CN118679268A - Use of tumor mutational burden as predictive biomarker for immune checkpoint inhibitor and chemotherapy effectiveness in cancer treatment - Google Patents

Abstract

Disclosed herein are methods of treating an individual having cancer, treating or identifying an individual having cancer to be treated, or stratifying an individual having cancer to be treated based on a tumor mutation burden (TMB) score or a TMB score and a microsatellite instability assessment.

Description

Use of tumor mutational burden as predictive biomarker for immune checkpoint inhibitor and chemotherapy effectiveness in cancer treatment

Cross Reference to Related Applications

The present application claims priority from U.S. provisional application number 63/309,449 filed on day 11 of 2.2022 and U.S. provisional application number 63/335,079 filed on day 26 of 4.2022, the contents of each of these U.S. provisional applications being hereby incorporated by reference in their entirety.

Technical Field

Provided herein are methods of selecting, treating, or identifying, or stratifying an individual having a cancer to be treated based on a Tumor Mutation Burden (TMB) score for an individual having a cancer.

Background

Cancer may be caused by genomic mutations, and cancer cells may accumulate mutations during cancer development and progression. These mutations may be the result of an intrinsic failure of the DNA repair, replication or modification mechanism, or may be the result of exposure to an external mutagen. Certain mutations confer growth advantages to cancer cells and are positively selected in the microenvironment of the tissue in which the cancer is present. Detection of these mutations in patient samples using Next Generation Sequencing (NGS) or other genomic analysis techniques may provide valuable insight into diagnosis, prognosis, and treatment of cancer.

Immune checkpoint inhibitor (ICPI) therapy has been increasingly used to treat metastatic cancer. However, despite success, many clinical trials fail to identify improved survival in patients treated with ICPI and chemotherapy. Thus, there is a need in the art to identify patient groups with comparable or superior results with respect to ICPI without chemotherapy, ICPI in the first line, and ICPI after a first line chemotherapy regimen versus chemotherapy.

Disclosure of Invention

Provided herein are methods for identifying an individual having a cancer to be treated with an immune checkpoint inhibitor therapy, the method comprising: determining a tumor mutation load (TMB) score for a tumor biopsy sample obtained from the individual, wherein if the TMB score is at least a threshold TMB score, the individual is identified as being to be treated with an immune checkpoint inhibitor therapy, wherein the cancer is metastatic urothelial cancer, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC).

Further provided herein are methods of selecting a treatment for an individual having cancer, the method comprising: determining a Tumor Mutation Burden (TMB) score for a tumor biopsy sample obtained from the individual, wherein a TMB score of at least a threshold TMB score identifies the individual as an individual who may benefit from treatment with an immune checkpoint inhibitor therapy, wherein the cancer is metastatic urothelial cancer, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC).

Further provided herein are methods of identifying one or more treatment options for an individual having cancer, the method comprising: (a) Determining a Tumor Mutation Burden (TMB) score for a tumor biopsy sample obtained from the individual; and (b) generating a report comprising the one or more treatment options identified for the individual, wherein a TMB score of at least a threshold TMB score identifies the individual as an individual who may benefit from treatment with an immune checkpoint inhibitor therapy, wherein the cancer is metastatic urothelial cancer, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC).

Further provided herein are methods of stratifying an individual having a cancer to be treated with a therapy, the method comprising: determining a Tumor Mutation Burden (TMB) score for a tumor biopsy sample obtained from the individual; and (a) identifying the individual as a candidate to receive immune checkpoint inhibitor therapy if the TMB score is at least a threshold TMB score, or (b) identifying the individual as a candidate to receive chemotherapy regimen if the TMB score is less than the threshold TMB score; wherein the cancer is metastatic urothelial cancer, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer or non-small cell lung cancer (NSCLC).

In some embodiments of the foregoing method, the method further comprises: and assessing microsatellite instability, wherein the identifying is further based on the cancer being microsatellite instability high (MSI-H). In some embodiments, microsatellite instability is assessed by Next Generation Sequencing (NGS).

In some embodiments of the foregoing methods, the individual is identified as having an increased survival period as compared to treatment with a chemotherapy regimen.

Further provided herein are methods of predicting the survival of an individual having cancer, the method comprising: obtaining knowledge of a tumor mutation load (TMB) score for a tumor biopsy sample obtained from an individual, wherein if the TMB score for the tumor biopsy sample obtained from the individual is at least a threshold TMB score, the individual is predicted to have an increased survival when treated with an immune checkpoint inhibitor as compared to treatment with a chemotherapy regimen, wherein the cancer is metastatic urothelial cancer, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC). Further provided herein are methods of monitoring, assessing or screening an individual for cancer, the method comprising: obtaining knowledge of a tumor mutation load (TMB) score for a tumor biopsy sample obtained from an individual, wherein if the TMB score for the tumor biopsy sample obtained from the individual is at least a threshold TMB score, the individual is predicted to have an increased survival when treated with an immune checkpoint inhibitor as compared to treatment with a chemotherapy regimen, wherein the cancer is metastatic urothelial cancer, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC). In some embodiments of the foregoing method, the further increased lifetime of the method is an increased total lifetime (OS). In some embodiments of the foregoing methods, the further increased lifetime of the method is increased progression free lifetime (PFS). Further provided herein are methods of predicting the survival of an individual having cancer, the method comprising: obtaining knowledge of a tumor mutation load (TMB) score for a tumor biopsy sample obtained from an individual, wherein if the TMB score for the tumor biopsy sample obtained from the individual is at least a threshold TMB score, the individual is predicted to have an increased survival when treated with an immune checkpoint inhibitor as compared to a patient having a TMB score that is less than the threshold TMB score, wherein the cancer is metastatic urothelial cancer, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC). Further provided herein are methods of monitoring, assessing or screening an individual for cancer, the method comprising: obtaining knowledge of a tumor mutation load (TMB) score for a tumor biopsy sample obtained from an individual, wherein if the TMB score for the tumor biopsy sample obtained from the individual is at least a threshold TMB score, the individual is predicted to have an increased survival when treated with an immune checkpoint inhibitor as compared to a patient having a TMB score that is less than the threshold TMB score, wherein the cancer is metastatic urothelial cancer, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC). In some embodiments, the increased lifetime is an increased overall lifetime (OS). In some embodiments, the increased lifetime is an increased progression free lifetime (PFS).

Further provided herein are methods of predicting the duration of a therapeutic response to an individual having cancer, the method comprising: obtaining knowledge of a Tumor Mutation Burden (TMB) score for a tumor biopsy sample obtained from an individual; and comparing the TMB score for the sample to a threshold TMB score, wherein if the TMB score is greater than or equal to the threshold TMB score, then predicting the individual as having a longer duration of treatment response to the immune checkpoint inhibitor; and wherein if the TMB score is less than the threshold TMB score, the subject is predicted to have a shorter duration of therapeutic response to the immune checkpoint inhibitor. In some embodiments, the longer duration of the therapeutic response is one or more of the following: increased progression-free survival (PFS) and total survival (OS) (e.g., as compared to PFS or OS of an individual having a threshold TMB score), and wherein the shorter duration of the therapeutic response is one or more of: reduced PFS and reduced OS (e.g., as compared to PFS or OS of an individual having a threshold TMB score).

Further provided herein are methods for treating an individual having cancer, the method comprising: (a) Determining a Tumor Mutation Burden (TMB) score for a tumor biopsy sample obtained from the individual; and (b) treating the individual with an immune checkpoint inhibitor therapy if the TMB score is at least a threshold TMB score; wherein the cancer is metastatic urothelial cancer, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer or non-small cell lung cancer (NSCLC). In some embodiments, the method further comprises: the microsatellite instability is assessed, wherein (b) is further based on the cancer being microsatellite instability high (MSI-H). In some embodiments, microsatellite instability is assessed by Next Generation Sequencing (NGS).

In some embodiments of the foregoing method, the method further comprises: if the TMB score is less than the threshold TMB score, the individual is treated with chemotherapy. In some embodiments, the chemotherapy comprises one or more of the following or any combination thereof: alkylating agents, aziridines, ethyleneimines, methyl melamines (METHYLAMELAMINE), polyacetyls, camptothecins, bryostatin, kelistatin (callystatin), CC-1065, candidiasis, ceromorphin, carcinomycin, acanthopanaxadiin (eleutherobin), podocarpine, sarcodictyin, spongostatin (spongistatin), nitrogen mustard, nitrosoureas, antibiotics, dactinomycin, bisphosphonates, epothilones, neocarcinomycin chromophores or related pigment protein enediyne antibiotic chromophores, antimetabolites, folic acid analogues, purine analogues, pyrimidine analogues, androgens, anti-adrenoids, folic acid supplements, aldehyde phosphoramide glycosides, aminolevulinic acid, enimine, amsacrine, bestrabucil, bisacodyl, idatrazine (edatraxate), defofamine, dimetidine, mitoquinone, elformithine, irinotecan, epothilone, etodolac, gallium nitrate, hydroxyurea, lentinan, lonidainine, maytansinoids (maytansinoid), mitoguanazone, mitoxantrone, mopidanmol, nitraerine, jelutamine, valicarb (phenamet), pirarubicin, loxohexanthrone, podophylloic acid, 2-ethylhydrazide, procarbazine, PSK polysaccharide complex, ranibixacin, rhizobiacin (rhizoxin), sirzopyran, gepirramine, tenasconic acid, triamcinolone, 2', 2' -trichlorotriethylamine, trichothecene, urethane (urethan), vindesine, dacarbazine, mannatine, dibromomannitol, dibromodulcitol, pipobromine, gacytosine, arabinoside ("Ara-C"), cyclophosphamide, taxane, 6-thioguanine, mercaptopurine, platinum coordination complexes, vinblastine, platinum, etoposide (VP-16), ifosfamide, mitoxantrone, vincristine, vinorelbine, novantrone, teniposide, idatroxas, daunomycin, aminopterin, hilder, sodium ibandronate, irinotecan, topoisomerase inhibitor RFS2000, difluoromethylornithine (DMFO), retinoic acid, capecitabine, carboplatin, procarbazine, plicomycin, gemcitabine, novitide, farnesyl protein transferase inhibitor, trans-platinum (transplatinum).

In some embodiments of the foregoing methods, the threshold TMB score is about 8 mutations/Mb, about 9 mutations/Mb, about 10 mutations/Mb, about 11 mutations/Mb, about 12 mutations/Mb, about 13 mutations/Mb, about 14 mutations/Mb, about 15 mutations/Mb, about 16 mutations/Mb, about 17 mutations/Mb, about 18 mutations/Mb, about 19 mutations/Mb, or about 20 mutations/Mb. In some embodiments of the foregoing methods, the threshold TMB score is about 10 mutations/Mb. In some embodiments of the foregoing methods, the threshold TMB score is 10 mutations/Mb. In some embodiments of the foregoing methods, the threshold TMB score is about 20 mutations/Mb. In some embodiments of the foregoing methods, the threshold TMB score is 20 mutations/Mb. In some embodiments of the foregoing methods, the TMB score is determined based on between about 100kb to about 10Mb of sequenced DNA. In some embodiments of the foregoing methods, the TMB score is determined based on between about 0.8Mb and about 1.1Mb of sequenced DNA.

In some embodiments of the foregoing method, the method further comprises: an individual is treated with an immune checkpoint inhibitor if the TMB score is at least a threshold TMB score.

In some embodiments of the foregoing methods, the cancer is a prostate cancer that is metastatic castration-resistant prostate cancer.

In some embodiments of the foregoing methods, the cancer is NSCLC and the NSCLC is advanced NSCLC (asnsclc).

In some embodiments of the foregoing methods, the cancer is metastatic urothelial cancer.

In some embodiments of the foregoing methods, the cancer is metastatic gastric adenocarcinoma.

In some embodiments of the foregoing methods, the cancer is metastatic endometrial cancer.

In some embodiments of the foregoing methods, the immune checkpoint inhibitor comprises a small molecule inhibitor, an antibody, a nucleic acid, an antibody-drug conjugate, a recombinant protein, a fusion protein, a natural compound, a peptide, a proteolytically targeted chimeric (PROTAC), a cell therapy, a treatment for cancer being tested in a clinical trial, an immunotherapy, or any combination thereof. In some embodiments, the immune checkpoint inhibitor is a PD-1 inhibitor. In some embodiments, the immune checkpoint inhibitor comprises one or more of the following: nivolumab, pembrolizumab, cimetidine Li Shan, or rituximab. In some embodiments, the immune checkpoint inhibitor is a PD-L1 inhibitor. In some embodiments, the immune checkpoint inhibitor comprises one or more of the following: alemtuzumab Avermectin or Avermectin Devaluzumab. In some embodiments, the immune checkpoint inhibitor is a CTLA-4 inhibitor. In some embodiments, the CTLA-4 inhibitor comprises ipilimumab.

In some embodiments of the foregoing methods, the individual has previously received treatment with an anti-cancer therapy for the cancer. In some embodiments, the anti-cancer therapy is one or more of the following or any combination thereof: small molecule inhibitors, chemotherapeutic agents, cancer immunotherapy, antibodies, cell therapies, nucleic acids, surgery, radiation therapy, anti-angiogenic therapy, anti-DNA repair therapy, anti-inflammatory therapy, anti-tumor agents, growth inhibitors, cytotoxic agents.

In some embodiments of the foregoing methods, the individual has not previously received a chemotherapy regimen for the cancer.

In some embodiments of the foregoing methods, the individual has previously received a chemotherapy regimen for the cancer. In some embodiments, the prior chemotherapy regimen comprises one or more of the following or any combination thereof: alkylating agents, aziridines, ethyleneimines, methyl melamines (METHYLAMELAMINE), polyacetyls, camptothecins, bryostatin, kelistatin (callystatin), CC-1065, candidiasis, ceromorphin, carcinomycin, acanthopanaxadiin (eleutherobin), podocarpine, sarcodictyin, spongostatin (spongistatin), nitrogen mustard, nitrosoureas, antibiotics, dactinomycin, bisphosphonates, epothilones, neocarcinomycin chromophores or related pigment protein enediyne antibiotic chromophores, antimetabolites, folic acid analogues, purine analogues, pyrimidine analogues, androgens, anti-adrenoids, folic acid supplements, aldehyde phosphoramide glycosides, aminolevulinic acid, enimine, amsacrine, bestrabucil, bisacodyl, idatrazine (edatraxate), defofamine, dimetidine, mitoquinone, elformithine, irinotecan, epothilone, etodolac, gallium nitrate, hydroxyurea, lentinan, lonidainine, maytansinoids (maytansinoid), mitoguanazone, mitoxantrone, mopidanmol, nitraerine, jelutamine, valicarb (phenamet), pirarubicin, loxohexanthrone, podophylloic acid, 2-ethylhydrazide, procarbazine, PSK polysaccharide complex, ranibixacin, rhizobiacin (rhizoxin), sirzopyran, gepirramine, tenasconic acid, triamcinolone, 2', 2' -trichlorotriethylamine, trichothecene, urethane (urethan), vindesine, dacarbazine, mannatine, dibromomannitol, dibromodulcitol, pipobromine, gacytosine, arabinoside ("Ara-C"), cyclophosphamide, taxane, 6-thioguanine, mercaptopurine, platinum coordination complexes, vinblastine, platinum, etoposide (VP-16), ifosfamide, mitoxantrone, vincristine, vinorelbine, novantrone, teniposide, idatroxas, daunomycin, aminopterin, hilder, sodium ibandronate, irinotecan, topoisomerase inhibitor RFS2000, difluoromethylornithine (DMFO), retinoic acid, capecitabine, carboplatin, procarbazine, plicomycin, gemcitabine, novitide, farnesyl protein transferase inhibitor, trans-platinum (transplatinum).

In some embodiments of the foregoing methods, the immune checkpoint inhibitor therapy is the only anti-cancer therapy indicated or administered for the cancer.

In some embodiments of the foregoing methods, the immune checkpoint inhibitor therapy is a single active agent therapy.

In some embodiments of the foregoing methods, the immune checkpoint inhibitor therapy comprises two or more active agents.

In some embodiments of the foregoing methods, the immune checkpoint inhibitor therapy comprises a first round of immune checkpoint inhibitor and a subsequent round of therapy with a different immune checkpoint inhibitor.

In some embodiments of the foregoing methods, the immune checkpoint inhibitor therapy is a first-line therapy for cancer.

In some embodiments of the foregoing methods, the immune checkpoint inhibitor therapy is a two-wire therapy for cancer.

In some embodiments of the foregoing method, the method further comprises: the individual is treated with additional anti-cancer therapies. In some embodiments, the additional anti-cancer therapy comprises one or more of the following or any combination thereof: small molecule inhibitors, chemotherapeutic agents, cancer immunotherapy, antibodies, cell therapies, nucleic acids, surgery, radiation therapy, anti-angiogenic therapy, anti-DNA repair therapy, anti-inflammatory therapy, anti-tumor agents, growth inhibitors, cytotoxic agents.

In some embodiments of the foregoing methods, the TMB score or microsatellite instability is determined by sequencing. In some embodiments, sequencing comprises using a large-scale parallel sequencing (MPS) technique, whole Genome Sequencing (WGS), whole Exome Sequencing (WES), targeted sequencing, direct sequencing, next Generation Sequencing (NGS), or Sanger sequencing technique. In some embodiments, sequencing comprises: (a) Providing a plurality of nucleic acid molecules obtained from a tumor biopsy sample, wherein the plurality of nucleic acid molecules comprises a mixture of tumor nucleic acid molecules and non-tumor nucleic acid molecules; (b) Optionally, ligating one or more adaptors to one or more nucleic acid molecules from the plurality of nucleic acid molecules; (c) Amplifying nucleic acid molecules from the plurality of nucleic acid molecules; (d) Capturing a nucleic acid molecule from the amplified nucleic acid molecule, wherein the captured nucleic acid molecule is captured from the amplified nucleic acid molecule by hybridization with one or more decoy molecules; (e) At least a portion of the captured nucleic acid molecules are sequenced by a sequencer to obtain a plurality of sequence reads corresponding to one or more genomic loci within a subgenomic interval in the sample. In some embodiments, the adapter comprises one or more of the following: an amplification primer sequence, a flow cell adaptor hybridization sequence, a unique molecular identification sequence, a substrate adaptor sequence, or a sample index sequence. In some embodiments, amplifying the nucleic acid molecule comprises: polymerase Chain Reaction (PCR) techniques, non-PCR amplification techniques, or isothermal amplification techniques are performed. In some embodiments, the one or more decoy molecules comprise one or more nucleic acid molecules, each comprising a region complementary to a region of the captured nucleic acid molecule. In some embodiments, the one or more bait molecules each comprise a capture moiety. In some embodiments, the capture moiety is biotin.

In some embodiments of the foregoing methods, the individual is a human.

In some embodiments of the foregoing methods, if the TMB score is at least a threshold TMB score, the individual is predicted to have an increased time to next treatment as compared to chemotherapy when treated with the immune checkpoint inhibitor (TTNT).

Further provided herein is a kit comprising an immune checkpoint inhibitor and instructions for use according to any of the foregoing methods.

Drawings

Various aspects of at least one example are discussed below with reference to the accompanying drawings, which are not intended to be drawn to scale. The accompanying drawings are included to provide a further understanding of the disclosure and provide a further understanding of the various aspects and examples, and are incorporated in and constitute a part of this specification, but are not intended to be a definition of the limits of the specific examples. The drawings together with the remainder of the specification serve to explain the principles and operation of the described and claimed aspects and examples. In the drawings, each identical or nearly identical component that is illustrated in various figures is represented by a like numeral. For purposes of clarity, not every component may be labeled in every drawing.

Fig. 1A-1B show trend weights (pre-and post-adjustment balances) for patients with urothelial cancer stratified by less than 10 mutations/Mb of TMB (fig. 1A) and at least 10 of TMB (fig. 1B), showing a bias towards chemotherapy (left bias) or immune checkpoint inhibition therapy (right bias).

Fig. 2A-2C are a series of Kaplan-Meier survival curves for urothelial cancer patients receiving 1-line single agent immune checkpoint inhibition therapy, without weighting or adjustment, stratified by tumor mutation burden, and assessed by Progression Free Survival (PFS) (fig. 2A), time To Next Treatment (TTNT) (fig. 2B), and total survival (OS) (fig. 2C). The X-axis was truncated at 36 months for PFS and TTNT and 48 months for OS. The total lifetime estimate is truncated, wherein the risk table is adjusted accordingly.

Fig. 3A-3F are a series of Kaplan-Meier survival curves for urothelial cancer patients showing imbalance-adjusted (i.e., biased) treatment results for 1-line immune checkpoint inhibitor (ICPI) and chemotherapy as assessed by PFS (fig. 3A-3B), TTNT (fig. 3C-3D) and OS (fig. 3E and 3F) and stratified by TMB of less than 10 mutations/Mb and TMB of at least 10 mutations/Mb. The X-axis was truncated at 36 months for PFS and TTNT and 48 months for OS. The total lifetime estimate is truncated, wherein the risk table is adjusted accordingly. ICPI curves reflect the observed unadjusted PFS, TTNT and OS, whereas the chemotherapy group was adjusted by trend weights.

Fig. 4A-4F are a series of Kaplan-Meier survival curves for urothelial cancer patients showing 1-line ICPI versus chemotherapy treatment results without imbalance adjustment (i.e., without trend weights) as assessed by PFS (fig. 4A-4B), TTNT (fig. 4C-4D) and OS (fig. 4E-4F) and stratified by TMB of less than 10 mutations/Mb and TMB of at least 10 mutations/Mb. The X-axis was truncated at 36 months for PFS and TTNT and 48 months for OS. The total lifetime estimate is truncated. ICPI curves reflect the observed unadjusted PFS, TTNT and OS, whereas the chemotherapy group was adjusted by trend weights.

Fig. 5A-5C show assessment of ICPI with TMB and PD-L1 with chemotherapy results as assessed by PFS (fig. 5A), TTNT (fig. 5B) and OS (fig. 5C). 64.3% of the analysis queues have no appreciable PD-L1, and only those with appreciable PD-L1 are represented. With respect to the central vertical axis, the left bias indication favors ICPI and the right bias indication favors chemotherapy.

Fig. 6A-6C show a comparison of the real world analysis cohort with three randomized controlled clinical trials (DANUBE, IMvigor130,130 and KEYNOTE-361). ECOG performance scores are shown in fig. 6A. The real world analysis cohort and three clinical trials were stratified for patient results by TMB (less than 10 mutations/Mb and at least 10 mutations/Mb) as assessed by PFS (fig. 6B) and OS (fig. 6C).

Fig. 7 shows a flow chart for analysis of ICPI and chemotherapy for patients with metastatic gastric adenocarcinoma.

Fig. 8A-8D are a series of Kaplan-Meier survival curves for metastatic gastric adenocarcinoma patients showing 2-line ICPI versus time to next treatment for TMB with less than 10 mutations/Mb (TTNT) (fig. 8A), TTNT with TMB of at least 10 mutations/Mb (fig. 8B), OS with TMB of less than 10 mutations/Mb (fig. 8C), and OS with TMB of at least 10 mutations/Mb (fig. 8D) adjusted for imbalance (i.e., weighted) treatment results.

Fig. 9A-9D are a series of Kaplan-Meier survival curves for metastatic gastric adenocarcinoma patients showing the results of 2-line ICPI versus chemotherapy treatment for TTNT with TMB of less than 10 mutations/Mb (fig. 9A), TTNT with TMB of at least 10 mutations/Mb (fig. 9B), OS with TMB of less than 10 mutations/Mb (fig. 9C), and OS with TMB of at least 10 mutations/Mb (fig. 9D) without adjustment for imbalance (i.e., without applied trend weights).

Fig. 10A-10D are analyses of metastatic gastric adenocarcinoma patients who received 1-line chemotherapy followed by 2-line ICPI. Fig. 10A shows TTNT for individual patients by a stacked horizontal bar graph of each patient with TMB of less than 10 mutations/Mb in the sequential cohort. Fig. 10B shows TTNT for individual patients by a horizontal bar graph of a stack of each patient with TMB of at least 10 mutations/Mb. The MSI status is listed at the right hand side of the bar. Fig. 10C shows the point estimates and confidence intervals from the Cox model of TTNT in the comparative patient. Fig. 10D shows the unadjusted total survival through TMB from the time of initiation of 1-line chemotherapy.

Fig. 11A-11C show point estimates and confidence intervals for a group of metastatic gastric adenocarcinoma patients defined by biomarkers, as assessed by TTNT in a 2-line ICPI and chemotherapy cohort (fig. 11A), OS in a 2-line ICPI and chemotherapy cohort (fig. 11B), and intra-patient TTNT (fig. 11C).

Fig. 12A-12B show KeyNote-061 and real world analysis queues (2L comparison effectiveness queues) compared against their patient ECOG score distribution (fig. 12A) and total survival through TMB subgroups (fig. 12B). KN-061 has less than 1% ECOG 2 and the real world analysis queue has less than 1% ECOG 0, none of which are labeled. The high TMB for the real world analysis queue is a TMB of at least 10 mutations/Mb; for KN-061, a whole exome sequencing assay with a "high" threshold was selected to be consistent with TMB being at least 10 mutations/Mb.

Fig. 13A-13D are a series of Kaplan-Meier survival curves for metastatic gastric adenocarcinoma patients showing the results of treatment with 1-line ICPI versus time to next treatment with chemotherapy (TTNT) for TMB with less than 10 mutations/Mb (fig. 13A), TTNT with TMB with at least 10 mutations/Mb (fig. 13B), OS with TMB with less than 10 mutations/Mb (fig. 13C), and OS with TMB with at least 10 mutations/Mb (fig. 13D) adjusted for imbalance. The X-axis is truncated at 36 months for TTNT and 48 months for OS. The total lifetime estimate is truncated, wherein the risk table is adjusted accordingly. The visualization is adjusted by the trend weights.

Fig. 14A-14D are a series of Kaplan-Meier survival curves for metastatic gastric adenocarcinoma patients showing the results of 1-line ICPI versus time to next treatment for TMB with less than 10 mutations/Mb (TTNT) (fig. 14A), TTNT with TMB of at least 10 mutations/Mb (fig. 14B), OS with TMB of less than 10 mutations/Mb (fig. 14C), and OS with TMB of at least 10 mutations/Mb (fig. 14D) without adjustment for imbalance (i.e., without applied trend weighting). The X-axis is truncated at 36 months for TTNT and 48 months for OS. The total lifetime estimate is truncated, wherein the risk table is adjusted accordingly.

Fig. 15 shows the results of treatment of metastatic castration resistant prostate cancer (mCRPC) patients as assessed by changes in Prostate Specific Antigen (PSA) that received a single agent taxane and stratified by TMB of less than 10 and TMB of at least 10.

Fig. 16 shows the treatment results for mCRPC patients as assessed by changes in PSA receiving single agent anti-PD 1 axis therapy and stratified by TMB of less than 10 and TMB of at least 10.

Fig. 17A-17D are a series of Kaplan-Meier survival curves for mCRPC patients showing the results of treatment of single agent taxane with ICPI for Time To Next Treatment (TTNT) of TMB with less than 10 mutations/Mb (fig. 17A), TTNT of TMB with at least 10 mutations/Mb (fig. 17B), total survival (OS) of TMB with less than 10 mutations/Mb (fig. 17C), and OS with TMB with at least 10 (fig. 17D).

Fig. 18 provides a flow chart illustrating a queue selection scheme used in example 4.

Fig. 19A provides an adjusted Kaplan-Meier plot for real world progression free survival (rwPFS) of NCLC patients treated with ICPI monotherapy. Fig. 19B provides an adjusted Kaplan-Meier plot for rwPFS for NCLC patients treated with ICPI therapy + chemotherapy. Fig. 19C provides an adjusted Kaplan-Meier plot for the real world total survival (rwOS) of NCLC patients treated with ICPI monotherapy. Fig. 19D provides an adjusted Kaplan-Meier plot for rwOS for NCLC patients treated with ICPI therapy + chemotherapy. Results were stratified by TMB <10 and TMB > =10.

Fig. 20A provides an adjusted Kaplan-Meier plot for real world progression free survival (rwPFS) of NCLC patients treated with ICPI monotherapy. Fig. 20B provides an adjusted Kaplan-Meier plot for rwPFS for NCLC patients treated with ICPI therapy + chemotherapy. Fig. 20C provides an adjusted Kaplan-Meier plot for the real world total survival (rwOS) of NCLC patients treated with ICPI monotherapy. Fig. 20D provides an adjusted Kaplan-Meier plot for rwOS for NCLC patients treated with ICPI therapy + chemotherapy. Results were stratified by TMB <20 and TMB > =20.

FIG. 21A provides a Kaplan-Meier plot for rwPFS of patients treated with ICPI-containing regimens. Results were stratified by TMB and PDL1 levels: PDL1<1% and TMB <10 (i.e., PDL 1-/TMB-), PDL1>1% and TMB <10 (i.e., pdl1+/TMB-), PDL1<1% and TMB > =10 (i.e., PDL 1-/tbm+), and PDL1>1% and TMB > =10 (i.e., pdl1+/tmb+). Fig. 21B provides results from a multivariate CoxPh model that detects associations between clinical or genomic features and rwPFS. FIG. 21C provides a Kaplan-Meier plot for rwOS of patients treated with ICPI-containing regimens. Results were stratified by TMB and PDL1 levels: PDL1<1% and TMB <10 (i.e., PDL 1-/TMB-), PDL1>1% and TMB <10 (i.e., pdl1+/TMB-), PDL1<1% and TMB > =10 (i.e., PDL 1-/tbm+), and PDL1>1% and TMB > =10 (i.e., pdl1+/tmb+). Fig. 21D provides results from a multivariate CoxPh model that detects associations between clinical or genomic features and rwOS.

FIG. 22A provides a Kaplan-Meier plot for rwPFS of patients treated with ICPI-containing regimens. Results were stratified by TMB and PDL1 levels: PDL1<1% and TMB <20 (i.e., PDL 1-/TMB-), PDL1>1% and TMB <20 (i.e., pdl1+/TMB-), PDL1<1% and TMB > =20 (i.e., PDL 1-/tbm+), and PDL1>1% and TMB > =20 (i.e., pdl1+/tmb+). Fig. 22B provides results from a multivariate CoxPh model that detects associations between clinical or genomic features and rwPFS. FIG. 22C provides a Kaplan-Meier plot for rwOS of patients treated with ICPI-containing regimens. Results were stratified by TMB and PDL1 levels: PDL1<1% and TMB <20 (i.e., PDL 1-/TMB-), PDL1>1% and TMB <20 (i.e., pdl1+/TMB-), PDL1<1% and TMB > =20 (i.e., PDL 1-/tbm+), and PDL1>1% and TMB > =20 (i.e., pdl1+/tmb+). Fig. 22D provides results from a multivariate CoxPh model that detects associations between clinical or genomic features and rwOS.

Fig. 23A shows the point estimates and 95% confidence intervals for HR (risk ratio) for biomarkers, and shows the therapeutic interactions for different TMB or PDL1 cut-off values for rwPFS. Fig. 23B shows the point estimates and 95% confidence intervals for HR (risk ratio) for biomarkers, and shows the therapeutic interactions for different TMB or PDL1 cut-off values for rwOS. Figure 23C provides Kaplan-Meier plots for rwPFS patients with PD-L1 scores between 1% and 49% treated with ICPI monotherapy or ICPI therapy + chemotherapy. Fig. 23D provides Kaplan-Meier plots for rwPFS of patients treated with ICPI monotherapy or ICPI therapy + chemotherapy with a > = 50% PD-L1 score.

Fig. 24 shows the first 30 altered genes in ICPI monotherapy cohorts (-) and ICPI therapy + chemotherapy cohorts (+). A plurality of: a plurality of changes in the indicated genes; RE: rearranging; CN: copy number variation; SV: short variant mutations (base substitutions or insertions/deletions).

Fig. 25A shows an adjusted Kaplan-Meier plot for rwPFS of patients treated with ICPI monotherapy. Fig. 25B shows an adjusted Kaplan-Meier plot for rwPFS of patients treated with ICPI therapy + chemotherapy. Fig. 25C shows an adjusted Kaplan-Meier plot for rwOS of patients treated with ICPI monotherapy. Fig. 25D shows an adjusted Kaplan-Meier plot for rwOS of patients treated with ICPI therapy + chemotherapy. Results were stratified by PDL1 TPS <1% and PDL1 TPS > =1%.

Fig. 26A shows an adjusted Kaplan-Meier plot for rwPFS of patients treated with ICPI monotherapy. Fig. 26B shows an adjusted Kaplan-Meier plot for rwPFS of patients treated with ICPI therapy + chemotherapy. Fig. 26C shows an adjusted Kaplan-Meier plot for rwOS of patients treated with ICPI monotherapy. Fig. 26D shows an adjusted Kaplan-Meier plot for rwOS of patients treated with ICPI therapy + chemotherapy. Results were stratified by PDL1 TC <50% and PDL1 TC > =50%.

Fig. 27 provides box plots of TMB levels in different PDL1 subgroups to show the association between PDL1 expression and TMB. Kruskal-Wallis test p=0.007, effect size: 0.0046.

Fig. 28A shows a Kaplan-Meier plot for rwPFS of patients treated with ICPI monotherapy. Fig. 28B shows a Kaplan-Meier plot for rwPFS of patients treated with ICPI therapy + chemotherapy. Fig. 28C shows a Kaplan-Meier plot for rwOS of patients treated with ICPI monotherapy. Fig. 28D shows a Kaplan-Meier plot for rwOS of patients treated with ICPI therapy + chemotherapy.

Fig. 29A-B show the pan-tumor assessment of clinical efficacy of TMB to predict the outcome of receiving single agent ICPI. Pan tumor association was assessed using a stratified Cox proportional risk (CoxPH model, labeled "estimate"). Fig. 29A shows the observed temporal correlation of features to the next treatment. Fig. 29B shows the observed correlation of features over the total lifetime.

Fig. 30A-B show the results of each tumor type assessment of clinical efficacy of TMB to predict ICPI for receipt of a single agent. The Cox model adjusted for ECOG (eastern tumor co-tissue score), treatment normal, sex, age, and opioid use is shown by disease type for time to next treatment (fig. 30A) and total survival (fig. 30B).

Fig. 31A-B show the results of each tumor type assessment of clinical efficacy of TMB to predict single agent ICPI for patients with tumors with MSS status. Results for patients with tumors of MSS (microsatellite stabilized) and TMB.gtoreq.10 compared to those with TMB <10 for MSS group. Disease areas are shown for those with a minimum of 5 patients per group. The Cox model adjusted for ECOG, treatment normals, gender, age, and opioid use is shown by disease type for time to next treatment (fig. 31A) and total survival (fig. 31B).

Fig. 32A-B show a pan-tumor assessment of clinical efficacy of TMB to predict outcome of ICPI combination therapy. The pan-tumor association of the observed features was assessed using a layered CoxPH model. The "estimate" indicates the Cox proportional risk. Fig. 32A shows the observed temporal correlation of features to the next treatment. FIG. 32B shows the observed correlation of features over total lifetime.

Detailed Description

Described herein are methods comprising: determining a Tumor Mutation Burden (TMB) score for a sample obtained from an individual having cancer, and comparing the determined TMB score to a threshold TMB score. It has been found that comparing the determined TMB score to a threshold TMB score can help guide treatment decisions, including selecting between a chemotherapy regimen and an immune checkpoint inhibitor (ICPI) therapy.

