tissue were observed and samples were classified by diagnostic category. During the examination of the slides by the pathologist, the visually estimated percentage of tissue implicated by the tumor was recorded and the fraction of malignant nucleated cells was indicated. Auxiliary studies such as ER/PR and Her-2/neu expression studies are performed by methods including immunohistochemistry and fluorescence in situ hybridization. These results, along with accompanying pathological and clinical data, are annotated in the sample catalog and management databases (Ascenta, Bioexpress databases; Gene Logic, Gaithersburg, Md.).

RNA extraction, quality control and expression profiling: RNA was extracted from the samples as follows: according to the manufacturer's recommendations atReagent (Invitrogen, Carlsbad, CA) followed by isolation using RNeasy kit (Qiagen, Valencia, CA). RNA quality and integrity (28 s/18s ratio and RNA integrity values obtained with an Agilent 2100 Bioanalyzer), purity (by the ratio of absorbance at A260/A280), and quantity (by absorbance at A260 or alternative tests) were evaluated. Gene expression levels were assessed using Affymetrix Human Genome U133A and BGeneChips (45,000 probe sets representing more than 39000 transcripts from approximately 33000 well-documented genes). 2. mu.g (2. mu.g) of total RNA was collected and used for Superscript II ^TM(Invitrogen, Carlsbad, Calif.) and T7 oligo dT primer (for cDNA Synthesis) and AffymetrixIVT Labeling Kit (Affymetrix, Santa Clara, Calif.) prepared cRNA. UV absorption was used to assess the amount and purity of the cRNA synthesis product. The quality of cRNA synthesis was evaluated using an agilent bioanalyzer or MOPS agarose gel. The labeled cRNA was then fragmented and 10. mu.g was used for hybridization at 45 ℃ for 16-24 hours for each array. The arrays were washed, stained according to the manufacturer's recommendations, and scanned on Affymetrix GeneChip Scanners. Array data quality was evaluated using proprietary high throughput applications that evaluated the data using a number of objective criteria, including 5 '/3' GAPDH ratio, signal/noise ratio, background, and other additional indicators that must be incorporated into the analysis by the back (e.g., outliers, vertical variation). The GeneChip analysis was performed using Microarray analysis suite version 5.0, Data Mining Tool 2.0, and Microarray database software (www.affymetrix.com). All genes present on the GeneChip were globally normalized (globallel normalized) and scaled to a signal intensity of 100.

Quality comparison: RNA was evaluated for quality and integrity (28 s/18s ratio and RNA Integrity Number (RIN) by Agilent 2100 Bioanalyzer), purity (by the ratio of absorbance at A260/A280), and quantity (by absorbance at A260 or alternative tests (i.e., ribogreen)). UV absorption was used to assess the amount and purity of the cRNA synthesis product. The quality of the cRNA synthesis was evaluated using Agilent Bioanalyzer or MOPS agarose gels. Array quality was assessed using proprietary high throughput applications that evaluated data using several strict objective criteria, such as 5 '/3' GAPDH ratio, signal/noise ratio, background, and over thirty additional indicators (e.g., outliers, vertical variation). The data generated in the whole process is controlled in a quality system to ensure the data integrity of the data.

BRCA1, BRCA2, and PARP levels were determined and evaluated in normal as well as cancerous breast tissues.

PARP1 inhibitors and inhibitors of co-regulated genes may be administered as in example 11.

While embodiments of the present invention have been shown and described herein, it will be obvious to those skilled in the art that such embodiments are provided by way of example only. Numerous variations, modifications, and alternatives will occur to those skilled in the art without departing from the embodiments described herein. It should be understood that various alternatives to the embodiments of the invention described herein may be employed in practicing the invention. It is intended that the following claims define the scope of the invention. Methods and structures within the scope of these claims and equivalents thereof are also intended to be encompassed by this scope.

Claims (122)

1. A method of identifying a treatment for a PARP mediated disease, said method comprising identifying in a plurality of samples from a population of patients the expression level of a panel of identified genes comprising at least PARP, and making a decision regarding treatment of said PARP mediated disease, wherein the treatment decision is made based on the expression level of at least one identified gene in the panel.

2. The method of claim 1 wherein the set of genes comprises genes expressed in the PARP, IGF1 receptor, or EGFR pathway.

3. The method of claim 1, wherein said set of genes comprises IGF, IGFR, EGFR, mdm, Bcl, ETS, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK, VAV, AURKA, ERBB, MIF, VEGF, VEGFR, CDK, farnesyltransferase, UBE2, ABCC, ABCD, ACADM, ACLSL, ACSL, ACY1L, ADM, ADRM, AGPAT, AHCY, AK3L, AKIIP, AKR1C, ALDH18A, ALDOA, ALPL, ANP32, ACF, APG5, ARFGEF, ARL, ARPP-19, ASF, ATF, ATC, BACE 7, ATP1A, ALDH18A, ALDOA, ALCD, ALOX, ALPL, ACAT, ATP5, ATP5, ATP B, CDC, ATP-5, CDK, ACAT, CDK, ACAT, ACK, ACAT, ACK-1L, ACK-1C, ACK-1, ACK, CDK, AC, CHST6, CHSY1, CKLFSF4, CKLFSF6, CKS1B, CMKOR1, CNDP 1, CPD, CPE, CPSF 1, CPT 11, CRR 1, CSH 1, CSK, CSNK 21, CSPG 1, CTPSCTSB, CTSD, CXADR, CXCR 1, CXXC 1, DAXC 1, DCK, DDAH1, DDIT 1, DDX 1, DHTKD1, DLAT, DNAJA1, DNJB 1, DNJC 1, HSPDNADN 1, HSP 1, HSPFANGGFAGN 1, HSPGFAGN 1, HSPGFAGFLAGN 1, HSPGFAGFLAGFLEXP 1, HSPGFAGGFAGFLX 1, HSPGFAGFLX 1, HSPGFAGGFAGFLX 1, HSPGFAGGFAG3672, HSPGFAGGFAGGFAGGFDG 1, HSPGFAGGFAGGFAGGFAGGFAGGF3672, 1, HSPGFAGGFAGGFDG 1, HSPGFAGGFAGGFAGGFDG 1, HSPGF3672, 1, HSPGFAGGFAGGFAGGFAGGFAGGF3672, 1, HSPGFAGGFAGGFAGGFAGGF3672, 1, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGF3672, 1, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGF3672, 1, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGF3672, 1, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG 1, HSPGFAGGFAGGF3672, 1, HSPGFAGGFAGGFAGGFAGGFAGGF3672, HSPGF3672, 1, HSPGFAGGFAGGFAGGFAGGFAGGF3672, 1, HSPGF, MAD2L1, MADP-1, MAGED1, MAKK 1, MALAT1, MAP2K 1, MAP3K1, MAP4K 1, MAPK1, MARCKS, MBTPS 1, MCM 1, MCTS1, MDH1, ME1, METAP 1, METTL 1, MGAT 41, MKNK 1, MLPH, MOBK 11, MOBKL KL 11, MSH 1, MTHFD 1, MUC1, MX1, MYCBP, NAJD1, NAT1, NBS1, NDFIP 1, NEK 1, NET1, NMP 1, NNT, NQO1, NRAS, NSE 1, PSVPPAR 1, PSVPPARP 1, PSPMSPP 1, PSPCP 1, PSMP 1, PSPCP 1, PSNFCP 1, PSNPPDN 1, PSRPP 1, PSNPPDN 1, PSPDN 1, PSNPPDN 1, PSP 1, PSNPPDN 1, PSP 1, PSPDN 1, PSNPPDN 1, PSPDN 1, PSNPPDN 1, PSP 1, PSNPPDN 1, PSP 1, PSNPPDN 1, PSP 36, RNASEH2, RNGTT, RNPEP, ROBO 1, RRAS, SART, SAT, SCAP, SCD, SDC, SEMA3, SERPINE, SFI, SGPL, SGPP, SH3GLB, SHC, SMARCC, SMC4L, SMS, SNRPD, SORD, SORL, SPP, SQLE, SRD5A2, SRM, SRPK, SS, SSBP, SSR, ST3GAL, ST6GALNAC, STX, SULF, SWAP, TA-KRP, TALA, TBL1XR, TFRC, TIAM, TKT, TMPO, TNFAIP, TNFSF, TOX, TPD, TPI, TPAE, TRA, TRIP, TRPS, TSPAN, TSNL, NL, NRAP 2, WHAP 2, WH 2, TXDH, UBC, UBAC 14, UBV, UBAC, USP, UBS, USP, UB 5, USP, or a combination thereof.

4. The method of claim 1, wherein the panel of genes comprises PARP, IGF1, IGF2, IGFR, EGFR, mdm2, Bcl2, ETS1, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK1, VAV3, AURKA, ERBB3, MIF, VEGF, VEGFR2, CDK1, CDK2, CDK9, farnesyl transferase, UBE2S, or a combination thereof.

