CN113286898B - Biomarkers for predicting the occurrence of hereditary ovarian cancer and their uses - Google Patents
Biomarkers for predicting the occurrence of hereditary ovarian cancer and their uses Download PDFInfo
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Abstract
本公开内容涉及用于预测遗传性卵巢癌发生的生物标志物及其用途，更具体地，涉及用于预测遗传性卵巢癌发生的标志物组合物，用于预测遗传性卵巢癌发生的组合物和试剂盒，以及提供用于预测遗传性卵巢癌发生的信息的方法。伴随有BRCA突变的遗传性卵巢癌发生的存在或不存在可以通过测量根据本公开内容的生物标志物基因的mRNA或蛋白水平来早期预测，并且所述生物标志物可以有效地用于开发靶向所述生物标志物的遗传性卵巢癌的治疗剂。
The present disclosure relates to biomarkers for predicting the occurrence of hereditary ovarian cancer and their uses, and more specifically, to a marker composition for predicting the occurrence of hereditary ovarian cancer, a composition and a kit for predicting the occurrence of hereditary ovarian cancer, and a method for providing information for predicting the occurrence of hereditary ovarian cancer. The presence or absence of hereditary ovarian cancer with BRCA mutation can be predicted early by measuring the mRNA or protein level of the biomarker gene according to the present disclosure, and the biomarker can be effectively used to develop a therapeutic agent for hereditary ovarian cancer targeting the biomarker.
Description
Technical Field
The present disclosure relates to biomarkers for predicting hereditary ovarian carcinogenesis and uses thereof, and more particularly, to a marker composition for predicting hereditary ovarian carcinogenesis, a composition and kit for predicting hereditary ovarian carcinogenesis, and a method of predicting hereditary ovarian carcinogenesis.
Background
Ovarian cancer is one of the first ten causes of cancer and death occurring in korean females, more than 60% of ovarian cancer patients are diagnosed with advanced stages, and the 5-year survival rate at this time is less than 30%. The symptoms of ovarian cancer are not obvious, and it is difficult to identify abdominal distension, dyspepsia, diarrhea, and constipation as symptoms of ovarian cancer. Moreover, most importantly, there is no effective detection method that can detect ovarian cancer at an early stage. Therefore, an effective means of preventing and early detecting ovarian cancer is an unmet significant medical need.
About 25% of high grade serous ovarian cancers (which are the most common ovarian cancer types) are known to be associated with the BRCA1 gene. The BRCA1 gene is located on chromosome 17, has been demonstrated for the first time as a gene that increases the risk of developing breast and ovarian cancer, and BRCA2 has also been reported to increase the risk of developing the above cancer types after BRCA 1. The probability of ovarian carcinogenesis in humans with BRCA1 mutations reaches 44% before age 70, and the mutated BRCA gene can be inherited not only from the maternal line but also from the paternal line. About 10% of ovarian cancers are known to be associated with mutations in the BRCA1 and BRCA2 genes, and when mutations are present in both genes, the incidence of ovarian cancer increases by 10-fold or more compared to normal persons, and the recurrence rate of ovarian cancer also increases. Furthermore, it was reported that BRCA1 (23.8%) and BRCA2 (25.7%) were accompanied by BRCA mutations in korean ovarian cancer patients regardless of family history (Choi et al, jgo.2016).
However, despite these effects of BRCA mutations, a prophylactic risk-reducing tubal-ovariectomy (RRSO) is the only method to prevent ovarian cancer caused by BRCA mutations, and no other method has been established. In women of childbearing age, "preventive risk-reducing tubal-ovariectomy" causes premature menopause, resulting in reduced quality of life, and the proportion of korean aged mothers (> 35 year old children) increases from 11% in 1999 to 28.6% in 2009, which means an increase of 17.6% in 10 years, resulting in a reduction in the number of BRCA1 carriers that can be administered RRSO at the appropriate time. Therefore, there is an urgent need to develop a method other than RRSO capable of predicting and preventing the occurrence of ovarian cancer.
In recent studies on breast cancer and BRCA genes, RANKL/RANK inhibitors (e.g., denosumab) have been proposed to act as prophylactic agents for breast cancer in BRCA positive subjects. Based on this, it was judged that it was necessary to find biomarkers capable of predicting hereditary ovarian cancer, and furthermore to develop a target inhibitor using the selective biomarkers as a therapeutic agent for hereditary ovarian cancer for therapies other than RRSO.
BRIEF SUMMARY OF THE PRESENT DISCLOSURE
Technical problem
As described above, as a result of research work to predict whether there is hereditary ovarian cancer occurrence accompanied by BRCA gene mutation and, in addition, present targets for therapeutic agent development for the disease, the inventors of the present application found 11 types of markers whose expression was significantly changed in ovarian cancer patients having BRCA mutation compared to normal persons having BRCA mutation, completing the present disclosure.
Accordingly, the present disclosure relates to providing marker compositions for predicting hereditary ovarian carcinogenesis.
Furthermore, the present disclosure relates to providing a composition for predicting hereditary ovarian carcinogenesis and a kit for predicting hereditary ovarian carcinogenesis comprising the composition.
Furthermore, the present disclosure relates to methods for providing information for predicting hereditary ovarian cancer occurrence.
However, technical problems to be achieved by the present disclosure are not limited to the above-mentioned problems, and other problems not mentioned will be clearly understood by those skilled in the art from the following description.