Thus, described herein are methods for identifying an individual having a cancer to be treated with an immune checkpoint inhibitor therapy, the method comprising: a tumor mutation load (TMB) score is determined for a sample obtained from the individual, wherein the individual is identified as to be treated with an immune checkpoint inhibitor therapy if the TMB score is at least a threshold TMB score. Further described herein are methods of selecting a treatment for an individual having cancer, the method comprising: a Tumor Mutation Burden (TMB) score is determined for a sample obtained from an individual, wherein a TMB score of at least a threshold TMB score identifies the individual as an individual who may benefit from treatment with an immune checkpoint inhibitor therapy. Further described herein are methods of identifying one or more treatment options for an individual having cancer, the method comprising: (a) Determining a Tumor Mutation Burden (TMB) score for a sample obtained from the individual; and (b) generating a report comprising the one or more treatment options identified for the individual, wherein a TMB score of at least a threshold TMB score identifies the individual as an individual who may benefit from treatment with an immune checkpoint inhibitor therapy. Further described herein are methods of stratifying an individual having a cancer to be treated with a therapy, the method comprising: determining a Tumor Mutation Burden (TMB) score for a sample obtained from the individual; And (a) identifying the individual as a candidate to receive immune checkpoint inhibitor therapy if the TMB score is at least a threshold TMB score, or (b) identifying the individual as a candidate to receive chemotherapy regimen if the TMB score is less than the threshold TMB score. Further described herein are methods of predicting the survival of an individual having cancer, the method comprising: a knowledge of a tumor mutation load (TMB) score for a sample obtained from an individual is obtained, wherein if the TMB score for a tumor biopsy sample obtained from the individual is at least a threshold TMB score, the individual is predicted to have an increased survival when treated with an immune checkpoint inhibitor compared to treatment with a chemotherapy regimen. Further described herein are methods of monitoring, assessing or screening an individual for cancer, the method comprising: a knowledge of a tumor mutation load (TMB) score for a sample obtained from an individual is obtained, wherein if the TMB score for the sample obtained from the individual is at least a threshold TMB score, the individual is predicted to have an increased survival when treated with an immune checkpoint inhibitor as compared to treatment with a chemotherapy regimen. Further described herein are methods for treating an individual having cancer, the method comprising: (a) Determining a Tumor Mutation Burden (TMB) score for a sample obtained from the individual; and (b) treating the individual with immune checkpoint inhibitor therapy if the TMB score is at least a threshold TMB score. In any of the provided methods, in addition to determining the TMB score, the method may further comprise: microsatellite instability was assessed. It has been found that assessing microsatellite instability as high in microsatellite instability (MSI-H) or high in non-microsatellite instability, such as low in MSI (MSI-L) or stable Microsatellite (MSS), in combination with TMB that is below or at least a threshold TMB score, can further guide treatment decisions, including selecting between chemotherapy regimens and immune checkpoint inhibitor (ICPI) therapies for individuals with cancer. In some embodiments of these methods, the sample is a tumor biopsy sample. In some embodiments of these methods, the sample is a blood sample.

Further described herein are methods comprising: microsatellite instability was assessed for tumor biopsies obtained from individuals with cancer. Assessing microsatellite instability as high (i.e., MSI-H) or non-MSI-H (such as MSI-L or MSS) may help guide treatment decisions, including selecting between chemotherapy regimens and immune checkpoint inhibitor (ICPI) therapies.

Thus, described herein are methods for identifying an individual having a cancer to be treated with an immune checkpoint inhibitor therapy, the method comprising: microsatellite instability is assessed for a sample obtained from an individual, wherein if the microsatellite instability is MSI-H, the individual is identified as to be treated with an immune checkpoint inhibitor therapy. Further described herein are methods of selecting a treatment for an individual having cancer, the method comprising: microsatellite instability for a sample obtained from an individual is assessed, wherein microsatellite instability for MSI-H identifies the individual as an individual who may benefit from treatment with an immune checkpoint inhibitor therapy. Further described herein are methods of identifying one or more treatment options for an individual having metastatic cancer, the method comprising: (a) Assessing microsatellite instability for a sample obtained from an individual; and (b) generating a report comprising the one or more treatment options identified for the individual, wherein microsatellite instability for MSI-H identifies the individual as an individual who may benefit from treatment with an immune checkpoint inhibitor therapy. Further described herein are methods of stratifying an individual having a cancer to be treated with a therapy, the method comprising: assessing microsatellite instability for a sample obtained from an individual; and (a) identifying the individual as a candidate to receive immune checkpoint inhibitor therapy if the microsatellite instability is MSI-H, or (b) identifying the individual as a candidate to receive chemotherapy regimen if the microsatellite instability is not MSI-H. Further described herein are methods of predicting the survival of an individual having cancer, the method comprising: knowledge of microsatellite instability for a sample obtained from an individual is obtained, wherein if the microsatellite instability for a sample obtained from an individual is MSI-H, the individual is predicted to have an increased survival when treated with an immune checkpoint inhibitor compared to treatment with a chemotherapy regimen. Further described herein are methods of monitoring, assessing or screening an individual for cancer, the method comprising: knowledge of microsatellite instability for a sample obtained from an individual is obtained, wherein if the microsatellite instability for a sample obtained from an individual is MSI-H, the individual is predicted to have an increased survival when treated with an immune checkpoint inhibitor compared to treatment with a chemotherapy regimen. Further described herein are methods for treating an individual having cancer, the method comprising: (a) Assessing microsatellite instability for a sample obtained from an individual; and (b) treating the individual with an immune checkpoint inhibitor therapy if microsatellite instability is assessed as MSI-H. In some embodiments of these methods, the sample is a tumor biopsy sample. In some embodiments of these methods, the sample is a blood sample.

I. General technique

The techniques and procedures described or cited herein are generally well understood by those skilled in the art and are generally employed using conventional methodologies, such as the widely used methodologies described in the following references: sambrook et al, molecular Cloning: A Laboratory Manual, version 3, (2001)Cold Spring Harbor Laboratory Press,Cold Spring Harbor,N.Y.;Current Protocols in Molecular Biology(F.M.Ausubel et al, (2003)); Methods in Enzymology book (ACADEMIC PRESS, inc.): PCR 2:A Practical Approach (M.J.MacPherson, B.D.Hames and g.r.taylor edit (1995)), harlow and Lane edit (1988) Antibodies, A Laboratory Manual, AND ANIMAL CELL Culture (r.i.fresnel, edit (1987)); Oligonucleotide Synthesis (m.j. Gait, edit, 1984); methods in Molecular Biology, humana Press; cell Biology ALaboratory Notebook (J.E.Cellis, eds., 1998) ACADEMIC PRESS; ANIMAL CELL Culture (R.I. Freshney), edit, 1987); introduction to Cell and Tissue Culture (J.P.Mather and P.E.Roberts, 1998) Plenum Press; Cell and Tissue Culture: laboratory Procedures (A.Doyle, J.B.Griffiths and D.G.Newell, eds., 1993-8) J.Wiley and Sons; handbook of Experimental Immunology (d.m.weir and c.c.blackwell, editions); GENE TRANSFER Vectors for MAMMALIAN CELLS (J.M.Miller and M.P.Calos, eds., 1987); PCR The Polymerase Chain Reaction (Mullis et al, eds., 1994); current Protocols in Immunology (J.E. Coligan et al, eds., 1991); short Protocols in Molecular Biology (Wiley and Sons, 1999); immunobiology (c.a. janeway and p.convers, 1997); Antibodies (P.Finch, 1997); antibodies: A PRACTICAL applications (D.Catty., eds., IRL Press, 1988-1989); monoclonal Antibodies: A PRACTICAL Approx (P.shepherd and C.dean, editions, oxford University Press, 2000); using Antibodies A Laboratory Manual (E.Harlow and D.Lane (Cold Spring Harbor Laboratory Press, 1999); The Antibodies (m.zanetti and j.d. capra, editions, harwood Academic Publishers, 1995); PRINCIPLES AND PRACTICE of Oncology (V.T. DeVita et al, eds., J.B. Lippincott Company, 1993).

II. Definition of

Certain terms are defined. Additional terms are defined throughout this specification.

As used herein, the articles "a" and "an" refer to one or more than one (e.g., to at least one) of the grammatical object of the article.

"About" and "approximately" shall generally mean an acceptable degree of error for the measured quantity given the nature or accuracy of the measurement. Exemplary degrees of error are within 20 percent (%) of a given value or range of values, typically within 10%, and more typically within 5%.

It should be understood that the aspects and embodiments of the invention described herein include, consist of, and consist essentially of the recited aspects and embodiments.

The terms "cancer" and "tumor" are used interchangeably herein. These terms refer to the presence of cells having typical characteristics of oncogenic cells, such as uncontrolled proliferation, immortality, metastatic potential, rapid growth and proliferation rate, and certain characteristic morphological characteristics. Cancer cells are typically in the form of tumors, but such cells may be present in the animal alone, or may be non-tumorigenic cancer cells, such as leukemia cells. These terms include solid tumors, soft tissue tumors, or metastatic lesions. As used herein, the term "cancer" includes premalignant as well as malignant cancers.

"Polynucleotide", "nucleic acid" or "nucleic acid molecule" as used interchangeably herein refers to a polymer of nucleotides of any length, and includes DNA and RNA. The nucleotide may be a deoxyribonucleotide, a ribonucleotide, a modified nucleotide or base, and/or an analog thereof, or any substrate that can be incorporated into a polymer by a DNA or RNA polymerase or by a synthetic reaction. Thus, for example, polynucleotides as defined herein include, but are not limited to, single-and double-stranded DNA, DNA comprising single-and double-stranded regions, single-and double-stranded RNA, and RNA comprising single-and double-stranded regions, hybrid molecules comprising DNA and RNA, which may be single-stranded or more typically double-stranded or comprise single-and double-stranded regions. In addition, as used herein, the term "polynucleotide" refers to a triple-stranded region comprising RNA or DNA or both RNA and DNA. Chains in such regions may be from the same molecule or from different molecules. The region may include all of one or more of the molecules, but more typically only regions involving some of the molecules. One of the molecules of the triple helical region is typically an oligonucleotide. The term "polynucleotide" specifically includes cDNA.

Polynucleotides may comprise modified nucleotides, such as methylated nucleotides and analogs thereof. The nucleotide structure, if present, may be modified before or after assembly of the polymer. The nucleotide sequence may be interrupted by non-nucleotide components. The polynucleotide may be further modified after synthesis, such as by conjugation with a label. Other types of modifications include, for example, "caps"; substitution of one or more of the naturally occurring nucleotides with an analog; Internucleotide modifications such as, for example, those with uncharged linkages (e.g., methylphosphonate, phosphotriester, phosphoramidate, carbamate, etc.) as well as charged linkages (e.g., phosphorothioate, phosphorodithioate, etc.), those containing pendant moieties such as, for example, proteins (e.g., nucleases, toxins, antibodies, signal peptides, poly-L-lysine, etc.), those with intercalators (e.g., acridine, psoralen, etc.), those containing chelators (e.g., metals, radioactive metals, boron, oxidative metals, etc.), those containing alkylating agents, those with modified linkages (e.g., Alpha anomeric nucleic acid); And unmodified forms of one or more polynucleotides. Furthermore, any of the hydroxyl groups typically present in the sugar may be replaced, for example, by phosphonate groups, phosphate groups, protected by standard protecting groups, or activated to make additional linkages to additional nucleotides, or may be conjugated to a solid or semi-solid carrier. The 5 'and 3' terminal OH groups may be phosphorylated or partially substituted with amines or organic end capping groups of 1 to 20 carbon atoms. Other hydroxyl groups may also be derivatized as standard protecting groups. Polynucleotides may also contain similar forms of ribose or deoxyribose commonly known in the art, including, for example, 2 '-0-methyl-, 2' -0-allyl-, 2 '-fluoro-or 2' -azido-ribose, carbocyclic sugar analogs, a-anomeric sugars, epimeric sugars (such as arabinose, xylose or lyxose), pyranose, furanose, sedoheptulose, acyclic analogs, and abasic nucleoside analogs (such as methyl ribonucleoside). one or more phosphodiester linkages may be replaced with alternative linking groups. these alternative linking groups include, but are not limited to, the following examples: wherein the phosphate is replaced by P (0) S ("thioester"), P (S) S ("dithioester"), (0) NR ₂ ("amidate"), P (0) R, P (0) OR ', CO OR CH ₂ ("methylal"), wherein each R OR R' is independently H OR a substituted OR unsubstituted alkyl group (1 to 20C), which optionally contains an ether (-0-) linkage, aryl, alkenyl, cycloalkyl, cycloalkenyl, or aralkyl. Not all linkages in a polynucleotide need be identical. The polynucleotide may contain one or more different types of modifications and/or multiple modifications of the same type as described herein. The foregoing description applies to all polynucleotides referred to herein, including RNA and DNA.

The term "detection" includes any means of detection, including direct and indirect detection. As used herein, the term "biomarker" refers to an indicator that is detectable in a sample, e.g., a predictive, diagnostic, and/or prognostic indicator. Biomarkers can be used as indicators of specific subtypes of a disease or disorder (e.g., cancer) characterized by certain characteristics, molecular characteristics, pathological characteristics, histological characteristics, and/or clinical characteristics (e.g., responsiveness to therapy (e.g., immune checkpoint inhibitors)). In some embodiments, the biomarker is a collection of genes or a number of mutations/alterations (e.g., somatic mutations) in a collection of genes. Biomarkers include, but are not limited to, polynucleotides (e.g., DNA and/or RNA), polynucleotide alterations (e.g., polynucleotide copy number alterations, e.g., DNA copy number alterations or other mutations or alterations), polypeptides, polypeptide and polynucleotide modifications (e.g., post-translational modifications), carbohydrates, and/or glycolipid-based molecular markers.

As used herein, "amplification" generally refers to the process of producing multiple copies of a desired sequence. By "multiple copies" is meant at least two copies. "copy" does not necessarily mean complete sequence complementarity or identity with the template sequence. For example, the copy may include nucleotide analogs such as deoxyinosine, intentional sequence alterations (e.g., introduced by primers that include sequences that are hybridizable but not complementary to the template), and/or sequence errors that occur during amplification.

As used herein, "polymerase chain reaction" or "PCR" techniques generally refer to a process in which minute amounts of specific fragments of nucleic acids, RNA, and/or DNA are amplified, for example, as in U.S. patent No. 4,683,195. In general, it is necessary to obtain sequence information at the end of the target region or more so that oligonucleotide primers can be designed; these primers are identical or similar in sequence to the opposite strand of the template to be amplified. The 5' terminal nucleotides of the two primers may be identical to the ends of the amplified material. PCR can be used to amplify specific RNA sequences, specific DNA sequences from total genomic DNA, cdnas transcribed from total cellular RNA, phage or plasmid sequences, and the like. See generally Mullis et al Cold Spring Harbor Symp. Quant. Biol.51:263 (1987) and Erlich editions, PCR Technology (Stockton Press, N.Y., 1989). As used herein, PCR is considered to be one example, but not the only example, of a nucleic acid polymerase reaction method for amplifying a nucleic acid test sample, which includes using known nucleic acids (DNA or RNA) as primers and using a nucleic acid polymerase to amplify or generate specific nucleic acid fragments, or to amplify or generate specific nucleic acid fragments that are complementary to specific nucleic acids.

An "individual response" or "response" may be assessed using any endpoint that indicates a benefit to an individual, including, but not limited to (1) inhibiting disease progression (e.g., cancer progression) to some extent, including slowing or total arrest; (2) reducing tumor size; (3) Inhibit (i.e., reduce, slow or completely stop) infiltration of cancer cells into adjacent peripheral organs and/or tissues; (4) Inhibit (i.e., reduce, slow or stop altogether) the transfer; (5) To some extent, alleviate one or more symptoms associated with a disease or disorder (e.g., cancer); (6) Increasing or extending the length of the lifetime, including total lifetime and progression-free lifetime; and/or (7) reduce mortality at a given point in time after treatment.

An "effective response" of a patient or a "responsiveness" of a patient to a drug treatment and similar expressions refer to conferring a clinical or therapeutic benefit to a patient at risk of or suffering from a disease or disorder, such as cancer. In one embodiment, such benefits include any one or more of the following: prolonged survival (including overall survival and/or progression free survival); generating an objective response (including a complete response or a partial response); or ameliorating signs or symptoms of cancer.

As used herein, "treatment" (and grammatical variations thereof, such as "treatment" or "treatment") refers to a clinical intervention that attempts to alter the natural course of the treated individual, and may be performed for prophylaxis or during clinical pathology. Desirable effects of treatment include, but are not limited to, preventing occurrence or recurrence of a disease, alleviating symptoms, reducing any direct or indirect pathological consequences of a disease, preventing metastasis, reducing the rate of disease progression, improving or alleviating a disease state, and alleviating or improving prognosis.

As used herein, the terms "individual," "patient," or "subject" are used interchangeably and refer to any single animal in need of treatment, e.g., a mammal (including non-human animals such as, for example, dogs, cats, horses, rabbits, zoo animals, cows, pigs, sheep, and non-human primates). In certain embodiments, the patient herein is a human.

As used herein, "administration" means a method of administering a dose of an agent or pharmaceutical composition (e.g., a pharmaceutical composition comprising the agent) to a subject (e.g., a patient). Administration may be by any suitable means, including parenteral, intrapulmonary, and intranasal, and if topical treatment is desired, intralesional administration. Parenteral infusion includes, for example, intramuscular, intravenous, intraarterial, intraperitoneal, or subcutaneous administration. Administration may be by any suitable route, for example by injection, such as intravenous or subcutaneous injection, depending in part on whether administration is brief or chronic. Various dosing schedules are contemplated herein, including but not limited to single or multiple administrations at various points in time, bolus administrations, and pulse infusion.

The term "simultaneously" or "in combination" is used herein to refer to the administration of two or more therapeutic agents, wherein at least portions of the administrations overlap in time. Thus, simultaneous administration includes a dosing regimen when administration of one or more agents is continued after cessation of administration of one or more other agents.

The term "acquire" or "acquire" as used herein refers to obtaining possession of a physical entity or value (e.g., a numerical value) by "directly acquiring" or "indirectly acquiring" the physical entity or value. "directly obtained" means that a certain process (e.g., performing a synthetic or analytical method) is performed to obtain a physical entity or value. "indirectly acquiring" refers to receiving a physical entity or value from another party or source (e.g., a third party laboratory that directly acquires the physical entity or value). Directly acquiring the physical entity includes: a process is performed that includes a physical change in a physical substance (e.g., starting material). Exemplary variations include: the method comprises the steps of producing a physical entity from two or more starting materials, shearing or breaking up the material, separating or purifying the material, combining two or more separate entities into a mixture, performing a chemical reaction comprising breaking or forming covalent or non-covalent bonds. Directly acquiring the value includes: performing a process that includes a physical change in a sample or another substance, e.g., performing an analytical process (sometimes referred to herein as "physical analysis") that includes a physical change in a substance (e.g., a sample, analyte, or reagent), performing an analytical method, e.g., a method that includes one or more of: separating or purifying one substance (e.g., an analyte or fragment or other derivative thereof) from another substance; combining the analyte or fragment or other derivative thereof with another substance (e.g., a buffer, solvent, or reactant); or altering the structure of the analyte or fragment or other derivative thereof, for example, by disrupting or forming covalent or non-covalent bonds between the first and second atoms of the analyte; or by altering the structure of the agent or a fragment or other derivative thereof, for example, by disrupting or forming covalent or non-covalent bonds between the first and second atoms of the agent.

The term "acquire a sequence" or "acquire a read" as used herein refers to obtaining possession of a nucleotide sequence or amino acid sequence by "directly acquiring" or "indirectly acquiring" the sequence or read. "directly acquiring" a sequence or read means performing a certain procedure (e.g., performing a synthetic or analytical method) to obtain the sequence, such as performing a sequencing method (e.g., a Next Generation Sequencing (NGS) method). "indirectly acquiring" a sequence or a read refers to receiving information or knowledge of the sequence from another party or source (e.g., a third party laboratory that directly acquired the sequence) or receiving the sequence. The sequence or read obtained need not be a complete sequence, e.g., sequencing of at least one nucleotide, or obtaining information or knowledge as present in a sample, biopsy, or subject that identifies one or more of the changes disclosed herein constitutes an acquisition order.

Directly acquiring a sequence or read includes: a process is performed that includes a physical change in a physical substance (e.g., a starting material, such as a sample as described herein). Exemplary variations include: producing physical entities from two or more starting materials, shearing or disrupting materials (such as genomic DNA fragments); isolating or purifying the substance (e.g., isolating a nucleic acid sample from a tissue); combining two or more separate entities into a mixture, performing a chemical reaction that includes breaking or forming covalent or non-covalent bonds. Directly acquiring the value includes: a process as described above is performed that includes a physical change in the sample or another substance. The size of the fragment (e.g., the average size of the fragment) may be 2500bp or less, 2000bp or less, 1500bp or less, 1000bp or less, 800bp or less, 600bp or less, 400bp or less, or 200bp or less. In some embodiments, the fragment (e.g., cfDNA) is between about 150bp to about 200bp in size (e.g., between about 160bp to about 170 bp). In some embodiments, the fragment (e.g., a DNA fragment from a liquid biopsy sample) is between about 150bp to about 250bp in size. In some embodiments, the fragment (e.g., a cDNA fragment obtained from RNA in a liquid biopsy sample) is between about 100bp to about 150bp in size.

As used herein, an "alteration" or "altered structure" of a gene or gene product (e.g., a marker gene or gene product) refers to the presence of one or more mutations within the gene or gene product, e.g., mutations that affect the integrity, sequence, structure, amount, or activity of the gene or gene product as compared to a normal or wild-type gene. The alteration may be in terms of amount, structure and/or activity in a cancerous tissue or cell as compared to its amount, structure and/or activity in a normal or healthy tissue or cell (e.g., a control), and associated with a disease state such as cancer. For example, a change associated with cancer or prediction of responsiveness to an anti-cancer therapy may have an altered nucleotide sequence (e.g., mutation), amino acid sequence, chromosomal translocation, intrachromosomal inversion, copy number, expression level, protein activity, epigenetic modification (e.g., methylation or acetylation status, or post-translational modification) in a cancer tissue or cancer cell as compared to a normal, healthy tissue or cell. Exemplary mutations include, but are not limited to, point mutations (e.g., silent, missense, or nonsense), deletions, insertions, inversions, replications, amplifications, translocations, interchhromosomal rearrangements, and intrachromosomal rearrangements. Mutations may be present in the coding or non-coding regions of the gene. In certain embodiments, the alteration is detected as a rearrangement, e.g., a genomic rearrangement (e.g., one or more rearrangements in the 5 '-and/or 3' -UTR) comprising one or more introns or fragments thereof. In certain embodiments, the alteration is associated with (or not associated with) a phenotype, such as a cancerous phenotype (e.g., one or more of cancer risk, cancer progression, cancer treatment, or resistance to cancer treatment). In one embodiment, the alteration (or tumor mutational burden) is associated with one or more of the following: genetic risk factors for cancer, positive treatment response predictors, negative treatment response predictors, positive prognosis factors, negative prognosis factors, or diagnostic factors.

As used herein, the term "indel" refers to an insertion, deletion, or both of one or more nucleotides in a nucleic acid of a cell. In certain embodiments, an indel comprises both an insertion and a deletion of one or more nucleotides, wherein both the insertion and the deletion are in proximity on the nucleic acid. In certain embodiments, the indels cause a net change in the total number of nucleotides. In certain embodiments, the indels cause a net change of about 1 to about 50 nucleotides.

The term "subgenomic interval" as used herein refers to a portion of a genomic sequence. In embodiments, a subgenomic interval can be a single nucleotide position, e.g., where a variant is associated with a tumor phenotype (positive or negative). In embodiments, the subgenomic interval comprises more than one nucleotide position. Such embodiments include sequences of at least 2, 5, 10, 50, 100, 150, or 250 nucleotide positions in length. A subgenomic interval may comprise the entire gene or a portion thereof (e.g., a coding region (or portion thereof), an intron (or portion thereof), or an exon (or portion thereof)). The subgenomic interval may comprise all or a portion of a fragment of a naturally occurring (e.g., genomic DNA) nucleic acid. For example, the subgenomic region may correspond to a fragment of genomic DNA that is subject to a sequencing reaction. In embodiments, the subgenomic interval is a contiguous sequence from a genomic source. In embodiments, the subgenomic interval comprises a sequence that is discontinuous in the genome, e.g., the subgenomic interval in the cDNA may comprise an exon-exon junction due to splicing. In embodiments, the subgenomic interval comprises a tumor nucleic acid molecule. In embodiments, the subgenomic interval comprises a non-tumor nucleic acid molecule.

In embodiments, the subgenomic interval comprises or consists of: a single nucleotide position; an intragenic region or an intergenic region; an exon or an intron or a fragment thereof, typically an exon sequence or a fragment thereof; coding or non-coding regions, e.g., promoters, enhancers, 5 'untranslated regions (5' utrs) or 3 'untranslated regions (3' utrs) or fragments thereof; cDNA or a fragment thereof; SNP; somatic mutation, germ line mutation, or both; alterations, e.g., point or single mutation; deletion mutations (e.g., in-frame deletions, in-gene deletions, total gene deletions); insertion mutations (e.g., intra-gene insertion); inversion mutations (e.g., intrachromosomal inversion); reverse replication mutation; tandem replication (e.g., intrachromosomal tandem replication); translocation (e.g., chromosomal translocation, non-reciprocal translocation); a rearrangement (e.g., a genomic rearrangement (e.g., a rearrangement of one or more introns, a rearrangement of one or more exons, or a combination and/or fragment thereof; rearranged introns may comprise 5 '-and/or 3' -UTRs)); variations in gene copy number; changes in gene expression; changes in RNA levels; or a combination thereof. "copy number of a gene" refers to the number of DNA sequences encoding a particular gene product in a cell. Generally, for a given gene, a mammal has two copies of each gene. Copy number may be increased, for example, by gene amplification or replication, or decreased by deletion.

The term "subject interval" as used herein refers to a subgenomic interval or expressed subgenomic interval. In an embodiment, the subgenomic interval corresponds to the expressed subgenomic interval, meaning that the expressed subgenomic interval comprises a sequence expressed by the corresponding subgenomic interval. In an embodiment, the subgenomic interval and the expressed subgenomic interval are non-corresponding, meaning that the expressed subgenomic interval does not comprise a sequence expressed by the non-corresponding subgenomic interval, but corresponds to a different subgenomic interval. In an embodiment, the subgenomic interval and the expressed subgenomic interval partly correspond, meaning that the expressed subgenomic interval comprises a sequence expressed by the corresponding subgenomic interval and a sequence expressed by a different corresponding subgenomic interval.

As used herein, the term "library" refers to a collection of nucleic acid molecules. In one embodiment, the library comprises a collection of nucleic acid molecules, e.g., a collection of whole genome fragments, subgenomic fragments, cdnas, cDNA fragments, RNAs (e.g., mRNA), RNA fragments, or combinations thereof. Typically, the nucleic acid molecule is a DNA molecule, e.g., genomic DNA or cDNA. The nucleic acid molecule may be fragmented (e.g., sheared or enzymatically prepared) genomic DNA. The nucleic acid molecule comprises a sequence from the subject, and may also comprise sequences that are not derived from the subject, e.g., an adapter sequence, a primer sequence, or other sequences that allow for identification, e.g., a "barcode" sequence. In one embodiment, a portion or all of the library nucleic acid molecules comprise an adapter sequence. The adaptor sequences may be located at one or both ends. The adaptor sequences can be used, for example, in sequencing methods (e.g., NGS methods), for amplification, for reverse transcription, or for cloning into vectors. A library can include a collection of nucleic acid molecules (e.g., target nucleic acid molecules (e.g., tumor nucleic acid molecules, reference nucleic acid molecules, or a combination thereof)). The nucleic acid molecules of the library may be from a single individual. In embodiments, a library may comprise nucleic acid molecules from more than one subject (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, or more subjects), e.g., two or more libraries of different subjects may be combined to form a library comprising nucleic acid molecules from more than one subject. In one embodiment, the subject is a human having or at risk of having a cancer or tumor.

"Complementary" refers to sequence complementarity between regions of two nucleic acid strands or between two regions of the same nucleic acid strand. It is known that adenine residues of a first nucleic acid region are capable of forming specific hydrogen bonds ("base pairing") with residues of a second nucleic acid region antiparallel to the first region if the residues are thymine or uracil. Similarly, it is known that if the residue is guanine, then the cytosine residue of a first nucleic acid strand is capable of base pairing with a residue of a second nucleic acid strand antiparallel to the first strand. The first region of a nucleic acid is complementary to the second region of the same or a different nucleic acid, provided that at least one nucleotide residue of the first region is capable of base pairing with a residue of the second region if the two regions are arranged in an antiparallel manner. In certain embodiments, the first region comprises a first portion and the second region comprises a second portion, whereby at least about 50%, at least about 75%, at least about 90%, or at least about 95% of the nucleotide residues of the first portion are capable of base pairing with the nucleotide residues in the second portion when the first and second portions are arranged in an antiparallel manner. In other embodiments, all nucleotide residues of the first moiety are capable of base pairing with nucleotide residues in the second moiety.

As used herein, "possible" or "increased likelihood" refers to an increased probability that an item, object, thing, or person will appear. Thus, in one example, a subject who is likely to be responsive to a treatment has an increased probability of being responsive to the treatment relative to a reference subject or group of subjects.

"Unlikely" refers to a reduced probability that an event, item, object, thing, or person will occur relative to a reference. Thus, a subject that is unlikely to be responsive to treatment has a reduced probability of being responsive to treatment relative to a reference subject or group of subjects.

As used herein, "next generation sequencing" or "NGS" or "NG sequencing" refers to any sequencing method that determines the nucleotide sequence of any individual nucleic acid molecule (e.g., in single molecule sequencing) or a clonally amplified surrogate (proxy) for an individual nucleic acid molecule in a high throughput manner (e.g., sequencing more than 10 ³, 10 ⁴, 10 ⁵, or more molecules simultaneously). In one embodiment, the relative abundance of nucleic acid species in a library can be estimated by counting the relative number of occurrences of their homologous sequences in the data generated by the sequencing experiments. Next generation sequencing methods are known in the art and are described, for example, in Metzker, m. (2010) Nature Biotechnology Reviews11:31-46, which is incorporated herein by reference. Next generation sequencing can detect variants present in less than 5% or less than 1% of the nucleic acids in the sample.

As referred to herein, "nucleotide number" refers to the identity of a nucleotide occupying or assigned to a nucleotide position. Typical nucleotide numbers include: loss (e.g., absence); additional (e.g., insertion of one or more nucleotides, the identity of which may or may not be included); or present (occupied); a, A is as follows; t is a T; c, performing operation; or G. Other values may be, for example, other than Y, where Y is A, T, G or C; a or X, wherein X is one or both of T, G or C; t or X, wherein X is one or both of A, G or C; g or X, wherein X is one or both of T, A or C; c or X, wherein X is one or both of T, G or A; pyrimidine nucleotides; or purine nucleotides. The nucleotide number can be the frequency of 1 or more (e.g., 2,3, or 4) bases (or other values described herein, e.g., deletions or additions) at the nucleotide position. For example, the nucleotide number may include the frequency of a and the frequency of G at the nucleotide position.

"Or" is used herein to mean and is used interchangeably with the term "and/or" unless the context clearly indicates otherwise. The use of the term "and/or" in some places herein does not mean that the use of the term "or" is not interchangeable with the term "and/or" unless the context clearly indicates otherwise.

As used herein, "control nucleic acid" or "reference nucleic acid" refers to a nucleic acid molecule from a control or reference sample. Typically, it is DNA that does not contain alterations or variations in the gene or gene product, e.g., genomic DNA or cDNA derived from RNA. In certain embodiments, the reference or control nucleic acid sample is a wild-type or non-mutated sequence. In certain embodiments, the reference nucleic acid sample is purified or isolated (e.g., it is removed from its natural state). In other embodiments, the reference nucleic acid sample is from a blood control, a Normal Adjacent Tumor (NAT), or any other non-cancerous sample from the same or a different subject. In some embodiments, the reference nucleic acid sample comprises a normal DNA mixture. In some embodiments, the normal DNA mixture is a process-matched control. In some embodiments, the reference nucleic acid sample has a germline variant. In some embodiments, the reference nucleic acid sample does not have a somatic change, e.g., is used as a negative control.

As used herein, a "threshold" is a value that is a function of the number of reads that need to be present to assign a nucleotide value to a subject interval (e.g., a subgenomic interval or expressed subgenomic interval). For example, it is a function of the number of reads required to assign a particular nucleotide value (e.g., "a") at that nucleotide position in a subgenomic interval to that nucleotide position. The threshold value may be expressed, for example, as (or as a function of) the following: the number of reads (e.g., an integer) or the proportion of reads having that value. For example, if the threshold is X and there are x+1 reads with a nucleotide value of "a", the value of "a" is assigned to a location in the subject interval (e.g., a subgenomic interval or expressed subgenomic interval). The threshold may also be expressed as a function of mutation or variant expectations, mutation frequencies, or bayesian priors. In an embodiment, the mutation frequency will require the number or proportion of reads having a nucleotide number (e.g., a or G) at a position to be referred to as the nucleotide number. In embodiments, the threshold may be a function of mutation expectations (e.g., mutation frequency and tumor type). For example, a variant at a nucleotide position may have a first threshold if the patient has a first tumor type, and a variant at a nucleotide position may have a second threshold if the patient has a second tumor type.

As used herein, "target nucleic acid molecule" refers to a nucleic acid molecule that one desires to isolate from a nucleic acid library. In one embodiment, the target nucleic acid molecule can be a tumor nucleic acid molecule, a reference nucleic acid molecule, or a control nucleic acid molecule, as described herein.

As used herein, a "tumor nucleic acid molecule" or other similar term (e.g., "tumor or cancer-associated nucleic acid molecule") refers to a nucleic acid molecule having a sequence from a tumor cell. The terms "tumor nucleic acid molecule" and "tumor nucleic acid" are sometimes used interchangeably herein. In one embodiment, the tumor nucleic acid molecule comprises a subject interval having a sequence (e.g., a nucleotide sequence) that has a change (e.g., a mutation) associated with a cancerous phenotype. In other embodiments, the tumor nucleic acid molecule comprises a subject interval having a wild-type sequence (e.g., a wild-type nucleotide sequence). For example, from a subject interval of heterozygous or homozygous wild-type alleles present in cancer cells. The tumor nucleic acid molecule can include a reference nucleic acid molecule. Typically, it is DNA from a sample, e.g., genomic DNA or cDNA derived from RNA. In certain embodiments, the sample is purified or isolated (e.g., it is removed from its natural state). In some embodiments, the tumor nucleic acid molecule is cfDNA. In some embodiments, the tumor nucleic acid molecule is ctDNA. In some embodiments, the tumor nucleic acid molecule is DNA from CTCs.

As used herein, "variant" refers to a structure that may exist at a subgenomic interval that may have more than one structure, e.g., an allele at a polymorphic locus.

An "isolated" nucleic acid molecule is a nucleic acid molecule that is separated from other nucleic acid molecules that are present in the natural source of the nucleic acid molecule. In certain embodiments, an "isolated" nucleic acid molecule is free of sequences (such as protein coding sequences) that naturally flank the nucleic acid (i.e., sequences located at the 5 'and 3' ends of the nucleic acid) in the genomic DNA of the organism from which the nucleic acid is derived. For example, in various embodiments, an isolated nucleic acid molecule can contain a nucleotide sequence that flanks a nucleic acid molecule that is naturally located in genomic DNA of a cell from which the nucleic acid is derived that is less than about 5kB, less than about 4kB, less than about 3kB, less than about 2kB, less than about 1kB, less than about 0.5kB, or less than about 0.1 kB. Furthermore, an "isolated" nucleic acid molecule (such as an RNA molecule or a cDNA molecule) may be substantially free of other cellular material or culture medium (e.g., when produced by recombinant techniques) or substantially free of chemical precursors or other chemicals (e.g., when chemically synthesized).

Individuals to be treated, assessed and identified

In certain embodiments, the methods of the present disclosure relate to an individual having cancer and/or a sample obtained from an individual having cancer (such as a tumor biopsy sample and/or a blood sample). In some embodiments, the method provides improved treatment for an individual based on determining TMB scores in a sample obtained from the individual and/or assessing microsatellite instability in the sample. In some embodiments, the methods provide methods of selecting a treatment, identifying one or more treatment options, stratifying an individual to be treated with a therapy, predicting the survival of the individual, and/or monitoring, assessing, or screening for improvement in the individual, each based in part on determining TMB score and/or microsatellite instability of a sample obtained from the individual.