5. The method of claim 1, wherein expression is measured in said panel.

6. The method of claim 5, wherein expression is measured using a polymerase chain reaction assay.

7. The method of claim 1, wherein the plurality of samples are selected from the group consisting of human normal samples, tumor samples, hair, blood, cells, tissues, organs, brain tissue, blood, serum, sputum, saliva, plasma, nipple aspirate, synovial fluid, cerebrospinal fluid, sweat, urine, fecal matter, pancreatic fluid, trabecular fluid, cerebrospinal fluid, tears, bronchial lavage, swabs, bronchial aspirate, semen, prostatic fluid, pre-cervical fluid, vaginal fluid, and pre-ejaculate.

8. The method of claim 1 wherein the level of PARP is up-regulated and the treatment decision is a decision to treat said disease with a PARP inhibitor and an inhibitor of at least one up-regulated gene in said group.

9. The method of claim 1, wherein said treatment is determined to treat said disease with an inhibitor of each gene in said group that shows upregulation of expression, including PARP upregulation.

10. The method of claim 9, wherein said PARP inhibitor is selected from the group consisting of benzamide, quinolone, isoquinolone, benzopyrone, cyclic benzamide, benzimidazole, indole, and pharmaceutically salts, solvates, isomers, tautomers, metabolites, analogs, or prodrugs thereof.

11. The method of claim 10, wherein said PARP inhibitor is 4-iodo-3-nitrobenzamide or a metabolite thereof.

12. The method of claim 1, wherein the method further comprises providing a conclusion regarding the disease to a patient, a healthcare provider, or a healthcare manager, wherein the conclusion is based on the decision.

13. The method of claim 1, wherein the treatment is selected from the group consisting of oral administration, transmucosal administration, buccal administration, nasal administration, inhalation, parenteral administration, intravenous administration, subcutaneous administration, intramuscular administration, sublingual administration, transdermal administration, and rectal administration.

14. The method of claim 1 wherein said PARP mediated disease is selected from the group consisting of cancer, inflammation, metabolic disease, CVS disease, CNS disease, lymphohematopoietic disease, endocrine and neuroendocrine disease, viral infection, urinary tract disease, respiratory disease, female reproductive disease and male reproductive disease.

15. The method of claim 14, wherein the cancer is selected from the group consisting of colon adenocarcinoma, esophageal adenocarcinoma, hepatocellular carcinoma, squamous cell carcinoma, pancreatic adenocarcinoma, islet cell tumor, rectal adenocarcinoma, gastrointestinal stromal tumor, gastric adenocarcinoma, adrenal cortical cell carcinoma, follicular carcinoma, papillary carcinoma, breast cancer, ductal carcinoma, lobular carcinoma, intraductal carcinoma, mucinous carcinoma, phyllodes tumor, ewing's sarcoma, ovarian adenocarcinoma, endometrial adenocarcinoma, granulosa cell tumor, mucinous cystadenocarcinoma, cervical adenocarcinoma, vulval squamous cell carcinoma, basal cell carcinoma, prostate adenocarcinoma, giant cell tumor of bone, osteosarcoma, laryngeal carcinoma tumor, lung adenocarcinoma, kidney carcinoma, bladder carcinoma, wilms' tumor, and lymphoma.

16. The method of claim 14, wherein said inflammation is selected from the group consisting of non-hodgkin's lymphoma, wegener's granulomatosis, hashimoto's thyroiditis, hepatocellular carcinoma, chronic pancreatitis, rheumatoid arthritis, reactive lymphoid hyperplasia, osteoarthritis, ulcerative colitis, and papillary carcinoma.

17. The method of claim 14, wherein the metabolic disease is diabetes or obesity.

18. The method of claim 14 wherein the CVS disease is selected from the group consisting of atherosclerosis, coronary artery disease, granulomatous myocarditis, chronic myocarditis, myocardial infarction, and primary hypertrophic cardiomyopathy.

19. The method of claim 14 wherein said CNS disorder is selected from the group consisting of alzheimer's disease, cocaine abuse, schizophrenia and parkinson's disease.

20. The method of claim 14, wherein said lymphohematopoietic disease is selected from the group consisting of non-hodgkin's lymphoma, chronic lymphocytic leukemia, and reactive lymphoid hyperplasia.

21. The method of claim 14, wherein the endocrine and neuroendocrine disorders are selected from nodular hyperplasia, hashimoto's thyroiditis, islet cell tumor of pancreas, and papillary carcinoma.

22. The method of claim 14, wherein the urinary tract disorder is selected from the group consisting of renal cell carcinoma, transitional cell carcinoma, and wilms' tumor.

23. The method of claim 14, wherein the respiratory disease is selected from the group consisting of adenosquamous carcinoma, squamous cell carcinoma, and large cell carcinoma.

24. The method of claim 14, wherein the female reproductive system disorder is selected from the group consisting of adenocarcinoma, leiomyoma, mucinous cystadenocarcinoma, and serous cystadenocarcinoma.

25. The method of claim 14, wherein the male reproductive system disease is selected from the group consisting of prostate cancer, benign nodular hyperplasia, and seminoma.

26. The method of claim 14, wherein said viral infection is selected from the group consisting of HIV infection, hepatitis b virus infection, and hepatitis c virus infection.

27. A method of identifying a gene useful in treating a patient having a disease susceptible to treatment with a PARP inhibitor, comprising:

a. identifying a disease treatable with at least one PARP modulator, wherein the expression level of PARP is modulated in a plurality of samples from a patient population as compared to a control sample;

b. determining the expression level of a set of genes in a plurality of samples; and

c. identifying a gene that is co-regulated with said PARP regulation, wherein the expression level of said co-regulated gene is increased or decreased in a plurality of samples as compared to a control sample;

wherein modulation of said gene that is co-modulated with PARP modulation is useful in treating diseases susceptible to PARP modulator treatment.

28. The method of claim 27, wherein said co-regulated genes comprise genes expressed in the PARP, IGF1 receptor, or EGFR pathway.

29. The method of claim 27 wherein said PARP modulator is a PARP inhibitor.

30. The method of claim 29, wherein said PARP inhibitor is selected from the group consisting of benzamide, quinolone, isoquinolone, benzopyrone, cyclic benzamide, benzimidazole, indole, and pharmaceutically salts, solvates, isomers, tautomers, metabolites, analogs, or prodrugs thereof.

31. The method of claim 27, wherein said co-regulated gene comprises IGF, IGFR, EGFR, mdm, Bcl, ETS, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK, VAV, AURKA, ERBB, MIF, VEGF, VEGFR, CDK, farnesyltransferase, UBE2, ABCC, ABCD, ACADM, ACLSL, ACY1L, ADM, ADRM, AGPAT, AHCY, AK3L, AKIIP, AKR1B, AKR1C, ALDH18A, ALDOA, ALOX, ALPL, ANP32, ANF, APG5, FGEF, ARL-19, ARPH, ASF, ATF7, ATP, ATC, ATP1A, ATP 5A, ATP5, ATP, CDC, ATP5, CDC, ATP, CDC, ATP-1B, CDC, ATP, CDC, ATP, CDK, CDC, ATP5, CDK, CDC, ATP, CDK, CDC, ABC, CDC, CDK, ABC, ACY, ACOCK, ACOX, CDC, CDK, ACAD 1L, CDC, CD, CHST6, CHSY1, CKLFSF4, CKLFSF6, CKS1B, CMKOR B, CNDP B, CPD, CPE, CPSF B, CPT1B, CRR B, CSH B, CSK, CSNK2A B, CSPG B, CTPSCTSB, CTSD, CXADR, CXCR B, CXXC B, DAXC B, DCK, DDAH B, DDIT B, DDX B, DHTKD B, DLAT, DNAJA B, DNJB B, DNJC B, HSPDNADN B, HSPFALG B, HSPGFAGN B, HSPGFAGGFAGN B, HSPGFAGFLAGFLEXP B, HSPGFAGFLX B, HSPGFAGGFAGGFAGFLX B, HSPGFAGGFAGFLD B, HSPGFAGFLD B, HSPGFAG3672, HSPGFAGFLXC B, HSPGFAGFLX B, HSPGFAGGFAGGFAG3672, B, HSPGFAGGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGFAGGFDG B, HSPGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGF3672, B, HSPGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGFDG B, HSPGFAGGFX B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFX B, HSPGFDG B, HSPGFX B, HSPGFAGGFAGGF3672, HSPGFX B, HSPGFAGGFAGGFAGGFAGGF3672, HSPGFX B, HSPGFAGGFAGGFAGGF, MADP-1, MAGED1, MAK3, MALAT 3, MAP2K3, MAP3K 3, MAP4K 3, MAPK 3, MARCKS, MBTPS 3, MCM 3, MDH 3, ME 3, METAP 3, METTL 3, MGAT4 3, MKNK 3, MLPH, MOBKL 13, MSH 3, MTHFD 3, MUC 3, MX 3, MYCBP, NAJD 3, NAT 3, NBS 3, NDP 3, NEK 3, QO 3, NMP 3, NNT 3, NNFP 3, NRAS, NSE 3, PGS 36SAP 3, PSPMSPP 3, PSWPP 3, PSMP 3, PSNPPEPCP 3, PSNPPEPTCP 3, PSNPCP 3, PSNPPEPTCP 3, PSP 3, PSCP 3, PSP 3, PSNPPEPTCP 3, PSP 3, PSNPPEPTCP 3, PSPEPTCP 3, PSP 3, PS, RNGTT, RNPEP, ROBO, RRAS, SART, SAT, SCAP, SCD, SDC, SEMA3, SERPINE, SFI, SGPL, SGPP, SH3GLB, SHC, SMARCC, SMC4L, SMS, SNRPD, SORD, SORL, SPP, SQLE, SRD5A2, SRM, SRPK, SS, SSBP, SSR, ST3GAL, ST6 GALNC, STX, SULF, SWAP, TA-KRP, TALA, TBL1XR, TFRC, TIAM, TKT, TMPO, TNFAIP, TNFSF, TOX, TPD, TPI, TPP, TRA, TRIP, TRPS, TSPAN, TSTA, TXN, NL, NRD, UBAP2, WHE 2, TXDH, WUBV, WUBC, YUBV, USP, YUBA, USP, YUBA, USP, TXN, or a combination thereof.