Technical proposal
To achieve the objects of the present disclosure as described above, one aspect of the present disclosure provides a marker composition for predicting hereditary ovarian carcinogenesis comprising at least one gene selected from aldolase, fructose-bisphosphate A (ALDOA) (GenBank accession number: NM_ 001243177), cadherin 2 (CDH 2) (NM_ 001792, NM_ 001308176), latent transforming growth factor β -binding protein 1 (LTBP 1) (NM_ 000627, NM_001166264, NM_001166265, NM_001166266, NM_ 206943), mannose receptor type C-1 (MRC 1) (NM_ 002438), pre-platelet basic protein (NM_ 002704), retinol binding protein 4 (RBP 4) (NM_ 001323517, NM_001323518, NM_ 006744), cysteine-rich secretory acidic protein (SPARC) (003118, NM_001309443, NM_ 001309444), members of the PISERR_5 (NM_4375), PISERb1 (PINC1) (NM_3757), members of the PISER1 family (NM_ 000624), PINg 000624 (PINC1), PIN1 (PINC2_ 000624), PIN1 (PINg 000624) and PIN1 (PINg 000624).
In addition, another aspect of the present disclosure provides a composition for predicting hereditary ovarian carcinogenesis and a kit for predicting hereditary ovarian carcinogenesis comprising the composition comprising reagents for measuring mRNA levels of at least one gene selected from aldolase, fructose-bisphosphate a (aloa) (GenBank accession No. nm_ 001243177), cadherin 2 (CDH 2) (nm_ 001792, nm_ 001308176), latent transforming growth factor β -binding protein 1 (LTBP 1) (nm_ 000627, nm_001166264, nm_001166265, nm_001166266, nm_ 206943), mannose receptor type C-1 (MRC 1) (nm_ 002438), pre-platelet basic protein (PPBP) (nm_ 002704), retinol binding protein 4 (RBP 4) (001323517, nm_001323518, nm_ 006744), cysteine-rich rc-type acidic protein (nm_ 003118, nm_5) (p-5) and members of the family (p-ser1) (nm_4375) (p 5) and members of the family (p-ser1) (nm_n_4375) (nm_5 ) (p 5, nm_5) members (p 5, nm_n 2, nm_p 5) (p 5).
In embodiments of the present disclosure, the hereditary ovarian cancer may be accompanied by a mutation in the BRCA1 or BRCA2 gene.
In another embodiment of the present disclosure, the reagents for measuring the mRNA level of at least one gene may be sense and antisense primers or probes, each complementarily binding the mRNA of the at least one gene.
In another embodiment of the present disclosure, the reagent for measuring protein level may be an antibody that specifically binds to a protein encoded by the at least one gene.
Furthermore, a further aspect of the present disclosure provides a method for providing information for predicting hereditary ovarian carcinogenesis, the method comprising measuring the mRNA level of at least one gene selected from the group consisting of aldolase, fructose-bisphosphate A (ALDOA) (GenBank accession number: NM_ 001243177), cadherin 2 (CDH 2) (NM_ 001792, NM_ 001308176), latent transforming growth factor β -binding protein 1 (LTBP 1) (NM_ 000627, NM_001166264, NM_001166265, NM_001166266, NM_ 206943), mannose receptor type C-1 (MRC 1) (NM_ 002438), pre-platelet basic protein (NM_ 002704), retinol binding protein 4 (RBP 4) (NM_ 001323517, NM_001323518, NM_ 006744), cysteine-rich secretory acidic protein (SPARC) (003118, NM_001309443, NM_ 001309444), members of the PISERR_5 (NM_4375), PISERR2 (PINC1) (NM_4357), members of the PISERR2 family (NM_ 000624), PISERR2 (PINC1) and PISERR2 (PINC1_4375).
In embodiments of the present disclosure, the subject may have a mutation in the BRCA1 or BRCA2 gene.
In another embodiment of the present disclosure, the occurrence of hereditary ovarian cancer may be predicted when the mRNA level of at least one gene selected from RBP4, SERPINA5, SERPINC1, and SERPINF2, or the protein level encoded by the at least one gene, is reduced compared to a healthy normal control group.
In another embodiment of the present disclosure, the occurrence of hereditary ovarian cancer can be predicted when the mRNA level of or the protein level encoded by at least one gene selected from aloa, CDH2, LTBP1, MRC1, PPBP, SPARC, and THBS1 is increased compared to a healthy normal control group.
In another embodiment of the present disclosure, the expression level of mRNA can be measured by at least one method selected from the group consisting of in situ hybridization, polymerase Chain Reaction (PCR), reverse Transcription (RT) -PCR, real-time PCR, RNase Protection Assay (RPA), microarray and northern blot.
In another embodiment of the present disclosure, the expression level of the protein may be measured by at least one method selected from the group consisting of Western blotting, radioimmunoassay (RIA), radioimmunoassay, enzyme-linked immunosorbent assay (ELISA), immunoprecipitation, flow cytometry, immunofluorescence, ouchterlony two-way immunodiffusion, complement fixation assay, and protein chip.
Advantageous effects
In the present disclosure, since 11 types of biomarkers capable of early predicting the occurrence of hereditary ovarian cancer in a subject having BRCA gene mutation are found, the occurrence of hereditary ovarian cancer accompanied by BRCA mutation can be early predicted by measuring mRNA or protein levels of biomarker genes according to the present disclosure, and the biomarkers can be effectively used for developing a therapeutic agent for hereditary ovarian cancer by targeting the biomarkers.
Drawings
FIG. 1A is an experimental protocol for the discovery of proteins whose expression is specifically altered in BRCA gene mutation positive (BRCA+) ovarian cancer patients to obtain candidate marker proteins for predicting hereditary ovarian carcinogenesis accompanied by BRCA gene mutation.
FIG. 1B shows the results of analysis of differentially expressed proteins using volcanic mapping (volcanic plot) using plasma samples obtained from BRCA mutant positive normal group and ovarian cancer patients.
FIG. 1C shows an analysis of the function of the corresponding proteins of 19 types of proteins with reduced expression and 61 types of proteins with increased expression in ovarian cancer patients as a result of the analysis of FIG. 1B by network analysis.