In some embodiments, the individual has cancer. In some embodiments, the individual has received or is receiving treatment for cancer. In some embodiments, the individual is in need of being monitored for cancer progression or regression, e.g., after treatment with a cancer therapy. In some embodiments, the individual needs to be monitored for cancer recurrence. In some embodiments, the individual is at risk of developing cancer. In some embodiments, the individual is suspected of having cancer. In some embodiments, the individual is undergoing a test for cancer. In some embodiments, the individual has a genetic susceptibility to cancer (e.g., has a mutation that increases his or her baseline risk of developing cancer). In some embodiments, the individual has been exposed to an environment (e.g., radiation or chemicals) that increases his or her risk of developing cancer. In some embodiments, the individual needs to be monitored for the progression of cancer. In some embodiments, the individual is in need of first line treatment for cancer. In some embodiments, the individual is in need of two-line therapy for cancer.

In certain embodiments, the sample is from an individual having cancer. Exemplary cancers include, but are not limited to, B-cell cancers, e.g., multiple myeloma, melanoma, breast cancer, lung cancer (such as non-small cell lung cancer or NSCLC), bronchial cancer, colorectal cancer, prostate cancer, pancreatic cancer, gastric cancer, ovarian cancer, bladder cancer, brain or central nervous system cancer, peripheral nervous system cancer, esophageal cancer, cervical cancer, uterine or endometrial cancer, oral or pharyngeal cancer, liver cancer, renal cancer, testicular cancer, biliary tract cancer, small intestine or appendiceal cancer, salivary gland cancer, thyroid cancer, adrenal gland cancer, osteosarcoma, chondrosarcoma, blood tissue cancer, adenocarcinoma, inflammatory myofibroblastic tumor, gastrointestinal stromal tumor (GIST), Colon cancer, multiple Myeloma (MM), myelodysplastic syndrome (MDS), myeloproliferative disease (MPD), acute Lymphoblastic Leukemia (ALL), acute Myeloblastic Leukemia (AML), chronic Myelogenous Leukemia (CML), chronic Lymphoblastic Leukemia (CLL), polycythemia vera, hodgkin's lymphoma, non-hodgkin's lymphoma (NHL), soft tissue sarcoma, fibrosarcoma, myxosarcoma, liposarcoma, osteogenic sarcoma, chordoma, angiosarcoma, endotheliosarcoma, lymphangiosarcoma, lymphangioendotheliosarcoma, synovioma, mesothelioma, ewing's tumor, leiomyosarcoma, leukemia, and the like, Rhabdomyosarcoma, squamous cell carcinoma, basal cell carcinoma, adenocarcinoma, sweat gland carcinoma, sebaceous gland carcinoma, papillary adenocarcinoma, medullary carcinoma, bronchogenic carcinoma, renal cell carcinoma, liver cancer, bile duct carcinoma, choriocarcinoma, seminoma, embryonal carcinoma, wilms' tumor, bladder carcinoma, epithelial carcinoma, glioma, astrocytoma, medulloblastoma, craniopharyngeoma, ependymoma, pineal tumor, angioblastoma, acoustic neuroma, oligodendroglioma, meningioma, neuroblastoma, retinoblastoma, follicular lymphoma, diffuse large B-cell lymphoma, mantle cell lymphoma, hepatocellular carcinoma, thyroid carcinoma, Gastric cancer, head and neck cancer, small cell cancer, primary thrombocytosis, idiopathic myelometaplasia, eosinophilia syndrome, systemic mastocytosis, common eosinophilia, chronic eosinophilic leukemia, neuroendocrine cancer, carcinoid tumor, etc. In some embodiments, the cancer is NSCLC (such as advanced NSCLCL or "aNSCLC", colorectal cancer, cholangiocarcinoma, breast cancer, gastric cancer, melanoma, pancreatic cancer, prostate cancer, ovarian cancer, esophageal cancer, or primary unknown cancer in some embodiments, the cancer is metastatic urothelial cancer in some embodiments, in some embodiments, the cancer is a metastatic gastric adenocarcinoma, in some embodiments, the cancer is a breast cancer, in some embodiments, the cancer is a metastatic endometrial cancer, in some embodiments, the cancer is a prostate cancer, in some embodiments, the cancer is a castration-resistant prostate cancer, in some embodiments, the cancer is a colorectal cancer. In some embodiments, the cancer is lung cancer. In some embodiments, the cancer is melanoma. In some embodiments, the cancer is non-small cell lung cancer (NSCLC). In some embodiments, the NSCLC is advanced NSCLC (asnsclc).

In certain embodiments, the sample is from an individual having a solid tumor, hematological cancer, or metastatic form thereof. In certain embodiments, the sample is obtained from a subject having or at high risk of having cancer. In certain embodiments, the sample is obtained from an individual who has not received therapy for treating cancer, is receiving therapy for treating cancer, or has received therapy for treating cancer, as described herein.

In some embodiments, the cancer is a hematological malignancy (or precancerous lesion). As used herein, hematological malignancy refers to a tumor of hematopoietic or lymphoid tissue, such as a tumor affecting blood, bone marrow, or lymph nodes. Exemplary hematological malignancies include, but are not limited to, leukemia (e.g., acute Lymphoblastic Leukemia (ALL), acute myeloid leukemia (acute myeloid leukemia, AML), chronic Lymphocytic Leukemia (CLL), chronic myelogenous leukemia (chronic myelogenous leukemia, CML), hairy cell leukemia, acute monocytic leukemia (acute monocytic leukemia, AMoL), chronic granulocytic leukemia (chronic myelomonocytic leukemia, CMML), juvenile granulocytic leukemia (juvenile myelomonocytic leukemia, JMML) or large granular lymphocytic leukemia), lymphomas (e.g., AIDS-related lymphomas, cutaneous T-cell lymphomas, hodgkin 'S lymphomas (e.g., classical or nodular lymphocytic-predominant hodgkin' S lymphoma), mycosis fungoides, non-hodgkin 'S lymphomas (e.g., B-cell non-hodgkin' S lymphomas (e.g., burkitt 'S lymphoma, small lymphocytic lymphomas (CLL/SLL), diffuse large B-cell lymphomas, follicular lymphomas, immunoblastic large cell lymphomas, precursor B-lymphoblastic lymphomas or mantle cell lymphomas) or T-cell non-hodgkin' S lymphomas (mycosis fungoides, anaplastic large cell lymphomas or precursor T-lymphoblastic lymphomas), primary central nervous system lymphomas, S zary syndrome,Macroglobulinemia), chronic myeloproliferative neoplasms, langerhans cell histiocytosis (LANGERHANS CELL histiocytosis), multiple myeloma/plasma cell neoplasms, myelodysplastic syndrome, or myelodysplastic/myeloproliferative neoplasms. As used herein, a precancerous lesion refers to a tissue that has not yet been, but is about to become, malignant.

In some embodiments, the individual has previously been treated with an anti-cancer therapy (e.g., one or more anti-cancer therapies (e.g., any of the anti-cancer therapies of the present disclosure)). For example, the sample may be from an individual who has been treated with an anti-cancer therapy comprising one or more of the following: small molecule inhibitors, chemotherapeutic agents, cancer immunotherapy, antibodies, cell therapies, nucleic acids, surgery, radiation therapy, anti-angiogenic therapy, anti-DNA repair therapy, anti-inflammatory therapy, anti-tumor agents, growth inhibitors, or cytotoxic agents. In some embodiments, the individual has previously been treated with chemotherapy or immunooncology therapy. In some embodiments, a post-anticancer therapy sample, e.g., a specimen, is obtained (e.g., collected) for a patient who has previously received treatment with an anticancer therapy. In some embodiments, the post-anticancer therapy sample is a sample obtained (e.g., collected) after completion of the targeted therapy.

In some embodiments, the individual has not previously received or is not currently receiving treatment for cancer. In some embodiments, the individual has not previously received a chemotherapy regimen. In some embodiments, the individual has not received chemotherapy for cancer.

In some embodiments, the individual has previously received or is currently receiving treatment for cancer. In some embodiments, the individual has previously received a chemotherapy regimen. In some embodiments, the individual has previously received chemotherapy for cancer.

In some embodiments, the individual is in need of first line therapy for cancer. In some embodiments, the individual is in need of two-wire therapy for cancer.

In some embodiments, the individual is a human. In some embodiments, the subject is a non-human mammal.

IV. sample and treatment

In certain embodiments, the methods of the present disclosure relate to determining or assessing characteristics (such as TMB score and/or microsatellite instability) of a sample obtained from an individual with cancer. In some embodiments, the sample is associated with a cancer to be treated or assessed. In some embodiments, the sample is from a solid tumor (e.g., a tumor biopsy sample). In some embodiments, the sample is from a liquid sample (e.g., a liquid biopsy sample). In some embodiments, the sample is from a blood sample.

In some embodiments, the sample is associated with: cancers that are B cell cancers (e.g., multiple myeloma), melanoma, breast cancer, lung cancer (such as non-small cell lung cancer or NSCLC, including, for example, advanced NSCLC), bronchial cancer, colorectal cancer, prostate cancer, pancreatic cancer, gastric cancer, ovarian cancer, bladder cancer, brain or central nervous system cancer, peripheral nervous system cancer, esophageal cancer, cervical cancer, uterine or endometrial cancer, oral or pharyngeal cancer, liver cancer, renal cancer, testicular cancer, biliary tract cancer, small intestine or appendiceal cancer, salivary gland cancer, thyroid cancer, adrenal cancer, osteosarcoma, chondrosarcoma, blood tissue cancer, cancer of the liver, cancer of the stomach, or cancer of the liver, kidney, testicular cancer, biliary tract, small intestine or appendiceal cancer, salivary gland cancer, thyroid cancer, adrenal gland cancer, osteosarcoma, chondrosarcoma, cancer of the blood tissue cancer, Adenocarcinoma, inflammatory myofibroblastic tumor, gastrointestinal stromal tumor (GIST), colon cancer, multiple Myeloma (MM), myelodysplastic syndrome (MDS), myeloproliferative disorder (MPD), acute Lymphoblastic Leukemia (ALL), acute Myelogenous Leukemia (AML), and Chronic Myelogenous Leukemia (CML), chronic Lymphocytic Leukemia (CLL), polycythemia vera, hodgkin's lymphoma, non-Hodgkin's lymphoma (NHL), soft tissue sarcoma, fibrosarcoma, myxosarcoma, liposarcoma, osteogenic sarcoma, chordoma, angiosarcoma, endothelial sarcoma, and, Lymphosarcoma, lymphoendotheliosarcoma, synovioma, mesothelioma, ewing's tumor, leiomyosarcoma, rhabdomyosarcoma, squamous cell carcinoma, basal cell carcinoma, adenocarcinoma, sweat gland carcinoma, sebaceous gland carcinoma, papillary adenocarcinoma, medullary carcinoma, bronchogenic carcinoma, renal cell carcinoma, liver cancer, cholangiocarcinoma, choriocarcinoma, seminoma, embryonal carcinoma, wilms' tumor, bladder carcinoma, epithelial carcinoma, glioma, astrocytoma, neuroblastoma, craniopharyngeoma, ependymoma, pineal tumor, angioblastoma, auditory neuroma, oligodendroglioma, meningioma, neuroblastoma, retinoblastoma, Follicular lymphoma, diffuse large B-cell lymphoma, mantle cell lymphoma, hepatocellular carcinoma, thyroid carcinoma, gastric cancer, head and neck cancer, small cell carcinoma, primary thrombocytosis, agnostic myeloid metaplasia, hypereosinophilia syndrome, systemic mastocytosis, common hypereosinophilia, chronic eosinophilic leukemia, neuroendocrine carcinoma, carcinoid tumor, etc. In some embodiments, the cancer is NSCLC (e.g., advanced NSCLC), colorectal cancer, cholangiocarcinoma, breast cancer, gastric cancer, melanoma, pancreatic cancer, prostate cancer, ovarian cancer, esophageal cancer, or primary focus unknown cancer. In some embodiments, the tumor biopsy sample is associated with metastatic urothelial cancer. In some embodiments, the sample is associated with gastric adenocarcinoma. In some embodiments, the sample is associated with breast cancer. In some embodiments, the sample is associated with metastatic endometrial cancer. In some embodiments, the sample is associated with prostate cancer. In some embodiments, the sample is associated with metastatic castration-resistant prostate cancer. in some embodiments, the sample is associated with colorectal cancer. In some embodiments, the sample is associated with lung cancer. In some embodiments, the lung cancer is NSCLC. In some embodiments, the NSCLC is advanced NSCLC. In some embodiments, the sample is associated with melanoma.

In some embodiments, the sample comprises nucleic acids, e.g., DNA, RNA, or both. In certain embodiments, the sample comprises one or more nucleic acids from cancer. In certain embodiments, the sample further comprises one or more non-nucleic acid components from the tumor, e.g., cells, proteins, carbohydrates, or lipids. In certain embodiments, the sample further comprises one or more nucleic acids from a non-tumor cell or tissue.

In some embodiments, the sample comprises one or more nucleic acids (e.g., DNA, RNA, or both) from the following: pre-malignant or malignant cells, cells from solid tumors, soft tissue tumors or metastatic lesions, cells from hematological cancers, histologically normal cells, circulating Tumor Cells (CTCs), or combinations thereof. In some embodiments, the sample comprises one or more cells selected from the group consisting of: pre-malignant or malignant cells, cells from solid tumors, soft tissue tumors or metastatic lesions, cells from hematological cancers, histologically normal cells, circulating Tumor Cells (CTCs), or combinations thereof.

In some embodiments, the sample comprises RNA (e.g., mRNA), DNA, circulating tumor DNA (ctDNA), cell-free DNA (cfDNA), or cell-free RNA (cfRNA) from cancer. In some embodiments, the sample comprises cell-free DNA (cfDNA). In some embodiments, cfDNA includes DNA from healthy tissue (e.g., non-diseased cells) or tumor tissue (e.g., tumor cells). In some embodiments, cfDNA from tumor tissue comprises circulating tumor DNA (ctDNA). In some embodiments, the sample further comprises a non-nucleic acid component, e.g., a cell, protein, carbohydrate, or lipid, e.g., from a tumor.

In some embodiments, the sample is a liquid sample comprising blood, plasma, serum, cerebrospinal fluid, sputum, stool, urine, or saliva. In some embodiments, the sample comprises blood, plasma, or serum. In certain embodiments, the sample comprises cerebrospinal fluid (CSF). In certain embodiments, the sample comprises pleural effusion. In certain embodiments, the sample comprises ascites fluid. In certain embodiments, the sample comprises urine.

In some embodiments, the sample comprises or is derived from a blood sample, e.g., is or is derived from a peripheral whole blood sample. In some embodiments, the peripheral whole blood sample is collected in, for example, two tubes, e.g., with about 8.5ml of blood per tube. In some embodiments, the peripheral whole blood sample is collected by venipuncture (e.g., according to CLSI H3-A6). In some embodiments, the blood is mixed immediately after collection, for example, by gently tumbling, for example, about 8 to 10 times. In some embodiments, flipping is performed by, for example, a complete (e.g., full) 180 ° rotation of the wrist. In some embodiments, the blood sample is delivered on the day of collection, for example, at ambient temperature (e.g., 43°f to 99°f or 6 ℃ to 37 ℃). In some embodiments, the blood sample is not frozen or refrigerated. In some embodiments, the collected blood sample is maintained (e.g., stored) at 43°f to 99°f or 6 ℃ to 37 ℃.

In some embodiments of the methods described herein, the method further comprises: isolating nucleic acid from a sample as described herein. In some embodiments of the methods described herein, the method comprises: isolating nucleic acids from the sample to provide an isolated nucleic acid sample. In an embodiment, the method comprises: isolating nucleic acids from the control to provide an isolated control nucleic acid sample. In an embodiment, a method further comprises: samples without detectable nucleic acid were knocked out.

In some embodiments of the methods described herein, the method further comprises: obtaining a value for the yield of nucleic acid in the sample, and comparing the obtained value to a reference standard, e.g., wherein nucleic acid is amplified prior to library construction if the obtained value is less than the reference standard. In an embodiment, a method further comprises: obtaining a value for the size of the nucleic acid fragment in the sample, and comparing the obtained value to a reference standard (e.g., a size of at least 300bp, 600bp, or 900bp, e.g., an average size). The parameters described herein may be adjusted or selected in response to the determination.

In some embodiments, the nucleic acid is isolated when the nucleic acid is partially purified or substantially purified. In some embodiments, the nucleic acid is isolated when purified away from other cellular components (e.g., proteins, carbohydrates, or lipids) or other contaminants by standard techniques.

Protocols for DNA isolation from a sample are known in the art, e.g. as provided in example 1 of international patent application publication No. WO 2012/092426. Additional methods for isolating nucleic acids (e.g., DNA) from formaldehyde or paraformaldehyde fixed paraffin-embedded (FFPE) tissue are disclosed, for example, in Cronin M. Et al, (2004) Am J Pathol.164 (1): 35-42; masuda N.et al, (1999) Nucleic Acids Res.27 (22): 4436-4443; specht K, et al ,(2001)Am JPathol.158(2):419–429、Ambion RecoverAll^TMTotal Nucleic Acid Isolation Protocol(Ambion, catalog number AM1975, month 9 of 2008),16FFPE Plus LEV DNA Purification Kit Technical Manual (Promega Literature # TM349, month 2 2011),FFPE DNA KIT Handbook (OMEGA bio-tek, norcross, GA, product numbers D3399-00, D3399-01 and D3399-02, 6 th 2009) andDNA FFPE Tissue Handbook (Qiagen, catalog number 37625, 10 months of 2007). RecoverAll ^TM Total Nucleic Acid Isolation Kit the paraffin-embedded samples were lysed using xylene at elevated temperature and the nucleic acids were captured using a glass fiber filter.16FFPE Plus LEV DNA Purification Kit and16 Instruments were used together to purify genomic DNA from 1 μm to 10 μm sections of FFPE tissue. The DNA was purified using silica coated paramagnetic particles (PMP) and eluted at low elution volumes.FFPE DNA kits use spin columns and buffer systems to isolate genomic DNA.DNA FFPE Tissue Kit use ofDNA Micro technology to purify genomic and mitochondrial DNA. Protocols for DNA isolation from blood are disclosed, for example16 LEV Blood DNA Kit and Maxwell 16 Buccal Swab LEV DNA Purification Kit Technical Manual (Promega Literature #tm333, 2011, 1 month, 1 day).

Protocols for RNA isolation are disclosed, for example, in16Total RNA Purification Kit Technical Bulletin (Promega Literature #TB351, 8 months 2009).

Isolated nucleic acids (e.g., genomic DNA) can be fragmented or sheared by practicing conventional techniques. For example, genomic DNA may be fragmented by physical shearing methods, enzymatic cleavage methods, chemical cleavage methods, and other methods well known to those skilled in the art. The nucleic acid library may contain all or substantially all of the complexity of the genome. The term "substantially all" in this context means that in practice there may be some possibility of unnecessary loss of genome complexity during the initial steps of the procedure. The methods described herein are also useful in cases where the nucleic acid library is part of the genome (e.g., where the complexity of the genome is reduced by design). In some embodiments, any selected portion of the genome can be used with the methods described herein. In certain embodiments, the entire exome or a subset thereof is isolated.

In certain embodiments, the method further comprises: nucleic acids are isolated from a sample to provide a library (e.g., a nucleic acid library as described herein). In certain embodiments, the sample comprises the entire genome, subgenomic fragments, or both. The isolated nucleic acids can be used to prepare a nucleic acid library. Protocols for isolation and preparation of libraries from whole genomes or subgenomic fragments are known in the art (e.g., genomic DNA sample preparation kit of Illumina). In certain embodiments, genomic or subgenomic DNA fragments are isolated from a sample of a subject (e.g., a sample as described herein).

In still other embodiments, the nucleic acid used to generate the library comprises RNA or cDNA derived from RNA. In some embodiments, the RNA comprises total cellular RNA. In other embodiments, some of the abundant RNA sequences (e.g., ribosomal RNAs) have been depleted. In some embodiments, the poly (a) tail mRNA fraction in the total RNA preparation has been enriched. In some embodiments, the cDNA is produced by a randomly primed cDNA synthesis method. In other embodiments, cDNA synthesis is initiated at the poly (A) tail of the mature mRNA by priming via an oligo (dT) -containing oligonucleotide. Methods for depletion, poly (A) enrichment and cDNA synthesis are well known to those skilled in the art.

In other embodiments, the nucleic acid is fragmented or sheared by physical or enzymatic methods, and optionally ligated to synthetic adaptors, size-selected (e.g., by preparative gel electrophoresis), and amplified (e.g., by PCR). Alternative methods for DNA cleavage are known in the art, for example as described in example 4 of international patent application publication No. WO 2012/092426. For example, alternative DNA shearing methods may be more automatable and/or more efficient (e.g., with degraded FFPE samples). Alternative methods to DNA cleavage methods can also be used to avoid ligation steps during library preparation.

In other embodiments, the isolated DNA (e.g., genomic DNA) is fragmented or sheared. In some embodiments, the library comprises less than 50% genomic DNA, such as a subfraction of genomic DNA, which is a simplified representation or defined portion of the genome, e.g., which has been sub-fractionated by other means. In other embodiments, the library comprises all or substantially all genomic DNA.

In other embodiments, fragmented and adaptor-ligated nucleic acid sets are used without explicit size selection or amplification prior to hybrid selection. In some embodiments, the nucleic acid is amplified by specific or non-specific nucleic acid amplification methods well known to those of skill in the art. In some embodiments, the nucleic acid is amplified, for example, by a whole genome amplification method (such as random primed strand displacement amplification).

For example, when the amount of source DNA or RNA is limited (e.g., even after whole genome amplification), a small amount of nucleic acid may be used to perform the methods described herein. In one embodiment, the nucleic acid comprises less than about 5 μg, 4 μg, 3 μg, 2 μg, 1 μg, 0.8 μg, 0.7 μg, 0.6 μg, 0.5 μg, or 400ng, 300ng, 200ng, 100ng, 50ng, 10ng, 5ng, 1ng or less of the nucleic acid sample. For example, one can typically start from 50ng to 100ng of genomic DNA. However, if one were to amplify genomic DNA (e.g., using PCR) prior to the hybridization step (e.g., solution hybridization), one could start with a smaller amount. Thus, it is possible, but not necessary, to amplify genomic DNA prior to hybridization (e.g., solution hybridization).

In some embodiments, sequencing comprises: providing a plurality of nucleic acid molecules obtained from a sample; amplifying nucleic acid molecules from the plurality of nucleic acid molecules; capturing a nucleic acid molecule from the amplified nucleic acid molecule; and sequencing the captured nucleic acid molecules by a sequencer to obtain a plurality of sequence reads corresponding to one or more genomic loci within a subgenomic interval in the sample. In some embodiments, the plurality of nucleic acid molecules comprises a mixture of tumor nucleic acid molecules and non-tumor nucleic acid molecules.

In some embodiments, amplification of the nucleic acid molecule is performed by Polymerase Chain Reaction (PCR) techniques, non-PCR amplification techniques, or isothermal amplification techniques.

In some embodiments, sequencing further comprises: ligating one or more adaptors to one or more nucleic acid molecules from the plurality of nucleic acid molecules. In some embodiments, the adapter comprises one or more of the following: an amplification primer sequence, a flow cell adaptor hybridization sequence, a unique molecular identification sequence, a substrate adaptor sequence, or a sample index sequence.

In some embodiments, for example, solution hybridization is used to isolate nucleic acid molecules from a library, thereby providing a library trap. Library traps or subsets thereof may be sequenced. Thus, the methods described herein may further comprise: library captures are analyzed. In some embodiments, library traps are analyzed by a sequencing method (e.g., a next generation sequencing method as described herein). In some embodiments, the method comprises: library traps are isolated by solution hybridization and nucleic acid sequencing is performed on the library traps. In certain embodiments, library captures are resequenced.

In some embodiments, the captured nucleic acid molecules are captured from the amplified nucleic acid molecules by hybridization to one or more decoy molecules. In some embodiments, the one or more decoy molecules comprise one or more nucleic acid molecules, each comprising a region complementary to a region of the captured nucleic acid molecule. In some embodiments, the one or more bait molecules each comprise a capture moiety. In some embodiments, the capture moiety is biotin.

Any sequencing method known in the art may be used. Sequencing of nucleic acids (e.g., isolated by solution hybridization) is typically performed using Next Generation Sequencing (NGS). Sequencing methods suitable for use herein are described in the art, for example, as described in international patent application publication No. WO 2012/092426. In some embodiments, sequencing is performed using a large-scale parallel sequencing (MPS) technique, whole Genome Sequencing (WGS), whole Exome Sequencing (WES), targeted sequencing, direct sequencing, next Generation Sequencing (NGS), or Sanger sequencing technique.

In some embodiments, sequencing comprises: changes present in the genome, whole exome or transcriptome of the individual are detected. In some embodiments, sequencing includes DNA and/or RNA sequencing, e.g., targeted DNA and/or RNA sequencing. In some embodiments, sequencing comprises detecting a change (e.g., an increase or decrease) in the level of a gene or gene product, e.g., a change in the expression of a gene or gene product described herein.

Optionally, sequencing may include the step of enriching the sample for target RNA. In other embodiments, sequencing includes the step of depleting the sample of certain high abundance RNAs (e.g., ribosomal or globulin RNAs). The RNA sequencing methods may be used alone or in combination with the DNA sequencing methods described herein. In one embodiment, the sequencing includes a DNA sequencing step and an RNA sequencing step. The method may be performed in any order. For example, the method may include: altered expression as described herein is confirmed by RNA sequencing, e.g., by mutation or fusion detected by the DNA sequencing methods of the invention. In other embodiments, sequencing comprises: an RNA sequencing step is performed, followed by a DNA sequencing step.

In some embodiments, the sample is associated with a cancer that has not previously been treated with an anti-cancer therapy. In some embodiments, the sample is associated with a cancer that has not previously been treated with chemotherapy. In some embodiments, the sample is associated with a cancer that has been previously treated with an anti-cancer therapy. In some embodiments, the sample is associated with a cancer that has been previously treated with chemotherapy.

In some embodiments, the sample is a mammalian sample. In some embodiments, the sample is a human sample. In some embodiments, the sample is a non-human mammalian sample.

V. method for determining tumor mutation burden

Tumor Mutational Burden (TMB) is broadly the number of somatic mutations per megabase of a genomic region. It has been found that TMB scores (which may be expressed as mutations per megabase, i.e., mutations/Mb), for example, may inform treatment decisions, including in some embodiments: whether to administer immune checkpoint inhibitor therapy to the patient if the TMB score is at least a threshold TMB score, or to administer a chemotherapy regimen if the TMB score is below the threshold TMB score. TMB scores may be determined using a variety of techniques, including Next Generation Sequencing (NGS) techniques.

In some embodiments, the methods of the present disclosure include: a Tumor Mutation Burden (TMB) score in a sample, such as a tumor sample, is determined. In some embodiments, the TMB score is a blood TMB (bTMB) score. In some embodiments, the TMB score is an organization TMB score (tTMB score).

In some embodiments, the TMB score is determined by sequencing. In some embodiments, the TMB score is determined by sequencing using high throughput sequencing techniques, such as Next Generation Sequencing (NGS), NGS-based methods, or NGS-derived methods. In some embodiments, the NGS method is selected from Whole Genome Sequencing (WGS), whole Exome Sequencing (WES), or comprehensive genomic analysis (CGP). In some embodiments, sequencing comprises: a panel of cancer genes was sequenced. In some embodiments, the TMB score reflects the number of non-synonymous mutations (such as missense mutations or nonsense mutations) in the sequence. In some embodiments, the TMB score is determined by: matched tumor biopsy sample sequences were normalized to germline sequences to exclude genetic germline mutations.

As used herein, a "threshold TMB score" refers to a predetermined TMB score with which a measured TMB score (i.e., a TMB score determined in a sample from an individual with cancer) is compared. In certain embodiments, a comparison of the determined TMB score to a threshold TMB score is used to inform a treatment decision or identify a treatment option for the individual. In some embodiments, the threshold TMB score is at least 8 mutations/Mb, such as at least any one of: about 9 mutations/Mb, about 10 mutations/Mb, about 11 mutations/Mb, about 12 mutations/Mb, about 13 mutations/Mb, about 14 mutations/Mb, about 15 mutations/Mb, about 16 mutations/Mb, about 17 mutations/Mb, about 18 mutations/Mb, about 19 mutations/Mb, about 20 mutations/Mb, about 21 mutations/Mb, about 22 mutations/Mb, about 23 mutations/Mb, about 24 mutations/Mb, about 25 mutations/Mb, about, About 26 mutations/Mb, about 27 mutations/Mb, about 28 mutations/Mb, about 29 mutations/Mb, about 30 mutations/Mb, about 31 mutations/Mb, about 32 mutations/Mb, about 33 mutations/Mb, about 34 mutations/Mb, about 35 mutations/Mb, about 36 mutations/Mb, about 37 mutations/Mb, about 38 mutations/Mb, about 39 mutations/Mb, about 40 mutations/Mb, about 41 mutations/Mb, about 42 mutations/Mb, about 43 mutations/Mb, about 44 mutations/Mb, about 45 mutations/Mb, about 46 mutations/Mb, about 47 mutations/Mb, about 48 mutations/Mb, about 49 mutations/Mb, or about 50 mutations/Mb. In some embodiments, the threshold TMB score is about 8 mutations/Mb, such as at least any one of: about 9 mutations/Mb, about 10 mutations/Mb, about 11 mutations/Mb, about 12 mutations/Mb, about 13 mutations/Mb, about 14 mutations/Mb, about 15 mutations/Mb, about 16 mutations/Mb, about 17 mutations/Mb, about 18 mutations/Mb, about 19 mutations/Mb, about 20 mutations/Mb, about 21 mutations/Mb, about 22 mutations/Mb, about 23 mutations/Mb, about 24 mutations/Mb, about 25 mutations/Mb, about, About 26 mutations/Mb, about 27 mutations/Mb, about 28 mutations/Mb, about 29 mutations/Mb, about 30 mutations/Mb, about 31 mutations/Mb, about 32 mutations/Mb, about 33 mutations/Mb, about 34 mutations/Mb, about 35 mutations/Mb, about 36 mutations/Mb, about 37 mutations/Mb, about 38 mutations/Mb, about 39 mutations/Mb, about 40 mutations/Mb, about 41 mutations/Mb, about 42 mutations/Mb, about 43 mutations/Mb, about 44 mutations/Mb, about 45 mutations/Mb, about 46 mutations/Mb, about 47 mutations/Mb, about 48 mutations/Mb, about 49 mutations/Mb, or about 50 mutations/Mb. In some embodiments, the threshold TMB score is about 10 mutations/Mb. In some embodiments, the threshold TMB score is 10 mutations/Mb. In some embodiments, the threshold TMB score is a "high tumor mutation load score," e.g., a TMB score of at least about 10 mutations/Mb or greater, such as any one or more of at least about 15 mutations/Mb, about 20 mutations/Mb, about 25 mutations/Mb, about 30 mutations/Mb, about 35 mutations/Mb, about 40 mutations/Mb, about 45 mutations/Mb, about 50 mutations/Mb.

As used herein, the terms "solid tumor TMB score," "tissue TMB score," and "tTMB score" are used interchangeably and refer to a numerical value reflecting the number of somatic mutations detected in a tumor biopsy sample (e.g., a solid tumor biopsy sample) obtained from an individual (e.g., an individual at risk of having cancer or having cancer). The tTMB score may be measured, for example, on a whole genome or exome basis, or on a subset (e.g., a predetermined set) of the genome or exome. In some embodiments, tTMB scores may be measured based on intergenic sequences. In some embodiments, tTMB scores measured on a genomic or exome basis may be extrapolated to determine a whole genome or exome tTMB score. In certain embodiments, the predetermined set of genes does not comprise the entire genome or the entire exome. In other embodiments, the subgenomic interval set does not comprise the entire genome or the entire exome. In some embodiments, the predetermined gene set comprises a plurality of genes that are associated in mutant form with an effect on cell division, growth, or survival, or with cancer. In some embodiments, the predetermined gene set comprises at least about 50 or more, about 100 or more, about 150 or more, about 200 or more, about 250 or more, about 300 or more, about 350 or more, about 400 or more, about 450 or more, or about 500 or more genes. In some embodiments, the predetermined gene set covers about 1Mb (e.g., about 1.1Mb, e.g., about 1.125 Mb). In some embodiments, tTMB scores are determined from measuring the number of somatic mutations in cell-free DNA (cfDNA) in the sample. In some embodiments, the tTMB score is determined from measuring the number of somatic mutations in circulating tumor DNA (ctDNA) in the sample. In some embodiments, the number of somatic mutations is the number of Single Nucleotide Variants (SNVs) counted, or the sum of the number of SNVs and the number of indel mutations counted. In some embodiments, tTMB score refers to the number of somatic mutations accumulated in a tumor.

As used herein, the terms "hematological tumor burden score (blood tumor mutational burden score)", "hematological tumor burden score (blood tumor mutation burden score)", and "bTMB score" (each of which may be used interchangeably) refer to a numerical value reflecting the number of somatic mutations detected in a blood sample (e.g., a whole blood sample, a plasma sample, a serum sample, or a combination thereof) obtained from an individual (e.g., an individual at risk of having cancer or having cancer). The bTMB score may be measured, for example, on a whole genome or exome basis, or on a subset (e.g., a predetermined set) of the genome or exome. In certain embodiments, bTMB scores may be measured based on intergenic sequences. In some embodiments, bTMB scores measured on a genomic or exome basis may be extrapolated to determine a whole genome or exome bTMB score. In certain embodiments, the predetermined set of genes does not comprise the entire genome or the entire exome. In other embodiments, the subgenomic interval set does not comprise the entire genome or the entire exome. In some embodiments, the predetermined gene set comprises a plurality of genes that are associated in mutant form with an effect on cell division, growth, or survival, or with cancer. In some embodiments, the predetermined gene set comprises at least about 50 or more, about 100 or more, about 150 or more, about 200 or more, about 250 or more, about 300 or more, about 350 or more, about 400 or more, about 450 or more, or about 500 or more genes. In some embodiments, the predetermined gene set covers about 1Mb (e.g., about 1.1Mb, e.g., about 1.125 Mb). In some embodiments, bTMB scores are determined from measuring the number of somatic mutations in cell-free DNA (cfDNA) in the sample. In some embodiments, the bTMB score is determined from measuring the number of somatic mutations in circulating tumor DNA (ctDNA) in the sample. In some embodiments, the number of somatic mutations is the number of Single Nucleotide Variants (SNVs) counted, or the sum of the number of SNVs and the number of indel mutations counted. In some embodiments, bTMB score refers to the number of somatic mutations accumulated in a tumor.

In some embodiments, the tumor mutational burden (e.g., bTMB or solid tumor TMB) is measured using any suitable method known in the art. For example, tumor mutation burden can be measured using Whole Exome Sequencing (WES), next generation sequencing, whole genome sequencing, gene targeting sequencing, or sequencing of the genome (e.g., a genome comprising a cancer-associated gene). See, e.g., melendez et al, transl Lung CANCER RES (2018) 7 (6): 661-667. In some embodiments, tumor mutational burden is measured using gene-targeted sequencing (e.g., using a nucleic acid hybridization-capture method (e.g., in combination with sequencing)). See, e.g., fancello et al, J Immunother Cancer (2019) 7:183.