32. The method of claim 27, wherein said co-regulated gene comprises IGF1, IGF2, IGFR, EGFR, mdm2, Bcl2, ETS1, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK1, VAV3, aua, ERBB3, MIF, VEGF, VEGFR2, CDK1, CDK2, CDK9, farnesyl transferase, UBE2S, or a combination thereof.

33. The method of claim 27, wherein the mRNA level of each co-regulated gene is measured.

34. The method of claim 33, wherein the mRNA level is measured using a polymerase chain reaction assay.

35. The method of claim 27, wherein the tissue sample is selected from the group consisting of a tumor sample, hair, blood, cells, tissue, organ, brain tissue, blood, serum, sputum, saliva, plasma, nipple aspirate, synovial fluid, cerebrospinal fluid, sweat, urine, fecal matter, pancreatic fluid, trabecular fluid, cerebrospinal fluid, tears, bronchial lavage, swabbing, bronchial aspirate, semen, prostatic fluid, pre-cervical fluid, vaginal fluid, and pre-ejaculate.

36. The method of claim 27, wherein the disease is breast cancer, lung cancer, endometrial cancer, or ovarian cancer.

37. The method of claim 36, wherein the breast cancer is triple negative breast cancer.

38. A method of treating a patient having a disease susceptible to treatment with a PARP modulator, the method comprising:

a. identifying a disease treatable with at least one PARP modulator, wherein the expression level of PARP in a sample from a patient having said disease is modulated compared to a reference sample;

b. identifying at least one co-regulated gene in the sample as compared to a reference sample;

c. treating said patient with PARP and a modulator of the co-regulated gene.

39. The method of claim 38, wherein said co-regulated genes comprise genes expressed in the PARP, IGF1 receptor, or EGFR pathway.

40. The method of claim 38, wherein said co-regulated gene is IGF, IGFR, EGFR, mdm, Bcl, ETS, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK, VAV, AURKA, ERBB, MIF, VEGF, VEGFR, UBE2, CDK, farnesyltransferase, ABCC, ABCD, ACADM, ACLSL, ACSL, ACY1L, ADM, ADRM, AGPAT, AHCY, AK3L, AKIIP, AKR1B, AKR1C, ALDH18A, ALDOA, ALOX, ALPL, ANP32, ANF, APG5, FGEF, ARL-19, PH, ASF, ATF7, ATCA 1C, ATP11A, ATP1B, ATP, CAOB 5, CDC, ATP, CDC, CDB, ATP, CDK, CDC, ATP, CDB, ATP, CDK, ABC, ATP, CDC, ATP, CDK, ABC, CDC, ATP, CDK, CDC, ABC, CDC, CDK, ACAD 1L, ACAD 3L, CDC, CDK, CDC, AGPAT, CGI-3690, CHST6, CHSY1, CKLFSF4, CKLFSF6, CKS1B, CMKOR1, CNDP2, CPD, CPE, CPSF 2, CPT 12, CRR 2, CSH2, CSK, CSNK2A 2, CSPG2, CTPSCTSB, CTSD, CXADR, CXCR 2, CXXC 2, DAAM 2, DCK, DDAH 2, DDIT 2, DDR 36FADD 2, DDX2, DHTKD 2, DLAT, DNAJD 2, DNJB 2, HSPDNJC 2, DNADN 36JC 36XC 2, GGDND 2, HSP GFAGGFAGGFAGGFAGGFAGGFAGN 2, HSP 2, HSP 2, LTB4DH, LYN, MAD2L1, MADP-1, MAGED1, MAKK 1, MALAT1, MAP2K 1, MAP3K1, MAP4K 1, MAPK1, MARCKS, MBTPS 1, MCM 1, MCTS1, MDH1, ME1, METAP 1, METTL 1, MGAT 41, MKNK 1, MLPH, MOBK 11, MOBKL KL1, MSH 1, MTHFD 1, PSC 1, MX1, MYCBP, NAJD1, NBS1, NDFIP 1, NEK 1, NET1, NME PGM, NNT, NQoP 1, NRAS 1, PSNPPHSPP 1, PSNPPHAPN 1, PSNPPSNPPSP 1, PSNPPSNPPDN 1, PSNPPDN 1, PSCP 1, PSNPPDN 1, PSCP 1, PSNPPDN 1, PSP 1, PSNPPDN 1, PSNFP 1, PSP 1, PSNFP 1, PSP 1, PSNFP 1, PSP 1, PSNFP 1, RGS19IP, RHOTB, RNASEH2, RNGTT, RNPEP, ROBO, RRAS, SART, SAT, SCAP, SCD, SDC, SEMA3, SERPINE, SFI, SGPL, SGPP, SH3GLB, SHC, SMARCC, SMC4L, SMS, SNRPD, SORD, SORL, SPP, SQLE, SRD5A2, SRM, SRPK, SS, SSBP, SSR, ST3GAL, ST6GALNAC, STX, SUAP, SWAP, TA-KRP, TALA, TBL1XR, TFRC, TIAM, TKT, TMPO, TNFAIP, TNFSF, TOX, TPD, TPI, TPP, TRA, TRIP, TRPS, TSN, TSNL, TXRB 2, TXUBC, UB 2, USP, UB 5, USP, YUBAB, USP, TXUB, or a combination thereof.

41. The method of claim 38, wherein said co-regulated gene is IGF1, IGF2, IGFR, EGFR, mdm2, Bcl2, ETS1, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK1, VAV3, aua, ERBB3, MIF, VEGF, VEGFR2, CDK1, CDK2, CDK9, farnesyl transferase, UBE2S, or a combination thereof.

42. The method of claim 38, wherein the disease is cancer.

43. The method of claim 42, wherein the cancer is selected from the group consisting of colon adenocarcinoma, esophageal adenocarcinoma, hepatocellular carcinoma, squamous cell carcinoma, pancreatic adenocarcinoma, islet cell tumor, rectal adenocarcinoma, gastrointestinal stromal tumor, gastric adenocarcinoma, adrenal cortical cell carcinoma, follicular carcinoma, papillary carcinoma, breast cancer, ductal carcinoma, lobular carcinoma, intraductal carcinoma, mucinous carcinoma, phyllodes tumor, Ewing's sarcoma, ovarian adenocarcinoma, endometrial adenocarcinoma, granulosa cell tumor, mucinous cystadenocarcinoma, cervical adenocarcinoma, vulval squamous cell carcinoma, basal cell carcinoma, prostate adenocarcinoma, giant cell tumor of bone, osteosarcoma, laryngeal carcinoma tumor, lung adenocarcinoma, kidney carcinoma, bladder carcinoma, Wilms' tumor, and lymphoma.

44. The method of claim 38 wherein the expression levels of said PARP and said co-regulated gene are up-regulated and the treatment is determined to treat said disease with an inhibitor of PARP and said co-regulated gene.

45. The method of claim 38 wherein said PARP and said co-regulated gene are down-regulated and the treatment is determined not to treat said disease with an inhibitor of PARP and said co-regulated gene.

46. The method of claim 38 wherein said PARP modulator is a PARP inhibitor.

47. The method of claim 46, wherein said PARP inhibitor is selected from the group consisting of benzamide, quinolone, isoquinolone, benzopyrone, cyclic benzamide, benzimidazole, indole, and pharmaceutically salts, solvates, isomers, tautomers, metabolites, analogs, or prodrugs thereof.