FIG. 1D is a comparison of the results of significantly increased protein numbers expressed in each of the BRCA mutant positive normal group (BRCA+ subject: HC), normal group (HC), BRCA mutant positive ovarian cancer patient (BRCA+ subject: OC) and ovarian cancer patient (OC).
FIG. 1E is the results of Venn diagrams after comparative analysis of the proteins identified in the four groups of FIG. 1D, and the results of 24 types of proteins obtained therefrom, whose expression was specifically decreased or increased only in the BRCA mutant positive ovarian cancer patient group.
Fig. 2A is a result of analyzing whether there is a statistically significant difference in protein expression level between 4 groups (BRCA mutation negative normal group (HN), BRCA mutation positive normal group (HP), BRCA mutation negative ovarian cancer patient group (ON), and BRCA mutation positive ovarian cancer patient group (OP)) for each of SERPINA5 and IGFBP5 in 9 types of proteins with reduced expression specificity in BRCA mutation positive ovarian cancer patients.
FIG. 2B is a result of analyzing whether each of F2 and TFRC in 9 types of proteins with reduced expression specificity in BRCA mutant-positive ovarian cancer patients is statistically significant in the differences in protein expression levels between the same four groups as shown in FIG. 2A.
Fig. 2C is a result of analyzing whether there is a statistically significant difference in protein expression levels between four identical groups as shown in fig. 2A for each of SELL and APOC3 in 9 types of proteins with reduced expression specificity in BRCA mutation-positive ovarian cancer patients.
Fig. 2D is a result of analyzing whether there is a statistically significant difference in protein expression levels between the same four groups as shown in fig. 2A for each of SERPINF2 and SERPINC1 in 9 types of proteins with reduced expression specificity in BRCA mutation-positive ovarian cancer patients.
FIG. 2E is a result of analyzing whether there is a statistically significant difference in protein expression levels between the same four groups as shown in FIG. 2A for RBP4 in 9 types of proteins with reduced expression specificity in BRCA mutant positive ovarian cancer patients.
Fig. 3A is a result of analyzing whether there is a statistically significant difference in protein expression level between 4 groups (BRCA mutation negative normal group (HN), BRCA mutation positive normal group (HP), BRCA mutation negative ovarian cancer patient group (ON), and BRCA mutation positive ovarian cancer patient group (OP)) for each of VNN1 and PPBP in 15 types of proteins that express increased specificity in BRCA mutation positive ovarian cancer patients.
Fig. 3B is a result of analyzing whether there is a statistically significant difference in protein expression levels between the same four groups as shown in fig. 3A for each of aloa and VWF in 15 types of proteins with increased expression specificity in BRCA mutation-positive ovarian cancer patients.
FIG. 3C is a result of analyzing whether there is a statistically significant difference in protein expression levels between the same four groups as shown in FIG. 3A for each of SERPINE1 and GPI in 15 types of proteins with increased expression specificity in BRCA mutant positive ovarian cancer patients.
Fig. 3D is a result of analyzing whether there is a statistically significant difference in protein expression levels between the same four groups as shown in fig. 3A for each of PSAP and HEXB in 15 types of proteins expressing increased specificity in BRCA mutation-positive ovarian cancer patients.
FIG. 3E is a result of analyzing whether there is a statistically significant difference in protein expression levels between the same four groups as shown in FIG. 3A for each of THBS1 and SPARC in 15 types of proteins with increased expression specificity in BRCA mutant positive ovarian cancer patients.
FIG. 3F is a result of analyzing whether each of CDH2 and MRC1 in 15 types of proteins with increased expression specificity in BRCA mutant positive ovarian cancer patients is statistically significant in the differences in protein expression levels between the same four groups as shown in FIG. 3A.
Fig. 3G is a result of analyzing whether there is a statistically significant difference in protein expression levels between the same four groups as shown in fig. 3A for each of HSPA4 and RELN in 15 types of proteins with increased expression specificity in BRCA mutant positive ovarian cancer patients.
FIG. 3H is a result of analyzing whether there is a statistically significant difference in protein expression levels between the same four groups as shown in FIG. 3A for LTBP1 in 15 types of proteins with increased expression specificity in BRCA mutant-positive ovarian cancer patients.
FIG. 4A is the result of performing ROC curve analysis and deriving AUC values to investigate the accuracy of expressing each of SERPINA5 (Uniprot ID: P5154) and IGFBP5 (P24593) in 9 types of proteins with reduced specificity in BRCA mutant positive ovarian cancer patients.
FIG. 4B is the result of ROC curve analysis and derivation of AUC values to investigate the accuracy of expressing each of F2 (P00744) and TFRC (P02786) in 9 types of proteins with reduced specificity in BRCA mutant positive ovarian cancer patients.
FIG. 4C is the result of performing ROC curve analysis and deriving AUC values to investigate the accuracy of expressing each of SELL (P14151.2) and APOC3 (P02656) in 9 types of proteins with reduced specificity in BRCA mutant positive ovarian cancer patients.
FIG. 4D is the result of performing ROC curve analysis and deriving AUC values to investigate the accuracy of expressing each of SELL (P08697) and APOC3 (P01008) in 9 types of proteins with reduced specificity in BRCA mutant positive ovarian cancer patients.
FIG. 4E is the result of ROC curve analysis and derivation of AUC values to investigate the accuracy of RBP4 (P02753) in expressing 9 types of proteins with reduced specificity in BRCA mutant positive ovarian cancer patients.
FIG. 5A is a result of ROC curve analysis and derivation of AUC values to investigate the accuracy of expressing one of VNN1 (Uniprot ID: O95497) and PPBP (P02775) in 15 types of proteins with increased specificity in BRCA mutant-positive ovarian cancer patients.
Fig. 5B is the result of ROC curve analysis and deriving AUC values to investigate the accuracy of expressing each of aloa (P04075.2) and VWF (P04275) in 15 types of proteins with increased specificity in BRCA mutation-positive ovarian cancer patients.