In some embodiments, tumor mutational burden is measured according to the method provided in WO2017151524A1, hereby incorporated by reference in its entirety. In some embodiments, tumor mutational burden is measured according to the method described in Montesion, M.et al, cancer Discovery (2021) 11 (2): 282-92. In some embodiments, tumor mutational burden is measured according to the method described in Chalmers et al ,"Analysis of 100,00human cancer genomes reveals the landscape of tumor mutational burden,"Genome Med.2017;9(1):34). In some embodiments, tumor mutational burden is measured according to the method described in Huang, r.et al "Durable responders in advanced NSCLC with elevated TMB and treated with 1L immune checkpoint inhibitor:a real-world outcomes analysis,"J Immunother Cancer(2023)11(1):e005801. In some embodiments, tumor mutational burden is measured according to the method described in Quintanilha, j. Et al ,"Comparative Effectiveness ofImmune Checkpoint Inhibitors vs Chemotherapy in Patients With Metastatic Colorectal Cancer With Measures of Microsatellite Instability,Mismatch Repair,or Tumor Mutational Burden,"JAMA Netw Open.(2023)6(1):e2252244.

In some embodiments, tumor mutation burden is assessed based on the number of non-driven somatic encoding mutations per megabase sequenced genomes (mutations/Mb).

In some embodiments, tumor mutational burden is measured in the sample using next generation sequencing. In some embodiments, tumor mutational burden is measured in the sample by whole exome sequencing. In some embodiments, tumor mutational burden is measured in the sample using whole genome sequencing. In some embodiments, tumor mutational burden is measured in the sample by gene-targeted sequencing. In some embodiments, tumor mutation burden is measured on between about 0.8Mb and about 1.3Mb of sequenced DNA. In some embodiments, the tumor mutation burden is measured on any of about 0.8Mb, about 0.81Mb, about 0.82Mb, about 0.83Mb, about 0.84Mb, about 0.85Mb, about 0.86Mb, about 0.87Mb, about 0.88Mb, about 0.89Mb, about 0.9Mb, about 0.91Mb, about 0.92Mb, about 0.93Mb, about 0.94Mb, about 0.95Mb, about 0.96Mb, about 0.97Mb, about 0.98Mb, about 0.99Mb, about 1Mb, about 1.01Mb, about 1.02Mb, about 1.03Mb, about 1.04Mb, about 1.05Mb, about 1.06Mb, about 1.07Mb, about 1.08Mb, about 1.09Mb, about 1.1Mb, about 1.2Mb, or about 1.3. In some embodiments, tumor mutation burden is measured on about 0.8Mb of sequenced DNA. In some embodiments, tumor mutation burden is measured on between about 0.83Mb and about 1.14Mb of sequenced DNA. In some embodiments, tumor mutation burden is measured on up to about 1.24Mb of sequenced DNA. In some embodiments, tumor mutation burden is measured on up to about 1.1Mb of sequenced DNA. In some embodiments, tumor mutation burden is measured on about 0.79Mb of sequenced DNA.

In some embodiments, the TMB score is less than about 10 mutations/Mb. In some embodiments, the TMB score is greater than about 10 mutations/Mb. In some embodiments, the TMB score is at least 10 mutations/Mb. In some embodiments, the TMB score is a high tumor mutation load score (e.g., of at least about 10 mutations/Mb). In some embodiments, the TMB score is at least about 10 mutations/Mb. In some embodiments, the TMB score is at least about 20 mutations/Mb. In some embodiments, the TMB score is between about 10 mutations/Mb and about 15 mutations/Mb, between about 15 mutations/Mb and about 20 mutations/Mb, between about 20 mutations/Mb and about 25 mutations/Mb, between about 25 mutations/Mb and about 30 mutations/Mb, between about 30 mutations/Mb and about 35 mutations/Mb, between about 35 mutations/Mb and about 40 mutations/Mb, between about 40 mutations/Mb and about 45 mutations/Mb, between about 45 mutations/Mb and about 50 mutations/Mb, between about 50 mutations/Mb and about 55 mutations/Mb, Between about 55 mutations/Mb and about 60 mutations/Mb, between about 60 mutations/Mb and about 65 mutations/Mb, between about 65 mutations/Mb and about 70 mutations/Mb, between about 70 mutations/Mb and about 75 mutations/Mb, between about 75 mutations/Mb and about 80 mutations/Mb, between about 80 mutations/Mb and about 85 mutations/Mb, between about 85 mutations/Mb and about 90 mutations/Mb, between about 90 mutations/Mb and about 95 mutations/Mb, or between about 95 mutations/Mb and about 100 mutations/Mb. In some embodiments, the TMB score is between about 100 mutations/Mb and about 110 mutations/Mb, between about 110 mutations/Mb and about 120 mutations/Mb, between about 120 mutations/Mb and about 130 mutations/Mb, between about 130 mutations/Mb and about 140 mutations/Mb, between about 140 mutations/Mb and about 150 mutations/Mb, between about 150 mutations/Mb and about 160 mutations/Mb, between about 160 mutations/Mb and about 170 mutations/Mb, between about 170 mutations/Mb and about 180 mutations/Mb, Between about 180 mutations/Mb and about 190 mutations/Mb, between about 190 mutations/Mb and about 200 mutations/Mb, between about 210 mutations/Mb and about 220 mutations/Mb, between about 220 mutations/Mb and about 230 mutations/Mb, between about 230 mutations/Mb and about 240 mutations/Mb, between about 240 mutations/Mb and about 250 mutations/Mb, between about 250 mutations/Mb and about 260 mutations/Mb, between about 260 mutations/Mb and about 270 mutations/Mb, between about 270 mutations/Mb and about 280 mutations/Mb, Between about 280 mutations/Mb and about 290 mutations/Mb, between about 290 mutations/Mb and about 300 mutations/Mb, between about 300 mutations/Mb and about 310 mutations/Mb, between about 310 mutations/Mb and about 320 mutations/Mb, between about 320 mutations/Mb and about 330 mutations/Mb, between about 330 mutations/Mb and about 340 mutations/Mb, between about 340 mutations/Mb and about 350 mutations/Mb, between about 350 mutations/Mb and about 360 mutations/Mb, between about 360 mutations/Mb and about 370 mutations/Mb, between about 370 mutations/Mb and about 380 mutations/Mb, between about 380 mutations/Mb and about 390 mutations/Mb, between about 390 mutations/Mb and about 400 mutations/Mb, or greater than 400 mutations/Mb. In some embodiments, the TMB score is at least about 100 mutations/Mb, at least about 110 mutations/Mb, at least about 120 mutations/Mb, at least about 130 mutations/Mb, at least about 140 mutations/Mb, at least about 150 mutations/Mb, or greater. In some embodiments, the TMB score is determined based on between about 0.8Mb and about 1.1 Mb.

Method for determining microsatellite instability

Some aspects of the present disclosure provide for further analysis of microsatellite instability (MSI) status. It has been found that assessment of microsatellite instability can inform treatment decisions, including in some embodiments: whether to administer immune checkpoint inhibitor therapy to a patient if MSI is assessed as MSI-H in a sample obtained from an individual with cancer, or whether to administer chemotherapy to a patient if MSI is assessed as not MSI-H (such as MSI-L or MSS) in a sample obtained from an individual with cancer. Microsatellites are sequences of 1 to 6 nucleotides, typically repeated 5 to 50 times within the genome. Microsatellite instability can be categorized into a degree category such as high (MSI-H), low (MSI-L) or stable (MSS). MSS refers to a microsatellite status that does not exhibit somatic changes in the number of repeated nucleotide sequences. MSI-L refers to microsatellite status with an intermediate phenotype between MSS and MSI-H.

Microsatellite instability may be assessed using any suitable method known in the art. Microsatellite instability can be measured, for example, using next generation sequencing (see, e.g., HEMPELMANN et al, JImmunother Cancer (2018) 6 (1): 29), fluorescent multiplex PCR and capillary electrophoresis (see, e.g., arulananda et al, J Thorac Oncol (2018) 13 (10): 1588-94), immunohistochemistry (see, e.g., cheah et al, malays J Pathol (2019) 41 (2): 91-100), or single molecule inversion probes (smMIP, see, e.g., waalkes et al, clin Chem (2018) 64 (6): 950-8). In some embodiments, microsatellite instability is assessed based on DNA sequencing (e.g., next generation sequencing) of up to about 114 loci. In some embodiments, microsatellite instability is assessed based on DNA sequencing (e.g., next generation sequencing) of intronic homopolymer repeat loci for length variability. In some embodiments, microsatellite instability is assessed based on DNA sequencing (e.g., next generation sequencing) for length variability for about 114 intronic homopolymer repeat loci. In some embodiments, microsatellite instability status (e.g., microsatellite instability high) such as Trabucco et al, J Mol diagn.2019, month 11; 21 (6) 1053-1066.

VII immune checkpoint inhibitor

In certain embodiments, the methods described herein relate to predicting the efficacy of immune checkpoint inhibitor (ICPI) therapy and/or the manner in which ICPI is administered to an individual with cancer. In some embodiments, the efficacy of ICPI therapy is predicted to be first line therapy. In some embodiments, ICPI therapy is administered as a first line therapy for cancer. In some embodiments, ICPI therapy is the only treatment administered or indicated. In some embodiments, ICPI therapy consists of a single active agent (such as a single immune checkpoint inhibitor). In some embodiments, the efficacy of ICPI therapy is predicted to be two-line therapy. In some embodiments, ICPI therapy is administered as a two-wire therapy for cancer. In some embodiments, ICPI therapy is administered with or indicated as being administered with another therapy (such as a non-ICPI therapy). In some embodiments, ICPI therapies include combination ICPI therapies comprising two or more ICPI, i.e., two or more different active agents that target an immune checkpoint. In some embodiments, the two or more different active agents each target a different immune checkpoint protein.

As known in the art, checkpoint inhibitors target at least one immune checkpoint protein to alter modulation of immune responses. Immune checkpoint proteins include, for example, CTLA4、PD-L1、PD-1、PD-L2、VISTA、B7-H2、B7-H3、B7-H4、B7-H6、2B4、ICOS、HVEM、CEACAM、LAIR1、CD80、CD86、CD276、VTCN1、I MHC class II MHC, GALS, adenine, TGFR, CSF1R, MICA/B, arginase, CD160, gp49B, PIR-B, KIR family receptor 、TIM-1、TIM-3、TIM-4、LAG-3、BTLA、SIRPalpha(CD47)、CD48、2B4(CD244)、B7.1、B7.2、ILT-2、ILT-4、TIGIT、LAG-3、BTLA、IDO、OX40 and A2aR. In some embodiments, molecules involved in modulating immune checkpoints include, but are not limited to: PD-1 (CD 279), PD-L1 (B7-H1, CD 274), PD-L2 (B7-CD, CD 273), CTLA-4 (CD 152), HVEM, BTLA (CD 272), killer cell immunoglobulin-like receptor (KIR)、LAG-3(CD223)、TIM-3(HAVCR2)、CEACAM、CEACAM-1、CEACAM-3、CEACAM-5、GAL9、VISTA(PD-1H)、TIGIT、LAIR1、CD160、2B4、TGFRbeta、A2AR、GITR(CD357)、CD80(B7-1)、CD86(B7-2)、CD276(B7-H3)、VTCNI(B7-H4)、I class MHC, class II MHC, GALS, adenine 、TGFR、B7-H1、OX40(CD134)、CD94(KLRD1)、CD137(4-1BB)、CD137L(4-1BBL)、CD40、IDO、CSF1R、CD40L、CD47、CD70(CD27L)、CD226、HHLA2、ICOS(CD278)、ICOSL(CD275)、LIGHT(TNFSF14,CD258)、NKG2a、NKG2d、OX40L(CD134L)、PVR(NECL5,CD155)、SIRPa、MICA/B and/or arginase. In some embodiments, an immune checkpoint inhibitor (i.e., a checkpoint inhibitor) reduces the activity of a checkpoint protein that negatively regulates immune cell function, e.g., in order to enhance T cell activation and/or an anti-cancer immune response. In other embodiments, the checkpoint inhibitor increases the activity of a checkpoint protein that positively regulates immune cell function, e.g., in order to enhance T cell activation and/or an anti-cancer immune response. In some embodiments, the checkpoint inhibitor is an antibody. Examples of checkpoint inhibitors include, but are not limited to, PD-1 axis binding antagonists, PD-L1 axis binding antagonists (e.g., anti-PD-L1 antibodies, e.g., alemtuzumab (MPDL 3280A)), an antagonist against a co-inhibitory molecule (e.g., a CTLA4 antagonist (e.g., an anti-CTLA 4 antibody), a TIM-3 antagonist (e.g., an anti-TIM-3 antibody), or a LAG-3 antagonist (e.g., an anti-LAG-3 antibody)), or any combination thereof. In some embodiments, the immune checkpoint inhibitor comprises a drug, such as a small molecule, a recombinant form of a ligand or receptor, or an antibody, such as a human antibody (see, e.g., international patent publication No. W02015016718; pardoll, NAT REV CANCER,12 (4): 252-64,2012; each of which is incorporated herein by reference). In some embodiments, known immune checkpoint protein inhibitors or analogs thereof may be used, particularly chimeric, humanized or human forms of antibodies may be used.

In some embodiments according to any one of the embodiments described herein, the immune checkpoint inhibitor comprises a PD-1 antagonist/inhibitor or a PD-L1 antagonist/inhibitor.

In some embodiments, the checkpoint inhibitor is a PD-L1 axis binding antagonist, e.g., a PD-1 binding antagonist, a PD-L1 binding antagonist, or a PD-L2 binding antagonist. PD-1 (programmed death 1) is also known in the art as "programmed cell death 1", "PDCD1", "CD279" and "SLEB" 2". An exemplary human PD-1 is shown in UniProtKB/Swiss-Prot accession number Q15116. PD-L1 (programmed death ligand 1) is also known in the art as "programmed cell death 1 ligand 1", "PDCD1 LG1", "CD274", "B7-H" and "PDL1". An exemplary human PD-L1 is shown in UniProtKB/Swiss-Prot accession number Q9NZQ7.1. PD-L2 (programmed death ligand 2) is also known in the art as "programmed cell death 1 ligand 2", "PDCD1 LG2", "CD273", "B7-DC", "Btdc" and "PDL2". An exemplary human PD-L2 is shown in UniProtKB/Swiss-Prot accession number Q9BQ 51. In some cases, PD-1, PD-L1, and PD-L2 are human PD-1, PD-L1, and PD-L2.

In some cases, a PD-1 binding antagonist/inhibitor is a molecule that inhibits the binding of PD-1 to its ligand binding partner. In specific embodiments, the PD-1 ligand binding partner is PD-L1 and/or PD-L2. In another instance, the PD-L1 binding antagonist/inhibitor is a molecule that inhibits the binding of PD-L1 to its binding ligand. In particular embodiments, the PD-L1 binding partner is PD-1 and/or B7-1. In another instance, a PD-L2 binding antagonist is a molecule that inhibits the binding of PD-L2 to its ligand binding partner. In a specific embodiment, the PD-L2 binding ligand partner is PD-1. The antagonist may be an antibody, antigen binding fragment thereof, immunoadhesin, fusion protein or oligopeptide. In some embodiments, the PD-1 binding antagonist is a small molecule, a nucleic acid, a polypeptide (e.g., an antibody), a carbohydrate, a lipid, a metal, or a toxin.

In some cases, the PD-1 binding antagonist is an anti-PD-1 antibody (e.g., a human, humanized, or chimeric antibody), e.g., as described below. In some cases, the anti-PD-1 antibody is MDX-1 106 (Nawuzumab), MK-3475 (pembrolizumab,Semipril Li Shan antibody, rituximab, MEDI-0680 (AMP-514), PDR001, REGN2810, MGA-012, JNJ-63723283, BI 754091, or BGB-108. In other cases, the PD-1 binding antagonist is an immunoadhesin (e.g., an immunoadhesin comprising an extracellular or PD-1 binding portion of PD-L1 or PD-L2 fused to a constant region (e.g., an Fc region of an immunoglobulin sequence)). In some cases, the PD-1 binding antagonist is AMP-224. Another example of an anti-PD-1 antibody includes, but is not limited to, MEDI-0680 (AMP-514; astraZeneca), PDR001 (CAS REGISTRY No.1859072-53-9; novartis), REGN2810Or cimetidine Li Shan anti -rwlc;Regeneron)、BGB-108(BeiGene)、BGB-A317(BeiGene)、BI 754091、JS-001(Shanghai Junshi)、STI-A1110(Sorrento)、INCSHR-1210(Incyte)、PF-06801591(Pfizer)、TSR-042(, also known as ANB011;Tesaro/AnaptysBio)、AM0001(ARMO Biosciences)、ENUM 244C8(Enumeral Biomedical Holdings)、ENUM 388D4(Enumeral Biomedical Holdings)., in some embodiments, the PD-1 axis binding antagonist comprises tislelizumab(BGB-A317)、BGB-108、STI-A1110、AM0001、BI 754091、sintilimab(IBI308)、cetrelimab(JNJ-63723283)、toripalimab(JS-001)、camrelizumab(SHR-1210,INCSHR-1210,HR-301210)、MEDI-0680(AMP-514)、MGA-012(INCMGA 0012)、 nivolumab (BMS-936558, mdx1106, ono-4538), spartalizumab (PDR 00 l), pembrolizumab (MK-3475, sch 900475,PF-06801591, cimip Li Shan anti (REGN-2810, REGEN 2810), rituximab (TSR-042, ANB 011), FITC-YT-16 (PD-1 binding peptide), APL-501 or CBT-501 or genolimzumab(GB-226)、AB-122、AK105、AMG 404、BCD-100、F520、HLX10、HX008、JTX-4014、LZM009、Sym021、PSB205、AMP-224( fusion protein targeting PD-1)、CX-188(PD-1probody)、AGEN-2034、GLS-010、budigalimab(ABBV-181)、AK-103、BAT-1306、CS-1003、AM-0001、TILT-123、BH-2922、BH-2941、BH-2950、ENUM-244C8、ENUM-388D4、HAB-21、H EISCOI 11-003、IKT-202、MCLA-134、MT-17000、PEGMP-7、PRS-332、RXI-762、STI-1110、VXM-10、XmAb-23104、AK-112、HLX-20、SSI-361、AT-16201、SNA-01、AB122、PD1-PIK、PF-06936308、RG-7769、CAB PD-1Abs、AK-123、MEDI-3387、MEDI-5771、4H1128Z-E27、REMD-288、SG-001、BY-24.3、CB-201、IBI-319、ONCR-177、Max-1、CS-4100、JBI-426、CCC-0701 or CCX-4503 or derivatives thereof.

In some embodiments, the PD-L1 binding antagonist is a small molecule that inhibits PD-1. In some embodiments, the PD-L1 binding antagonist is a small molecule that inhibits PD-L1. For some embodiments, the PD-L1 binding antagonist is a small molecule that inhibits PD-L1 and VISTA or PD-L1 and TIM 3. In some embodiments, the PD-L1 binding antagonist is CA-170 (also known as AUPM-170). In some embodiments, the PD-L1 binding antagonist is an anti-PD-L1 antibody. In some embodiments, the anti-PD-L1 antibody may bind to human PD-L1, e.g., human PD-L1 shown in UniProtKB/Swiss-Prot accession number Q9NZQ7.1 or a variant thereof. In some embodiments, the PD-L1 binding antagonist is a small molecule, a nucleic acid, a polypeptide (e.g., an antibody), a carbohydrate, a lipid, a metal, or a toxin.

In some cases, for example, as described below, the PD-L1 binding antagonist is an anti-PD-L1 antibody. In some cases, the anti-PD-L1 antibody is capable of inhibiting binding between PD-L1 and PD-1 and/or between PD-L1 and B7-1. In some cases, the anti-PD-L1 antibody is a monoclonal antibody. In some cases, the anti-PD-L1 antibody is an antibody fragment selected from the group consisting of Fab, fab '-SH, fv, scFv, or (Fab') 2 fragments. In some cases, the anti-PD-L1 antibody is a humanized antibody. In some cases, the anti-PD-L1 antibody is a human antibody. In some cases, the anti-PD-L1 antibody is selected from yw243.55.s70, MPDL3280A (alemtuzumab), MDX-1 105, MEDI4736 (de valuzumab), or MSB0010718C (avermectin). In some embodiments, the PD-L1 axis binding antagonist comprises Abelmoschus, dewaruzumab (imfinzi), BGB-A333, SHR-1316 (HTI-1088), CK-301, BMS-936559, en Wo Lishan anti (KN035、ASC22)、CS1001、MDX-1105(BMS-936559)、LY3300054、STI-A1014、FAZ053、CX-072、INCB086550、GNS-1480、CA-170、CK-301、M-7824、HTI-1088(HTI-131、SHR-1316)、MSB-2311、AK-106、AVA-004、BBI-801、CA-327、CBA-0710、CBT-502、FPT-155、IKT-201、IKT-703、10-103、JS-003、KD-033、KY-1003、MCLA-145、MT-5050、SNA-02、BCD-135、APL-502(CBT-402 or TQB2450)、IMC-001、KD-045、INBRX-105、KN-046、IMC-2102、IMC-2101、KD-005、IMM-2502、89Zr-CX-072、89Zr-DFO-6E11、KY-1055、MEDI-1109、MT-5594、SL-279252、DSP-106、Gensci-047、REMD-290、N-809、PRS-344、FS-222、GEN-1046、BH-29xx, or FS-118, or derivatives thereof.

In some embodiments, the checkpoint inhibitor is an antagonist/inhibitor of CTLA 4. In some embodiments, the checkpoint inhibitor is a small molecule antagonist of CTLA 4. In some embodiments, the checkpoint inhibitor is an anti-CTLA 4 antibody. CTLA4 is part of the immune checkpoint molecule CD28-B7 immunoglobulin superfamily, which can negatively regulate T cell activation, particularly CD 28-dependent T cell responses. CTLA4 competes with CD28 for binding to common ligands such as CD80 (B7-1) and CD86 (B7-2) and binds to these ligands with higher affinity than CD 28. Blocking CTLA4 activity (e.g., using anti-CTLA 4 antibodies) is thought to enhance CD 28-mediated co-stimulation (resulting in increased T cell activation/priming), affect T cell development, and/or deplete tregs (such as intratumoral tregs). In some embodiments, the CTLA4 antagonist is a small molecule, nucleic acid, polypeptide (e.g., antibody), carbohydrate, lipid, metal, or toxin. In some embodiments, the CTLA-4 inhibitor comprises ipilimumab (IBI 310, BMS-734016, MDX010, MDX-CTLA4, MEDI 4736), tremelimumab (CP-675, CP-675,206), APL-509, AGEN1884, CS1002, AGEN1181, abelipul (Orencia, BMS-188667, RG2077), BCD-145, ONC-392, ADU-1604, REGN4659, ADG116, KN044, KN046, or derivatives thereof.

In some embodiments, the anti-PD-1 antibody or antibody fragment is MDX-1106 (Nawuzumab), MK-3475 (pembrolizumab,Cimipran Li Shan antibody, rituximab 、MEDI-0680(AMP-514)、PDR001、REGN2810、MGA-012、JNJ-63723283、BI 754091、BGB-108、BGB-A317、JS-001、STI-A1110、INCSHR-1210、PF-06801591、TSR-042、AM0001、ENUM 244C8, or ENUM 388D4. In some embodiments, the PD-1 binding antagonist is an anti-PD-1 immunoadhesin. In some embodiments, the anti-PD-1 immunoadhesin is AMP-224. In some embodiments, the anti-PD-L1 antibody or antibody fragment is YW243.55.S70, MPDL3280A (Ab), MDX-1105, MEDI4736 (Dewaruzumab), MSB0010718C (Ab-Ab), LY3300054, STI-A1014, KN035, FAZ053, or CX-072.

In some embodiments, the immune checkpoint inhibitor comprises a LAG-3 inhibitor (e.g., an antibody, antibody conjugate, or antigen-binding fragment thereof). In some embodiments, LAG-3 inhibitors include small molecules, nucleic acids, polypeptides (e.g., antibodies), carbohydrates, lipids, metals, or toxins. In some embodiments, the LAG-3 inhibitor comprises a small molecule. In some embodiments, the LAG-3 inhibitor comprises a LAG-3 binding agent. In some embodiments, the LAG-3 inhibitor comprises an antibody, antibody conjugate, or antigen-binding fragment thereof. In some embodiments, the LAG-3 inhibitor comprises Ai Tai mold (eftilagimod) alpha (IMP 321, IMP-321, EDDP-202, EOC-202), ruila Li Shan anti (relatlimab) (BMS-986016), GSK2831781 (IMP-731), LAG525 (IΜ pi 701), TSR-033, EVIP321 (soluble LAG-3 protein), BI 754111, IMP761, REGN3767, MK-4280, MGD-013, xmAb22841, INCAGN-2385, ENUM-006, AVA-017, AM-0003, iOnctura anti-LAG-3 antibodies, arcus Biosciences LAG-3 antibodies, sym022, derivatives thereof, or antibodies competing with any of the foregoing.

In some embodiments, the immune checkpoint inhibitor is monovalent and/or monospecific. In some embodiments, the immune checkpoint inhibitor is multivalent and/or multispecific.

In some embodiments, the immune checkpoint inhibitor may be administered in combination with an immune modulatory molecule or cytokine. An immunomodulating profile is required to trigger an effective immune response and balance the subject's immunity. Examples of suitable immunomodulatory cytokines include, but are not limited to, interferons (e.g., IFNα, IFNβ, and IFNγ), interleukins (e.g., IL-1, IL-2, IL-3, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-12, and IL-20), tumor necrosis factors (e.g., TNFα and TNF β), erythropoietin (EPO), FLT-3 ligands, gIp, TCA-3, MCP-1, MIF, MIP-1 α, MIP-1 β, rantes, macrophage colony stimulating factor (M-CSF), granulocyte colony stimulating factor (G-CSF), or granulocyte-macrophage colony stimulating factor (GM-CSF), and functional fragments thereof. In some embodiments, any immunomodulatory chemokine that binds to a chemokine receptor, i.e., CXC, CC, C, or CX3C chemokine receptor, can be used in the context of the present disclosure. Examples of chemokines include, but are not limited to MIP-3α(Lax)、MIP-3β、Hcc-1、MPIF-1、MPIF-2、MCP-2、MCP-3、MCP-4、MCP-5、Eotaxin、Tarc、Elc、I309、IL-8、GCP-2Groα、Gro-β、Nap-2、Ena-78、Ip-10、MIG、I-Tac、SDF-1 or BCA-1 (Blc), and functional fragments thereof. In some embodiments, the immunoregulatory molecule is included in any of the treatments provided herein.

In some embodiments, the immune checkpoint inhibitor is a first-line immune checkpoint inhibitor (e.g., it is a first-line therapy for cancer). In some embodiments, the immune checkpoint inhibitor is a two-wire immune checkpoint inhibitor (e.g., it is a two-wire therapy for cancer). In some embodiments, the immune checkpoint inhibitor is administered in combination with one or more additional anti-cancer therapies or treatments.

Chemotherapy of

In certain embodiments, the methods described herein relate to predicting the efficacy of a chemotherapy regimen and/or the manner in which the chemotherapy regimen is administered to an individual with cancer. For example, in some embodiments, when the TMB score of a tumor is determined to be below a threshold level, such as below 10 mutations/megabase or below 20 mutations/megabase, then the tumor is not indicated as a suitable candidate for ICPI therapy, but is indicated for therapy with a chemotherapy regimen.

In some embodiments, the methods provided herein include: chemotherapy is administered to an individual. Examples of chemotherapeutic agents include alkylating agents such as thiotepa and cyclophosphamide; alkyl sulfonates such as busulfan, imperoshu and piposhu; aziridines such as benzotepa, carboquinone, rituximab, and uratepa; ethylene imines and methyl melamine, and the like, comprises altretamine, triethylenemelamine triethylenephosphoramide triethylenes phosphoramides (P); polyacetyl (especially bullatacin and bullatacin ketone); camptothecins (including the synthetic analog topotecan); bryostatin; Kelitastatin; CC-1065 (including adoxolone, calzelone and bizelone analogues thereof); nostoc (in particular, nostoc 1 and nostoc 8); dolastatin; the sesqui-carcinomycin (including synthetic analogues KW-2189 and CB1-TM 1); acanthopanaxgenin; a podophylline; sarcodictyin; spongosine; nitrogen mustards such as chlorambucil, chlorpheniramine (chlomaphazine), chlorsphosphamide, estramustine, ifosfamide, dichloromethyldiethylamine, mechlorethamine hydrochloride, melphalan, new enbixing, chlorambucil cholesterol, prednimustine, trolophosmine and uracil mustard; Nitrosoureas such as carmustine, chlorourea, fotemustine, lomustine, nimustine and ramustine (ranimnustine); antibiotics, such as enediyne antibiotics (e.g., ka Li Jimei, especially ka Li Jimei, γll and ka Li Jimei, ωll); daptomycin, including daptomycin a; bisphosphonates, such as chlorophosphonate; epothilone; And neocarcinomycin chromophores and related pigmentary protein enediyne antibiotic chromophores, aclacinomycin (aclacinomysin), actinomycin, anthramycin (authramycin), azoserine, bleomycin, actinomycin C (cactinomycin), cartrubicin (carabicin), carminomycin, carcinophilin, chromomycin (chromomycinis), actinomycin D (dactinomycin), daunomycin, ditropine, 6-diazo-5-oxo-L-norleucine, doxorubicin (including morpholino-doxorubicin, doxorubicin), cyanomorpholino-doxorubicin, 2-pyrrolido-doxorubicin and deoxydoxorubicin), and epirubicin, elxorubicin, idarubicin, and marselomycin; Mitomycin, such as mitomycin C, mycophenolic acid, norgamycin, olivomycin, percomycin, methylmitomycin (potfiromycin), puromycin, doxorubicin, rodobicin, streptozotocin, tuberculin, ubenimex, jingstatin, and zorubicin; antimetabolites such as methotrexate and 5-fluorouracil (5-FU); folic acid analogs such as dimethyl folic acid, pterin, and trimetrexate; purine analogs such as fludarabine, 6-mercaptopurine, thioxanthine, and thioguanine; pyrimidine analogs such as ambcitabine, azacytidine, 6-azauridine, carmofur, cytarabine, dideoxyuridine, doxifluridine, enocitabine, and floxuridine; androgens such as carbosterone, drotasone propionate, cyclothioandrostanol, emaandran and testosterone lactone; anti-adrenal agents such as mitotane and Qu Luosi; folic acid supplements such as folinic acid; acetoglucurolactone; aldehyde phosphoramide glycosides; aminolevulinic acid; enuracil; amsacrine; bestrabucil; a specific group; eda traxas; defofamine; dimecoxin; a filariquinone; elformithine; ammonium elegance; epothilones; eggshell robust; gallium nitrate; hydroxyurea; lentinan; lonidainine; a maytansinoid compound which is used as a drug, such as maytansine and ansamitocins; Mitoguazone; mitoxantrone; mopidanmol; nitraerine; prastatin; egg ammonia nitrogen mustard; pirarubicin; losoxantrone; podophylloic acid; 2-ethyl hydrazide; procarbazine; PSK polysaccharide complex; carrying out a process of preparing the raw materials; rhizobia element; a sirzopyran; germanium spiroamine; tenuazonic acid; triiminoquinone; 2,2',2 "-trichlorotriethylamine; trichothecenes (especially T-2 toxin, verracurin A, plaque a and serpentine (anguidine)); a urethane; vindesine; dacarbazine; mannitol; dibromomannitol; dibromodulcitol; Pipobromine; gacytosine; arabinoside ("Ara-C"); cyclophosphamide; taxanes, such as paclitaxel and docetaxel gemcitabine; 6-thioguanine; mercaptopurine; platinum coordination complexes such as cisplatin, oxaliplatin, and carboplatin; vinblastine; platinum; etoposide (VP-16); ifosfamide; mitoxantrone; vincristine; vinorelbine; novantrone; teniposide; eda traxas; daunomycin; aminopterin; hilded; ibandronate sodium; irinotecan (e.g., CPT-ll); topoisomerase inhibitor RFS2000; Difluoromethyl ornithine (DMFO); retinoids such as retinoic acid; capecitabine; carboplatin, procarbazine, plicomycin, gemcitabine, noviby, farnesyl protein transferase inhibitors, trans-platinum, and pharmaceutically acceptable salts, acids, or derivatives of any of the foregoing.

Some non-limiting examples of chemotherapeutic drugs of the present disclosure are carboplatin (Paraplatin), cisplatin (Platinol, platinol-AQ), cyclophosphamide (Cytoxan, neosar), docetaxel (Taxote), doxorubicin (Adriamycin), erlotinib (Tarceva), etoposide (VePesid), fluorouracil (5-FU), gemcitabine (Gemzar), imatinib mesylate (Gleevec), irinotecan (Camptosar), methotrexate (Folex, mexate, amethopterin), paclitaxel (Taxol, abraxane), sorafenib (Nexavar), sunitinib (Suntent), topotecan (Hycamtin), vincristine (Oncovin, VINCASAR PFS), and vinblastine (Velban).

IX. additional anticancer agents

In some embodiments, the additional anti-cancer agent is administered in addition to the treatment described otherwise (e.g., in addition to the chemotherapy regimen as described in section VIII or in addition to ICPI as described in section VII). It will be appreciated that if a tumor is determined to be a suitable candidate for ICPI therapy using the methods described herein, such as if the tumor is found to have a TMB score of at least 10 mutations/megabase or at least 20 mutations/megabase, then in some embodiments, a subject with a tumor may further benefit from treatment with additional anti-cancer agents in addition to ICPI therapy. Likewise, if a tumor is determined to be a suitable candidate for a chemotherapy regimen, such as if the tumor is found to have a TMBV score of less than 10 mutations per megabase, in some embodiments, a subject with a tumor may further benefit from treatment with additional anti-cancer agents in addition to the chemotherapy regimen.

In some embodiments, the additional anti-cancer therapy comprises a kinase inhibitor. In some embodiments, the methods provided herein include: a kinase inhibitor, e.g., in combination with another therapy, such as an immune checkpoint inhibitor, is administered to an individual. Examples of kinase inhibitors include those that target: one or more receptor tyrosine kinases, such as BCR-ABL、B-Raf、EGFR、HER-2/ErbB2、IGF-IR、PDGFR-a、PDGFR-β、cKit、Flt-4、Flt3、FGFR1、FGFR3、FGFR4、CSF1R、c-Met、RON、c-Ret or ALK; one or more cytoplasmic tyrosine kinases, such as c-SRC, c-YES, abl or JAK-2; one or more serine/threonine kinases such as ATM, aurora a & B, CDKs, mTOR, PKCi, PLKs, b-Raf, S6K or STK11/LKB1; or one or more lipid kinases such as PI3K or SKI. Small molecule kinase inhibitors include PHA-739358, nilotinib, dasatinib, PD166326, NSC 743411, lapatinib (GW-572016), kanatinib (CI-1033), sematinib (SU 5416), watanib (PTK 787/ZK 222584), sutent (SU 11248), sorafenib (BAY 43-9006) or leflunomide (SU 101). Additional non-limiting examples of tyrosine kinase inhibitors include imatinib (Gleevec/Glivec) and gefitinib (Iressa).