48. The method of claim 47, wherein said PARP inhibitor is 4-iodo-3-nitrobenzamide or a metabolite thereof.

49. A computer readable medium adapted to convey analysis results from a plurality of samples from a patient population regarding treatment of a disease with at least one PARP modulator and at least one modulator of at least one co-regulated gene; the information is obtained as follows: by identifying in each of said plurality of samples levels of PARP and co-regulated genes, and based on said levels of PARP and said levels of co-regulated genes, making a decision regarding treatment of said disease with said RP modulator and said modulator of at least one co-regulated gene.

50. The method of claim 49, wherein at least one step is performed using a computer.

51. A method of treating a disease, the method comprising:

a. providing a plurality of samples from patients afflicted with the disease;

b. identifying at least one regulated gene in each sample as compared to a reference sample;

c. treating a patient suffering from the disease with a modulator of the identified regulated gene and a PARP modulator.

52. The method of claim 51 wherein said modulated genes comprise genes expressed in the PARP, IGF1 receptor or EGFR pathway.

53. The method of claim 51 wherein said PARP modulator is a PARP inhibitor.

54. The method of claim 53, wherein said PARP inhibitor is selected from the group consisting of benzamide, quinolone, isoquinolone, benzopyrone, cyclic benzamide, benzimidazole, indole, and pharmaceutically salts, solvates, isomers, tautomers, metabolites, analogs, or prodrugs thereof.

55. The method of claim 51, wherein said modulated gene comprises IGF, IGFR, EGFR, mdm, Bcl, ETS, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK, VAV, AURKA, ERBB, MIF, VEGF, VEGFR, CDK, farnesyltransferase, UBE2, ABCC, ABCD, ACADM, ACLSL, ACSL, ACY1L, ADM, ADRM, AGPAT, AHCY, AK3L, AKIIP, AKR1B, AKR1C, ALDH18A, ALDOA, ALCACACACL, ALPF, ANP32, APF, APG5, ARFGEF, ARL, ARPP-19, PH, ATF, ASF 7, ATC, ACAT 1C, ALDH18A, ALDOA, ALCD 5, ACAC, ATP, CDC, ATP5, CDK, ACAK 1L, ACAK 3L, ACAD 3L, ACAT, ACAD 3L, ACAT, ACAD 5, CDC, ACOCB, CHST6, CHSY1, CKLFSF4, CKLFSF6, CKS1B, CMKOR B, CNDP B, CPD, CPE, CPSF B, CPT1B, CRR B, CSH B, CSK, CSNK2A B, CSPG B, CTPSCTSB, CTSD, CXADR, CXCR B, CXXC B, DAXC B, DCK, DDAH B, DDIT B, DDX B, DHTKD B, DLAT, DNAJA B, DNJB B, DNJC B, HSPDNADN B, HSPFALG B, HSPGFAGN B, HSPGFAGGFAGN B, HSPGFAGFLAGFLEXP B, HSPGFAGFLX B, HSPGFAGGFAGGFAGFLX B, HSPGFAGGFAGFLD B, HSPGFAGFLD B, HSPGFAG3672, HSPGFAGFLXC B, HSPGFAGFLX B, HSPGFAGGFAGGFAG3672, B, HSPGFAGGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGFAGGFDG B, HSPGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGF3672, B, HSPGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGFDG B, HSPGFAGGFX B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFX B, HSPGFDG B, HSPGFX B, HSPGFAGGFAGGF3672, HSPGFX B, HSPGFAGGFAGGFAGGFAGGF3672, HSPGFX B, HSPGFAGGFAGGFAGGF, MADP-1, MAGED1, MAK3, MALAT 3, MAP2K3, MAP3K 3, MAP4K 3, MAPK 3, MARCKS, MBTPS 3, MCM 3, MDH 3, ME 3, METAP 3, METTL 3, MGAT4 3, MKNK 3, MLPH, MOBKL 13, MSH 3, MTHFD 3, MUC 3, MX 3, MYCBP, NAJD 3, NAT 3, NBS 3, NDP 3, NEK 3, QO 3, NMP 3, NNT 3, NNFP 3, NRAS, NSE 3, PGS 36SAP 3, PSPMSPP 3, PSWPP 3, PSMP 3, PSNPPEPCP 3, PSNPPEPTCP 3, PSNPCP 3, PSNPPEPTCP 3, PSP 3, PSCP 3, PSP 3, PSNPPEPTCP 3, PSP 3, PSNPPEPTCP 3, PSPEPTCP 3, PSP 3, PS, RNGTT, RNPEP, ROBO, RRAS, SART, SAT, SCAP, SCD, SDC, SEMA3, SERPINE, SFI, SGPL, SGPP, SH3GLB, SHC, SMARCC, SMC4L, SMS, SNRPD, SORD, SORL, SPP, SQLE, SRD5A2, SRM, SRPK, SS, SSBP, SSR, ST3GAL, ST6 GALNC, STX, SULF, SWAP, TA-KRP, TALA, TBL1XR, TFRC, TIAM, TKT, TMPO, TNFAIP, TNFSF, TOX, TPD, TPI, TPP, TRA, TRIP, TRPS, TSPAN, TSTA, TXN, NL, NRD, UBAP2, WHE 2, TXDH, WUBV, USP, YUBZ, USP, UBZ, USP, UBAB 5, or a combination thereof.

56. The method of claim 51, wherein said modulated gene comprises IGF1, IGF2, IGFR, EGFR, mdm2, Bcl2, ETS1, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK1, VAV3, RKAUA, ERBB3, MIF, VEGF, VEGFR2, CDK1, CDK2, CDK9, farnesyl transferase, UBE2S, or a combination thereof.

57. The method of claim 51, wherein mRNA levels of each of the co-regulated genes are measured.

58. The method of claim 57, wherein the mRNA level is measured using a polymerase chain reaction assay.

59. The method of claim 51, wherein the tissue sample is selected from the group consisting of a tumor sample, hair, blood, cells, tissue, organ, brain tissue, blood, serum, sputum, saliva, plasma, nipple aspirate, synovial fluid, cerebrospinal fluid, sweat, urine, fecal matter, pancreatic fluid, trabecular fluid, cerebrospinal fluid, tears, bronchial lavage, swabbing, bronchial aspirate, semen, prostatic fluid, pre-cervical fluid, vaginal fluid, and pre-ejaculate.

60. The method of claim 51, wherein the disease is breast cancer, lung cancer, endometrial cancer, or ovarian cancer.

61. The method of claim 60, wherein the breast cancer is triple negative breast cancer.

62. A method of treating a disease susceptible to treatment with a PARP modulator, the method comprising:

a. identifying a disease treatable with at least one PARP modulator, wherein the expression level of PARP is modulated in a plurality of samples as compared to a reference sample;

b. identifying at least one co-regulated gene in the plurality of samples as compared to a reference sample;

c. treating a patient suffering from said disease with PARP and a modulator of said co-regulated gene.

63. The method of claim 62, wherein said co-regulated genes comprise genes expressed in the PARP, IGF1 receptor, or EGFR pathway.