FIG. 5C is the result of performing ROC curve analysis and deriving AUC values to investigate the accuracy of expressing each of SERPINE1 (P05121) and GPI (P06744.2) in 15 types of proteins with increased specificity in BRCA mutant positive ovarian cancer patients.
Fig. 5D is the result of performing ROC curve analysis and deriving AUC values to investigate the accuracy of expressing each of PSAP (P07602.3) and HEXB (P07686) in 15 types of proteins with increased specificity in BRCA mutant positive ovarian cancer patients.
FIG. 5E is the result of performing ROC curve analysis and deriving AUC values to investigate the accuracy of expressing each of THBS1 (P07996) and SPARC (P09486) in 15 types of proteins with increased specificity in BRCA mutant positive ovarian cancer patients.
FIG. 5F is the result of performing ROC curve analysis and deriving AUC values to investigate the accuracy of expressing each of CDH2 (P19022) and MRC1 (P22897) in 15 types of proteins with increased specificity in BRCA mutant positive ovarian cancer patients.
Fig. 5G is the result of ROC curve analysis and deriving AUC values to investigate the accuracy of expressing each of HSPA4 (P34932) and RELN (P78509) in 15 types of proteins with increased specificity in BRCA mutant positive ovarian cancer patients.
FIG. 5H is the result of performing ROC curve analysis and deriving AUC values to investigate the accuracy of LTBP1 (Q14766.4) in expressing 15 types of proteins with increased specificity in BRCA mutant-positive ovarian cancer patients.
Figure 6 shows a schematic diagram of a 2-fold cross-validation of the validity of 24 types of marker candidate sets.
Best mode for carrying out the invention
As a result of research work to predict hereditary ovarian cancer accompanied by BRCA gene mutation and, in addition, to present targets for developing therapeutic agents for the disease, the inventors of the present application discovered 11 types of markers whose expression was significantly changed in ovarian cancer patients having BRCA mutation compared to normal persons having BRCA mutation and verified the effectiveness thereof, thereby completing the present disclosure.
Accordingly, a marker composition for predicting hereditary ovarian carcinogenesis is provided, comprising at least one gene selected from aldolase, fructose-bisphosphate A (ALDOA) (GenBank accession number: NM_ 001243177), cadherin 2 (CDH 2) (NM_ 001792, NM_ 001308176), latent transforming growth factor beta-binding protein 1 (LTBP 1) (NM_ 000627, NM_001166264, NM_001166265, NM_001166266, NM_ 206943), mannose receptor type C-1 (MRC 1) (NM_ 002438), pre-platelet basic protein (PPBP) (NM_ 002704), retinol binding protein 4 (RBP 4) (NM_ 001323517, NM_001323518, NM_ 006744), cysteine-rich secreted acidic protein (SPARC) (NM_ 003118, NM_001309443, NM_ 001309444), ser family member 5 (SERN_4393, NM_4357), mannose receptor type C-1 (NM_ 002438), pre-platelet basic protein (PPBP) (NM_ 002704), retinol binding protein 4 (NM_ 001323517, NM_001323518, NM_ 006744), cysteine-rich secreted acidic protein (SPARC) (NM_ 003118, NM_001309443, NM_ 001309444), ser family member 5 (PINAr5) (PINC1) and PINC1 (PINC1) member (PINC1) and PISER1_4375) (PINC1).
In addition, compositions for predicting hereditary ovarian carcinogenesis are provided, comprising reagents for measuring mRNA levels of at least one gene selected from aldolase, fructose-bisphosphate A (ALDOA) (GenBank accession number: NM_ 001243177), cadherin 2 (CDH 2) (NM_ 001792, NM_ 001308176), latent transforming growth factor β -binding protein 1 (LTBP 1) (NM_ 000627, NM_001166264, NM_001166265, NM_001166266, NM_ 206943), mannose receptor type C-1 (MRC 1) (NM_ 002438), pre-platelet basic protein (PPBP) (NM_ 002704), retinol binding protein 4 (RBP 4) (NM_ 001323517, NM_001323518, NM_ 006744), cysteine-rich secreted acid protein (SPARC) (NM_ 003118, NM_001309443, NM_ 001309444), serpin family A5 (NM_5243), serC 5 (NM_4375), serC_4375 (PINC1), and ser1 (PINC2_4375) (PINC2_ 000624).
Furthermore, a kit for predicting hereditary ovarian carcinogenesis is provided, comprising the composition.
The inventors of the present application have discovered 11 types of biomarkers capable of predicting hereditary ovarian cancer occurrence through specific embodiments, and confirmed their effectiveness.
In embodiments of the present disclosure, plasma samples from the BRCA mutation positive normal and BRCA mutation positive ovarian cancer patient groups were used to identify 19 types of proteins with significantly reduced expression and 61 types of proteins with significantly increased expression in the ovarian cancer patient group as compared to the normal group, and those proteins overlapping with proteins with increased expression and independent of BRCA mutation in all normal and ovarian cancer patient groups, respectively, were excluded from the above proteins to obtain 24 types of marker candidate histones with significantly altered expression specificity in the BRCA mutation positive ovarian cancer patient group (see example 2).
In another embodiment of the present disclosure, the difference in protein expression levels between four groups (BRCA negative normal group (HN), BRCA positive normal group (HP), BRCA negative ovarian cancer patient group (ON), and BRCA positive ovarian cancer patient group (OP)) for each of the 24 types of proteins was analyzed for the presence of statistical significance, and each of the 24 types of proteins was identified as having statistical significance between BRCA positive normal group (HP) and BRCA positive ovarian cancer patient group (OP) (see example 3).
In another embodiment of the present disclosure, ROC curve analysis was performed and AUC values were derived to investigate the accuracy of each of the 24 types of proteins to identify sensitivity and specificity (see example 4).