In some embodiments, the additional anti-cancer therapy comprises an anti-angiogenic agent. In some embodiments, the methods provided herein include: an anti-angiogenic agent, e.g., in combination with another therapy, such as an immune checkpoint inhibitor, is administered to an individual. Angiogenesis inhibitors prevent the extensive growth of blood vessels (angiogenesis) required for tumor survival. Non-limiting examples of angiogenesis-mediating molecules or angiogenesis inhibitors that may be used in the methods of the present disclosure include soluble VEGF (e.g., VEGF isoforms, such as VEGF121 and VEGF165; And co-receptors, such as Neuropilin-1 and Neuropilin-2), NRP-1, angiopoietin 2, TSP-1 and TSP-2, angiostatin and related molecules, endostatin, angiostatin, calreticulin, platelet factor-4, TIMP and CDAI, methyl-1 and methyl-2, IFN alpha, IFN-beta and IFN-gamma, CXCL10, IL-4, IL-12 and IL-18, prothrombin (tricyclic domain-2), antithrombin III fragment, prolactin, VEGI, SPARC, osteopontin, Mammary gland silk-inhibiting protein, angiostatin, dormitoxin-related proteins, dormancy proteins and drugs such as bevacizumab, itraconazole, carboxyamidotriazole, TNP-470, CM101, IFN-alpha, platelet factor-4, suramin, SU5416, thrombospondin, VEGFR antagonist, angiostatic steroid and heparin, cartilage-derived angiogenesis inhibitor, matrix metalloproteinase inhibitor, 2-methoxyestradiol, ticagrelor, tetrathiomolybdate, thalidomide, thrombospondin, prolactin vβ3 inhibitor, lisinoamine or taquinimod. in some embodiments, known therapeutic candidates that may be used according to the methods of the present disclosure include naturally occurring angiogenesis inhibitors, including but not limited to angiostatin, endostatin, or platelet factor-4. In another embodiment, therapeutic candidates that may be used according to the methods of the present disclosure include, but are not limited to, specific inhibitors of endothelial cell growth, such as TNP-470, thalidomide, and interleukin-12. Other anti-angiogenic agents that may be used according to the methods of the present disclosure include those that neutralize angiogenic molecules, including but not limited to antibodies to fibroblast growth factor, antibodies to vascular endothelial growth factor, antibodies to platelet derived growth factor, or antibodies to receptors for EGF VEGF or PDGF, or other types of inhibitors. In some embodiments, anti-angiogenic agents that may be used in accordance with the methods of the present disclosure include, but are not limited to, suramin and analogs thereof, and tekegatran. In other embodiments, anti-angiogenic agents that may be used according to the methods of the present disclosure include, but are not limited to, agents that neutralize angiogenic factor receptors or agents that interfere with the vascular basement membrane and extracellular matrix, including, but not limited to, metalloproteinase inhibitors and vasoinhibitory steroids. Another group of anti-angiogenic compounds that may be used according to the methods of the present disclosure include, but are not limited to, anti-adhesion molecules, such as antibodies to integrin αvβ3. Other anti-angiogenic compounds or compositions that may be used according to the methods of the present disclosure include, but are not limited to, kinase inhibitors, thalidomide, itraconazole, carboxyamidotriazole, CM101, IFN- α, IL-12, SU5416, thrombospondin, chondrogenic angiogenesis inhibitor, 2-methoxyestradiol, tetrathiomolybdate, thrombospondin, prolactin He Linuo amine. in a particular embodiment, the anti-angiogenic compound that can be used according to the methods of the present disclosure is an antibody against VEGF, such asBevacizumab (Genentech).

In some embodiments, the additional anti-cancer therapy comprises an anti-DNA repair therapy. In some embodiments, the methods provided herein include: an anti-DNA repair therapy is administered to an individual, for example, in combination with another therapy, such as an immune checkpoint inhibitor. In some embodiments, the anti-DNA repair therapy is a PARP inhibitor (e.g., tazopanib, rebamipramine, olapanib), a RAD51 inhibitor (e.g., RI-1), or an inhibitor of DNA damage response kinase, e.g., CHCK (e.g., AZD 7762), ATM (e.g., KU-55933, KU-60019, NU7026, or VE-821), and ATR (e.g., NU 7026).

In some embodiments, the additional anti-cancer therapy comprises a radiation sensitizer. In some embodiments, the methods provided herein include: a radiation sensitizer is administered to an individual, e.g., in combination with another therapy, such as an immune checkpoint inhibitor. Exemplary radiation sensitizers include hypoxic radiation sensitizers, such as misnidazole, metronidazole, and disodium crocetin, a compound that helps to increase the diffusion of oxygen into hypoxic tumor tissue. The radiosensitizer may also be a DNA damage response inhibitor interfering with Base Excision Repair (BER), nucleotide Excision Repair (NER), mismatch repair (MMR), recombination repair including Homologous Recombination (HR) and non-homologous end joining (NHEJ), and direct repair mechanisms. Single Strand Break (SSB) repair mechanisms include BER, NER or MMR pathways, whereas Double Strand Break (DSB) repair mechanisms consist of HR and NHEJ pathways. The radiation causes DNA fragmentation which, if not repaired, can be fatal. SSB is repaired by a combination of BER, NER and MMR mechanisms using the complete DNA strand as a template. The main pathway for SSB repair is BER using a related enzyme family known as poly (ADP-ribose) polymerase (PARP). Thus, the radiation sensitizer may comprise a DNA damage response inhibitor, such as a PARP inhibitor.

In some embodiments, the additional anti-cancer therapy comprises an anti-inflammatory agent. In some embodiments, the methods provided herein: comprising administering to the individual an anti-inflammatory agent, e.g., in combination with another therapy, such as an immune checkpoint inhibitor. In some embodiments, the anti-inflammatory agent is an agent that blocks, inhibits, or reduces inflammation or a signal from an inflammatory signaling pathway. In some embodiments, the anti-inflammatory agent inhibits or reduces the activity of any one or more of: IL-1, IL-2, IL-3, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-12, IL-13, IL-15, IL-18, IL-23; interferons (IFNs), such as IFNα, IFNβ, IFNγ, IFN- γ inducing factor (IGIF); transforming growth factor-beta (TGF-beta); transforming growth factor-alpha (TGF-alpha); tumor necrosis factors, such as TNF-α、TNF-β、TNF-RI、TNF-RII;CD23;CD30;CD40L;EGF;G-CSF;GDNF;PDGF-BB;RANTES/CCL5;IKK;NF-κB;TLR2;TLR3;TLR4;TL5;TLR6;TLR7;TLR8;TLR8;TLR9; and/or any cognate receptor thereof. In some embodiments, the anti-inflammatory agent is IL-1 or an IL-1 receptor antagonist, such as anakinraLi Naxi prizes or canumab. In some embodiments, the anti-inflammatory agent is IL-6 or an IL-6 receptor antagonist, e.g., an anti-IL-6 antibody or an anti-IL-6 receptor antibody, such as tolizumabOlolomab, claduzumab, sha Lim mab, cetrimide Lu Kushan, cetuximab, or ALX-0061. In some embodiments, the anti-inflammatory agent is a TNF-a antagonist, e.g., an anti-tnfa antibody, such as infliximabGolimumabAdalimumabPolyethylene glycol conjugated cetuximabOr etanercept. In some embodiments, the anti-inflammatory agent is a corticosteroid. Exemplary corticosteroids include, but are not limited to, cortisone (hydrocortisone, hydrocortisone sodium phosphate, hydrocortisone sodium succinate,HydrocortHydrocodone phosphateDecaluron (dexamethasone, dexamethasone acetate, dexamethasone sodium phosphate), Methylprednisolone (6-methylprednisolone, methylprednisolone acetate, methylprednisolone sodium succinate), Prednisolone And prednisoneLiquid And bisphosphonates (e.g., pamidronate)And zoledronic acid

In some embodiments, the additional anti-cancer therapy comprises an anti-hormonal agent. In some embodiments, the methods provided herein include: an anti-hormonal agent is administered to the individual, for example in combination with another therapy such as an immune checkpoint inhibitor. An anti-hormonal agent is an agent capable of modulating or inhibiting the action of a hormone on a tumor. Examples of anti-hormonal agents include antiestrogens and Selective Estrogen Receptor Modulators (SERMs) including, for example, tamoxifen (includingTamoxifen), raloxifene, droloxifene, 4-hydroxy tamoxifen, trawoxifene, raloxifene, LY117018, onapristone andToremifene; aromatase inhibitors that inhibit aromatase, which regulates estrogen production in the adrenal gland, such as, for example, 4 (5) -imidazole, aminoglutethimide,Megestrol acetate,Exemestane, formestane, farinose, qu,Voltammetric acid chloride,Letrozole and process for preparing the same(Anastrozole); antiandrogens such as flutamide, nilutamide, bicalutamide, leuprorelin, and goserelin; troxacitabine (1, 3-dioxolane nucleoside cytosine analogue); antisense oligonucleotides, particularly those that inhibit gene expression in signaling pathways associated with abnormal cell proliferation, such as, for example, PKC- α, raf, H-Ras, and epidermal growth factor receptor (EGF-R); vaccines, such as gene therapy vaccines, e.g.Vaccine(s),Vaccine and method for producing the sameA vaccine;rIL-2； Topoisomerase 1 inhibitors; rmRH; and pharmaceutically acceptable salts, acids or derivatives of any of the above.

In some embodiments, the anti-cancer therapy comprises an antimetabolite chemotherapeutic agent. In some embodiments, the methods provided herein include: an anti-metabolic chemotherapeutic agent, e.g., in combination with another therapy, such as an immune checkpoint inhibitor, is administered to an individual. Antimetabolite chemotherapeutic agents are agents that are similar in structure to metabolites but cannot be used by the body in an efficient manner. Many antimetabolite chemotherapeutic agents interfere with the production of RNA or DNA. Examples of antimetabolite chemotherapeutic agents include gemcitabine5-Fluorouracil (5-FU), capecitabine (XELODA ^TM), 6-mercaptopurine, methotrexate, 6-thioguanine, pemetrexed, raltitrexed, arabinocytides ARA-C cytarabineDacarbazine (DTIC-DOMED), azocytosine (azocytosine), deoxycytosine, pyridmidene, fludarabineCladribine and 2-deoxy-D-glucose. In some embodiments, the antimetabolite chemotherapeutic agent is gemcitabine. Gemcitabine hydrochloride is sold under the trademark Eli LillyAnd (5) selling.

In some embodiments, the additional anti-cancer therapy comprises a platinum-based chemotherapeutic agent. In some embodiments, the methods provided herein include: a platinum-based chemotherapeutic agent, e.g., in combination with another therapy (such as an immune checkpoint inhibitor), is administered to an individual. Platinum-based chemotherapeutic agents are those comprising an organic compound containing platinum as a constituent of a molecule. In some embodiments, the chemotherapeutic agent is a platinum agent. In some such embodiments, the platinum agent is selected from cisplatin, carboplatin, oxaliplatin, nedaplatin, triplatinum tetranitrate, phenanthriplatin, picoplatin, or satraplatin.

In some embodiments, the additional anti-cancer therapy includes cancer immunotherapy, such as cancer vaccine, cell-based therapy, T Cell Receptor (TCR) based therapy, adjuvant immunotherapy, cytokine immunotherapy, and oncolytic virus therapy. In some embodiments, the methods provided herein include: cancer immunotherapy, such as cancer vaccine, cell-based therapy, T Cell Receptor (TCR) based therapy, adjuvant immunotherapy, cytokine immunotherapy, and oncolytic virus therapy, for example, in combination with another therapy, such as an immune checkpoint inhibitor, is administered to an individual. In some embodiments, cancer immunotherapy includes small molecules, nucleic acids, polypeptides, carbohydrates, toxins, cell-based agents, or cell-binding agents. Examples of cancer immunotherapy are described in more detail herein, but are not intended to be limiting. In some embodiments, cancer immunotherapy activates one or more aspects of the immune system to attack cells (e.g., tumor cells) that express a neoantigen (e.g., a neoantigen expressed by a cancer of the present disclosure). Cancer immunotherapy of the present disclosure is contemplated for use as monotherapy, or in a combination method comprising any combination or number of two or more, depending on the medical judgment. Any cancer immunotherapy (optionally as monotherapy or in combination with another cancer immunotherapy described herein or other therapeutic agent) may be used in any of the methods described herein.

In some embodiments, the cancer immunotherapy comprises a cancer vaccine. A range of cancer vaccines have been tested that employ different approaches to promote immune responses against tumors (see, e.g., emens L A, expert Opin Emerg Drugs (2): 295-308 (2008) and US 20190367613). Several approaches have been devised to enhance the response of B cells, T cells or professional antigen presenting cells to tumors. Exemplary types of cancer vaccines include, but are not limited to, DNA-based vaccines, RNA-based vaccines, virus-transduced vaccines, peptide-based vaccines, dendritic cell vaccines, oncolytic viruses, whole tumor cell vaccines, tumor antigen vaccines, and the like. In some embodiments, the cancer vaccine may be prophylactic or therapeutic. In some embodiments, the cancer vaccine is formulated as a peptide-based vaccine, a nucleic acid-based vaccine, an antibody-based vaccine, or a cell-based vaccine. For example, the vaccine composition may comprise naked cDNA in a cationic lipid formulation; lipopeptides (e.g., vitiello, A. Et al, J.Clin. Invest.95:341,1995), naked cDNA or peptides, e.g., encapsulated in poly (DL-lactide-co-glycolide) ("PLG") microspheres (see, e.g., eldridge, et al, molecular immunol.28:287-294,1991; alonso et al, vaccine 12:299-306,1994; jones et al, vaccine 13:675-681,1995); peptide compositions contained in immunostimulatory complexes (ISCOMS) (e.g., takahashi et al, nature 344:873-875,1990; hu et al, clin. Exp. Immunol.113:235-243, 1998); or a multi-antigen peptide system (MAP) (see, e.g., tam, J.P., proc.Natl Acad.Sci.U.S.A.85:5409-5413,1988; tam, J.P., J.Immunol. Methods 196:17-32,1996). In some embodiments, the cancer vaccine is formulated as a peptide-based vaccine or a nucleic acid-based vaccine, wherein the nucleic acid encodes a polypeptide. In some embodiments, the cancer vaccine is formulated as an antibody-based vaccine. In some embodiments, the cancer vaccine is formulated as a cell-based vaccine. In some embodiments, the cancer vaccine is a peptide cancer vaccine, in some embodiments, it is a personalized peptide vaccine. In some embodiments, the cancer vaccine is a multivalent long peptide, polypeptide, peptide mixture, hybrid peptide, or peptide pulsed dendritic cell vaccine (see, e.g., yamada et al CANCER SCI, 104:14-21), 2013. In some embodiments, such cancer vaccines enhance anti-cancer responses.

In some embodiments, the cancer vaccine comprises a polynucleotide encoding a neoantigen, e.g., a neoantigen expressed by a cancer of the present disclosure. In some embodiments, the cancer vaccine comprises DNA or RNA encoding a neoantigen. In some embodiments, the cancer vaccine comprises a polynucleotide encoding a neoantigen. In some embodiments, the cancer vaccine further comprises one or more additional antigens, neoantigens, or other sequences that promote antigen presentation and/or immune responses. In some embodiments, the polynucleotide is complexed with one or more additional agents, such as liposomes or liposome complexes (lipoplex). In some embodiments, the polynucleotide is taken up and translated by an Antigen Presenting Cell (APC) that then presents the neoantigen via MHC class I on the surface of the APC cell.

In some embodiments, the cancer vaccine is selected from sipuleucel-TDendreon/Valeant Pharmaceuticals) which has been approved for the treatment of asymptomatic or slightly symptomatic metastatic castration-resistant (hormone refractory) prostate cancer; and talimogene laherparepvecBioVex/Amgen, previously known as T-VEC), a transgenic oncolytic virus therapy, is approved for the treatment of unresectable skin, subcutaneous, and lymph node lesions in melanoma. In some embodiments, the cancer vaccine is selected from oncolytic virus therapies, such as pexastimogene devacirepvec (PexaVec/JX-594, sillajen/formerly Jennerex Biotherapeutics), a thymidine kinase- (TK-) deficient vaccinia virus, engineered to express GM-CSF for hepatocellular carcinoma (NCT 02562755) and melanoma (NCT 00429312); pelareorep AOncolytics Biotech), a variant of respiratory enteroorphan virus (reovirus), which in many cancers, including colorectal cancer (NCT 01622543), prostate cancer (NCT 01619813), head and neck squamous cell carcinoma (NCT 01166542), pancreatic cancer (NCT 00998322) and non-small cell lung cancer (NSCLC) (NCT 00861627), does not replicate in cells that are not activated by the RAS; enadenotucirev (NG-348, psioxus, formerly ColoAdl), an adenovirus engineered to express full-length CD80 and antibody fragments specific for the T cell receptor CD3 protein in ovarian cancer (NCT 02028117), metastatic or advanced epithelial tumors, such as colorectal cancer, bladder cancer, head and neck squamous cell carcinoma, and salivary gland carcinoma (NCT 02636036); ONCOS-102 (Targovax/formerly Oncos), an adenovirus engineered to express GM-CSF in melanoma (NCT 03003676) and peritoneal, colorectal or ovarian cancer (NCT 02963831); GL-ONC1 (GLV-1 h68/GLV-1h153,Genelux GmbH), vaccinia virus engineered to express β -galactosidase (β -gal)/β -glucuronidase or β -gal/human sodium-iodine transporter (hNIS), studied in peritoneal metastasis (NCT 01443260), fallopian tube cancer, ovarian cancer (NCT 02759588), respectively; Or CG0070 (Cold Genesys), an adenovirus engineered to express GM-CSF in bladder cancer (NCT 02365818); anti-gp 100; STINGVAX; GVAX; DCVaxL and DNX-2401. In some embodiments, the cancer vaccine is selected from JX-929 (SillaJen/original Jennerex Biotherapeutics), a TK and vaccinia growth factor deficient vaccinia virus engineered to express cytosine deaminase, capable of converting the prodrug 5-fluorocytosine to the cytotoxic drug 5-fluorouracil; TGO1 and TG02 (Targovax/ortho Oncos), peptide-based immunotherapeutic agents targeting refractory RAS mutations; and TILT-123 (TILT Biotherapeutics), a designed engineered adenovirus: ad5/3-E2F-delta24-hTNFα -IRES-hIL20; and VSV-GP (ViraTherapeutics), a Vesicular Stomatitis Virus (VSV) engineered to express the Glycoprotein (GP) of lymphocytic choriomeningitis virus (LCMV), which can be further engineered to express antigens intended to enhance antigen-specific cd8+ T cell responses. In some embodiments, the cancer vaccine comprises a vector-based tumor antigen vaccine. A vector-based tumor antigen vaccine can be used as a means to provide a stable antigen supply to stimulate an anti-tumor immune response. In some embodiments, a vector encoding a tumor antigen is injected into an individual (possibly with a pro-inflammatory agent or other attractant such as GM-CSF), taken up by cells in vivo to produce a specific antigen, which then elicits the desired immune response. In some embodiments, the carrier may be used to deliver more than one tumor antigen at a time to enhance the immune response. In addition, recombinant viral, bacterial or yeast vectors may trigger their own immune response, which may also enhance the overall immune response.

In some embodiments, the cancer vaccine comprises a DNA-based vaccine. In some embodiments, DNA-based vaccines can be used to stimulate an anti-tumor response. The ability to directly inject DNA encoding an antigenic protein to elicit a protective immune response has been demonstrated in a number of experimental systems. Vaccination by direct injection of DNA encoding an antigenic protein to elicit a protective immune response will typically produce both cell-mediated and humoral responses. Furthermore, it has been reported that the repeated immune response of mice to DNA encoding various antigens substantially lasts for the lifetime of the animal (see, e.g., yankauckas et al (1993) DNA Cell biol., 12:771-776). In some embodiments, plasmid (or other vector) DNA comprising sequences encoding proteins operably linked to regulatory elements required for gene expression is administered to an individual (e.g., a human patient, a non-human mammal, etc.). In some embodiments, cells of the individual take up the administered DNA and express the coding sequence. In some embodiments, the antigen so produced becomes the target against which the immune response is directed.

In some embodiments, the cancer vaccine comprises an RNA-based vaccine. In some embodiments, RNA-based vaccines can be used to stimulate an anti-tumor response. In some embodiments, the RNA-based vaccine comprises a self-replicating RNA molecule. In some embodiments, the self-replicating RNA molecule may be an alphavirus-derived RNA replicon. Self-replicating RNA (or "SAM") molecules are well known in the art and can be produced by using replication elements derived from, for example, an alphavirus and substituting a structural viral protein with a nucleotide sequence encoding the protein of interest. Self-replicating RNA molecules are typically +strand molecules that can be directly translated after delivery to a cell, such translation providing an RNA-dependent RNA polymerase, and then producing antisense transcripts and sense transcripts from the delivered RNA. Thus, the delivered RNA results in the production of multiple daughter RNAs. These daughter RNAs, as well as co-linear subgenomic transcripts, may be translated themselves to provide in situ expression of the encoded polypeptide, or may be transcribed to provide further transcripts of the same meaning as the delivered RNA, which are translated to provide in situ expression of the antigen.

In some embodiments, cancer immunotherapy comprises a cell-based therapy. In some embodiments, the cancer immunotherapy comprises a T cell-based therapy. In some embodiments, the cancer immunotherapy comprises adoptive therapy, e.g., T cell-based adoptive therapy. In some embodiments, the T cell is autologous or allogeneic to the recipient. In some embodiments, the T cell is a cd8+ T cell. In some embodiments, the T cell is a cd4+ T cell. Adoptive immunotherapy refers to a therapeutic method for treating cancer or infectious diseases in which immune cells are administered to a host in order for the cells to directly or indirectly mediate specific immunity to (i.e., generate an immune response against) the cancer cells. In some embodiments, the immune response results in inhibition of tumor and/or metastatic cell growth and/or proliferation, and in related embodiments, death and/or resorption of tumor cells. The immune cells may be derived from different organisms/hosts (exogenous immune cells) or may be cells obtained from the subject organism (autoimmune cells). In some embodiments, immune cells (e.g., autologous or allogeneic T cells (e.g., regulatory T cells, cd4+ T cells, cd8+ T cells, or gamma-delta T cells), NK cells, unchanged NK cells, or NKT cells) can be genetically engineered to express antigen receptors, such as engineered TCRs and/or Chimeric Antigen Receptors (CARs). For example, host cells (e.g., autologous or allogeneic T cells) are modified to express T Cell Receptors (TCRs) that are antigen specific for cancer antigens. In some embodiments, NK cells are engineered to express a TCR. NK cells can be further engineered to express CARs. Multiple CARs and/or TCRs, such as different antigens, may be added to a single cell type, such as a T cell or NK cell. In some embodiments, the cells include one or more nucleic acids/expression constructs/vectors encoding one or more antigen receptors introduced via genetic engineering, as well as genetically engineered products of such nucleic acids. In some embodiments, the nucleic acid is heterologous, i.e., is not normally present in the cell or in a sample obtained from the cell, such as a nucleic acid obtained from another organism or cell, e.g., it is not normally present in an engineered cell and/or in an organism from which such cell is derived. In some embodiments, the nucleic acid is not naturally occurring, such as a nucleic acid that does not exist in nature (e.g., chimeric). In some embodiments, the population of immune cells may be obtained from a subject in need of treatment or suffering from a disease associated with reduced immune cell activity. Thus, the cells are autologous to the subject in need of treatment. In some embodiments, the population of immune cells may be obtained from a donor, such as a histocompatibility matched donor. In some embodiments, the population of immune cells may be harvested from peripheral blood, cord blood, bone marrow, spleen, or any other organ/tissue of immune cells present in the subject or donor. In some embodiments, immune cells may be isolated from a subject and/or donor pool, such as from pooled cord blood. In some embodiments, when the population of immune cells is obtained from a donor other than a subject, the donor may be allogeneic, so long as the obtained cells are subject compatible in that they may be introduced into the subject. In some embodiments, the allogeneic donor cells may or may not be human-leukocyte-antigen (HLA) -compatible. In some embodiments, to compatibilize the subject, the allogeneic cells may be treated to reduce immunogenicity.

In some embodiments, the cell-based therapy comprises a T cell-based therapy, such as autologous cells, e.g., tumor Infiltrating Lymphocytes (TILs); using autologous DCs, lymphocytes, artificial Antigen Presenting Cells (APCs) or beads coated with T cell ligands and activated antibodies, or T cells activated ex vivo by capturing cells isolated from the target cell membrane; allogeneic cells naturally expressing anti-host tumor T Cell Receptors (TCRs); and non-tumor specific autologous or allogeneic cells that have been genetically reprogrammed or "redirected" to express tumor-reactive TCR or chimeric TCR molecules that exhibit antibody-like tumor recognition capabilities, termed "T-bodies". Several methods for isolating, derivatizing, engineering or modifying, activating and expanding functional anti-tumor effector cells have been described over the past twenty years and may be used according to any of the methods provided herein. In some embodiments, the T cells are derived from blood, bone marrow, lymph, umbilical cord, or lymphoid organs. In some embodiments, the cell is a human cell. In some embodiments, the cells are primary cells, such as those isolated directly from the subject and/or isolated from the subject and frozen. In some embodiments, the cells include one or more T cell subsets or other cell types, such as whole T cell populations, cd4+ cells, cd8+ cells, and subsets thereof, such as those defined by function, activation state, maturity, differentiation potential, expansion, recycling, localization and/or persistence, antigen specificity, type of antigen receptor, presence in a specific organ or compartment, marker or cytokine secretion profile, and/or degree of differentiation. In some embodiments, the cells may be allogeneic and/or autologous. In some embodiments, such as for off-the-shelf technology, the cells are pluripotent (pluripotent and/or multipotent), such as stem cells, such as induced pluripotent stem cells (ipscs).

In some embodiments, the T cell-based therapy comprises Chimeric Antigen Receptor (CAR) -T cell-based therapy. This method involves engineering a CAR that specifically binds to an antigen of interest and that includes one or more intracellular signaling domains for T cell activation. The CAR is then expressed on the surface of an engineered T cell (CAR-T) and administered to a patient, resulting in a T cell specific immune response against the antigen-expressing cancer cell.

In some embodiments, the T cell-based therapy comprises T cell expression of a recombinant T Cell Receptor (TCR). The method involves recognizing a TCR that specifically binds to an antigen of interest, and then using it to replace the endogenous or native TCR on the surface of an engineered T cell administered to a patient, resulting in a T cell-specific immune response against the antigen-expressing cancer cell.

In some embodiments, the T cell-based therapy comprises Tumor Infiltrating Lymphocytes (TILs). For example, TIL may be isolated from a tumor or cancer of the present disclosure, then isolated and amplified in vitro. Some or all of these TILs may specifically recognize antigens expressed by the tumors or cancers of the present disclosure. In some embodiments, the TIL is exposed to one or more neoantigens, e.g., a neoantigen, in vitro after isolation. The TIL is then administered to the patient (optionally in combination with one or more cytokines or other immunostimulatory substances).

In some embodiments, the cell-based therapy comprises Natural Killer (NK) cell-based therapy. Natural Killer (NK) cells are a subset of lymphocytes that have spontaneous cytotoxicity against a variety of tumor cells, virus-infected cells, and some normal cells in the bone marrow and thymus. NK cells are key effectors of early innate immune responses to transformed and virally infected cells. NK cells can be detected by specific surface markers such as CD16, CD56 and CD8 in humans. NK cells do not express T cell antigen receptor, the ubiquitin T marker CD3 or the surface immunoglobulin B cell receptor. In some embodiments, NK cells are derived from human Peripheral Blood Mononuclear Cells (PBMCs), unstimulated leukocyte isolation Products (PBSCs), human embryonic stem cells (hescs), induced pluripotent stem cells (ipscs), bone marrow, or umbilical cord blood by methods well known in the art.

In some embodiments, the cell-based therapy comprises a Dendritic Cell (DC) based therapy, e.g., a dendritic cell vaccine. In some embodiments, the DC vaccine comprises antigen presenting cells capable of inducing specific T cell immunity, which are harvested from a patient or donor. In some embodiments, the DC vaccine may then be exposed to the peptide antigen in vitro, thereby generating T cells in the patient. In some embodiments, the antigen-bearing dendritic cells are then injected back into the patient. In some embodiments, immunization may be repeated multiple times, if desired. Methods for harvesting, expanding and administering dendritic cells are known in the art; see, for example, WO2019178081. Dendritic cell vaccines (such as Sipuleucel-T, also known as APC8015 andIs a vaccine that involves the administration of dendritic cells that act as APCs to present one or more cancer specific antigens to the patient's immune system. In some embodiments, the dendritic cells are autologous or allogeneic to the recipient.

In some embodiments, the cancer immunotherapy comprises TCR-based therapy. In some embodiments, cancer immunotherapy comprises administering one or more TCRs or TCR-based therapeutic agents that specifically bind to antigens expressed by cancers of the disclosure. In some embodiments, the TCR-based therapeutic agent may further comprise a moiety that binds to an immune cell (e.g., a T cell), such as an antibody or antibody fragment that specifically binds to a T cell surface protein or receptor (e.g., an anti-CD 3 antibody or antibody fragment).

In some embodiments, the immunotherapy comprises adjuvant immunotherapy. Adjuvant immunotherapy involves the use of one or more agents that activate components of the innate immune system, e.g., target the TLR7 pathway(Imiquimod).

In some embodiments, the immunotherapy comprises cytokine immunotherapy. Cytokine immunotherapy involves the use of one or more cytokines that activate components of the immune system. Examples include, but are not limited to, aldesleukinInterleukin 2), interferon alpha-2 a Interferon alpha-2 bAnd polyethylene glycol interferon alpha-2 b

In some embodiments, the immunotherapy comprises oncolytic virus therapy. Oncolytic virus therapy uses transgenic viruses to replicate in and kill cancer cells, resulting in the release of antigens that stimulate an immune response. In some embodiments, replication-competent oncolytic viruses that express tumor antigens include any naturally occurring (e.g., from a "wild-source") or modified replication-competent oncolytic virus. In some embodiments, oncolytic viruses may be modified to increase the selectivity of the virus for cancer cells in addition to expressing tumor antigens. In some embodiments of the present invention, in some embodiments, oncolytic viruses with replication capacity include, but are not limited to, as myophaidae, longueidae, shorttail, stratified phage, covering phage, budding phage, lipophagostimulaidae, minifusidae, poxviridae, iridoviridae, algae deoxyriboviridae, baculovirus, herpesviridae, adenoviridae, papovaviridae, polydeoxyriboviridae, filoviridae, microviridae, geminiviridae, the family of circoviridae, parvoviridae, hepadnaviridae, retrovirus, vesicular viridae, reoviridae, Oncolytic viruses of members of the families of the picornaviridae, paramyxoviridae, rhabdoviridae, filoviridae, orthomyxoviridae, bunyaviridae, arenaviridae, smooth viridae, picornaviridae, companion viridae, cowpea mosaic viridae, potyviridae, calicivviridae, astroviridae, rowidaviridae, tetraviridae, tomato plexstuviridae, coronaviridae, flaviviridae, togaviridae and baculoviridae. In some embodiments, replication competent oncolytic viruses include adenovirus, retrovirus, reovirus, rhabdovirus, newcastle Disease Virus (NDV), polyoma virus, vaccinia virus (VacV), herpes simplex virus, picornavirus, coxsackie virus, and parvovirus. In some embodiments, replication competent oncolytic vaccinia viruses expressing tumor antigens can be engineered to lack one or more functional genes to increase cancer selectivity of the virus. In some embodiments, the oncolytic vaccinia virus is engineered to lack Thymidine Kinase (TK) activity. In some embodiments, the oncolytic vaccinia virus can be engineered to lack vaccinia Virus Growth Factor (VGF). In some embodiments, the oncolytic vaccinia virus can be engineered to lack both VGF and TK activity. In some embodiments, the oncolytic vaccinia virus can be engineered to lack one or more genes involved in evading a host Interferon (IFN) response, such as E3L, K3L, B R or B8R. In some embodiments, the replication competent oncolytic vaccinia virus is the WESTERN RESERVE, copenhagen, lister, or Wyeth strain and lacks a functional TK gene. In some embodiments, the oncolytic vaccinia virus is a WESTERN RESERVE, copenhagen, lister, or Wyeth strain lacking a functional B18R and/or B8R gene. In some embodiments, the replicative oncolytic vaccine viruses expressing tumor antigens may be administered to a subject locally or systemically, e.g., via intratumoral, intraperitoneal, intravenous, intraarterial, intramuscular, intradermal, intracranial, subcutaneous, or intranasal administration.

In some embodiments, the anti-cancer therapy comprises a nucleic acid molecule, such as dsRNA, siRNA or shRNA. In some embodiments, the methods provided herein comprise administering to an individual a nucleic acid molecule, such as dsRNA, siRNA or shRNA, for example in combination with another anticancer therapy. Dsrnas having a double-stranded (duplex) structure can be effective in inducing RNA interference (RNAi), as known in the art. In some embodiments, the anti-cancer therapy comprises a small interfering RNA molecule (siRNA). dsRNA and siRNA can be used to silence gene expression in mammalian cells (e.g., human cells). In some embodiments, the dsRNA of the present disclosure comprises any one of the following: between about 5 and about 10 base pairs, between about 10 and about 12 base pairs, between about 12 and about 15 base pairs, between about 15 and about 20 base pairs, between about 20 and 23 base pairs, between about 23 and about 25 base pairs, between about 25 and about 27 base pairs, or between about 27 and about 30 base pairs. As known in the art, siRNA is a small dsRNA optionally comprising an overhang. In some embodiments, the duplex region of the siRNA is about 18 to 25 nucleotides, e.g., any of 18, 19, 20, 21, 22, 23, 24, or 25 nucleotides. siRNA may also include short hairpin RNAs (shrnas), for example, stems with about 29 base pairs and 2 nucleotide 3' overhangs. Methods for designing, optimizing, generating, and using dsRNA, siRNA, or shRNA are known in the art.

X. treatment and therapeutic effect

The methods described herein provide improved therapies and/or therapeutic effects. The improved therapy and/or therapeutic effect is based in part on stratification of individuals with cancer having a TMB score below a threshold TMB score and individuals with cancer having a TMB score of at least the threshold TMB score, stratification of individuals with cancer who are MSI-H and individuals with cancer who are not MSI-H (such as MSI-L or MSS), or both. Once the TMB score is determined and/or the microsatellite instability status is assessed, the individual may receive appropriate therapy, resulting in improved clinical outcome, including improved survival (such as improved progression-free survival and/or improved total survival) and/or increased Time To Next Treatment (TTNT). The individual may be any of the individuals described in section III above.

Thus, in some embodiments, the method comprises: an immune checkpoint inhibitor (ICPI, such as ICPI described in section VII) is administered if the TMB score in a sample from an individual with cancer is at least a threshold TMB score. In some embodiments, the method comprises: chemotherapy (such as the chemotherapy described in section VIII) is administered if the TMB score is below the threshold TMB score. In some embodiments, the method comprises: if a sample from an individual is rated MSI-H, ICPI (such as the ICPI described in section VII) is administered. In some embodiments, the method comprises: if the sample from the individual is rated as not MSI-H (such as MSS or MSI-L), chemotherapy (such as described in section VIII) is administered.

In some embodiments, the methods of treatment described herein provide clinical benefit and/or improved clinical benefit to individuals with cancer. In some embodiments, the method provides improved clinical benefit when compared to alternative therapies. For example, in some embodiments, the method includes: ICPI is administered, wherein the individual will benefit or is expected to benefit from ICPI therapy as compared to treatment with a chemotherapy regimen. In some embodiments, the method comprises: a chemotherapy regimen is administered, wherein the individual will benefit or is expected to benefit from the chemotherapy regimen as compared to treatment with ICPI therapy.

In some embodiments, the clinical benefit is improved survival (such as improved PFS and/or improved OS). In some embodiments, after administration, the treatment improves PFS for at least one month, such as any one of at least about 2 months, at least about 3 months, at least about 4 months, at least about 5 months, at least about 6 months, at least about 7 months, at least about 8 months, at least about 9 months, at least about 10 months, at least about 11 months, at least about 12 months, at least about 18 months, at least about 2 years, at least about 3 years, at least about 4 years, or more. In some embodiments, after administration, the treatment improves OS for at least one month, such as any one of at least about 2 months, at least about 3 months, at least about 4 months, at least about 5 months, at least about 6 months, at least about 7 months, at least about 8 months, at least about 9 months, at least about 10 months, at least about 11 months, at least about 12 months, at least about 18 months, at least about 2 years, at least about 3 years, at least about 4 years, or more. In some embodiments, the method of treatment provides an improved objective response rate of at least 20%, such as any of about 25%, about 30%, about 35%, about 40%, about 45%, about 50%, about 55%, about 60%, about 65%, about 70%, about 75%, about 80%, about 85%, about 90%, about 95%, or about 100%.