64. The method of claim 62, wherein said co-regulated gene comprises IGF, IGFR, EGFR, mdm, Bcl, ETS, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK, VAV, AURKA, ERBB, MIF, VEGF, VEGFR, CDK, farnesyltransferase, UBE2, ABCC, ABCD, ACADM, ACLSL, ACY1L, ADM, ADRM, AGPAT, AHCY, AK3L, AKIIP, AKR1B, AKR1C, ALDH18A, ALDOA, ALOX, ALPL, ANP32, ANF, APG5, FGEF, ARL-19, ARPH, ASF, ATF7, ATP, ATC, ATP1A, ATP 5A, ATP5, ATP, CDC, ATP5, CDC, ATP, CDC, ATP-1B, CDC, ATP, CDC, ATP, CDK, CDC, ATP, CDC, ATP5, CDK, CDC, CDK, ABC, CDC, CDK, ABC, ACY, ACAD 1L, ACOCK, ACAD 1L, CDC, ACOCK, CDC, CHST6, CHSY1, CKLFSF4, CKLFSF6, CKS1B, CMKOR B, CNDP B, CPD, CPE, CPSF B, CPT1B, CRR B, CSH B, CSK, CSNK2A B, CSPG B, CTPSCTSB, CTSD, CXADR, CXCR B, CXXC B, DAXC B, DCK, DDAH B, DDIT B, DDX B, DHTKD B, DLAT, DNAJA B, DNJB B, DNJC B, HSPDNADN B, HSPFALG B, HSPGFAGN B, HSPGFAGGFAGN B, HSPGFAGFLAGFLEXP B, HSPGFAGFLX B, HSPGFAGGFAGGFAGFLX B, HSPGFAGGFAGFLD B, HSPGFAGFLD B, HSPGFAG3672, HSPGFAGFLXC B, HSPGFAGFLX B, HSPGFAGGFAGGFAG3672, B, HSPGFAGGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGFAGGFDG B, HSPGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGF3672, B, HSPGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGFDG B, HSPGFAGGFX B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFX B, HSPGFDG B, HSPGFX B, HSPGFAGGFAGGF3672, HSPGFX B, HSPGFAGGFAGGFAGGFAGGF3672, HSPGFX B, HSPGFAGGFAGGFAGGF, MADP-1, MAGED1, MAK3, MALAT 3, MAP2K3, MAP3K 3, MAP4K 3, MAPK 3, MARCKS, MBTPS 3, MCM 3, MDH 3, ME 3, METAP 3, METTL 3, MGAT4 3, MKNK 3, MLPH, MOBKL 13, MSH 3, MTHFD 3, MUC 3, MX 3, MYCBP, NAJD 3, NAT 3, NBS 3, NDP 3, NEK 3, QO 3, NMP 3, NNT 3, NNFP 3, NRAS, NSE 3, PGS 36SAP 3, PSPMSPP 3, PSWPP 3, PSMP 3, PSNPPEPCP 3, PSNPPEPTCP 3, PSNPCP 3, PSNPPEPTCP 3, PSP 3, PSCP 3, PSP 3, PSNPPEPTCP 3, PSP 3, PSNPPEPTCP 3, PSPEPTCP 3, PSP 3, PS, RNGTT, RNPEP, ROBO, RRAS, SART, SAT, SCAP, SCD, SDC, SEMA3, SERPINE, SFI, SGPL, SGPP, SH3GLB, SHC, SMARCC, SMC4L, SMS, SNRPD, SORD, SORL, SPP, SQLE, SRD5A2, SRM, SRPK, SS, SSBP, SSR, ST3GAL, ST6 GALNC, STX, SULF, SWAP, TA-KRP, TALA, TBL1XR, TFRC, TIAM, TKT, TMPO, TNFAIP, TNFSF, TOX, TPD, TPI, TPP, TRA, TRIP, TRPS, TSPAN, TSTA, TXN, NL, NRD, UBAP2, WHE 2, TXDH, WUBV, WUBC, YUBV, USP, YUBA, USP, YUBA, USP, TXN, or a combination thereof.

65. The method of claim 62, wherein said co-regulated gene comprises IGF1, IGF2, IGFR, EGFR, mdm2, Bcl2, ETS1, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK1, VAV3, AUA, ERBB3, MIF, VEGF, VEGFR2, CDK1, CDK2, CDK9, farnesyl transferase, UBE2S, or a combination thereof.

66. The method of claim 62, wherein the disease is cancer.

67. The method of claim 66, wherein the cancer is selected from the group consisting of colon adenocarcinoma, esophageal adenocarcinoma, hepatocellular carcinoma, squamous cell carcinoma, pancreatic adenocarcinoma, islet cell tumor, rectal adenocarcinoma, gastrointestinal stromal tumor, gastric adenocarcinoma, adrenal cortical cell carcinoma, follicular carcinoma, papillary carcinoma, breast cancer, ductal carcinoma, lobular carcinoma, intraductal carcinoma, mucinous carcinoma, phyllodes tumor, Ewing's sarcoma, ovarian adenocarcinoma, endometrial adenocarcinoma, granulosa cell tumor, mucinous cystadenocarcinoma, cervical adenocarcinoma, vulval squamous cell carcinoma, basal cell carcinoma, prostate adenocarcinoma, giant cell tumor of bone, osteosarcoma, laryngeal carcinoma tumor, lung adenocarcinoma, kidney carcinoma, bladder carcinoma, Wilms' tumor, and lymphoma.

68. The method of claim 66, wherein the cancer is breast cancer, lung cancer, endometrial cancer, or ovarian cancer.

69. The method of claim 68, wherein said breast cancer is triple negative carcinoma.

70. The method of claim 62 wherein the expression levels of said PARP and said co-regulated gene are up-regulated and the treatment is determined to treat said disease with an inhibitor of PARP and said co-regulated gene.

71. The method of claim 62 wherein the expression levels of said PARP and said co-regulated gene are down-regulated and the treatment is determined not to treat said disease with an inhibitor of PARP and said co-regulated gene.

72. The method of claim 62 wherein said PARP modulator is a PARP inhibitor.

73. The method of claim 70, wherein said PARP inhibitor is selected from the group consisting of benzamides, quinolones, isoquinolones, benzopyrones, cyclic benzamides, benzimidazoles, indoles, and pharmaceutically salts, solvates, isomers, tautomers, metabolites, analogs, or prodrugs thereof.

74. The method of claim 70, wherein said PARP inhibitor is 4-iodo-3-nitrobenzamide or a metabolite thereof.

75. A method of treating a cancer susceptible to treatment with a PARP inhibitor, the method comprising:

a. identifying a cancer treatable with at least one PARP inhibitor, wherein the expression level of PARP is upregulated in a plurality of cancer samples;

b. Identifying at least one gene that is commonly up-regulated in the plurality of samples;

c. treating a patient having cancer with an inhibitor of PARP and said co-regulated gene.

76. The method of claim 75, wherein said co-regulated genes comprise genes expressed in the PARP, IGF1 receptor, or EGFR pathway.

77. The method of claim 75, wherein said co-regulated gene comprises IGF, IGFR, EGFR, mdm, Bcl, ETS, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK, VAV, AURKA, ERBB, MIF, VEGF, VEGFR, CDK, farnesyltransferase, UBE2, ABCC, ABCD, ACADM, ACLSL, ACY1L, ADM, ADRM, AGPAT, AHCY, AK3L, AKIIP, AKR1B, AKR1C, ALDH18A, ALDOA, ALOX, ALPL, ANP32, ANF, APG5, FGEF, ARL-19, ARPH, ASF, ATF7, ATP, ATC, ATP1A, ATP 5A, ATP5, ATP, CDC, ATP5, CDC, ATP, CDC, ATP-1B, CDC, ATP, CDC, ATP, CDK, CDC, ATP, CDC, ATP5, CDK, CDC, CDK, ABC, CDC, CDK, ABC, ACY, ACOCK, ACOX, CDC, ACAD 1L, CDC, CHST6, CHSY1, CKLFSF4, CKLFSF6, CKS1B, CMKOR B, CNDP B, CPD, CPE, CPSF B, CPT1B, CRR B, CSH B, CSK, CSNK2A B, CSPG B, CTPSCTSB, CTSD, CXADR, CXCR B, CXXC B, DAXC B, DCK, DDAH B, DDIT B, DDX B, DHTKD B, DLAT, DNAJA B, DNJB B, DNJC B, HSPDNADN B, HSPFALG B, HSPGFAGN B, HSPGFAGGFAGN B, HSPGFAGFLAGFLEXP B, HSPGFAGFLX B, HSPGFAGGFAGGFAGFLX B, HSPGFAGGFAGFLD B, HSPGFAGFLD B, HSPGFAG3672, HSPGFAGFLXC B, HSPGFAGFLX B, HSPGFAGGFAGGFAG3672, B, HSPGFAGGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGFAGGFDG B, HSPGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGF3672, B, HSPGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGFDG B, HSPGFAGGFX B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFX B, HSPGFDG B, HSPGFX B, HSPGFAGGFAGGF3672, HSPGFX B, HSPGFAGGFAGGFAGGFAGGF3672, HSPGFX B, HSPGFAGGFAGGFAGGF, MADP-1, MAGED1, MAK3, MALAT 3, MAP2K3, MAP3K 3, MAP4K 3, MAPK 3, MARCKS, MBTPS 3, MCM 3, MDH 3, ME 3, METAP 3, METTL 3, MGAT4 3, MKNK 3, MLPH, MOBKL 13, MSH 3, MTHFD 3, MUC 3, MX 3, MYCBP, NAJD 3, NAT 3, NBS 3, NDP 3, NEK 3, QO 3, NMP 3, NNT 3, NNFP 3, NRAS, NSE 3, PGS 36SAP 3, PSPMSPP 3, PSWPP 3, PSMP 3, PSNPPEPCP 3, PSNPPEPTCP 3, PSNPCP 3, PSNPPEPTCP 3, PSP 3, PSCP 3, PSP 3, PSNPPEPTCP 3, PSP 3, PSNPPEPTCP 3, PSPEPTCP 3, PSP 3, PS, RNGTT, RNPEP, ROBO, RRAS, SART, SAT, SCAP, SCD, SDC, SEMA3, SERPINE, SFI, SGPL, SGPP, SH3GLB, SHC, SMARCC, SMC4L, SMS, SNRPD, SORD, SORL, SPP, SQLE, SRD5A2, SRM, SRPK, SS, SSBP, SSR, ST3GAL, ST6 GALNC, STX, SULF, SWAP, TA-KRP, TALA, TBL1XR, TFRC, TIAM, TKT, TMPO, TNFAIP, TNFSF, TOX, TPD, TPI, TPP, TRA, TRIP, TRPS, TSPAN, TSTA, TXN, NL, NRD, UBAP2, WHE 2, TXDH, WUBV, WUBC, YUBV, USP, YUBA, USP, YUBA, USP, TXN, or a combination thereof.