In another embodiment of the present disclosure, 2-fold cross-validation was repeated 50 times to verify the effectiveness of 24 types of proteins as markers, and multiple results were collected to obtain the final 11 types of biomarkers (see example 5).
The term "hereditary ovarian cancer" as used in the present disclosure refers to ovarian cancer occurring due to a mutation or a defective gene inherited from at least one parent, and in the present disclosure, hereditary ovarian cancer may be accompanied by a mutation of BRCA1 or BRCA2 gene, and does not necessarily mean that the ovarian cancer is caused by the gene mutation.
The term "predicting" as used in this disclosure refers to determining whether there is a likelihood of developing hereditary ovarian cancer in a particular individual, whether the likelihood of developing hereditary ovarian cancer is relatively high, or whether hereditary ovarian cancer has developed. The methods of the present disclosure may be used to predict individuals with BRCA gene mutations as individuals at high risk of developing hereditary ovarian cancer, and may be used to delay or prevent the progression of the disease through the specific and appropriate management of these individuals.
In the present disclosure, the reagents for measuring the mRNA level of at least one gene may be sense and antisense primers or probes, each complementarily binding the mRNA of the at least one gene.
The term "primer" as used in the present disclosure is a short gene sequence as an origin of DNA synthesis, and refers to an oligonucleotide synthesized for diagnosis, DNA sequencing, and the like. Primers may be synthesized generally to a length of 15 to 30 base pairs, but may vary depending on the purpose of use, and may be modified by methylation, capping, or the like by a known method.
The term "probe" as used in the present disclosure refers to a nucleic acid capable of specifically binding to mRNA having a length of several bases to several hundred bases, which is produced by enzymatic chemical separation purification or synthesis. The radioisotope, enzyme or phosphor may be labeled to identify the presence of mRNA and may be designed and modified by known methods.
The reagent for measuring the protein level may be an antibody that specifically binds to a protein encoded by at least one gene, but is not limited thereto.
The term "antibody" as used in the present disclosure includes immunoglobulin molecules that are immunoreactive with a particular antigen, and includes monoclonal antibodies and polyclonal antibodies. Furthermore, antibodies include forms produced by genetic engineering, such as chimeric antibodies (e.g., humanized murine antibodies) and heterologous antibodies (e.g., bispecific antibodies).
Kits for predicting the reactivity of anticancer agents of the present disclosure may comprise compositions, solutions, or devices suitable for one or more other compositions of the analytical methods.
According to another aspect of the present disclosure, there is provided a method for providing information for predicting hereditary ovarian cancer occurrence, the method comprising measuring the mRNA level of at least one gene selected from aldolase, fructose-bisphosphate A (ALDOA) (GenBank accession number: NM_ 001243177), cadherin 2 (CDH 2) (NM_ 001792, NM_ 001308176), latent transforming growth factor β -binding protein 1 (LTBP 1) (NM_ 000627, NM_001166264, NM_001166265, NM_001166266, NM_ 206943), mannose receptor type C-1 (MRC 1) (NM_ 002438), pre-platelet basic protein (PPBP) (NM_ 002704), retinol binding protein 4 (RBP 4) (NM_ 001323517, NM_001323518, NM_ 006744), cysteine-rich secretory acidic protein (SPARC) (NM_ 003118, NM_001309443, NM_ 001309444), latent transforming growth factor β -binding protein 1 (LTBP 1) (NM_ 000627, NM_001166264, NM_001166266, NM_ 206943), mannose receptor type C-1 (MRC 1) (NM_ 002438), pre-platelet basic protein (NM_ 002704), retinol binding protein 4 (RBP 4) (NM_ 001323517, NM_001323518, NM_ 006744), cysteine-rich secretory protein (SPR_5) (SPR_SPR_5), PIN1) (NM_5), PIN1 (NM_5), PISEr2_5_5) (NM_5), PISEr2_5_5_5, PISEr2, and PISER_43 family (PISER_43).
The term "method of providing information for predicting hereditary ovarian cancer occurrence" as used in the present disclosure includes, as a preliminary step of predicting occurrence of a disease, providing objective basic information necessary for predicting hereditary ovarian cancer occurrence, and excluding clinical judgment or opinion of a doctor.
In embodiments of the present disclosure, a subject may have a mutation in the BRCA1 or BRCA2 gene.
In the present disclosure, the occurrence of hereditary ovarian cancer may be predicted when the mRNA level of at least one gene selected from RBP4, SERPINA5, SERPINC1, and SERPINF2 or the protein level encoded by the at least one gene is reduced compared to a healthy normal control group.
In the present disclosure, the occurrence of hereditary ovarian cancer can be predicted when the mRNA level of at least one gene selected from aloa, CDH2, LTBP1, MRC1, PPBP, SPARC, and THBS1 or the protein level encoded by the at least one gene is increased compared to a healthy normal control group.
Biological samples derived from a patient may include, but are not limited to, whole blood, saliva, tissue, cells, saliva, cerebrospinal fluid and urine.
The expression level of mRNA may be measured by at least one selected from the group consisting of Polymerase Chain Reaction (PCR), reverse Transcription (RT) -PCR, real-time PCR, RNase Protection Assay (RPA), microarray and northern blot, which are conventional methods known in the art, but is not limited thereto.
The expression level of the protein may be measured by at least one method selected from the group consisting of western blotting, radioimmunoassay (RIA), radioimmunoassay (radioimmunoassay), enzyme-linked immunosorbent assay (ELISA), immunoprecipitation, flow cytometry, immunofluorescence, ouchterlony bidirectional immunodiffusion method, complement fixation assay, and protein chip, which are conventional methods known in the art, but not limited thereto.