XI cancer to be assessed or treated

The methods described herein relate to individuals with cancer and assessing the cancer (by assessing a sample, such as a blood sample or a tumor biopsy sample) to identify suitable treatments for the individual. Exemplary cancers to be treated or assessed include, but are not limited to, B cell cancer (e.g., multiple myeloma), melanoma, breast cancer, lung cancer (such as non-small cell lung cancer or NSCLC, including advanced NSCLC), bronchial cancer, colorectal cancer, prostate cancer, pancreatic cancer, gastric cancer, ovarian cancer, bladder cancer, brain or central nervous system cancer, peripheral nervous system cancer, esophageal cancer, cervical cancer, uterine or endometrial cancer, oral or pharyngeal cancer, liver cancer, kidney cancer, testicular cancer, biliary tract cancer, small intestine or appendiceal cancer, salivary gland cancer, thyroid cancer, adrenal gland cancer, osteosarcoma, chondrosarcoma, blood tissue cancer, adenocarcinoma, inflammatory myofibroblastic tumor, Gastrointestinal stromal tumor (GIST), colon cancer, multiple Myeloma (MM), myelodysplastic syndrome (MDS), myeloproliferative disorder (MPD), acute Lymphoblastic Leukemia (ALL), acute Myelogenous Leukemia (AML), chronic Myelogenous Leukemia (CML), chronic Lymphocytic Leukemia (CLL), polycythemia vera, hodgkin's lymphoma, non-hodgkin's lymphoma (NHL), soft tissue sarcoma, fibrosarcoma, myxosarcoma, liposarcoma, osteogenic sarcoma, chordoma, angiosarcoma, endothelial sarcoma, lymphangiosarcoma, lymphatic endothelial sarcoma, and, Synovial tumor, mesothelioma, ewing's tumor, leiomyosarcoma, rhabdomyosarcoma, squamous cell carcinoma, basal cell carcinoma, adenocarcinoma, sweat gland carcinoma, sebaceous gland carcinoma, papillary adenocarcinoma, medullary carcinoma, bronchogenic carcinoma, renal cell carcinoma, liver cancer, cholangiocarcinoma, choriocarcinoma, seminoma, embryonal carcinoma, wilms' tumor, bladder carcinoma, epithelial carcinoma, glioma, astrocytoma, neuroblastoma, craniopharyngeoma, ependymoma, pineal tumor, angioblastoma, auditory neuroma, oligodendroglioma, meningioma, neuroblastoma, retinoblastoma, follicular lymphoma, diffuse large B-cell lymphoma, Mantle cell lymphoma, hepatocellular carcinoma, thyroid carcinoma, gastric cancer, head and neck cancer, small cell carcinoma, primary thrombocytosis, unknown myeloid metaplasia, hypereosinophilia syndrome, systemic mastocytosis, common hypereosinophilia, chronic eosinophilic leukemia, neuroendocrine carcinoma, carcinoid tumor, etc. in some embodiments, the cancer is NSCLC, colorectal cancer, cholangiocarcinoma, breast cancer, gastric cancer, melanoma, pancreatic cancer, prostate cancer, ovarian cancer, esophageal cancer, or primary unknown cancer. In some embodiments, the cancer is metastatic urothelial cancer. In some embodiments, the cancer is metastatic gastric adenocarcinoma. In some embodiments, the cancer is breast cancer. In some embodiments, the cancer is metastatic endometrial cancer. In some embodiments, the cancer is prostate cancer. In some embodiments, the cancer is castration-resistant prostate cancer. In some embodiments, the cancer is colorectal cancer. In some embodiments, the cancer is lung cancer. In some embodiments, the lung cancer is non-small cell lung cancer (NSCLC). In some embodiments, the NSCLC is advanced NSCLC (asnsclc). In some embodiments, the cancer is melanoma. In some embodiments, the cancer is a hematological malignancy (or precancerous lesion). As used herein, hematological malignancy refers to a tumor of hematopoietic or lymphoid tissue, such as a tumor affecting blood, bone marrow, or lymph nodes. Exemplary hematological malignancies include, but are not limited to, leukemia (e.g., acute Lymphoblastic Leukemia (ALL), acute myeloid leukemia (acute myeloid leukemia, AML), chronic Lymphocytic Leukemia (CLL), chronic myelogenous leukemia (chronic myelogenous leukemia, CML), hairy cell leukemia, acute monocytic leukemia (acute monocytic leukemia, AMoL), chronic granulomonocytic leukemia (chronic myelomonocytic leukemia, CMML), childhood granulocytic leukemia (juvenile myelomonocytic leukemia, JMML) or large granular lymphocytic leukemia), lymphomas (e.g., AIDS-related lymphomas, cutaneous T-cell lymphomas, hodgkin lymphomas (e.g., classical hodgkin's or nodular lymphomas predominately), mycosis fungoides, non-hodgkin's lymphomas (e.g., B-cell non-hodgkin's lymphomas (e.g., burkitt's lymphoma, small lymphocytic lymphomas (CLL/SLL), diffuse large B-cell lymphomas, follicular lymphomas, Immunocytoblast large cell lymphoma, precursor B lymphoblastic lymphoma or mantle cell lymphoma) or T-cell non-Hodgkin' S lymphoma (mycosis fungoides anaplastic large cell lymphoma or precursor T lymphoblastic lymphoma), primary central nervous system lymphoma, se zary syndrome,Macroglobulinemia), chronic myeloproliferative neoplasms, langerhans cell histiocytosis (LANGERHANS CELL histiocytosis), multiple myeloma/plasma cell neoplasms, myelodysplastic syndrome, or myelodysplastic/myeloproliferative neoplasms. As used herein, a precancerous lesion refers to a tissue that has not yet been, but is about to become, malignant.

In some embodiments, the cancer to be treated or assessed has never been treated with an anti-cancer therapy. In some embodiments, the cancer to be treated or assessed has never been treated with a chemotherapy regimen or is not currently being treated with a chemotherapy regimen. In some embodiments, the cancer to be treated or assessed has previously been treated with an anti-cancer therapy. In some embodiments, the cancer to be treated or assessed has previously been treated with a chemotherapy regimen.

In some embodiments, the cancer to be treated or assessed has a TMB score of any of at least 8 mutations/Mb, such as about 9 mutations/Mb, about 10 mutations/Mb, about 11 mutations/Mb, about 12 mutations/Mb, about 13 mutations/Mb, about 14 mutations/Mb, about 15 mutations/Mb, about 16 mutations/Mb, about 17 mutations/Mb, about 18 mutations/Mb, about 19 mutations/Mb, about 20 mutations/Mb, or more. In some embodiments, the cancer to be treated or assessed has a TMB score of at least 10 mutations/Mb. In some embodiments, the cancer to be treated or assessed has a TMB score of any of less than 12 mutations/Mb, such as less than about 11 mutations/Mb, about 10 mutations/Mb, about 9 mutations/Mb, about 8 mutations/Mb, about 7 mutations/Mb, about 6 mutations/Mb, or less. In some embodiments, the cancer to be treated or assessed has a TMB score of less than 10 mutations/Mb.

In some embodiments, the cancer to be treated or assessed is MSI-H. In some embodiments, the cancer to be treated or assessed is MSI-L. In some embodiments, the cancer to be treated or assessed is MSS.

In some embodiments, the cancer to be treated or assessed has a TMB score of at least 10 mutations/Mb and is MSI-H. In some embodiments, the cancer to be treated or assessed has a TMB score of at least 10 mutations/Mb and is MSI-L or MSS. In some embodiments, the cancer to be treated or assessed has a TMB score of less than 10 mutations/Mb and is MSI-H. In some embodiments, the cancer to be treated or assessed has a TMB score of less than 10 mutations/Mb and is MSI-L or MSS.

XII exemplary embodiment

The following examples are illustrative and are not intended to limit the scope of the invention.

Example 1. A method for identifying an individual having a cancer to be treated with an immune checkpoint inhibitor therapy, the method comprising: determining a tumor mutation load (TMB) score for a sample obtained from the individual, wherein the individual is identified as to be treated with an immune checkpoint inhibitor therapy if the TMB score is at least a threshold TMB score.

Example 2. A method of selecting a treatment for an individual having cancer, the method comprising: determining a Tumor Mutation Burden (TMB) score for a sample obtained from the individual, wherein a TMB score of at least a threshold TMB score identifies the individual as an individual who may benefit from treatment with an immune checkpoint inhibitor therapy.

Example 3a method of identifying one or more treatment options for an individual having cancer, the method comprising: (a) Determining a Tumor Mutation Burden (TMB) score for a sample obtained from the individual; and (b) generating a report comprising the one or more treatment options identified for the individual, wherein a TMB score of at least a threshold TMB score identifies the individual as an individual who may benefit from treatment with an immune checkpoint inhibitor therapy.

Example 4. A method of stratifying an individual having a cancer to be treated with a therapy, the method comprising: determining a Tumor Mutation Burden (TMB) score for a sample obtained from the individual; and (a) identifying the individual as a candidate to receive immune checkpoint inhibitor therapy if the TMB score is at least a threshold TMB score, or (b) identifying the individual as a candidate to receive chemotherapy regimen if the TMB score is less than a threshold TMB score.

Embodiment 5. The method of any of embodiments 1 to 4, further comprising: assessing microsatellite instability, wherein said identifying is further based on said cancer being microsatellite instability high (MSI-H).

Embodiment 6. The method of any one of embodiments 1 to 5, wherein the individual is identified as having an increased survival compared to treatment with a chemotherapy regimen.

Example 7. A method of predicting survival of an individual having cancer, the method comprising: obtaining knowledge of a tumor mutation load (TMB) score for a sample obtained from the individual, wherein if the TMB score for the sample obtained from the individual is at least a threshold TMB score, the individual is predicted to have an increased survival when treated with an immune checkpoint inhibitor as compared to treatment with a chemotherapy regimen.

Example 8. A method of monitoring, assessing or screening an individual for cancer, the method comprising: obtaining knowledge of a tumor mutation load (TMB) score for a sample obtained from the individual, wherein if the TMB score for the sample obtained from the individual is at least a threshold TMB score, the individual is predicted to have an increased survival when treated with an immune checkpoint inhibitor as compared to treatment with a chemotherapy regimen.

Embodiment 9. The method of any one of embodiments 6 to 8, wherein the increased lifetime is an increased total lifetime (OS).

Embodiment 10. The method of any one of embodiments 6 to 8, wherein the increased lifetime is an increased progression free lifetime (PFS).

Example 11 a method for treating an individual having cancer, the method comprising: (a) Determining a Tumor Mutation Burden (TMB) score for a sample obtained from the individual; and (b) treating the individual with immune checkpoint inhibitor therapy if the TMB score is at least a threshold TMB score.

Embodiment 12. The method of embodiment 11, the method further comprising: assessing microsatellite instability, wherein (b) is further based on the cancer being microsatellite instability high (MSI-H).

Embodiment 13. The method of any of embodiments 1 to 12, further comprising: if the TMB score is less than the threshold TMB score, the individual is treated with chemotherapy.

Embodiment 14. The method of embodiment 13, wherein the chemotherapy comprises one or more of the following or any combination thereof: alkylating agents, aziridines, ethyleneimines, methyl melamines, polyacetyls, camptothecins, bryostatin, kelitans, CC-1065, candidiasis, ceromorphins, sesquioxanes, acanthopanaxins, hydropodocarpine, sarcodictyin, cavernins, nitrogen mustards, nitrosoureas, antibiotics, dactinomycin, bisphosphonates, epothilones, neocarcinomycin chromophores or related pigmentary enediyne antibiotic chromophores, antimetabolites, folic acid analogs, purine analogs, pyrimidine analogs, androgens, anti-adrenaline agents, folic acid supplements aldehyde phosphoramide glycoside, aminolevulinic acid, enimine, amsacrine, bestrabucil, bisacodyl, idatroxacin, defofamine, dimecoxin, filigree quinone, elformithine, irinotecan, epothilone, etodolac, gallium nitrate, hydroxyurea, lentinan, lonidainine, maytansinoids, mitoguanadine, mitoxantrone, mopidanmol, nitraerine, jetstatin, validonine, pirarubicin, loxohexanthrone, podophylloic acid, 2-ethylhydrazide, procarbazine, PSK polysaccharide complex, rafoxanthin, rhizobium, cizopyran, gemini, tenascone, tenuifimbriae, triamcinolone, 2', 2' -trichlorotriethylamine, trichothecene, urethane, vindesine, dacarbazine, mannatine, dibromomannitol, dibromodulcitol, pipobromine, gacytosine, arabinoside ("Ara-C"), cyclophosphamide, taxane, 6-thioguanine, mercaptopurine, platinum coordination complex, vinca alkaloid, platinum, etoposide (VP-16), ifosfamide, mitoxantrone, vincristine, vinorelbine, novantrone, teniposide, idatroxazole, daunomycin, aminopterin, hilded, sodium ibandronate, irinotecan, topoisomerase inhibitor RFS2000, difluoromethylornithine (DMFO), retinoic acid, capecitabine, carboplatin, procarbazine, plicomycin, gemcitabine, novelte, farnesyl protein transferase inhibitor, trans-platinum.

Embodiment 15. The method of any one of embodiments 1 to 14, wherein the threshold TMB score is about 8 mutations/Mb, about 9 mutations/Mb, about 10 mutations/Mb, about 11 mutations/Mb, about 12 mutations/Mb, about 13 mutations/Mb, about 14 mutations/Mb, about 15 mutations/Mb, about 16 mutations/Mb, about 17 mutations/Mb, about 18 mutations/Mb, about 19 mutations/Mb, or about 20 mutations/Mb.

Embodiment 16. The method of any one of embodiments 1 to 15, wherein the threshold TMB score is about 10 mutations/Mb.

Embodiment 17. The method of any one of embodiments 1 to 16, wherein the threshold TMB score is 10 mutations/Mb.

Embodiment 18. The method of any one of embodiments 1 to 17, wherein the TMB score is determined based on between about 100kb to about 10MB of sequenced DNA.

Embodiment 19. The method of any one of embodiments 1 to 18, wherein the TMB score is determined based on between about 0.8Mb and about 1.1Mb of sequenced DNA.

Example 20 a method for identifying an individual having a cancer to be treated with an immune checkpoint inhibitor therapy, the method comprising: assessing microsatellite instability for a sample obtained from the individual, wherein if the microsatellite instability is MSI-H, the individual is identified as to be treated with an immune checkpoint inhibitor therapy.

Example 21 a method of selecting a treatment for an individual having cancer, the method comprising: the microsatellite instability for a sample obtained from the individual is assessed, wherein microsatellite instability for MSI-H identifies the individual as an individual who may benefit from treatment with an immune checkpoint inhibitor therapy.

Example 22 a method of identifying one or more treatment options for an individual having metastatic cancer, the method comprising: (a) Assessing microsatellite instability for a sample obtained from an individual; and (b) generating a report comprising the one or more treatment options identified for the individual, wherein microsatellite instability for MSI-H identifies the individual as an individual who may benefit from treatment with an immune checkpoint inhibitor therapy.

Example 23. A method of stratifying an individual having a cancer to be treated with a therapy, the method comprising: assessing microsatellite instability for a sample obtained from the individual; and (a) identifying the individual as a candidate to receive immune checkpoint inhibitor therapy if the microsatellite instability is MSI-H, or (b) identifying the individual as a candidate to receive chemotherapy regimen if the microsatellite instability is not MSI-H.

Embodiment 24. The method of any one of embodiments 20 to 23, wherein the individual is identified as having an increased survival compared to treatment with a chemotherapy regimen.

Example 25. A method of predicting survival of an individual having cancer, the method comprising: obtaining knowledge of microsatellite instability for a sample obtained from the individual, wherein if the microsatellite instability for the sample obtained from the individual is MSI-H, the individual is predicted to have an increased lifetime when treated with an immune checkpoint inhibitor compared to treatment with a chemotherapy regimen.

Example 26 a method of monitoring, assessing or screening an individual for cancer, the method comprising: obtaining knowledge of microsatellite instability for a sample obtained from the individual, wherein if the microsatellite instability for the sample obtained from the individual is MSI-H, the individual is predicted to have an increased lifetime when treated with an immune checkpoint inhibitor compared to treatment with a chemotherapy regimen.

Embodiment 27. The method of any one of embodiments 20 to 26, wherein the increased lifetime is an increased total lifetime (OS).

Embodiment 28. The method of any one of embodiments 20 to 26, wherein the increased lifetime is an increased progression-free lifetime (PFS).

Embodiment 29. The method of any of embodiments 1 to 28, further comprising: treating the individual with an immune checkpoint inhibitor.

Embodiment 30. A method for treating an individual having cancer, the method comprising: (a) Assessing microsatellite instability for a sample obtained from the individual; and (b) if the microsatellite instability is assessed as MSI-H, treating the individual with an immune checkpoint inhibitor therapy.

Embodiment 31. The method of any one of embodiments 20 to 30, wherein microsatellite instability is assessed by NGS.

Embodiment 32. The method of any of embodiments 20 to 31, further comprising: if the microsatellite instability is not assessed as MSI-H, the individual is treated with chemotherapy.

Embodiment 33. The method of embodiment 32, wherein the chemotherapy comprises one or more of the following or any combination thereof: alkylating agents, aziridines, ethyleneimines, methyl melamines, polyacetyls, camptothecins, bryostatin, kelitans, CC-1065, candidiasis, ceromorphins, sesquioxanes, acanthopanaxins, hydropodocarpine, sarcodictyin, cavernins, nitrogen mustards, nitrosoureas, antibiotics, dactinomycin, bisphosphonates, epothilones, neocarcinomycin chromophores or related pigmentary enediyne antibiotic chromophores, antimetabolites, folic acid analogs, purine analogs, pyrimidine analogs, androgens, anti-adrenaline agents, folic acid supplements aldehyde phosphoramide glycoside, aminolevulinic acid, enimine, amsacrine, bestrabucil, bisacodyl, idatroxacin, defofamine, dimecoxin, filigree quinone, elformithine, irinotecan, epothilone, etodolac, gallium nitrate, hydroxyurea, lentinan, lonidainine, maytansinoids, mitoguanadine, mitoxantrone, mopidanmol, nitraerine, jetstatin, validonine, pirarubicin, loxohexanthrone, podophylloic acid, 2-ethylhydrazide, procarbazine, PSK polysaccharide complex, rafoxanthin, rhizobium, cizopyran, gemini, tenascone, tenuifimbriae, triamcinolone, 2', 2' -trichlorotriethylamine, trichothecene, urethane, vindesine, dacarbazine, mannatine, dibromomannitol, dibromodulcitol, pipobromine, gacytosine, arabinoside ("Ara-C"), cyclophosphamide, taxane, 6-thioguanine, mercaptopurine, platinum coordination complex, vinca alkaloid, platinum, etoposide (VP-16), ifosfamide, mitoxantrone, vincristine, vinorelbine, novantrone, teniposide, idatroxazole, daunomycin, aminopterin, hilded, sodium ibandronate, irinotecan, topoisomerase inhibitor RFS2000, difluoromethylornithine (DMFO), retinoic acid, capecitabine, carboplatin, procarbazine, plicomycin, gemcitabine, novelte, farnesyl protein transferase inhibitor, trans-platinum.

Embodiment 34. The method of any one of embodiments 1-33, wherein the cancer is a metastatic cancer.

Embodiment 35. The method of any one of embodiments 1 to 34, wherein the cancer is B cell cancer, melanoma, breast cancer, lung cancer, bronchus cancer, colorectal cancer or cancer, prostate cancer, pancreatic cancer, gastric cancer, ovarian cancer, bladder cancer, brain cancer, central nervous system cancer, peripheral nervous system cancer, esophageal cancer, cervical cancer, uterine cancer, endometrial cancer, oral cancer, pharyngeal cancer, liver cancer, kidney cancer, testicular cancer, biliary tract cancer, small intestine cancer, appendiceal cancer, salivary gland cancer, thyroid cancer, adrenal cancer, osteosarcoma, chondrosarcoma, blood tissue cancer, adenocarcinoma, inflammatory myofibroblastic tumor, gastrointestinal stromal tumor (GIST), colon cancer, multiple Myeloma (MM), myelodysplastic syndrome (MDS), myeloproliferative disorder (MPD), acute Lymphoblastic Leukemia (ALL) Acute Myelogenous Leukemia (AML), chronic Myelogenous Leukemia (CML), chronic Lymphocytic Leukemia (CLL), polycythemia vera, hodgkin's lymphoma, non-Hodgkin's lymphoma (NHL), soft tissue sarcoma, fibrosarcoma, myxosarcoma, liposarcoma, osteogenic sarcoma, chordoma, angiosarcoma, endothelial sarcoma, lymphangiosarcoma, lymphangioendothelioma, synovioma, mesothelioma, ewing's tumor, leiomyosarcoma, rhabdomyosarcoma, squamous cell carcinoma, basal cell carcinoma, adenocarcinoma, sweat gland carcinoma, sebaceous gland carcinoma, papillary adenocarcinoma, medullary carcinoma, bronchogenic carcinoma, renal cell carcinoma, hepatoma, cholangiocarcinoma, choriocarcinoma, seminoma, embryonal carcinoma, wilms' tumor, bladder cancer, epithelial cancer, glioma, astrocytoma, medulloblastoma, craniopharyngeal medulloma, ependymoma, pineal tumor, angioblastoma, auditory neuroma, oligodendroglioma, meningioma, neuroblastoma, retinoblastoma, follicular lymphoma, diffuse large B-cell lymphoma, mantle cell lymphoma, hepatocellular carcinoma, thyroid cancer, gastric cancer or cancer, lung non-small cell lung cancer (NSCLC), head and neck cancer, small cell carcinoma, primary thrombocythemia, agnostic myeloplasia, hypereosinophilia syndrome, systemic mastocytosis, common hypereosinophilia, chronic eosinophilic leukemia, neuroendocrine cancer or carcinoid tumor.

Embodiment 36. The method of any one of embodiments 1 to 35, wherein the cancer is metastatic urothelial cancer.

Embodiment 37. The method of any one of embodiments 1-35, wherein the cancer is metastatic gastric adenocarcinoma.

Embodiment 38. The method of any one of embodiments 1 to 35, wherein the cancer is breast cancer.

Embodiment 39. The method of any one of embodiments 1 to 35, wherein the cancer is prostate cancer.

Embodiment 40. The method of embodiment 39, wherein the prostate cancer is metastatic castration-resistant prostate cancer.

Embodiment 41. The method of any one of embodiments 1 to 35, wherein the cancer is colorectal cancer.

Embodiment 42. The method of any one of embodiments 1 to 35, wherein the cancer is lung cancer.

Embodiment 43. The method of embodiment 42 wherein the lung cancer is non-small cell lung cancer (NSCLC).

The method of claim 43, wherein the NSCLC is advanced NSCLC (aNSCLC).

Embodiment 45. The method of any one of embodiments 1 to 35, wherein the cancer is endometrial cancer.

Embodiment 46. The method of any one of embodiments 1 to 35, wherein the cancer is melanoma.

Embodiment 47. The method of any one of embodiments 1 to 46, wherein the immune checkpoint inhibitor comprises a small molecule inhibitor, an antibody, a nucleic acid, an antibody-drug conjugate, a recombinant protein, a fusion protein, a natural compound, a peptide, a proteolytically targeted chimera (PROTAC), a cell therapy, a treatment against cancer being tested in a clinical trial, an immunotherapy, or any combination thereof.

Embodiment 48. The method of embodiment 47, wherein the immune checkpoint inhibitor is a PD-1 inhibitor.

Embodiment 49 the method of embodiment 47, wherein the immune checkpoint inhibitor comprises one or more of the following: nivolumab, pembrolizumab, cimetidine Li Shan, or rituximab.

Embodiment 50. The method of embodiment 47, wherein the immune checkpoint inhibitor is a PD-L1 inhibitor.

Embodiment 51. The method of embodiment 47, wherein the immune checkpoint inhibitor comprises one or more of the following: alemtuzumab Avermectin or Avermectin Devaluzumab.

Embodiment 52. The method of embodiment 47, wherein the immune checkpoint inhibitor is a CTLA-4 inhibitor.

Embodiment 53. The method of embodiment 52, wherein the CTLA-4 inhibitor comprises ipilimumab.

Embodiment 54 the method of any one of embodiments 1-53, wherein the individual has not previously received a chemotherapy regimen for the cancer.

Embodiment 55. The method of any one of embodiments 1-53, wherein the individual has previously received a chemotherapy regimen for the cancer.

Embodiment 56. The method of embodiment 55, wherein the prior chemotherapy regimen comprises one or more of the following or any combination thereof: alkylating agents, aziridines, ethyleneimines, methyl melamines, polyacetyls, camptothecins, bryostatin, kelitans, CC-1065, candidiasis, ceromorphins, sesquioxanes, acanthopanaxins, hydropodocarpine, sarcodictyin, cavernins, nitrogen mustards, nitrosoureas, antibiotics, dactinomycin, bisphosphonates, epothilones, neocarcinomycin chromophores or related pigmentary enediyne antibiotic chromophores, antimetabolites, folic acid analogs, purine analogs, pyrimidine analogs, androgens, anti-adrenaline agents, folic acid supplements aldehyde phosphoramide glycoside, aminolevulinic acid, enimine, amsacrine, bestrabucil, bisacodyl, idatroxacin, defofamine, dimecoxin, filigree quinone, elformithine, irinotecan, epothilone, etodolac, gallium nitrate, hydroxyurea, lentinan, lonidainine, maytansinoids, mitoguanadine, mitoxantrone, mopidanmol, nitraerine, jetstatin, validonine, pirarubicin, loxohexanthrone, podophylloic acid, 2-ethylhydrazide, procarbazine, PSK polysaccharide complex, rafoxanthin, rhizobium, cizopyran, gemini, tenascone, tenuifimbriae, triamcinolone, 2', 2' -trichlorotriethylamine, trichothecene, urethane, vindesine, dacarbazine, mannatine, dibromomannitol, dibromodulcitol, pipobromine, gacytosine, arabinoside ("Ara-C"), cyclophosphamide, taxane, 6-thioguanine, mercaptopurine, platinum coordination complex, vinca alkaloid, platinum, etoposide (VP-16), ifosfamide, mitoxantrone, vincristine, vinorelbine, novantrone, teniposide, idatroxazole, daunomycin, aminopterin, hilded, sodium ibandronate, irinotecan, topoisomerase inhibitor RFS2000, difluoromethylornithine (DMFO), retinoic acid, capecitabine, carboplatin, procarbazine, plicomycin, gemcitabine, novelte, farnesyl protein transferase inhibitor, trans-platinum.

Embodiment 57 the method of any one of embodiments 1-56, wherein the immune checkpoint inhibitor therapy is the only anti-cancer therapy indicated or administered for the cancer.

Embodiment 58 the method of any one of embodiments 1 to 56, wherein the immune checkpoint inhibitor therapy is a single active agent therapy.

Embodiment 59. The method of any one of embodiments 1 to 56, wherein the immune checkpoint inhibitor comprises two or more active agents of therapy.

Embodiment 60. The method of any one of embodiments 1 to 56, wherein the immune checkpoint inhibitor therapy comprises a first round of immune checkpoint inhibitor and a subsequent round of therapy with a different immune checkpoint inhibitor.

Embodiment 61 the method of any one of embodiments 1 to 60, wherein the immune checkpoint inhibitor therapy is a first line therapy for the cancer.

Embodiment 62. The method of any of embodiments 1 to 56, the method further comprising: the individual is treated with an additional anti-cancer therapy.

Embodiment 63. The method of embodiment 62, wherein the additional anti-cancer therapy comprises one or more of the following or any combination thereof: small molecule inhibitors, chemotherapeutic agents, cancer immunotherapy, antibodies, cell therapies, nucleic acids, surgery, radiation therapy, anti-angiogenic therapy, anti-DNA repair therapy, anti-inflammatory therapy, anti-tumor agents, growth inhibitors, cytotoxic agents.

Embodiment 64 the method of any one of embodiments 1-63, wherein the sample is a solid tumor biopsy sample obtained from the individual.

Embodiment 65. The method of any of embodiments 1-63, wherein the sample is a liquid biopsy sample obtained from the individual.

Embodiment 66. The method of embodiment 65, wherein the liquid biopsy sample comprises blood, plasma, serum, cerebrospinal fluid, sputum, stool, urine, or saliva.

Embodiment 67. The method of embodiment 65 or embodiment 66, wherein the liquid biopsy sample comprises mRNA, DNA, circulating tumor DNA (ctDNA), cell-free DNA, or cell-free RNA from the cancer.

Embodiment 68. The method of any one of embodiments 1-67, wherein the TMB score or microsatellite instability is determined by sequencing.

Embodiment 69. The method of embodiment 68, wherein the sequencing comprises using a large-scale parallel sequencing (MPS) technique, whole Genome Sequencing (WGS), whole exome sequencing, targeted sequencing, direct sequencing, next Generation Sequencing (NGS), or Sanger sequencing technique.

Embodiment 70. The method of embodiment 68 or embodiment 69, wherein the sequencing comprises: (a) Providing a plurality of nucleic acid molecules obtained from the sample, wherein the plurality of nucleic acid molecules comprises a mixture of tumor nucleic acid molecules and non-tumor nucleic acid molecules; (b) Optionally, ligating one or more adaptors to one or more nucleic acid molecules from said plurality of nucleic acid molecules; (c) Amplifying nucleic acid molecules from the plurality of nucleic acid molecules; (d) Capturing a nucleic acid molecule from an amplified nucleic acid molecule, wherein the captured nucleic acid molecule is captured from the amplified nucleic acid molecule by hybridization with one or more decoy molecules; (e) The captured nucleic acid molecules are sequenced by a sequencer to obtain a plurality of sequence reads corresponding to one or more genomic loci within a subgenomic interval in the sample.

Embodiment 71. The method of embodiment 70 wherein the adapter comprises one or more of the following: an amplification primer sequence, a flow cell adaptor hybridization sequence, a unique molecular identification sequence, a substrate adaptor sequence, or a sample index sequence.

Embodiment 72. The method of embodiment 70 or embodiment 71, wherein amplifying the nucleic acid molecule comprises: polymerase Chain Reaction (PCR) techniques, non-PCR amplification techniques, or isothermal amplification techniques are performed.

Embodiment 73 the method of any one of embodiments 70-72, wherein the one or more decoy molecules comprises one or more nucleic acid molecules, each nucleic acid molecule comprising a region complementary to a region of the captured nucleic acid molecule.

Embodiment 74. The method of embodiment 73, wherein each of the one or more bait molecules comprises a capture moiety.

Embodiment 75. The method of embodiment 74, wherein the capture moiety is biotin.

Embodiment 76 the method of any one of embodiments 1 to 75, wherein the subject is a human.

Example 77 a kit comprising an immune checkpoint inhibitor and instructions for use according to the method of any one of examples 1 to 76.

Example 1A method for identifying an individual having a cancer to be treated with an immune checkpoint inhibitor therapy, the method comprising: determining a tumor mutation load (TMB) score for a tumor biopsy sample obtained from the individual, wherein if the TMB score is at least a threshold TMB score, the individual is identified as being to be treated with an immune checkpoint inhibitor therapy, wherein the cancer is metastatic urothelial cancer, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC).

Example 2A method of selecting a treatment for an individual having cancer, the method comprising: determining a tumor mutation load (TMB) score for a tumor biopsy sample obtained from the individual, wherein a TMB score of at least a threshold TMB score identifies the individual as an individual who may benefit from treatment with an immune checkpoint inhibitor therapy, wherein the cancer is metastatic urothelial cancer, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC).

Example 3A. A method of identifying one or more treatment options for an individual having cancer, the method comprising:

Determining a Tumor Mutation Burden (TMB) score for a tumor biopsy sample obtained from the individual; and

Generating a report comprising one or more treatment options identified for the individual, wherein a TMB score of at least a threshold TMB score identifies the individual as an individual who may benefit from treatment with an immune checkpoint inhibitor therapy, wherein the cancer is metastatic urothelial cancer, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC).

Example 4A. A method of stratifying an individual having a cancer to be treated with a therapy, the method comprising: determining a Tumor Mutation Burden (TMB) score for a tumor biopsy sample obtained from the individual; and

Identifying the individual as a candidate to receive immune checkpoint inhibitor therapy if the TMB score is at least a threshold TMB score, or

Identifying the individual as a candidate to receive a chemotherapy regimen if the TMB score is less than a threshold TMB score;

Wherein the cancer is metastatic urothelial cancer, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer or non-small cell lung cancer (NSCLC).

Embodiment 5A. The method of any of embodiments 1A to 4A, the method further comprising: assessing microsatellite instability, wherein said identifying is further based on said cancer being microsatellite instability high (MSI-H).

Example 6A. The method according to example 5A, wherein microsatellite instability is assessed by Next Generation Sequencing (NGS).

Embodiment 7A. The method of any one of embodiments 1A-6A, wherein the individual is identified as having an increased survival compared to treatment with a chemotherapy regimen.

Example 8A. A method of predicting survival of an individual having cancer, the method comprising: obtaining knowledge of a tumor mutation load (TMB) score for a tumor biopsy sample obtained from the individual, wherein if the TMB score for the tumor biopsy sample obtained from the individual is at least a threshold TMB score, the individual is predicted to have an increased survival when treated with an immune checkpoint inhibitor compared to treatment with a chemotherapy regimen, wherein the cancer is metastatic urothelial cancer, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC).

Example 9A. A method of monitoring, assessing or screening an individual for cancer, the method comprising: obtaining knowledge of a tumor mutation load (TMB) score for a tumor biopsy sample obtained from the individual, wherein if the TMB score for the tumor biopsy sample obtained from the individual is at least a threshold TMB score, the individual is predicted to have an increased survival when treated with an immune checkpoint inhibitor compared to treatment with a chemotherapy regimen, wherein the cancer is metastatic urothelial cancer, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC).

Example 10A. A method of predicting survival of an individual having cancer, the method comprising: obtaining knowledge of a tumor mutation load (TMB) score for a tumor biopsy sample obtained from the individual, wherein if the TMB score for the tumor biopsy sample obtained from the individual is at least a threshold TMB score, the individual is predicted to have an increased survival when treated with an immune checkpoint inhibitor compared to a patient having a TMB score that is less than the threshold TMB score, wherein the cancer is metastatic urothelial cancer, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC).

Example 11A. A method of monitoring, assessing or screening an individual for cancer, the method comprising: obtaining knowledge of a tumor mutation load (TMB) score for a tumor biopsy sample obtained from the individual, wherein if the TMB score for the tumor biopsy sample obtained from the individual is at least a threshold TMB score, the individual is predicted to have an increased survival when treated with an immune checkpoint inhibitor compared to a patient having a TMB score that is less than the threshold TMB score, wherein the cancer is metastatic urothelial cancer, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC).

Embodiment 12A. The method of any one of embodiments 7A-11A, wherein the increased lifetime is an increased total lifetime (OS).

Embodiment 13A. The method of any one of embodiments 7A-11A, wherein the increased survival is increased Progression Free Survival (PFS).

Example 14A method of predicting the duration of a therapeutic response to an individual having cancer, the method comprising: obtaining knowledge of a Tumor Mutation Burden (TMB) score for a tumor biopsy sample obtained from the individual; and comparing the TMB score for the sample to a threshold TMB score, wherein if the TMB score is greater than or equal to the threshold TMB score, the individual is predicted to have a longer duration of therapeutic response to an immune checkpoint inhibitor; and wherein if the TMB score is less than the threshold TMB score, the subject is predicted to have a shorter duration of therapeutic response to an immune checkpoint inhibitor.

Embodiment 15A. The method of embodiment 14A, wherein the longer duration of the therapeutic response is one or more of: increased Progression Free Survival (PFS) and total survival (OS), and wherein the shorter duration of the therapeutic response is one or more of: reduced PFS and reduced OS.

Example 16A. A method for treating an individual having cancer, the method comprising: determining a Tumor Mutation Burden (TMB) score for a tumor biopsy sample obtained from the individual; and if the TMB score is at least a threshold TMB score, treating the individual with an immune checkpoint inhibitor therapy;

Wherein the cancer is metastatic urothelial cancer, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer or non-small cell lung cancer (NSCLC).

Embodiment 17A. The method of embodiment 16A, the method further comprising: assessing microsatellite instability, wherein (b) is further based on the cancer being microsatellite instability high (MSI-H).

Example 18A. The method according to example 17A, wherein microsatellite instability is assessed by Next Generation Sequencing (NGS).