78. The method of claim 75, wherein said co-regulated gene comprises IGF1, IGF2, IGFR, EGFR, mdm2, Bcl2, ETS1, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK1, VAV3, AUA, ERBB3, MIF, VEGF, VEGFR2, CDK1, CDK2, CDK9, farnesyl transferase, UBE2S, or a combination thereof.

79. The method of claim 75, wherein the cancer is selected from the group consisting of colon adenocarcinoma, esophageal adenocarcinoma, hepatocellular carcinoma, squamous cell carcinoma, pancreatic adenocarcinoma, islet cell tumor, rectal adenocarcinoma, gastrointestinal stromal tumor, gastric adenocarcinoma, adrenal cortical cell carcinoma, follicular carcinoma, papillary carcinoma, breast cancer, ductal carcinoma, lobular carcinoma, intraductal carcinoma, mucinous carcinoma, phyllodes tumor, Ewing's sarcoma, ovarian adenocarcinoma, endometrial adenocarcinoma, granulosa cell tumor, mucinous cystadenocarcinoma, cervical adenocarcinoma, vulval squamous cell carcinoma, basal cell carcinoma, prostate adenocarcinoma, giant cell tumor of bone, osteosarcoma, laryngeal carcinoma tumor, lung adenocarcinoma, kidney carcinoma, bladder carcinoma, Wilms' tumor, and lymphoma.

80. The method of claim 75, wherein said PARP inhibitor is selected from the group consisting of benzamide, quinolone, isoquinolone, benzopyrone, cyclic benzamide, benzimidazole, indole, and pharmaceutically salts, solvates, isomers, tautomers, metabolites, analogs, or prodrugs thereof.

81. The method of claim 75, wherein said PARP inhibitor is 4-iodo-3-nitrobenzamide or a metabolite thereof.

82. A method of treating breast cancer susceptible to treatment with a PARP inhibitor, the method comprising:

a. identifying a breast cancer treatable with at least one PARP inhibitor, wherein the expression level of PARP is up-regulated in a plurality of breast cancer samples;

b. identifying at least one gene that is commonly up-regulated in the plurality of samples;

c. treating a patient suffering from said breast cancer with an inhibitor of PARP and said co-regulated gene.

83. The method of claim 82, wherein said co-regulated genes comprise genes expressed in the PARP, IGF1 receptor, or EGFR pathway.

84. The method of claim 82, wherein said co-regulated gene comprises IGF, IGFR, EGFR, mdm, Bcl, ETS, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK, VAV, AURKA, ERBB, MIF, VEGF, VEGFR, CDK, farnesyltransferase, UBE2, ABCC, ABCD, ACADM, ACLSL, ACY1L, ADM, ADRM, AGPAT, AHCY, AK3L, AKIIP, AKR1B, AKR1C, ALDH18A, ALDOA, ALOX, ALPL, ANP32, ANF, APG5, FGEF, ARL-19, ARPH, ASF, ATF7, ATP, ATC, ATP1A, ATP1B, ATP, CDC, ATP, CDC, ATP, CDC, CDB, CDK, CDC, CDB, ATP, CDK, IRAB, IRK, ACAD 1L, ACAD, AGPAT, ACAD, CDC, ACAD 1L, CDC, ACAD 3L, CDC, CDK, CDC, CGI-3690, CHST6, CHSY1, CKLFSF4, CKLFSF6, CKS1B, CMKOR1, CNDP2, CPD, CPE, CPSF 2, CPT 12, CRR 2, CSH2, CSK, CSNK2A 2, CSPG2, CTPSCTSB, CTSD, CXADR, CXCR 2, CXXC 2, DAAM 2, DCK, DDAH 2, DDIT 2, DDR 36FADD 2, DDX2, DHTKD 2, DLAT, DNAJD 2, DNJB 2, HSPDNJC 2, DNADN 36JC 36XC 2, GGDND 2, HSP GFAGGFAGGFAGGFAGGFAGGFAGN 2, HSP 2, HSP 2, LTB4DH, LYN, MAD2L1, MADP-1, MAGED1, MAKK 1, MALAT1, MAP2K 1, MAP3K1, MAP4K 1, MAPK1, MARCKS, MBTPS 1, MCM 1, MCTS1, MDH1, ME1, METAP 1, METTL 1, MGAT 41, MKNK 1, MLPH, MOBK 11, MOBKL KL1, MSH 1, MTHFD 1, PSC 1, MX1, MYCBP, NAJD1, NBS1, NDFIP 1, NEK 1, NET1, NME PGM, NNT, NQoP 1, NRAS 1, PSNPPHSPP 1, PSNPPHAPN 1, PSNPPSNPPSP 1, PSNPPSNPPDN 1, PSNPPDN 1, PSCP 1, PSNPPDN 1, PSCP 1, PSNPPDN 1, PSP 1, PSNPPDN 1, PSNFP 1, PSP 1, PSNFP 1, PSP 1, PSNFP 1, PSP 1, PSNFP 1, RGS19IP, RHOTB, RNASEH2, RNGTT, RNPEP, ROBO, RRAS, SART, SAT, SCAP, SCD, SDC, SEMA3, SERPINE, SFI, SGPL, SGPP, SH3GLB, SHC, SMARCC, SMC4L, SMS, SNRPD, SORD, SORL, SPP, SQLE, SRD5A2, SRM, SRPK, SS, SSBP, SSR, ST3GAL, ST6GALNAC, STX, SUAP, SWAP, TA-KRP, TALA, TBL1XR, TFRC, TIAM, TKT, TMPO, TNFAIP, TNFSF, TOX, TPD, TPI, TPP, TRA, TRIP, TRPS, TSN, TSNL, TXRB, TXUBC, TXUBV 2, UB 2, USP, UBAB 2, USP, UBAB, USP, or a combination thereof.

85. The method of claim 82, wherein said co-regulated gene comprises IGF1, IGF2, IGFR, EGFR, mdm2, Bcl2, ETS1, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK1, VAV3, AUA, ERBB3, MIF, VEGF, VEGFR2, CDK1, CDK2, CDK9, farnesyl transferase, UBE2S, or a combination thereof.

86. The method of claim 82, wherein said breast cancer is selected from the group consisting of lymphoma, carcinoma, hormone-dependent tumor, small cell carcinoma, ductal carcinoma, invasive lobular carcinoma of the breast, mixed invasive carcinoma of the breast duct and lobular, and metastatic invasive ductal carcinoma.

87. The method of claim 82, wherein said breast cancer is triple negative carcinoma.

88. The method of claim 82, wherein said PARP inhibitor is selected from the group consisting of benzamides, quinolones, isoquinolones, benzopyrones, cyclic benzamides, benzimidazoles, indoles, and pharmaceutically salts, solvates, isomers, tautomers, metabolites, analogs, or prodrugs thereof.

89. The method of claim 82, wherein said PARP inhibitor is 4-iodo-3-nitrobenzamide or a metabolite thereof.

90. A method of treating lung cancer susceptible to treatment with a PARP inhibitor, the method comprising:

a. Identifying lung cancer treatable with at least one PARP inhibitor, wherein the expression level of PARP is up-regulated in a plurality of lung cancer samples;

b. identifying at least one gene that is commonly up-regulated in the plurality of samples;

c. treating a patient suffering from said lung cancer with an inhibitor of PARP and said co-regulated gene.

91. The method of claim 90, wherein said co-regulated genes comprise genes expressed in the PARP, IGF1 receptor, or EGFR pathway.