Hereinafter, preferred embodiments are presented to aid in understanding the present disclosure. However, the following examples are provided for easier understanding of the present disclosure, and the present disclosure is not limited by the following examples.
Examples
Example 1 Experimental methods
1-1 Recruiting subjects and obtaining samples
All samples in this example were processed after obtaining the appropriate consent and approval of the clinical study review board of the first holy's Hospital (Seoul st.mary's Hospital) at the university of forensic university of korea (The Catholic University of Korea, college of medicine). Plasma samples were obtained from 20 ovarian cancer patients and a healthy normal group of 20 individuals prior to surgery. Plasma samples derived from ovarian cancer patients were provided by the holy's hospital in the head and korean gynaecology's cancer library (the Korean Gynecologic Cancer Bank, KGCB), and plasma samples derived from healthy normal control groups were obtained from subjects who were subjected to medical examination in the holy's hospital in the case of BRCA mutation-negative subjects, and subjects who were obtained from visiting the holy's hospital in the head and who agreed to blood sampling in the case of BRCA mutation-positive subjects. All samples were frozen with liquid nitrogen and stored at-80 ℃ until use.
1-2 Pretreatment of plasma samples
Plasma samples obtained from a normal group of 20 individuals (10 BRCA1/2 gene mutations, 10 non-mutations) and 20 ovarian cancer patients (10 BRCA1/2 gene mutations, 10 non-mutations) were pretreated according to the following procedure. More specifically, 40. Mu.L of plasma samples were used for injection into HPLC multiplex affinity removal system 14 (MARS 14; agilent Technologies, inc.) columns from which 14 proteins (albumin, immunoglobulin A (IgA), immunoglobulin G (IgG), immunoglobulin M (IgM), α1-antitrypsin, α1-acid glycoprotein, apolipoprotein A1, apolipoprotein A2, complement C3, transferrin, α2-macroglobulin, haptoglobin, fibrinogen and transthyretin) were removed in high concentration. Next, the low concentration of plasma proteins was lyophilized and reabsorbed with 5% sds and 50mM 1M triethylammonium bicarbonate, dithiothreitol was added thereto to 20mM, and the mixture was then reacted at 95 ℃ for 10 minutes, thereby reducing disulfide bonds. Then, for alkylation, iodoacetamide was added thereto to 40mM, the mixture was reacted at room temperature under dark conditions for 30 minutes, and the lysis buffer and solution were discharged outside the filter using an S-TRAP filter (S-TRAP TM, protiFi), then only proteins were confined in the filter, and then centrifuged and washed. Subsequently, the filter was filled with digestion buffer, and then plasma protein and Lys-C/trypsin mixed enzyme (Promega) were added thereto at a mass ratio of 25:1, followed by a reaction at 37℃for 16 hours. Next, 100. Mu.L of 0.1% formic acid was dissolved in the dried sample, and 5. Mu.L thereof was used for LC-MS/MS analysis.
LC-MS/MS analysis
The Nano LC-Q-Exactive + mass spectrometry performed in examples 1-2 was performed according to the following method.
I) First, fractionation was performed using a 50cm C18 capillary column (OD 360Fm, ID 75 Fm), ii) in a gradient (5-45% acetonitrile and 0.1% formic acid) for 150 minutes, iii) data was collected on the first 20 intensity precursors in a Data Dependent Acquisition (DDA) mode, then iv) the collected data was compared to the human SWISSPROT sequence database using the Proteome discoverer 2.2.2 program to identify peptides and proteins, and the MS1 peak intensity of the identified peptides was used by the reduced (maximum information using minimum data) method, analyzed to find biomarkers by quantifying the results of the unlabeled quantification (LFQ) values of the proteins.
1-4 Data analysis
To compare the amount of target protein in plasma samples, six new plasma proteins were found as correctable normalization factors, without showing inter-group differences between endogenous plasma proteins. Six proteins are thyroxine-binding globulin (TBG), complement Factor I (CFI), complement component C6 (C6), silk bundle protein-2 (plastin-2, PLS 2), complement C2 (C2) and Complement Factor H (CFH). The LFQ values of representative peptides of the six proteins were divided by the intermediate LFQ value of each peptide from the original values in plasma from a total of 40 subjects.
During statistical analysis, P values were obtained by the mann-whitney test using normalized values, and it was found that the quantitative difference between the two groups was doubled or more, while proteins with P values of less than 0.05/374 were tested as post-test by bonferoni correction.
Example 2 discovery of candidate proteins with altered expression specificity in hereditary ovarian cancer patients
In order to find biomarkers capable of predicting hereditary ovarian carcinogenesis, the inventors of the present application tried to find proteins differentially expressed in plasma samples according to two protocols shown in fig. 1A and comprehensively analyze them to obtain markers expressing specific changes in hereditary ovarian cancer patients accompanied by BRCA gene mutation.
Identification of proteins differentially expressed between BRCA mutant Positive subjects (scheme I)
First, by the methods described in examples 1-2 and 1-3, analysis was performed using plasma samples obtained from BRCA mutant positive (BRCA+) normal group and ovarian cancer patients, and proteins differentially expressed according to the statistical analysis criteria of examples 1-4 were analyzed using volcanic images. As a result, as shown in fig. 1B, 19 types of proteins whose expression was significantly reduced and 61 types of proteins whose expression was significantly increased were found in BRCA mutation-positive ovarian cancer patients.
In addition, each protein with reduced expression and each protein with increased expression are distinguished by network analysis based on the function of the protein. As a result, as shown in fig. 1C, it was confirmed that 19 types of proteins whose expression was reduced in BRCA-positive ovarian cancer patients were associated with triglyceride catabolism, acute phase reaction, and thrombotic fibrin formation, and that 61 types of proteins whose expression was increased in BRCA-positive ovarian cancer patients were representatively associated with hydrogen peroxide metabolism, NADH metabolism, regulation of interleukin-8 production, interleukin-12 mediated signaling pathway, apoptosis regulation by oxidative stress, platelet aggregation, and upregulation of viral processes by the host.