Embodiment 19A. The method of any one of embodiments 1A to 18A, the method further comprising: if the TMB score is less than the threshold TMB score, the individual is treated with chemotherapy.

Embodiment 20A. The method of embodiment 19A, wherein the chemotherapy comprises one or more of the following or any combination thereof: alkylating agents, aziridines, ethyleneimines, methyl melamines, polyacetyls, camptothecins, bryostatin, kelitans, CC-1065, candidiasis, ceromorphins, sesquioxanes, acanthopanaxins, hydropodocarpine, sarcodictyin, cavernins, nitrogen mustards, nitrosoureas, antibiotics, dactinomycin, bisphosphonates, epothilones, neocarcinomycin chromophores or related pigmentary enediyne antibiotic chromophores, antimetabolites, folic acid analogs, purine analogs, pyrimidine analogs, androgens, anti-adrenaline agents, folic acid supplements aldehyde phosphoramide glycoside, aminolevulinic acid, enimine, amsacrine, bestrabucil, bisacodyl, idatroxacin, defofamine, dimecoxin, filigree quinone, elformithine, irinotecan, epothilone, etodolac, gallium nitrate, hydroxyurea, lentinan, lonidainine, maytansinoids, mitoguanadine, mitoxantrone, mopidanmol, nitraerine, jetstatin, validonine, pirarubicin, loxohexanthrone, podophylloic acid, 2-ethylhydrazide, procarbazine, PSK polysaccharide complex, rafoxanthin, rhizobium, cizopyran, gemini, tenascone, tenuifimbriae, triamcinolone, 2', 2' -trichlorotriethylamine, trichothecene, urethane, vindesine, dacarbazine, mannatine, dibromomannitol, dibromodulcitol, pipobromine, gacytosine, arabinoside ("Ara-C"), cyclophosphamide, taxane, 6-thioguanine, mercaptopurine, platinum coordination complex, vinca alkaloid, platinum, etoposide (VP-16), ifosfamide, mitoxantrone, vincristine, vinorelbine, novantrone, teniposide, idatroxazole, daunomycin, aminopterin, hilded, sodium ibandronate, irinotecan, topoisomerase inhibitor RFS2000, difluoromethylornithine (DMFO), retinoic acid, capecitabine, carboplatin, procarbazine, plicomycin, gemcitabine, novelte, farnesyl protein transferase inhibitor, trans-platinum.

Embodiment 21A. The method of any one of embodiments 1A-20A, wherein the threshold TMB score is about 8 mutations/Mb, about 9 mutations/Mb, about 10 mutations/Mb, about 11 mutations/Mb, about 12 mutations/Mb, about 13 mutations/Mb, about 14 mutations/Mb, about 15 mutations/Mb, about 16 mutations/Mb, about 17 mutations/Mb, about 18 mutations/Mb, about 19 mutations/Mb, or about 20 mutations/Mb.

Embodiment 22A. The method of any one of embodiments 1A-21A, wherein the threshold TMB score is about 10 mutations/Mb.

Embodiment 23A. The method of any one of embodiments 1A-22A, wherein the threshold TMB score is 10 mutations/Mb.

Embodiment 24A. The method of any one of embodiments 1A-22A, wherein the threshold TMB score is 20 mutations/Mb. Embodiment 25A. The method of any one of embodiments 1A-24A, wherein the TMB score is determined based on between about 100kb to about 10Mb of sequenced DNA.

Embodiment 26A. The method of any of embodiments 1A-25A, wherein the TMB score is determined based on between about 0.8Mb to about 1.1Mb of sequenced DNA.

Embodiment 27A. The method of any one of embodiments 1A to 26A, the method further comprising: if the TMB score is at least the threshold TMB score, the individual is treated with an immune checkpoint inhibitor.

Embodiment 28A. The method of any one of embodiments 1A-27A, wherein the cancer is a prostate cancer that is metastatic castration-resistant prostate cancer.

Embodiment 29A. The method of any one of embodiments 1A-27A, wherein the cancer is metastatic urothelial cancer.

Embodiment 30A. The method of any one of embodiments 1A-27A, wherein the cancer is metastatic gastric adenocarcinoma.

Embodiment 31A. The method of any one of embodiments 1A-27A, wherein the cancer is metastatic endometrial cancer.

Embodiment 32A. The method of any one of embodiments 1A-27A, wherein the cancer is NSCLC or advanced NSCLC (asnsclc).

Embodiment 33A. The method of any of embodiments 1A-32A, wherein the immune checkpoint inhibitor comprises a small molecule inhibitor, an antibody, a nucleic acid, an antibody-drug conjugate, a recombinant protein, a fusion protein, a natural compound, a peptide, a proteolytically targeted chimera (PROTAC), cell therapy, a treatment for cancer that is being tested in a clinical trial, immunotherapy, or any combination thereof.

Embodiment 34A. The method of embodiment 33A, wherein the immune checkpoint inhibitor is a PD-1 inhibitor.

Embodiment 35A. The method of embodiment 33A, wherein the immune checkpoint inhibitor comprises one or more of: nivolumab, pembrolizumab, cimetidine Li Shan, or rituximab.

Embodiment 36A. The method of embodiment 33A, wherein the immune checkpoint inhibitor is a PD-L1 inhibitor.

Embodiment 37A. The method of embodiment 33A, wherein the immune checkpoint inhibitor comprises one or more of: alemtuzumab Avermectin or Avermectin Devaluzumab.

Embodiment 38A. The method of embodiment 33A, wherein the immune checkpoint inhibitor is a CTLA-4 inhibitor.

Example 39A. The method of example 38A, wherein the CTLA-4 inhibitor comprises ipilimumab.

Embodiment 40A. The method of any one of embodiments 1A-39A, wherein the individual has previously received treatment with an anti-cancer therapy for the cancer.

Embodiment 41A. The method of embodiment 40A, wherein the anti-cancer therapy is one or more of the following or any combination thereof: small molecule inhibitors, chemotherapeutic agents, cancer immunotherapy, antibodies, cell therapies, nucleic acids, surgery, radiation therapy, anti-angiogenic therapy, anti-DNA repair therapy, anti-inflammatory therapy, anti-tumor agents, growth inhibitors, cytotoxic agents.

Embodiment 42A. The method of any one of embodiments 1A-41A, wherein the individual has not previously received a chemotherapy regimen for the cancer.

Embodiment 43A. The method of any one of embodiments 1A-41A, wherein the individual has previously received a chemotherapy regimen for the cancer.

Embodiment 44A. The method of embodiment 43A, wherein the prior chemotherapy regimen comprises one or more of the following or any combination thereof: alkylating agents, aziridines, ethyleneimines, methyl melamines, polyacetyls, camptothecins, bryostatin, kelitans, CC-1065, candidiasis, ceromorphins, sesquioxanes, acanthopanaxins, hydropodocarpine, sarcodictyin, cavernins, nitrogen mustards, nitrosoureas, antibiotics, dactinomycin, bisphosphonates, epothilones, neocarcinomycin chromophores or related pigmentary enediyne antibiotic chromophores, antimetabolites, folic acid analogs, purine analogs, pyrimidine analogs, androgens, anti-adrenaline agents, folic acid supplements aldehyde phosphoramide glycoside, aminolevulinic acid, enimine, amsacrine, bestrabucil, bisacodyl, idatroxacin, defofamine, dimecoxin, filigree quinone, elformithine, irinotecan, epothilone, etodolac, gallium nitrate, hydroxyurea, lentinan, lonidainine, maytansinoids, mitoguanadine, mitoxantrone, mopidanmol, nitraerine, jetstatin, validonine, pirarubicin, loxohexanthrone, podophylloic acid, 2-ethylhydrazide, procarbazine, PSK polysaccharide complex, rafoxanthin, rhizobium, cizopyran, gemini, tenascone, tenuifimbriae, triamcinolone, 2', 2' -trichlorotriethylamine, trichothecene, urethane, vindesine, dacarbazine, mannatine, dibromomannitol, dibromodulcitol, pipobromine, gacytosine, arabinoside ("Ara-C"), cyclophosphamide, taxane, 6-thioguanine, mercaptopurine, platinum coordination complex, vinca alkaloid, platinum, etoposide (VP-16), ifosfamide, mitoxantrone, vincristine, vinorelbine, novantrone, teniposide, idatroxazole, daunomycin, aminopterin, hilded, sodium ibandronate, irinotecan, topoisomerase inhibitor RFS2000, difluoromethylornithine (DMFO), retinoic acid, capecitabine, carboplatin, procarbazine, plicomycin, gemcitabine, novelte, farnesyl protein transferase inhibitor, trans-platinum.

Embodiment 45A the method of any one of embodiments 1A-44A, wherein the immune checkpoint inhibitor therapy is the only anti-cancer therapy indicated or administered for the cancer.

Embodiment 46A. The method of any one of embodiments 1A-45A, wherein the immune checkpoint inhibitor therapy is a single active agent therapy.

Embodiment 47A. The method of any one of embodiments 1A-45A, wherein the immune checkpoint inhibitor therapy comprises two or more active agents.

Embodiment 48A. The method of any one of embodiments 1A-47A, wherein the immune checkpoint inhibitor therapy comprises a first round of immune checkpoint inhibitor and a subsequent round of therapy with a different immune checkpoint inhibitor.

Embodiment 49A. The method of any one of embodiments 1A-48A, wherein the immune checkpoint inhibitor therapy is a first line therapy for the cancer.

Embodiment 50A. The method of any one of embodiments 1A-48A, wherein the immune checkpoint inhibitor therapy is a two-wire therapy for the cancer.

Embodiment 51A. The method of any one of embodiments 1A to 50A, the method further comprising: the individual is treated with an additional anti-cancer therapy.

Embodiment 52A. The method of embodiment 51A, wherein the additional anti-cancer therapy comprises one or more of the following or any combination thereof: small molecule inhibitors, chemotherapeutic agents, cancer immunotherapy, antibodies, cell therapies, nucleic acids, surgery, radiation therapy, anti-angiogenic therapy, anti-DNA repair therapy, anti-inflammatory therapy, anti-tumor agents, growth inhibitors, cytotoxic agents.

Embodiment 53A. The method of any one of embodiments 1A-52A, wherein the TMB score or microsatellite instability is determined by sequencing.

Embodiment 54A. The method of embodiment 53A, wherein the sequencing comprises using a large-scale parallel sequencing (MPS) technique, whole Genome Sequencing (WGS), whole Exome Sequencing (WES), targeted sequencing, direct sequencing, next Generation Sequencing (NGS), or Sanger sequencing technique.

Embodiment 55A. The method of embodiment 53A or embodiment 54A, wherein the sequencing comprises:

providing a plurality of nucleic acid molecules obtained from the tumor biopsy sample, wherein the plurality of nucleic acid molecules comprises a mixture of tumor nucleic acid molecules and non-tumor nucleic acid molecules;

optionally, ligating one or more adaptors to one or more nucleic acid molecules from said plurality of nucleic acid molecules;

amplifying nucleic acid molecules from the plurality of nucleic acid molecules;

capturing a nucleic acid molecule from an amplified nucleic acid molecule, wherein the captured nucleic acid molecule is captured from the amplified nucleic acid molecule by hybridization with one or more decoy molecules;

sequencing at least a portion of the captured nucleic acid molecules by a sequencer to obtain a plurality of sequence reads corresponding to one or more genomic loci within a subgenomic interval of the sample.

Embodiment 56A. The method of embodiment 55A, wherein the adapter comprises one or more of the following: an amplification primer sequence, a flow cell adaptor hybridization sequence, a unique molecular identification sequence, a substrate adaptor sequence, or a sample index sequence.

Example 57A. The method of example 55A or example 56A, wherein amplifying the nucleic acid molecule comprises: polymerase Chain Reaction (PCR) techniques, non-PCR amplification techniques, or isothermal amplification techniques are performed.

Embodiment 58A. The method of any of embodiments 55A to 57A, wherein the one or more decoy molecules comprises one or more nucleic acid molecules, each nucleic acid molecule comprising a region complementary to a region of the captured nucleic acid molecule.

Embodiment 59A. The method of embodiment 58A, wherein the one or more bait molecules each comprise a capture moiety.

Embodiment 60A. The method of embodiment 59A, wherein the capture moiety is biotin.

Embodiment 61A. The method of any one of embodiments 1A-60A, wherein the subject is a human.

Embodiment 62A the method of any one of embodiments 1A-61A, wherein if the TMB score is at least the threshold TMB score, the individual is predicted to have an increased time to next treatment as compared to chemotherapy when treated with an immune checkpoint inhibitor (TTNT).

Example 63A kit comprising an immune checkpoint inhibitor and instructions for use according to the method of any one of examples 1A to 62A.

Examples

Example 1: tumor mutational burden as a predictive biomarker for immune checkpoint inhibitors and chemotherapy benefit in metastatic urothelial cancer 1.

This example shows a comparison of results related to Tumor Mutational Burden (TMB) for real world patients receiving immune checkpoint inhibitor (ICPI) compared to patients receiving chemotherapy using results such as PFS and OS.

Study design and patient selection. The cohort consisted of patients diagnosed with metastatic urothelial cancer (mUC) who were included in the de-identified clinical genomic database. All patients underwent genomic testing using genomic analysis (CGP) assays.

The de-identified clinical data was derived from approximately 280 U.S. cancer clinics (approximately 800 care sites). Retrospective longitudinal clinical data is derived from Electronic Health Records (EHR) that contain patient-level structured and unstructured data organized via a technical-assisted abstraction of clinical records and radiological/pathological reports, which are associated with genomic data derived from tests by de-identified deterministic matches (see Singal et al ,"Association of Patient Characteristics and Tumor Genomics with Clinical Outcomes Among Patients with Non-Small Cell Lung Cancer using a Clinicogenomic Database,"JAMA 2019;321(14):1391-9). clinical data including demographic data, clinical and laboratory characteristics, timing of treatment exposure, treatment progress and survival).

Patients were included in this study if they received a first-line single agent anti-PD 1 axis therapy (pembrolizumab, atuzumab, na Wu Shankang, dewaruzumab, or aviuzumab) or carboplatin-based chemotherapy regimen and had TMB assessed via tissue biopsy. Patients receiving both ICPI and chemotherapy in combination were not enrolled. To reduce the immortalization time in the analysis, patients for whom CGP reports were received after cessation of 1-line therapy were excluded.

Comprehensive genomic analysis. Next Generation Sequencing (NGS) assays based on hybrid capture were performed on patient tumor specimens in a laboratory approved by the Clinical Laboratory Improvement Amendment (CLIA) institute of pathology (CAP). All exons from a minimum of 324 cancer-related genes were interrogated and introns from a minimum of 28 genes were selected for rearrangement detection. Samples were assessed for changes as previously described (see Frampton et al ,"Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing,"Nat.Biotechnol.2013;31(11):1023-31) for genotyping Tumor Mutational Burden (TMB) was determined on up to 1.1Mb of sequenced DNA (see Chalmers et al ,"Analysis of 100,00human cancer genomes reveals the landscape of tumor mutational burden,"Genome Med.2017;9(1):34) for measurement, MSI was determined on 95 to 114 loci as previously described (see Trabucco et al ,"A Novel Next-Generation Sequencing Approach to Detecting Microsatellite Instability and Pan-Tumor Characterization of 1000Microsatellite Instability-High Cases in 67,000Patient Samples,"J.Mol.Diagn.2019;21(6):1053-66) for genotyping).

As a result. PFS is calculated from the beginning of 1 line treatment to the progression event (radiographic, clinical or pathological) or death. Patients with no observed record of progression events or deaths were right deleted on their last clinical visit date. TTNT is calculated from the date of treatment initiation until the next treatment line is initiated (for any reason) or die. Patients that have not reached the next treatment line or die are right deleted on the date of the last clinical visit or structuring activity. OS was calculated from the beginning of line 1 treatment to death due to any cause, and patients without record of death were right deleted on the date of the last clinical visit. Because the patient cannot enter the database before the CGP report is delivered, the OS risk interval is truncated to the date of the CGP report to further account for the immortalized time. Truncated independence and deletion were assessed with Kendall's tau for both ICPI group and chemotherapy group, respectively, and both in combination, with p <0.05 considered acceptable. Database death information is comprehensive information derived from 3 sources: documents within EHR, social security death index, and commercial death datasets mining data from announce somebody's death and funeral parlor with verification reported in comparison to national death index (see Zhang et al ,"Validation analysis of acomposite real-world mortality endpoint for patients with cancer in the United States,"Health Services Research).

And (5) carrying out statistical analysis. Differences in event occurrence time results were assessed using a log rank test and a Cox Proportional Hazards (PH) model. Chi-square test and Wilcoxon rank sum test were used to assess the difference between the categorical variable set and the continuous variable set, respectively. Multiple comparison adjustments are not performed; the p-values are reported to quantify the intensity of the correlation for the biomarker and each result, rather than for the null hypothesis significance test, and the widely adopted interpretation considers the consistency of a plurality of result measurements (PFS, TTNT, OS) that cooperate, none of which are independent.

The missing values are processed by simple interpolation based on the expected values determined using the random forest with R-packet "missForest". In subsequent analysis, the estimates are processed in the same way as the measured values.

Trend analysis utilized a perfect match technique (R package "MatchIt") resulting in no patient being excluded, but the chemotherapy treatment received weight. The upper weight limit is 10 equivalents to limit the impact of each observation. Among patients receiving chemotherapy, those with features most similar to the ICPI patient population are weighted higher, and those less similar to the ICPI patient are weighted lower. These weights are included in all Kaplan-Meier visualizations and Cox PH models, unless otherwise indicated. The characteristics of the adjustments included in the trend model: age, ECOG performance score, egffr, stage at diagnosis, and TMB. The equilibrium was assessed using a normalized mean difference (SMD) and was considered acceptable to within 10% (see Austin and Stuart,"Moving towards best practice when using inverse probability of treatment weighting(IPTW)using the propensity score to estimate causal treatment effects in observational studies,"Stat.Med.2015;34(28):3661-79) for genotype filling).

For 10 mutations/Mb (10 mutations per megabase) thresholds, trend weights were created for TMB.gtoreq.10 groups and TMB <10 groups, respectively, to obtain the best possible intra-group balance. Predictive Biomarker association (see Ballman, "biomaker: PREDICTIVE OR PROGNOSTIC? 33 (33): 3968-71) utilize a trend weighted multivariate Cox proportional hazards regression model containing the following variables: drug class (ICPI or taxane), TMB (high and low), interaction term between drug class and biomarker. The risk ratio for the subgroup analysis is generated from the Cox model layered by group (i.e., TMB high and low). The R version 3.6.3 software was used for all statistical analyses.

Results-characteristics of the analysis queue. After selection, the cohort consisted of 401 unique patients receiving treatment in a 1-line setting, with 245 patients receiving ICPI and 156 patients receiving carboplatin-based chemotherapy (see table 1 below). Evaluating the difference in patients receiving ICPI versus carboplatin-based chemotherapy, there was no strong imbalance between gender, TMB, gfr, practice settings, primary cancer anatomy, smoking status, race, or PD-L1 staining (however, only 30% of the cohorts had PD-L1 staining available). Patients receiving ICPI are older (median 73, iqrs 66 to 80 vs median 69, iqr 63 to 76, p < 0.001), less likely to be in stage IV at diagnosis (p < 0.001), with higher ECOG scores (p < 0.001). Subsequent treatment of patients receiving chemotherapy varied significantly (p < 0.001), including more frequent use of ICPI (41.7% versus 3.7%). 122 (30.4%) of the 401 patients had TMB.gtoreq.10, and this subgroup showed similar imbalance (see Table 2 below).

Trend weighting. After trend weighting in TMB <10 groups, no features have >10% SMD. After trend weighting in TMB+.gtoreq.10 groups, residual imbalance >10% SMD was present, making ICPI-receiving patients more likely to be in stages I-III at the time of initial diagnosis and more likely to have ECOG scores of 3 or higher than chemotherapy-receiving patients (FIGS. 1A-1B).

Patients with TMB of at least 10 have more favorable PFS, TTNT and OS when receiving 1-line single agent ICPI. PFS, TTNT, and OS on ICPI are stratified according to whether the patient has TMB <10 or TMB.gtoreq.10. Patients with TMB.gtoreq.10 have more favorable PFS (HR: 0.59, 95% CI:0.41 to 0.85, p=0.0048), TTNT (HR: 0.59, 95% CI:0.43 to 0.83, p=0.0020) and OS (HR: 0.47, 95% CI:0.32 to 0.68, p=0.0001) than patients with TMB <10 (FIGS. 2A to 2C).

Comparing the results of patients receiving 1-line ICPI with carboplatin-based chemotherapy, patients with tmb+.10 have more favorable estimates for PFS (HR: 0.51, 95% ci:0.32 to 0.82, p=0.0058), TTNT (HR: 0.56, 95% ci:0.35 to 0.91, p=0.0197) and OS (HR: 0.56, 95% ci:0.29 to 1.08, p=0.084) with trend weights for known imbalances in treatment assignment (fig. 1A to 1B), whereas patients with tmb+.10 have comparable or less favorable PFS (HR: 1.26, 95% ci:0.89 to 1.80, p=0.20), TTNT (HR: 0.89, 95% ci:0.68 to 1.18, p=0.42) and OS (HR: 1.11;95% ci:0.79 to 1.084) (fig. 3F to 3). ICPI, which was not adjusted for treatment assignment imbalance, showed similar associations as a whole with chemotherapy assessment (fig. 4A-4F).

In addition, results from a subset of patients identified by TMB or PD-L1 were also compared. PD-L1 staining was only available for 35.7% of the queues. Although the confidence interval for PD-L1 group is unexpectedly wider than TMB group, the main effect estimate for PD-L1 CPS+.10 is weaker than TMB+.10 for PFS, TTNT and OS (FIGS. 5A-5C).

The analysis cohorts were compared to a randomized controlled trial population. Using ECOG scores as a surrogate for patient weakness, we compared patient characteristics for 1 line of patients in the analysis cohort with those of 1 line of patients in the randomized control trial (fig. 6A). DANUBE, IMvigor130 and KEYNOTE-361 studies reported that 53.2%, 52.2% and 44.8% of patients had ECOG scores of 0, respectively, while 0.3% in the real world analysis cohort had ECOG scores of 0. DANUBE, IMvigor130 and KEYNOTE-361 studies reported 0%, 10.8% and 6.9% of patients had ECOG scores of 2, respectively, while 42.3% in the real world analysis cohort had ECOG scores of 2. None of the line III trials included patients with ECOG scores of 3 or higher, while 19.2% of the real world analysis cohorts had ECOG scores of 3 or higher.

A summary of the real world and test results of ICPI and carboplatin-based chemotherapy in TMB was next evaluated. There was consistent enrichment for ICPI and the benefits of carboplatin-based chemotherapy in the tmb+.10 subgroup across both Randomized Control Trial (RCT) and real world analysis (fig. 6B-6C).

Conclusion (d). TMB high cut-off values (such as 10 mutations/Mb) have clinical efficacy in a 1-line setting to identify patients with mUC as likely to have improved results compared to chemotherapy (such as non-cisplatin chemotherapy) when receiving single agent ICPI.

Example 2: real world verification of tumor mutational burden as a predictive biomarker for immune checkpoint inhibitors and chemotherapy effectiveness in metastatic gastric adenocarcinoma in different patients and clinical practice.

This example shows a real world comparison of results of patients receiving immune checkpoint inhibitors (ICPI) stratified by biomarkers, including Tumor Mutation Burden (TMB) score, with chemotherapy.

Real world analytic designs. To assess the efficacy of biomarkers and the effectiveness of drugs using the observed data, two complementation techniques were used: trend analysis and crossover analysis, whose interpretation depends on consistency of observations across different cohorts and assessment methods, is similar to real world analysis in previous metastatic prostate cancer (see, e.g., graf et al ,"Predictive Genomic Biomarkers of Hormonal Therapy Versus Chemotherapy Benefit in Metastatic Castration-resistant Prostate Cancer,"European Urology,2021). first assessing ICPI versus chemotherapy effectiveness between patients stratified by TMB in a 2-wire setting, then assessing whether patients with TMB+.10 mutations/Mb have enhanced relative effectiveness of 2-wire ICPI when used after 1-wire chemotherapy in the same patient (flow chart is provided in FIG. 7.) finally, assessing the results of patients receiving 1-wire ICPI compared to patients receiving 1-wire chemotherapy (FIG. 7).

Patient selection. The study included patients diagnosed with gastric adenocarcinoma. All patients underwent genomic testing using a comprehensive genomic analysis (CGP) assay. The de-identified clinical data was derived from approximately 280 U.S. cancer clinics (approximately 800 care sites). Retrospective longitudinal clinical data is derived from Electronic Health Records (EHR) that contain patient-level structured and unstructured data organized via a technical-assisted abstraction of clinical records and radiological/pathological reports, which are associated with genomic data by de-identified deterministic matches (Singal et al ,"Association of Patient Characteristics and Tmor Genomics With Clinical Outcomes Among Patients With Non-Small Cell Lung Cancer Using a Clinicogenomic Database,"JAMA 321:1391-1399,2019). clinical data include demographic data, clinical and laboratory characteristics, timing and lifetime of treatment exposures.

Patient records were included in this study if patients received one-line or two-line single agent anti-PD 1 axis therapy or standard chemotherapy (platinum regimen for line 1, non-platinum regimen for line 2) and had TMB assessed via tissue specimens. Patients receiving both ICPI and chemotherapy in combination were not enrolled. Patients must be tested additionally negative for ERBB2 amplification and have not received anti-HER 2 agents. After the above exclusion, analysis was performed in 3 queues:

2L compare validity queue: patients receiving platinum chemotherapy in line 1, platinum chemotherapy to line 2, and single agent ICPI or non-platinum chemotherapy in line 2.

Sequential queues: patients receiving platinum chemotherapy in line 1, platinum chemotherapy to line 2, and single agent ICPI in line 2.

1L compare validity queue: patients receiving a single agent ICPI or platinum-containing chemotherapy regimen in line 1.

Comprehensive genomic analysis: next Generation Sequencing (NGS) assays based on hybrid capture were performed on patient tumor specimens in a laboratory approved by the Clinical Laboratory Improvement Amendment (CLIA) institute of pathology (CAP). All exons from a minimum of 324 cancer-related genes were interrogated and introns from a minimum of 28 genes were selected for rearrangement detection. Samples were assessed for changes as previously described (Frampton et al ,"Development and validation of aclinical cancer genomic profiling test based on massively parallel DNA sequencing,"Nat Biotechnol 31:1023-31,2013). Tumor Mutational Burden (TMB) was determined on up to 1.1Mb of sequenced DNA (see Chalmers et al ,"Analysis of 100,000human cancer genomes reveals the landscape of tumor mutational burden,"Genome Med 9:34,2017)., as previously described, MSI was determined at 95 to 114 loci (Trabucco et al) ,"A Novel Next-Generation Sequencing Approach to Detecting Microsatellite Instability and Pan-Tumor Characterization of 1000Microsatellite Instability-High Cases in 67,000Patient Samples,"J Mol Diagn 21:1053-1066,2019).

Results: the Time To Next Treatment (TTNT) is the same as PFS for event occurrence time replacement for drug clinical effectiveness (Khozin et al ,"Real-world progression,treatment,and survival outcomes during rapid adoption of immunotherapy for advanced non-small cell lung cancer,"Cancer 125:4019-4032,2019). calculate ttnt from treatment start date until next treatment line start (for any reason) or death patient not yet reaching next treatment line or death is right deleted on the date of last clinical visit or structuring activity, total life (OS) is calculated from treatment start until death due to any reason, and patient without death record is right deleted on the date of last clinical visit or structuring activity because patient cannot enter database before CGP report is delivered, OS risk interval is truncated to date of CGP report to consider immortality time (see McGough et al, "Penalized regression for left-truncated and right-censored survival data," Stat Med,2021; see also Brown et al ,"Implications of Selection Bias Due to Delayed Study Entry in Clinical Genomic Studies,"JAMA Oncology,2021).Flatiron Health database death information is comprehensive information derived from 3 sources: documents in EHR, social death index and commercial death data set from announce somebody's death and death support data are compared to the outside of the national funeral and mortem data, etc. the date is verified ,"Validation analysis of acomposite real-world mortality endpoint for patients with cancer in the United States,"Health Services Research).

Statistical analysis: differences in event occurrence time results were assessed using a log rank test and a Cox Proportional Hazards (PH) model. Chi-square test and Wilcoxon rank sum test were used to assess the difference between the categorical variable set and the continuous variable set, respectively. Multiple comparison adjustments are not performed; the p-values are reported to quantify the intensity of the correlation for the biomarker and each result, rather than for the null hypothesis significance test, and the widely adopted interpretation considers the consistency of multiple outcome measures (TTNT, OS) that cooperate across defined cohorts (inter-patient versus intra-patient), with none of the outcome measures or cohorts being independent. The default interpretation is that biomarkers within the queue that are related to OS instead of TTNT may be confounding artifacts, and biomarkers that are related to TTNT instead of OS may not be significant. Furthermore, while the effect size estimate may vary from queue to queue, the default assumption is that biomarker effects should not be specific to any of the queues being evaluated.

The missing values are processed by simple interpolation with the expected values determined using the random forest with R-packet "missForest". In subsequent analysis, the estimates are processed in the same way as the measured values.

Trend analysis utilized a perfect match technique (R package "MatchIt") resulting in no patient being excluded, but the chemotherapy treatment received weight. The upper weight limit is 10 equivalents to limit the impact of each observation. Among patients receiving chemotherapy, those with features most similar to the ICPI patient population are weighted higher, and those less similar to the ICPI patient are weighted lower. These weights are included in all Kaplan-Meier visualizations and Cox PH models, unless otherwise indicated. Available features related to treatment assignment for chemotherapy compared to ICPI are included to adjust in the trend model: ECOG (0 to 2 and 3+), laboratory abnormalities (bilirubin above ULN and/or albumin below ULN), PD-L1 (CPS 5 and none), stage at diagnosis (IV and none), surgery (yes or no), and TMB (continuous). Balance was assessed using normalized mean difference (SMD) and was considered acceptable to be within 10% (see Austin and Stuart,"Moving towards best practice when using inverse probability of treatment weighting(IPTW)using the propensity score to estimate causal treatment effects in observational studies,"Stat Med 34:3661-79,2015).

Since 10 mutations/Mb thresholds are of interest, trend weights are created for TMB+.10 and TMB <10 groups, respectively, to obtain the best possible intra-group balance. Predictive Biomarker association (see Ballman, "Biomarker: PREDICTIVE OR PROGNOSTIC," J Clin Oncol 33:3968-71,2015) utilizes a trend weighted multivariate Cox proportional risk regression model containing the following variables: drug class (ICPI or taxane), TMB (high and low), interaction term between drug class and biomarker. Models that evaluate intra-patient therapeutic interactions in sequential queues are additionally aggregated on individual patients using robust variances calculated by generalized estimation equations within the work-independence structure. The risk ratio (i.e., TMB high and low) is then generated from the hierarchically adjusted Cox model. The R version 3.6.3 software was used for all statistical analyses.

As a result. 2L compare validity queue: after selection 263 patients received 2-wire non-platinum chemotherapy following platinum chemotherapy in wire 1 and 99 patients received 2-wire ICPI following platinum chemotherapy in wire 1. No differences of p <0.05 for age, sex, stage at diagnosis, smoking status, previous surgery, ECOG, albumin or bilirubin were observed by the treatment group. However, patients receiving ICPI had higher TMB (p < 0.001), PD-L1 CPS scores (p < 0.001), and more frequent MSI-H (p < 0.001). See table 3 below.

Sequential queues: after selection, 65 patients received 1-line platinum chemotherapy followed by 2-line ICPI. Of these, 17 have TMB.gtoreq.10, and 48 have TMB <10. No differences of p <0.05 were observed for age, sex, stage at diagnosis, smoking status, previous surgery, ECOG, albumin, bilirubin or PD-L1 by TMB group. However, TMB and MSI are highly correlated (p < 0.001); in TMB. Gtoreq.10 group, 14 have MSI-H,2 have MSS, and 1 have unknown MSI status. Among TMB <10 groups, 0 is MSI-H,37 is MSS, and 11 is MSI unknown. See table 4 below.

1L compare validity queue: after selection, 659 patients received 1 line platinum chemotherapy and 33 patients received 1 line ICPI. Patients receiving ICPI are older (median 70 and 66, p=0.038), less likely to be in IC phase at diagnosis (27.3% and 66.5%, p < 0.001), more likely to have received previous surgery (69.7% and 20%, p < 0.001), and more likely to be available for PD-L1 testing (p < 0.001) than patients receiving chemotherapy. See table 5 below.

Adjustments were made for the known treatment assignment imbalance, with patients receiving 2-line ICPI having more favorable results compared to chemotherapy when TMB was ≡10 mutations/Mb instead of TMB <10 (fig. 8A-8D). In the TMB <10 subgroup, all features had SMB <10% after weighting. In TMB. Gtoreq.10 subgroups, there is a residual imbalance of SMD. Gtoreq.10% although the imbalance is greatly reduced, making patients receiving ICPI more likely to have undergone surgery, have PD-L1 CPS. Gtoreq.5, be older, have laboratory abnormalities, and be higher TMB. Among patients receiving treatment with single agent ICPI compared to non-platinum chemotherapy in line 2 (after platinum chemotherapy prior to line 1), those with TMB <10 had comparable TTNT (HR: 0.96, 95% ci:0.69 to 1.34, p=0.81) and OS (HR: 1.1, 95% ci:0.73 to 1.64, p=0.66). However, patients with TMB.gtoreq.10 have more favorable TTNT (HR: 0.16, 95% CI:0.07 to 0.35, p < 0.0001) and OS (HR: 0.21, 95% CI:0.09 to 0.49, p=0.0004). Sensitivity analysis without adjustment for imbalance showed similar results (fig. 9A-9D).

When TMB is ≡ 10 instead of TMB <10, patients receiving 2-line ICPI after 1-line chemotherapy have more favorable results when receiving 2-line ICPI than when receiving 1-line chemotherapy. TTNT for 1-line chemotherapy was visualized for those patients with TMB <10 (FIG. 10A) and those with TMB+.10 (FIG. 10B), with the bars colored in MSI status. In this queue, MSI status is highly correlated with the TMB threshold, where none of the patients with MSI-H have TMB <10, and 14 of 17 with TMB+.gtoreq.10 have MSI-H (2 MSS,1 MSI unknown). Two with MSS and TMB.gtoreq.10 have no record of the next treatment after ICPI began, 9.7 months and 16.0 months to date. The median value TTNT for 2-wire ICPI in TMB <10 groups was 3.3 months (95% ci:2.2 to 8.0). The point estimates and confidence intervals from the Cox model comparing TTNT in the patient are shown in fig. 10C. The total unadjusted survival from the onset of 1-wire chemotherapy by TMB is shown in fig. 10D.

TMB.gtoreq.10 and MSI-H are more predictive biomarkers for ICPI and chemotherapy benefits than PD-L1 CPS.gtoreq.5. MSI-H status is highly correlated with increasing TMB values (FIGS. 11A-11B), whereas PD-L1 CPS.gtoreq.5 is not particularly enriched in patients with high TMB (Table 6 below), indicating the degree of independence in these queues. The PD-L1 score was not available for 47% of the 2-line comparison availability queues and for 40% of the sequential queues. However, patients with PD-L1 CPS.gtoreq.5 have much higher prevalence than TMB.gtoreq.10 or MSI-H. In the 2L ICPI and chemotherapy cohort and sequential analysis, patients identified by TMB.gtoreq.10 and/or MSI-H had similar prevalence and enrichment for results favorable for ICPI and observed for chemotherapy (FIGS. 11A-11C). In patients identified by TTNT instead of PD-L1 CPS.gtoreq.5 in OS, there is a moderate enrichment for the results favorable to ICPI and observed for chemotherapy.