92. The method of claim 90, wherein said co-regulated gene comprises IGF, IGFR, EGFR, mdm, Bcl, ETS, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK, VAV, AURKA, ERBB, MIF, VEGF, VEGFR, CDK, farnesyltransferase, UBE2, ABCC, ABCD, ACADM, ACLSL, ACY1L, ADM, ADRM, AGPAT, AHCY, AK3L, AKIIP, AKR1B, AKR1C, ALDH18A, ALDOA, ALOX, ALPL, ANP32, ANF, APG5, FGEF, ARL-19, ARPH, ASF, ATF7, ATP, ATC, ATP1A, ATP 5A, ATP5, ATP, CDC, ATP5, CDC, ATP, CDC, ATP-1B, CDC, ATP, CDC, CDK, CDC, ABC, CDC, ABC, ATP, CDC, ATP5, CDK, CDC, CDK, ACY, ABC 1L, ACOD, ACAD 1L, CDK, ACOCK, CDC, CDK, ACOCK, CDC, AC, CHST6, CHSY1, CKLFSF4, CKLFSF6, CKS1B, CMKOR B, CNDP B, CPD, CPE, CPSF B, CPT1B, CRR B, CSH B, CSK, CSNK2A B, CSPG B, CTPSCTSB, CTSD, CXADR, CXCR B, CXXC B, DAXC B, DCK, DDAH B, DDIT B, DDX B, DHTKD B, DLAT, DNAJA B, DNJB B, DNJC B, HSPDNADN B, HSPFALG B, HSPGFAGN B, HSPGFAGGFAGN B, HSPGFAGFLAGFLEXP B, HSPGFAGFLX B, HSPGFAGGFAGGFAGFLX B, HSPGFAGGFAGFLD B, HSPGFAGFLD B, HSPGFAG3672, HSPGFAGFLXC B, HSPGFAGFLX B, HSPGFAGGFAGGFAG3672, B, HSPGFAGGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGFAGGFDG B, HSPGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGF3672, B, HSPGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGFDG B, HSPGFAGGFX B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFX B, HSPGFDG B, HSPGFX B, HSPGFAGGFAGGF3672, HSPGFX B, HSPGFAGGFAGGFAGGFAGGF3672, HSPGFX B, HSPGFAGGFAGGFAGGF, MADP-1, MAGED1, MAK3, MALAT 3, MAP2K3, MAP3K 3, MAP4K 3, MAPK 3, MARCKS, MBTPS 3, MCM 3, MDH 3, ME 3, METAP 3, METTL 3, MGAT4 3, MKNK 3, MLPH, MOBKL 13, MSH 3, MTHFD 3, MUC 3, MX 3, MYCBP, NAJD 3, NAT 3, NBS 3, NDP 3, NEK 3, QO 3, NMP 3, NNT 3, NNFP 3, NRAS, NSE 3, PGS 36SAP 3, PSPMSPP 3, PSWPP 3, PSMP 3, PSNPPEPCP 3, PSNPPEPTCP 3, PSNPCP 3, PSNPPEPTCP 3, PSP 3, PSCP 3, PSP 3, PSNPPEPTCP 3, PSP 3, PSNPPEPTCP 3, PSPEPTCP 3, PSP 3, PS, RNGTT, RNPEP, ROBO, RRAS, SART, SAT, SCAP, SCD, SDC, SEMA3, SERPINE, SFI, SGPL, SGPP, SH3GLB, SHC, SMARCC, SMC4L, SMS, SNRPD, SORD, SORL, SPP, SQLE, SRDD5A, SRD5A2, SRM, SRPK, SS, SSBP, SSR, ST3GAL, ST6 GALNC, STX, SULF, SWAP, TA-KRP, TALA, TBL1XR, TFRC, TIAM, TKT, TMPO, TNFAIP, TNFSF, TOX, TPD, TPI, TPP, TRA, TRIP, TRPS, TSPAN, TSTA, TXN, NL, NRD, UBAP2, WHE 2, TXDH, WUBV, WUBC, YUBV, USP, YUBA, USP, YUBA, USP, TXN, or a combination thereof.

93. The method of claim 90, wherein said co-regulated gene comprises IGF1, IGF2, IGFR, EGFR, mdm2, Bcl2, ETS1, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK1, VAV3, AUA, ERBB3, MIF, VEGF, VEGFR2, CDK1, CDK2, CDK9, farnesyl transferase, UBE2S, or a combination thereof.

94. The method of claim 90, wherein the lung cancer is selected from the group consisting of lung adenocarcinoma, small cell carcinoma, non-small cell carcinoma, squamous cell carcinoma, and large cell carcinoma.

95. The method of claim 90, wherein said PARP inhibitor is selected from the group consisting of benzamides, quinolones, isoquinolones, benzopyrones, cyclic benzamides, benzimidazoles, indoles, and pharmaceutically salts, solvates, isomers, tautomers, metabolites, analogs, or prodrugs thereof.

96. The method of claim 90, wherein said PARP inhibitor is 4-iodo-3-nitrobenzamide or a metabolite thereof.

97. A method of treating endometrial cancer susceptible to treatment with a PARP inhibitor, said method comprising:

a. identifying an endometrial cancer treatable with at least one PARP inhibitor, wherein the expression level of PARP is up-regulated in a plurality of endometrial cancer samples;

b. Identifying at least one gene that is commonly up-regulated in the plurality of samples;

c. treating said patient with an inhibitor of PARP and said co-regulated gene.

98. The method of claim 97, wherein said co-regulated genes comprise genes expressed in the PARP, IGF1 receptor, or EGFR pathway.

99. The method of claim 97, wherein said co-regulated gene comprises IGF, IGFR, EGFR, mdm, Bcl, ETS, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK, VAV, AURKA, ERBB, MIF, VEGF, VEGFR, CDK, farnesyltransferase, UBE2, ABCC, ABCD, ACADM, ACLSL, ACY1L, ADM, ADRM, AGPAT, AHCY, AK3L, AKIIP, AKR1B, AKR1C, ALDH18A, ALDOA, ALOX, ALPL, ANP32, ANF, APG5, FGEF, ARL-19, ARPH, ASF, ATF7, ATP, ATC, ATP1A, ATP 5A, ATP5, ATP, CDC, ATP5, CDC, ATP, CDC, ATP-1B, CDC, ATP, CDC, ATP, CDK, CDC, ATP, CDC, ATP5, CDK, CDC, CDK, ABC, CDC, CDK, ABC, ACY, ACOCK, ACOX, CDC, CDK, ACAD 1L, CDC, CHST6, CHSY1, CKLFSF4, CKLFSF6, CKS1B, CMKOR B, CNDP B, CPD, CPE, CPSF B, CPT1B, CRR B, CSH B, CSK, CSNK2A B, CSPG B, CTPSCTSB, CTSD, CXADR, CXCR B, CXXC B, DAXC B, DCK, DDAH B, DDIT B, DDX B, DHTKD B, DLAT, DNAJA B, DNJB B, DNJC B, HSPDNADN B, HSPFALG B, HSPGFAGN B, HSPGFAGGFAGN B, HSPGFAGFLAGFLEXP B, HSPGFAGFLX B, HSPGFAGGFAGGFAGFLX B, HSPGFAGGFAGFLD B, HSPGFAGFLD B, HSPGFAG3672, HSPGFAGFLXC B, HSPGFAGFLX B, HSPGFAGGFAGGFAG3672, B, HSPGFAGGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGFAGGFDG B, HSPGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGF3672, B, HSPGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGFDG B, HSPGFAGGFX B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFDG B, HSPGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFAGGFX B, HSPGFDG B, HSPGFX B, HSPGFAGGFAGGF3672, HSPGFX B, HSPGFAGGFAGGFAGGFAGGF3672, HSPGFX B, HSPGFAGGFAGGFAGGF, MADP-1, MAGED1, MAK3, MALAT 3, MAP2K3, MAP3K 3, MAP4K 3, MAPK 3, MARCKS, MBTPS 3, MCM 3, MDH 3, ME 3, METAP 3, METTL 3, MGAT4 3, MKNK 3, MLPH, MOBKL 13, MSH 3, MTHFD 3, MUC 3, MX 3, MYCBP, NAJD 3, NAT 3, NBS 3, NDP 3, NEK 3, QO 3, NMP 3, NNT 3, NNFP 3, NRAS, NSE 3, PGS 36SAP 3, PSPMSPP 3, PSWPP 3, PSMP 3, PSNPPEPCP 3, PSNPPEPTCP 3, PSNPCP 3, PSNPPEPTCP 3, PSP 3, PSCP 3, PSP 3, PSNPPEPTCP 3, PSP 3, PSNPPEPTCP 3, PSPEPTCP 3, PSP 3, PS, RNGTT, RNPEP, ROBO, RRAS, SART, SAT, SCAP, SCD, SDC, SEMA3, SERPINE, SFI, SGPL, SGPP, SH3GLB, SHC, SMARCC, SMC4L, SMS, SNRPD, SORD, SORL, SPP, SQLE, SRD5A2, SRM, SRPK, SS, SSBP, SSR, ST3GAL, ST6 GALNC, STX, SULF, SWAP, TA-KRP, TALA, TBL1XR, TFRC, TIAM, TKT, TMPO, TNFAIP, TNFSF, TOX, TPD, TPI, TPP, TRA, TRIP, TRPS, TSPAN, TSTA, TXN, NL, NRD, UBAP2, WHE 2, TXDH, WUBV, WUBC, YUBV, USP, YUBA, USP, YUBA, USP, TXN, or a combination thereof.

100. The method of claim 97, wherein said co-regulated gene comprises IGF1, IGF2, IGFR, EGFR, mdm2, Bcl2, ETS1, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK1, VAV3, aua, ERBB3, MIF, VEGF, VEGFR2, CDK1, CDK2, CDK9, farnesyl transferase, UBE2S, or a combination thereof.