2-2 Identification of differentially expressed proteins in Normal group and ovarian cancer patients (scheme II)
In this example, proteins that are differentially expressed in plasma samples derived from all normal groups and ovarian cancer patients were obtained in a similar manner to example 2-1, regardless of whether the BRCA gene was mutated or not, targeting all normal groups and ovarian cancer patients. The results demonstrate a significant increase in the expression of 13 types of proteins in the normal group and a significant increase in the expression of 48 types of proteins in ovarian cancer patients.
2-3 Identification of proteins expressing specific alterations in patients with hereditary ovarian cancer
The results obtained in examples 2-1 and 2-2 were then comprehensively analyzed. FIG. 1D shows a comparison between the expression of increased amounts of protein in each of the BRCA mutant positive normal group (BRCA+ subject: HC), normal group (HC), BRCA mutant positive ovarian cancer patient group (BRCA+ subject: OC) and ovarian cancer patient group (OC), and in FIG. 1E, the Venn diagram is used to distinguish between the expression of increased protein in each group and the expression of a common protein in increased protein in only one group. As a result, it was confirmed that 10 proteins were common among the increased expression proteins in each of the BRCA mutation-positive normal group and all the normal groups, and 46 proteins were common among the increased expression proteins in each of the BRCA mutation-positive ovarian cancer patients and all the ovarian cancer patients.
According to the above results, in addition to the proteins whose expression is increased together, proteins whose expression is reduced or increased only in the BRCA mutation-positive normal group, that is, 9 types of proteins whose expression is reduced only in the BRCA mutation-positive ovarian cancer patient group and 15 types of proteins whose expression is increased only in the BRCA mutation-positive ovarian cancer patient group were isolated, and these 24 types of proteins were obtained as marker candidate groups for predicting hereditary ovarian cancer occurrence. Information about 9 types and 15 types of proteins and genes encoding them are shown in tables 1 and 2, respectively.
TABLE 1
| Indexing of | Uniprot ID | Gene | Protein name |
| 1 | P05154 | SERPINA5 | Plasma serine protease inhibitors |
| 2 | P24593 | IGFBP5 | Insulin-like growth factor binding protein 5 |
| 3 | P00734 | F2 | Prothrombin |
| 4 | P02786 | TFRC | Transferrin receptor protein 1 |
| 5 | P14151-2 | SELL | L-selectin |
| 6 | P02656 | APOC3 | Apolipoprotein C-III |
| 7 | P08697 | SERPINF2 | Alpha-2-antiplasmin |
| 8 | P01008 | SERPINC1 | Antithrombin-III |
| 9 | P02753 | RBP4 | Retinol binding protein 4 |
TABLE 2
| Indexing of | UniprotID | Gene | Protein name |
| 1 | O95497 | VNN1 | Pantetheinase |
| 2 | P02775 | PPBP | Platelet basic protein |
| 3 | P04075-2 | ALDOA | Fructose bisphosphate aldolase A |
| 4 | P04275 | VWF | Von willebrand factor |
| 5 | P05121 | SERPINE1 | Plasminogen activator inhibitor 1 |
| 6 | P06744-2 | GPI | Glucose-6-phosphate isomerase |
| 7 | P07602-3 | PSAP | Sphingolipid activating protein (Prosaposin) |
| 8 | P07686 | HEXB | Beta-hexosaminidase subunit beta |
| 9 | P07996 | THBS1 | Thrombospondin-1 |
| 10 | P09486 | SPARC | Osteonectin |
| 11 | P19022 | CDH2 | Cadherin-2 |
| 12 | P22897 | MRC1 | Macrophage mannose receptor 1 |
| 13 | P34932 | HSPA4 | 70KDa Heat shock protein 4 |
| 14 | P78509 | RELN | Oscillating protein (Reelin) |
| 15 | Q14766-4 | LTBP1 | Latent transforming growth factor beta binding protein 1 |
Example 3 analysis of the statistical significance of the presence of proteins expressing specific alterations in patients with hereditary ovarian cancer
The inventors of the present application analyzed whether there was a statistical significance of differences between protein expression levels between four groups (BRCA negative normal group (HN), BRCA positive normal group (HP), BRCA negative ovarian cancer patient group (ON), and BRCA positive ovarian cancer patient group (OP)) relative to each of 24 types of proteins expressing specific changes in BRCA mutation positive ovarian cancer patients obtained by example 2.
The results of expressing reduced 9 types of proteins in ovarian cancer patients with BRCA mutations are shown in figures 2A-2E, and wherein the results of expressing increased 15 types of proteins are shown in figures 3A-3H. As a result of the analysis, it was confirmed that all 24 types of proteins have significant differences in expression levels between the BRCA mutation-positive normal group and the BRCA mutation-positive ovarian cancer patient group. In table 3 below, the average expression levels and standard deviations of 24 types of proteins in the BRCA mutation-positive normal group and the BRCA mutation-positive ovarian cancer patient group are shown.
TABLE 3
Example 4 sensitivity and specificity analysis of markers of 24 types
The inventors of the present application sought to analyze sensitivity and specificity, and therefore performed ROC curve analysis to identify the accuracy of 24 types of markers that express significant changes in the BRCA mutant positive ovarian cancer patient group. Sensitivity and specificity were assessed by calculating the area under ROC curve (AUC).
The results of expressing reduced 9 types of proteins in ovarian cancer patients with BRCA mutations are shown in fig. 4A-4E and table 4, and wherein the results of expressing increased 15 types of proteins are shown in fig. 5A-5H and table 5. When area=1, the test dataset was judged to have perfect accuracy, and when area=0.5, the test dataset was judged to have worthless accuracy. The accuracy criteria according to AUC values are as follows, 0.9-1 = excellent, 0.8-0.9 = good, 0.7-0.8 = general (C), 0.6-0.7 = poor (D), 0.5-0.6 = failed (F).