101. The method of claim 97, wherein the endometrial cancer is selected from the group consisting of endometrial adenocarcinoma, cervical adenocarcinoma, vulvar squamous cell carcinoma, basal cell carcinoma, uterine carcinoma, and lymphoma.

102. The method of claim 97, wherein said PARP inhibitor is selected from the group consisting of benzamide, quinolone, isoquinolone, benzopyrone, cyclic benzamide, benzimidazole, indole, and pharmaceutically salts, solvates, isomers, tautomers, metabolites, analogs, or prodrugs thereof.

103. The method of claim 97, wherein said PARP inhibitor is 4-iodo-3-nitrobenzamide or a metabolite thereof.

104. A method of treating ovarian cancer susceptible to treatment with a PARP inhibitor, the method comprising:

a. identifying an ovarian cancer treatable with at least one PARP inhibitor, wherein the expression level of PARP is upregulated in a plurality of ovarian cancer samples;

b. Identifying at least one gene that is commonly up-regulated in the plurality of samples;

c. treating said patient with an inhibitor of PARP and said co-regulated gene.

105. The method of claim 104, wherein said co-regulated genes comprise genes expressed in the PARP, IGF1 receptor, or EGFR pathway.

106. The method of claim 104, wherein said co-regulated gene comprises IGF, IGFR, EGFR, mdm, Bcl, ETS, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK, VAV, AURKA, ERBB, MIF, VEGF, VEGFR, CDK, farnesyltransferase, UBE2, ABCC, ABCD, ACADM, ACLSL, ACY1L, ADM, ADRM, AGPAT, AHCY, AK3L, AKIIP, AKR1B, AKR1C, ALDH18A, ALDOA, ALOX, ALPL, ANP32, ANF, APG5, FGEF, ARL-19, ARPH, ASF, ATF7, ATP, ATC, ATP1A, ATP 5A, ATP5, ATP, CDC, ATP5, CDC, ATP, CDC, ATP-1B, CDC, ATP, CDC, ATP, CDK, CDC, ATP, CDC, ATP5, CDK, CDC, CDK, ABC, CDC, CDK, ABC, ACY, ACOCK, ACOX, ACOD, CDC, ACAD 1C, CDC, CDK, ACAD 1L, CDC, AC, CHST6, CHSY1, CKLFSF4, CKLFSF6, CKS 1B, CMKOR1, CNDP2, CPD, CPE, CPSF3, CPT 13, CRR 3, CSH 3, CSK, CSNK2A 3, CSPG 3, CTPSCTSB, CTSD, CXADR, CXCX 3, CXXC 3, DA3672, DCK, DDAH 3, DDIT 3, DD3672, DDX3, DHTKD 3, DLAT, JADNA 3, DNJB 3, DNJC 36JC 3, DNJC 3, DNADJC 3, HSP GFAGN 3, HSP GFAGGFAGN 3, HSP 3, HSP 3, HSP 3, HSP 3, HSP 3, HSP 3, 36363672, 3, HSP 3, 363636363636363672, HSP 36363672, HSP 3, HSP 3, LYN, MAD2L1, MADP-1, MAGED1, MAK3, MALAT 3, MAP2K3, MAP3K 3, MAP4K 3, MAPK 3, MARCKS, MBTPS 3, MCM 3, MCTS 3, MDH 3, ME 3, METAP 3, METTL 3, MGAT4 3, MKNK 3, MLPH, MOBK 13, MOBKL 13, MSH 3, MTHFD 3, MUC 3, MX 3, MYCBP, NAJD 3, RFC3, NBS 3, NDFIP 3, NEK 3, NET 3, NME 3, NNT, NQO PGN 3, NRAS 3, PSVPR 3, PSNPPSVPR 3, PSMP 3, PSPMPA 3, PSNFP 3, PSMP 3, PSP 3, PSMP 3, PSP 3, PSNFP 3, PSP 3, PS, RHOBTB, RNASEH2, RNGTT, RNPEP, ROBO, RRAS, SART, SAT, SCAP, SCD, SDC, SEMA3, SERPINE, SFI, SGPL, SGPP, SH3GLB, SHC, SMARCC, SMC4L, SMS, SNRPD, SORD, SORL, SPP, SQLE, SRD5A2, SRM, SRPK, SS, SSBP, SSR, ST3GAL, ST6 GALNC, STX, SULF, SWAP, TA-KRP, TALA, TBL1XR, TFRC, TIAM, TXTT, TMPO, TNFAIP, TNFSF, TOX, TPD, TPI, TPP, TRA, TRIP, TRPS, PAN, TSTA, TSN, NL, NRAP, TK 2, TXDH, TXUBC, UB 2, UBV, USP, UB 2, UB 5, USP, UB, UBE, UB, UBE, USP, UB, and combinations thereof.

107. The method of claim 104, wherein said co-regulated gene comprises IGF1, IGF2, IGFR, EGFR, mdm2, Bcl2, ETS1, MMP-1, MMP-3, MMP-9, uPA, DHFR, TYMS, NFKB, IKK, REL, RELA, RELB, IRAK1, VAV3, aua, ERBB3, MIF, VEGF, VEGFR2, CDK1, CDK2, CDK9, farnesyl transferase, UBE2S, or a combination thereof.

108. The method of claim 104, wherein the ovarian cancer is selected from the group consisting of lymphoma, carcinoma, hormone-dependent tumor, follicular cancer, ovarian adenocarcinoma, ovarian cancer, and solid tumors of the ovarian follicle.

109. The method of claim 104, wherein said PARP inhibitor is selected from the group consisting of benzamide, quinolone, isoquinolone, benzopyrone, cyclic benzamide, benzimidazole, indole, and pharmaceutically salts, solvates, isomers, tautomers, metabolites, analogs, or prodrugs thereof.

110. The method of claim 104, wherein said PARP inhibitor is 4-iodo-3-nitrobenzamide or a metabolite thereof.

111. A kit for diagnosing or classifying a disease, the kit comprising:

a. means for measuring the expression level of PARP in the tissue sample;

b. means for measuring the expression level of a gene previously identified as being co-regulated with PARP; and

c. Comparing said expression levels of PARP and co-regulated genes with the expression level of a reference sample,

wherein the level of expression, as compared to a reference sample, is indicative of the presence of a disease or disease stage.

112. The kit of claim 111, wherein upregulation of PARP is indicative of the presence of disease.

113. The kit of claim 111, wherein upregulation of PARP and at least one co-regulated gene is indicative of the presence of disease.

114. The kit of claim 111, wherein the tissue sample is selected from the group consisting of a tumor sample, hair, blood, cells, tissue, organ, brain tissue, blood, serum, sputum, saliva, plasma, nipple aspirate, synovial fluid, cerebrospinal fluid, sweat, urine, fecal matter, pancreatic fluid, trabecular fluid, cerebrospinal fluid, tears, bronchial lavage, swabbing, bronchial aspirate, semen, prostatic fluid, pre-cervical fluid, vaginal fluid, and pre-ejaculate.

115. The kit of claim 111, wherein the mRNA level of each co-regulated gene is measured.

116. The kit of claim 111, wherein the mRNA level is measured using a polymerase chain reaction assay.

117. A kit for treating a disease susceptible to PARP inhibitors, the kit comprising:

a. A device for measuring the expression level of PARP in a tissue sample, wherein an increased expression level of PARP compared to a reference sample is indicative of a disease susceptible to PARP inhibitors;

b. means for measuring the expression level of a gene previously identified as co-regulated with PARP, wherein increased expression of said co-regulated gene is indicative of the use of an inhibitor of said co-regulated gene in the treatment of said disease; and

c. inhibitors of PARP and said co-regulated genes for use in the treatment of said diseases.

118. The kit of claim 117, wherein the tissue sample is selected from the group consisting of a tumor sample, hair, blood, cells, tissue, organ, brain tissue, blood, serum, sputum, saliva, plasma, nipple aspirate, synovial fluid, cerebrospinal fluid, sweat, urine, fecal matter, pancreatic fluid, trabecular fluid, cerebrospinal fluid, tears, bronchial lavage, swabbing, bronchial aspirate, semen, prostatic fluid, pre-cervical fluid, vaginal fluid, and pre-ejaculate.

119. The kit of claim 117, wherein mRNA levels of each of the co-regulated genes are measured.

120. The kit of claim 117, wherein the mRNA level is measured using a polymerase chain reaction assay.

121. The kit of claim 117, wherein said PARP inhibitor is selected from the group consisting of benzamide, quinolone, isoquinolone, benzopyrone, cyclic benzamide, benzimidazole, indole, and pharmaceutically salts, solvates, isomers, tautomers, metabolites, analogs, or prodrugs thereof.

122. The kit of claim 117, wherein said PARP inhibitor is 4-iodo-3-nitrobenzamide or a metabolite thereof.