TABLE 4
TABLE 5
| Indexing of | UniProt ID | Gene | Protein name | AUC values |
| 1 | O95497 | VNN1 | Pantetheinase | 0.533 |
| 2 | P02775 | PPBP | Platelet basic protein | 0.534 |
| 3 | P04075.2 | ALDOA | Fructose bisphosphate aldolase A | 0.844 |
| 4 | P04275 | VWF | Von willebrand factor | 0.792 |
| 5 | P05121 | SERPINE1 | Plasminogen activator inhibitor 1 | 0.642 |
| 6 | P06744.2 | GPI | Glucose-6-phosphate isomerase | 0.774 |
| 7 | P07602.3 | PSAP | Sphingolipid activating protein precursor | 0.771 |
| 8 | P07686 | HEXB | Beta-hexosaminidase subunit beta | 0.755 |
| 9 | P07996 | THBS1 | Thrombospondin-1 | 0.667 |
| 10 | P09486 | SPARC | Osteonectin | 0.664 |
| 11 | P19022 | CDH2 | Cadherin-2 | 0.868 |
| 12 | P22897 | MRC1 | Macrophage mannose receptor 1 | 0.816 |
| 13 | P34932 | HSPA4 | 70KDa Heat shock protein 4 | 0.826 |
| 14 | P78509 | RELN | Oscillating protein (Reelin) | 0.760 |
| 15 | Q14766.4 | LTBP1 | Latent transforming growth factor beta binding protein 1 | 0.674 |
Example 5 verification of the validity of markers of type 24
The inventors of the present application attempted to verify the effectiveness of 24 types of markers that were significantly altered with respect to expression in the BRCA mutation-positive ovarian cancer patient group as specific biomarkers capable of predicting the occurrence of hereditary ovarian cancer. For this purpose, 2-fold cross-validation was repeated 50 times for each of the 24 types of proteins, and a schematic diagram of the validation process is shown in fig. 6.
By analysis, the optimal K value (which is a variable selected from 24 types of candidate histones) was 15, the cross-validated AUC value was 0.983 or higher, 15 proteins with a probability of 0.70 or higher (selected k=7) were selected, and 7 proteins were selected by literature or the like. Furthermore, of the 24 types of candidate histones, PPBP, SPARC, THBS and LTBP1 proteins were added, which showed a significant difference in expression between BRCA mutation-positive normal group and ovarian cancer patient, and a significant difference in expression between BRCA mutation-positive group and BRCA mutation-negative group.
Thus, with the above examples, the following 11 types were finally found as biomarkers for predicting ovarian carcinogenesis after BRCA mutation, and information about these 11 types of biomarkers is shown in table 6 below.
TABLE 6
Industrial applicability
In accordance with the present disclosure, 11 types of biomarkers with altered specificity were found to be expressed in ovarian cancer patients with BRCA gene mutations and their effectiveness was verified, because by measuring the levels of mRNA or protein of 11 types of biomarker genes from subjects with BRCA gene mutations in clinical practice, information on the presence or absence of ovarian carcinogenesis can be provided early, the disease can be prevented, and the biomarkers can be effectively used as target molecules to develop targeted therapeutics against hereditary ovarian cancer accompanied by BRCA gene mutations.
Claims (6)
1. Use of a reagent for measuring the mRNA level of a retinol binding protein 4 (RBP 4) gene or the protein level encoded by the gene, and at least one gene selected from the group consisting of aldolase, fructose-bisphosphate a (aloa), cadherin 2 (CDH 2), mannose receptor type C-1 (MRC 1), pre-platelet basic protein (PPBP), serpin family a member 5 (SERPINA 5), serpin family C member 1 (SERPINC 1), and platelet reactive protein 1 (THBS 1), or the protein level encoded by the at least one gene, in the preparation of a kit for predicting hereditary ovarian carcinogenesis
Wherein the hereditary ovarian cancer is accompanied by a mutation in the BRCA1 or BRCA2 gene.
2. The use of claim 1, wherein the kit further comprises reagents for measuring at least one gene or protein encoded by the at least one gene selected from the group consisting of latent transforming growth factor beta-binding protein 1 (LTBP 1), cysteine-rich secreted acidic protein (SPARC) and serpin family F member 2 (SERPINF 2).
3. Use of an agent for measuring the mRNA level of a retinol binding protein 4 (RBP 4) gene or the protein level encoded by the gene, and at least one gene selected from the group consisting of aldolase, fructose-bisphosphate A (ALDOA), cadherin 2 (CDH 2), mannose receptor type C-1 (MRC 1), pre-platelet basic protein (PPBP), serpin family A member 5 (SERPINA 5), serpin family C member 1 (SERPINC 1), and platelet reactive protein 1 (THBS 1) or the protein level encoded by the at least one gene in the preparation of a composition for use in predicting hereditary ovarian carcinogenesis,
Wherein the hereditary ovarian cancer is accompanied by a mutation in the BRCA1 or BRCA2 gene.
4. The use according to claim 3, wherein the composition further comprises reagents for measuring at least one gene or protein encoded by the at least one gene selected from the group consisting of latent transforming growth factor beta-binding protein 1 (LTBP 1), cysteine-rich secreted acidic protein (SPARC) and serpin family F member 2 (SERPINF 2).
5. The use of claim 1 or 3, wherein the reagents for measuring mRNA levels of at least one gene are sense and antisense primers, or probes, each of which complementarily binds to mRNA of the at least one gene.
6. The use of claim 1 or 3, wherein the reagent for measuring protein levels is an antibody that specifically binds to a protein encoded by the at least one gene.
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