KeyNote-061 and real world queues have very different patient populations, similar drug class specific TMB associations. Using ECOG performance scores as a surrogate for total patient weakness across the cohort, a broad profile was shown from a phase III randomized control trial KeyNote-061 that compares pembrolizumab with paclitaxel as compared to ECOG scores in a 2-wire comparison efficacy cohort (see Shitara et al ,"Pembrolizumab versus paclitaxel for previously treated,advanced gastric or gastro-oesophageal junction cancer(KEYNOTE-061):a randomized,open-label,controlled,phase 3trial,"Lancet 392:123-133,2018)( fig. 12A). Total lifetime subgroup analysis for high TMB in KeyNote-061 was reported by the FDA as post hoc analysis (Marcus et al ,"FDA Approval Summary:Pembrolizumab for the Treatment of Tumor Mutational Burden-High Solid Tumors,"Clin Cancer Res,2021), and shown with the in-patient OS assessment on the 2-wire comparison effectiveness queue (FIG. 12B.) clinical trial assays for KeyNote-061 TMB assessment were whole exome sequencing assays, and "high" TMB was ⁶ determined by the tangent point most consistent with the FDA approved assay at TMB.gtoreq.10.

Adjustments were made for the known treatment assignment imbalance, with patients receiving 1-line ICPI having more favorable results compared to chemotherapy when TMB was ≡10 instead of TMB <10 (fig. 13A-13D). In the TMB <10 subgroup residual imbalance still exists, making it more likely that patients receiving ICPI have no PD-L1 score and have a lower likelihood of having a laboratory abnormality. Among the TMB.gtoreq.10 subgroup, patients receiving ICPI are more likely to be already in stage IV at the time of diagnosis. Among patients receiving treatment with single agent ICPI compared to non-platinum chemotherapy in line 1, those with TMB <10 had worse TTNT (HR: 2.42, 95% ci:1.29 to 4.57, p=0.0062) and were comparable to worse OS (HR: 1.71, 95% ci:0.82 to 3.57, p=0.16). However, patients with TMB.gtoreq.10 have a more favourable TTNT (HR: 0.14, 95% CI:0.04 to 0.52, p=0.0034) and are comparable to favourable OS (HR: 0.45, 95% CI:0.11 to 1.82, p=0.26). Sensitivity analysis without adjustment for imbalance showed similar results (fig. 14A-14D).

Taken together, the results show that the clinical efficacy of TMB.gtoreq.10 in a wide variety of real world patient populations is less consistent with clinical trials. Using two complementary approaches to comparative effectiveness that partially overcome their respective limitations, strong enrichment was observed for ICPI consistent with chemotherapy benefits in both inter-patient and intra-patient assessments of TMB.gtoreq.10 and NGS-assessed MSI. Consistent results of the same magnitude are not observed in the case of PD-L1 CPS.gtoreq.5. TMB.gtoreq.10 strongly identifies metastatic gastric patients with favorable outcome compared to chemotherapy when receiving 2-line single agent ICPI in a more diverse patient population and treatment settings than registered clinical trials. The effect in the 1-line data is consistent with the 2-line observations. The results indicate that if selected by TMB.gtoreq.10, the 1-line test of ICPI without chemotherapy may be successful compared to chemotherapy. Example 3: tumor mutational burden as a predictive biomarker for immune checkpoint inhibitors in metastatic castration-resistant prostate cancer with taxane chemotherapy benefit: real world biomarker analysis.

This example shows a comparison of treatment class-specific results stratified by TMB score for patients with metastatic castration-resistant prostate cancer (mCRPC) when receiving ICPI and taxane chemotherapy.

Genomic data is associated with clinical variables and outcomes in the cohort of patients with mCRPC. Longitudinal unidentified clinical data from about 280 american academic or community-based cancer clinics is derived from electronic health records, organized via technology-assisted abstraction, and associated with genomic testing by comprehensive genomic assays. 45 patients (14 with TMBs of at least 10 and 31 with TMBs less than 10) received single agent anti-PD-1 axis ICPI. 696 (30 with a TMB of at least 10 and 666 with a TMB of less than 10) received a single agent taxane as determined by the physician without randomization. For Time To Next Therapy (TTNT) and total survival (OS) assessment, imbalance between treatment groups was adjusted with trend weighting.

741 Patients were identified and included in the analysis. Patients receiving ICPI had higher TMB (median 3.5 and 2.5, p < 0.001), higher ECOG score (p=0.057) and more previous taxane usage (73.3% and 53.7%, p=0.01) than taxane. Comparison of baseline patient characteristics within the overall and ICPI and taxane subgroups, and characteristics between subgroups, is provided below

In table 7.

Figure 15 shows PSA responses for patients that can be assessed for PSA responses to single agent taxane therapies and stratified by TMB of less than 10 and TMB of at least 10. Figure 16 shows PSA responses for patients that can be assessed for PSA responses to receiving single agent anti-PD 1 axis therapies. Most of the patients with TMB of at least 10 responded to single agent anti-PD 1 axis therapy, while most of the patients with TMB of less than 10 did not. Among patients with an evaluable PSA response, no difference in TMB levels was observed upon receiving the taxane. If TMB is less than 10, no patient has a 50% or more PSA decline when receiving ICPI. 4 of 9 patients with TMB of at least 10 had PSA decline of 50% or more.

Fig. 17A to 17D show TTNT and the OS layered by TMB of less than 10 or at least 10. Patients with TMB less than 10 receiving ICPI had worse TTNT (median 2.4 months versus 4.1 months; HR:2.7, 95% ci:1.7 to 4.0, p < 0.001) and worse OS (median 4.2 months versus 6.0 months, HR:1.08;95% ci:0.68 to 1.7, p=0.73) than taxane. In contrast, ICPI and taxane usage are associated with more favorable TTNT (median 8.0 months and 2.4 months; HR:0.37, 95% CI:0.15 to 0.87, p=0.022) and OS (median 19.9 months and 4.2 months; HR:0.23, 95% CI:0.10 to 0.57, p=0.0014) for TMB of at least 10. Of all 741 patients, 44 had TMBs of at least 10, 22 had high microsatellite instability (MSI-H), and 20 had both. Therapeutic interactions with TMBs of at least 10 (TTNT: p <0.001, os: p=0.021) are stronger than MSI-H (TTNT: p=0.0038, os: p=0.080).

Taken together, these data indicate that ICPI is a viable alternative to taxane chemotherapy for patients with mCRPC having a TMB of at least 10.

Example 4A: clinical and genomic profile of patients with persistent benefit from immune checkpoint inhibitor (ICPI) in advanced non-small cell lung cancer (aNSCLC)

Materials and methods

Patient selection

Patients who were confirmed to be advanced NSCLC, included in the de-identified clinical genomic database, were selected for evaluation.

All patients underwent genomic testing using genomic analysis (CGP) assays. In addition, some patients underwent PD-L1 DAKO 22C3 or VENTANA SP142 IHC assays. The de-identified clinical data was derived from approximately 280 U.S. cancer clinics (approximately 800 care sites). Retrospective longitudinal clinical data is derived from Electronic Health Records (EHR) that contain patient-level structured and unstructured data organized via a technical-assisted abstraction of clinical records and radiological/pathological reports, which are associated with genomic data derived from tests by de-identified deterministic matches (Singal G, miller PG, agarwala V et al Association of Patient Characteristics and Tumor Genomics With Clinical Outcomes Among Patients With Non-Small Cell Lung Cancer Using a Clinicogenomic Database.Jama2019;321:1391-1399). clinical data include demographic data, clinical and laboratory characteristics, timing and lifetime of treatment exposure.

Patients were included in this study if they received a first-line single agent anti-PD 1 agent (pembrolizumab) or anti-PD 1 (pembrolizumab) + chemotherapy and had a Tumor Mutational Burden (TMB) assessed via tissue specimens collected prior to the initiation of first-line (1L) therapy. Patients must be additionally tested negative for EGFR mutations and ALK/ROS1/RET rearrangements via comprehensive genomic analysis (CGP). Patients diagnosed with advanced NSCLC more than 90 days prior to their first structuring activity or receiving their CGP reports more than 60 days after the date of the last structuring activity are excluded to (a) ensure that all therapies received prior to CGP are captured, and (b) exclude patients who left the network prior to CGP. Prior to the start of the study described in this example, the study protocol was approved by the institutional review board.

Comprehensive genomic analysis

Comprehensive genomic analysis (CGP) was performed on adaptor-based ligation libraries captured by hybridization using DNA and/or RNA extracted from FFPE tumors in a laboratory approved by the Clinical Laboratory Improvement Amendment (CLIA) and the american pathologist's institute (CAP). Up to 406 cancer-related genes of the sample were sequenced and gene rearrangements were selected (Frampton GM, fichtenholtz A, otto GA et al Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing.Nat Biotechnol 2013;31:1023-1031). Tumor Mutation Burden (TMB) were determined on up to 1.24Mb of sequenced DNA (chapmers ZR, connelly CF, fabrizio D et al Analysis of 100,000human cancer genomes reveals the landscape of tumor mutational burden.Genome Med 2017;9:34).

DAKO PD-L1 IHC 22C3 assay

DNA and/or RNA samples extracted from FFPE tumors of certain patients were also evaluated via the PD-L1 DAKO 22C3 IHC assay or VENTANA SP a 142 assay (i.e., in parallel with CGP). The results of the DAKO 22C3 PD-L1IHC and VENTANA SP142 assays were interpreted according to manufacturer's instructions for TPS and TC, respectively. The results from the DAKO 22C3 PD-L1IHC assay were interpreted using the DAKO tumor ratio scoring (TPS) method, in which tumor cell expression of PD-L1 was quantified. DAKO TPS scoring method is defined as tps=pd-L1 positive tumor cell number/(total number of PD-L1 positive tumor cells+pd-L1 negative tumor cells) (dako.pd-L1 IHC 22C3 pharmDx Interpretation Manual-NSCLC). The VENTANA SP142 assay also assessed a tumor cell score (TC), where the percentage of PD-L1 positive tumor cells/(total number of PD-L1 positive tumor cells + PD-L1 negative tumor cells) was similar to the DAKO assay.

Results

Total survival (OS) was calculated from the beginning of treatment to death due to any cause, and patients with no record of death were right-deleted on the date of the last clinical visit or structuring activity. Because patients cannot enter the database before the CGP report is delivered, the OS risk interval is truncated to the date of the CGP report to account for immortalized time (McGough SF, incerti D, lyalina S, Penalized regression for left-truncated and right-censored survival data.Stat Med2021;Brown S,Lavery JA,Shen R, etc. Implications of Selection Bias Due to Delayed Study Entry in Clinical Genomic Studies.JAMA Oncology 2021). database death information is a comprehensive information derived from 3 sources, documents within Electronic Health Records (EHRs), social security death index, and commercial death data sets from announce somebody's death and funeral parlor mining data. This death information is externally compared to the national death index, verified with an accuracy >90% (Zhang Q, gossai A, monroe S, et al Validation analysis of a composite real-world mortality endpoint for patients with cancer in the United States.Health Services Research.2021 months; 56 (6): 1281-1287). First progress date or death >14 days after treatment initiation to calculate Progression Free (PFS). If no progress or death is observed, patients are deleted on their last clinical record date. Intermediate PFS and OS values are estimated monthly with 95% confidence intervals.

Statistical analysis and interpretation

Differences in event occurrence time results were assessed using a log rank test and a Cox Proportional Hazards (PH) model. Chi-square test and Wilcoxon rank sum test were used to assess the difference between the categorical variable set and the continuous variable set, respectively. The P values were corrected for multiple tests. A multivariate Cox proportional hazards model was fitted over PFS and OS to estimate the adjusted risk ratio and its significance. The Cox model is characterized by TMB status, PDL1 status, age at the beginning of treatment, eastern tumor co-operating group (ECOG) performance status scores (0 to 1, 2+ and unknown), metastatic status, smoking history, disease histology, stage at initial diagnosis, and STK11 mutation status. For interaction analysis, the same multivariate Cox model was fitted with the interaction term between the therapy class and the biomarker.

When comparing the results achieved with R-package "MatchIt" between biomarker positive and negative cohorts, trend analysis exploits the inverse probability of treatment weights for average treatment effects. The features used in the trend model are: ECOG (0 to 1, 2+ and unknown), age at the beginning of therapy, PD-L1 (TPS > 1 nand), stage at diagnosis (stage IV nand), metastatic status and smoking history. Using normalized mean differences (SMD) to assess balance, and within 10% is considered acceptable (Austin PC,Stuart EA.Moving towards best practice when using inverse probability of treatment weighting(IPTW)using the propensity score to estimate causal treatment effects in observational studies.Stat Med 2015;34:3661-3679).

Predictive biomarker correlation (see Ballman KV. Biomaker: PREDICTIVE OR PROGNOSTICJ CLIN ONCOL 2015;33: 3968-3971) utilized an inverse trend weighted multivariate Cox proportional risk regression model that contained at least the following variables: drug class (ICPI or ICPI + chemotherapy), TMB (high and low), interaction term between drug class and biomarker. Models that evaluate intra-patient therapeutic interactions in sequential queues are additionally aggregated on individual patients using robust variances calculated by generalized estimation equations within the work-independence structure. The risk ratio (i.e., TMB high and low) is then generated from the hierarchically adjusted Cox model. The R version 3.6.3 software was used for all statistical analyses.

Disproportionate risk over time between treatment groups may limit the interpretability of the risk ratio as an effect measure. For this purpose, pre-specified risk ratio estimation method (Liang F,Zhang S,Wang Q,Li W.Treatment effects measured by restricted mean survival time in trials of immune checkpoint inhibitors for cancer.Ann Oncol 2018;29:1320-1324;Pak K,Uno H,Kim DH et al is enhanced with analysis of the average lifetime time of the three year limit Interpretability of Cancer Clinical Trial Results Using Restricted Mean Survival Time as an Alternative to the Hazard Ratio.JAMA Oncol 2017;3:1692-1696).

Results

Patient queue

There were a total of 15149 unique NSCLC patients in the clinical genomic database cohort, with 10139 patients having information about the previous normals to therapy. See fig. 18. Of 10139 patients, 2344 received immune checkpoint inhibitor (ICPI) monotherapy or immune checkpoint inhibitor therapy in combination with chemotherapy in a line. Patients with no PD-L1 immunohistochemical results, with specimens collected after initiation of immune checkpoint inhibitor therapy, and with EGFR mutations or ALK/ROS1/RET rearrangements were excluded. A total of 1722 patients remain under analysis. Of these 1722 patients, 630 received ICPI monotherapy and 1092 received ICPI therapy+chemotherapy. When comparing patient characteristics between ICPI monotherapy and ICPI therapy+chemotherapy groups, it was observed that patients in ICPI monotherapy groups were mainly elderly, smokers, women, had a higher ECOG score, were diagnosed at earlier stages, had a higher TMB score, and had a PD-L1 Tumor Proportion Score (TPS)/PD-L1 stained Tumor Cells (TC) >50% compared to patients in ICPI therapy+chemotherapy groups, see tables 8A and 8B.

TABLE 8A patient characteristics of the Main cohort—subgroup for TMB

TABLE 8B patient characterization of the Main cohort

Fig. 19A and 19B provide an adjusted Kaplan-Meier plot of real world progression free survival (rwPFS), and fig. 19C and 19D provide a real world total survival (rwOS) for patients treated with ICPI monotherapy (fig. 19A and 19C) or ICPI therapy+chemotherapy (fig. 19B and 19D). Results were stratified by TMB <10 and TMB > =10, where TMB of 10 is a cutoff value for high TMB. To adjust for imbalance, a perfect match is performed between TMB <10 and TMB > =10 queues. Variables used for matching include: age at the beginning of therapy, ECOGPS (0 to 1, 2+ and unknown), metastasis, smoking history, stage at diagnosis. The results shown in fig. 19A-D demonstrate that tumor mutational burden is prognostic for ICPI-containing protocols. Fig. 20A and 20B provide Kaplan-Meier plots of rwPFS, and fig. 20C and 20D provide rwOS for patients receiving treatment with ICPI monotherapy (fig. 20A and 20C) or ICPI therapy + chemotherapy (fig. 20B and 20D). Results were stratified by TMB <10, TMBs 10 to 19, and TMB > =20. The results shown in figures 20A-D demonstrate that tumor mutational burden is prognostic for ICPI-containing regimens in the first line.

FIG. 21A provides a Kaplan-Meier plot for rwPFS of patients treated with ICPI-containing regimens. Results were stratified by TMB and PDL1 levels: PDL1<1% and TMB <10 (i.e., PDL 1-/TMB-), PDL1>1% and TMB <10 (i.e., pdl1+/TMB-), PDL1<1% and TMB > =10 (i.e., PDL 1-/tbm+), and PDL1>1% and TMB > =10 (i.e., pdl1+/tmb+). Fig. 21B provides results from a multivariate CoxPh model that detects associations between clinical or genomic features and rwPFS. FIG. 21C provides a Kaplan-Meier plot for rwOS of patients treated with ICPI-containing regimens. Results were stratified by TMB and PDL1 levels: PDL1<1% and TMB <10 (i.e., PDL 1-/TMB-), PDL1>1% and TMB <10 (i.e., pdl1+/TMB-), PDL1<1% and TMB > =10 (i.e., PDL 1-/tbm+), and PDL1>1% and TMB > =10 (i.e., pdl1+/tmb+). Fig. 21D provides results from a multivariate CoxPh model that detects associations between clinical or genomic features and rwOS. FIG. 22A provides a Kaplan-Meier plot for rwPFS of patients treated with ICPI-containing regimens. Results were stratified by TMB and PDL1 levels: PDL1<1% and TMB <20 (i.e., PDL 1-/TMB-), PDL1>1% and TMB <20 (i.e., pdl1+/TMB-), PDL1<1% and TMB > =20 (i.e., PDL 1-/tbm+), and PDL1>1% and TMB > =20 (i.e., pdl1+/tmb+). Fig. 22B provides results from a multivariate CoxPh model that detects associations between clinical or genomic features and rwPFS. FIG. 22C provides a Kaplan-Meier plot for rwOS of patients treated with ICPI-containing regimens. Results were stratified by TMB and PDL1 levels: PDL1<1% and TMB <20 (i.e., PDL 1-/TMB-), PDL1>1% and TMB <20 (i.e., pdl1+/TMB-), PDL1<1% and TMB > =20 (i.e., PDL 1-/tbm+), and PDL1>1% and TMB > =20 (i.e., pdl1+/tmb+). Fig. 22D provides results from a multivariate CoxPh model that detects associations between clinical or genomic features and rwOS. The results of fig. 21A-D and fig. 22A-D indicate that TMB and PD-L1 expression are independent markers for ICPI results.

Fig. 23A shows the point estimates and 95% confidence intervals for HR (risk ratio) for biomarkers, and shows the therapeutic interactions for different TMB or PDL1 cut-off values for rwPFS. Fig. 23B shows the point estimates and 95% confidence intervals for HR (risk ratio) for biomarkers, and shows the therapeutic interactions for different TMB or PDL1 cut-off values for rwOS. Figure 23C provides Kaplan-Meier plots for rwPFS patients with PD-L1 scores between 1% and 49% treated with ICPI monotherapy or ICPI therapy + chemotherapy. Fig. 23D provides Kaplan-Meier plots for rwPFS of patients treated with ICPI monotherapy or ICPI therapy + chemotherapy with a > = 50% PD-L1 score. The results shown in fig. 23A-23D demonstrate that PD-L1 is a predictive biomarker for ICPI monotherapy and ICPI therapy + chemotherapy benefit.

Fig. 24 shows the first 30 altered genes in ICPI monotherapy cohorts (-) and ICPI therapy + chemotherapy cohorts (+). A plurality of: a plurality of changes in the indicated genes; RE: rearranging; CN: copy number variation; SV: short variant mutations (base substitutions or insertions/deletions).

Fig. 25A shows an adjusted Kaplan-Meier plot for rwPFS of patients treated with ICPI monotherapy. Fig. 25B shows an adjusted Kaplan-Meier plot for rwPFS of patients treated with ICPI therapy + chemotherapy. Fig. 25C shows an adjusted Kaplan-Meier plot for rwOS of patients treated with ICPI monotherapy. Fig. 25D shows an adjusted Kaplan-Meier plot for rwOS of patients treated with ICPI therapy + chemotherapy. In fig. 25A to 25D, the results were stratified by PDL1 TPS <1% and PDL1 TPS > =1%. To adjust for imbalance, a perfect match is performed between PDL1<1% and PDL1> =1% queues. Variables used for matching include: age at the beginning of therapy, ECOGPS (0 to 1, 2+ and unknown), metastasis, smoking history, stage at diagnosis. Fig. 26A shows an adjusted Kaplan-Meier plot for rwPFS of patients treated with ICPI monotherapy. Fig. 26B shows an adjusted Kaplan-Meier plot for rwPFS of patients treated with ICPI therapy + chemotherapy. Fig. 26C shows an adjusted Kaplan-Meier plot for rwOS of patients treated with ICPI monotherapy. Fig. 26D shows an adjusted Kaplan-Meier plot for rwOS of patients treated with ICPI therapy + chemotherapy. In fig. 26A to 26D, the results were layered by PDL1 TC <50% and PDL1 TC > =50%. To adjust for imbalance, a perfect match is performed between PDL1 TC <50% and PDL1 TC > =50% queues. Variables used for matching include: age at the beginning of therapy, ECOGPS (0 to 1, 2+ and unknown), metastasis, smoking history, stage at diagnosis. The results shown in fig. 25A to D and fig. 26A to D indicate that PDL1 is prognostic for ICPI-containing treatment regimens.

Fig. 27 provides box plots of TMB levels in different PDL1 subgroups to show the association between PDL1 expression and TMB. Kruskal-Wallis test p=0.007, effect size: 0.0046. tables 9A and 9B show likelihood ratio tests and significance to compare nested models.

Table 9A.

Table 9B.

Fig. 28A shows a Kaplan-Meier plot for rwPFS of patients treated with ICPI monotherapy. Fig. 28B shows a Kaplan-Meier plot for rwPFS of patients treated with ICPI therapy + chemotherapy. Fig. 28C shows a Kaplan-Meier plot for rwOS of patients treated with ICPI monotherapy. Fig. 28D shows a Kaplan-Meier plot for rwOS of patients treated with ICPI therapy + chemotherapy. Results were stratified by TMB and PDL1 levels: PDL1<1% and TMB <10 (i.e., PDL 1-/TMB-), PDL1>1% and TMB <10 (i.e., pdl1+/TMB-), PDL1<1% and TMB > =10 (i.e., PDL 1-/tbm+), and PDL1>1% and TMB > =10 (i.e., pdl1+/tmb+).

The results shown in fig. 27 and 28A-28D and in tables 9A and 9B indicate that TMB and PD-L1 expression are independent markers for ICPI results.

Discussion of the invention

In this study, TMB and PD-L1 Immunohistochemistry (IHC) were shown to be independent biomarkers for first-line NSCLC patients receiving treatment with ICPI-containing regimens (e.g., ICPI monotherapy or ICPI therapy + chemotherapy). In particular, the single biomarker positive (TMB-high/PD-L1 ^{Negative of} and TMB-low/PD-L1 ^{Positive and negative} ) groups have a higher rwPFS than the dual biomarker negative group (TMB-low/PD-L1 ^{Negative of} ). A significantly higher median rwOS (20.1 months) was observed among TMB-high/PD-L1 ^{Positive and negative} when compared to the 10.5 month to 12 month lifetime in the other three groups (i.e., TMB-low/PD-L1 ^{Positive and negative} , TMB-low/PD-L1 ^{Negative of} , and TMB-high/PD-L1 ^{Negative of} ). In summary, in addition to TMB and PD-L1 IHC being independent biomarkers that predict the outcome of an ICPI-containing regimen, the combination of the two biomarkers positively predicts the strongest response to the ICPI-containing regimen. The data herein indicate that in addition to PD-L1 IHC, TMB testing should be performed on 1L NSCLC patients.

TMB-high is highly prognostic for 1L NSCLC in both ICPI monotherapy and ICPI therapy+chemotherapy groups as an independent biomarker. This is exemplified by nearly doubling both rwPFS and rwOS in the TMB-high group when compared to the TMB-low group in the ICPI monotherapy cohort. The same trend was also seen in the ICPI + chemotherapy group, where an intermediate rwPFS of 10 months was observed in the TMB-high group, in contrast to 6.8 months in the TMB-low group; and the differences in rwOS are less pronounced but significant. While TMB is approved as an accompanying diagnosis in patients who have progressed after previous treatments, new emerging real world evidence has been demonstrated in urothelial cancer, with TMB having predictive value in first line settings. Taken together, these real world data indicate that TMB is a highly prognostic biomarker for ICPI-containing regimens in a variety of tumor types. PD-L1 is also an independent prognostic biomarker for first-line NSCLC at both TPS.gtoreq.1 and TPS.gtoreq.50 cut-off (Pak K, uno H, kim DH et al Interpretability of Cancer Clinical Trial Results Using Restricted Mean Survival Time as an Alternative to the Hazard Ratio.JAMA Oncol 2017;3:1692-1696).

While the most widely used TMB cut-off is currently 10 mutations/Mb, a higher cut-off at TMB.gtoreq.20 mutations/Mb may help select patients with a particular response to ICPI. In this example, it was seen that patients with TMB.gtoreq.20 responded very well to therapy in both ICPI monotherapy and ICPI therapy+chemotherapy groups. In particular, in rwOS of the ICPI monotherapy group, the TMB.gtoreq.20 cohort (median 33.7 months) had a lifetime of greater than 3-fold when compared to the <10 mutations/Mb group (median 9.4 months). The same trend was observed when examining the groups defined by TMB and PD-L1. rwOS in the double positive (PD-L1 ^{Positive and negative} /TMB ^{Negative of} ) group had an intermediate value rwOS of 33.7 months when compared to the double negative (PD-L1 ^{Negative of} /TMB ^{Negative of} ) group having rwOS of 11.2 months. Finally, patients with a permanent benefit >2 years after initiation of ICPI therapy in NSCLC represent a unique immune survivor population, with an intermediate value OS of approximately 5 years; 41% of patients stopped ICPI before the 2 year mark. Based on these data, it is necessary to further study TMB with higher cut-off values (such as 20 mutations/Mb) as biomarkers for the benefit of extension of ICPI in NSCLC.

The predictive value of TMB and PD-L1 for ICPI monotherapy and ICPI therapy+chemotherapy was assessed. In this cohort, no TMB (at cut-off values of 10 and 20 mutations/MB) was observed to be able to predict the more favorable rwPFS or rwOS of ICPI monotherapy versus ICPI therapy+chemotherapy. However, patients with PD-L1 IHC at TPS of 1 to 49 had significantly higher rwPFS in ICPI therapy+chemotherapy (intermediate rwPFS:7.3 months and 2.9 months) when compared to ICPI monotherapy groups, suggesting that PD-L1 IHC may be a biomarker that helps guide decisions for ICPI monotherapy and ICPI therapy+chemotherapy. This same trend was seen in rwOS and was consistent with previous FDA summary analyses (Akinboro O, vallejo JJ, mishara-KALYANI PS et al Outcomes of anti-PD-(L1)therapy in combination with chemotherapy versus immunotherapy(IO)alone for first-line(1L)treatment of advanced non-small cell lung cancer(NSCLC)with PD-L1 score 1-49％:FDA pooled analysis.Journal of Clinical Oncology 2021;39:9001-9001). in general), which data indicate that future clinical trials should be performed to better assess the predictive power of PD-L1 in this case.

Conclusion: in this example, a large real world patient cohort was used to demonstrate that TMB adds additional prognostic value to 1L NSCLC patients in addition to PD-L1 IHC. Such results indicate that these patients should receive tests for both TMB and PD-L1 IHC. Furthermore, such real world evidence is presented: PD-L1 can help predict whether to treat a 1L NSCLC patient with ICPI monotherapy and ICPI therapy + chemotherapy.

Example 4B: clinical and genomic profile of patients with persistent benefit from immune checkpoint inhibitor (ICPI) in advanced non-small cell lung cancer (aNSCLC)

Background: the 2-year mark has become a new milestone in patients with aNSCLC who received immunotherapy. In patients who do not progress at this time, a portion of the patients experience ongoing disease control even after cessation of active treatment. Some patients experience such impressive persistence for more than 2 years, which has raised a challenge for potential cure methods. Real world ("rw") Clinical Genome Databases (CGDB) were queried to better understand these patients with persistent benefits and their clinical and genomic features.

The method comprises the following steps: using a nationwide (about 280 american cancer clinics) de-identified Electronic Health Record (EHR) -derived Clinical Genome Database (CGDB) related to genomic data, patients receiving treatment with immune checkpoint inhibitor therapy (ICPI), either as monotherapy or in combination with chemotherapy, were selected. RW progress (rwP) is obtained via a technology-assisted abstraction of EHR data. The persistent benefit is classified as no rwP, death, or treatment failure (indicated by the change to neotherapy normals) within 24 months of initiation of ICPI therapy.

Results: of the 4,030 evaluable aNSCLC patients, 184 (4.6%) failed no rwP or treatment at 24 months. Of these 184 patients with permanent benefit, 84% received ICPI monotherapy and 16% received ICPI and chemotherapy; ICPI treatment is more often first line (1L, 43%) or 2L (38%). 59% of the durable benefit was still receiving ICPI at the 2 year mark, while 41% had stopped at an intermediate value of 11.4 months after the start of therapy. Of 109 patients still receiving ICPI for 2 years, the median time to ICPI was 36.3 months from the start of therapy. Overall, patients with persistent benefit have an intermediate-value real-world progression-free survival of 37.1 months (rwPFS) and an intermediate-value real-world total survival of 58.8 months (rwOS) from the start of ICPI therapy. Those patients with permanent benefit were more likely to have a history of smoking (94% and 86%) and no liver, brain or bone metastases (all p < 0.001) than patients with rwP who received ICPI therapy 24 months ago. In patients with persistent benefit, high tumor mutational burden (TMB. Gtoreq.10) was more common (62% versus 35%, p < 0.001) and STK11, CDKN2B, PIK3CA and EGFR changes were less seen than those with rwP received ICPI therapy 24 months ago. TMB.gtoreq.20 is significantly associated with longer rwPFS (HR 0.45% CI 0.24 to 0.83, p=0.01) while TMB.gtoreq.10 is slightly more significant (HR 0.65% CI 0.40 to 1.03, p=0.07) in a multivariate cox model of rwPFS over 24 months in patients with permanent benefit; treatment with ICPI and chemotherapy was significantly associated with poor rwPFS (HR 1.84 95%1.093.12,p =0.02). Although many patients in the dataset had unknown PD-L1 status, high PD-L1>50% was noted in 728 (19%) patients with no permanent benefit and 38 (21%) patients with permanent benefit.

Conclusion: patients with a long lasting benefit >2 years after initiation of ICPI therapy for aNSCLC represented a unique population of immune survivors, with an intermediate value OS of approximately 5 years; 41% of patients stopped ICPI before the 2 year mark. Elevated TMB was associated with prolonged rwPFS following receipt of ICPI and 2 year mark, and was worth further study as a biomarker for prolonged benefit of ICPI in aNSCLC.

Example 5: tumor Mutation Burden (TMB) measurements from CGP assays and real world total survival with single agent immune checkpoint inhibitor (ICPI).

Background: suitability and reliability of TMB across cancer types and assays from different manufacturers. This example investigated the diagnosis of pan-solid tumor concomitant with TMB 10 mutations/Mb or higher as single agent pembrolizumab in the 2-wire or additional normal therapy. Using a large real world dataset with well-validated outcome measures, clinical efficacy of TMB measures by CGP in more than 8,000 patients across 24 cancer types receiving a single agent ICPI.

The method comprises the following steps: using a nationwide (about 280 american cancer clinics) de-identified Electronic Health Record (EHR) -derived Clinical Genome Database (CGDB) related to genomic data, patients receiving treatment with immune checkpoint inhibitor therapy (ICPI), either as monotherapy (table 10) or in combination with chemotherapy, were selected. For patients with advanced or metastatic cancer, the therapy line is eligible if they receive ICPI, have an assessed tissue-assessed TMB, meet the 90-day gap rule, and the therapy normal is not entirely immortal time. The tumor-pan cohort included patients with advanced/metastatic disease from 24 cancer types of interest who received treatment with single agent anti-PD (L) 1 therapy in the FH network between month 11, 2021, 1 and month 9, 2022. This example uses the TMB algorithm from CGP assays, which supports diagnosis of pan-tumour concomitant and lifetime measurements for national mortality index verification.

Table 10: summary of ICPI monotherapy cohorts

Results: 8,440 patients from 24 cancer types met inclusion criteria for the pan-tumor cohort. Briefly, patients receiving at least one treatment normal in an advanced/metastatic setting for one of the diseases of interest are identified. Entries in which no late/metastatic diagnosis and/or no normals in late/metastatic setting are present in one of the diseases of interest are filtered out. Among the remaining entries, those entries that did not have TMB scores, had potential EHR gaps, and/or did not receive treatment with ICPI were also deleted from the analysis. Patients receiving ICPI as monotherapy or combination therapy were identified and those receiving anti-PD 1 or anti-PDL 1 ICPI monotherapy were selected for further analysis. The risk ratio of { HR, (95% CI) } versus TMB <5 for time to next treatment across the whole queue was 0.90 (0.85 to 0.96) for TMBs 5 to 10, 0.72 (0.67 to 0.77) for TMBs 10 to 20, and 0.51 (0.46 to 0.56) for tmb20+ (fig. 29A). The relative risk of death by TMB levels was assessed using a Cox PH model adjusted for ECOGPS, previous treatments, gender, age, pre-opioid rx therapy, genetic lineages, and socioeconomic assessment. The pan-tumor model was also tailored for MSI status, where baseline risk was stratified by cancer type. The relative risk of death { HR, (95% CI) } across the whole queue relative to TMB <5 is 0.95 (0.89 to 1.02) for TMBs 5 to 10, 0.79 (0.73 to 0.85) for TMBs 10 to 20, and 0.52 (0.47 to 0.58) for tmb20+ (fig. 29B). The adjusted Cox model comparing tmb.gtoreq.10 with TMB <10 is pre-assigned with at least 15 mortality events in each group for the cancer type. Patients with TMB.gtoreq.10 showed improved Time To Next Treatment (TTNT) and total survival (OS) when treated with single agent ICPI in multiple cancer types compared to patients with TMB below 10 (FIGS. 30A-B).

The cohorts were further analyzed based on TMB scores for those cancers that exhibited MSS status (fig. 31A-B). For certain cancer types, such as NSCLC, urothelial cancer, gastric cancer, head and neck cancer, melanoma and cervical cancer, patients with TMB ≡10 and designated MSS demonstrated an improved risk ratio for TTNT when treated with a single agent ICPI (fig. 31A). For certain cancer types, such as NSCLC, urothelial cancer, head and neck cancer, and melanoma, patients with tmb+.10 and designated MSS demonstrated an improved risk ratio for OS when receiving treatment with a single agent ICPI (fig. 31B).

Conclusion: elevated TMB using TMB measurements from FDA approved tests is associated with a more favorable survival period for receiving ICPI monotherapy than for similar patients with lower TMB levels across heterogeneous cohorts and in individual cancer types with sufficient capacity. Similarly, using elevated TMB from FDA approved test TMB measurements correlates with a more favorable time to next treatment for patients receiving ICPI monotherapy than for similar patients with lower TMB levels. For patients with MSS tumors, patients with (a) elevated TMB scores and (b) given ICPI monotherapy are also associated with more favorable survival and time to next treatment outcomes than patients with (a) low TMB scores and (b) given ICPI monotherapy.

Example 6: tumor Mutation Burden (TMB) measurements from FDA approved assays and real world total survival with combined immune checkpoint inhibitor therapy (ICPI).

8,440 Patients from the 24 cancer types met inclusion criteria for the pan-tumor cohort, identifying patients who received at least one treatment normal in the advanced/metastatic setting of one of the diseases of interest. Entries in which no late/metastatic diagnosis and/or no normals in late/metastatic setting are present in one of the diseases of interest are filtered out. Among the remaining entries, those entries that did not have TMB scores, had potential EHR gaps, and/or did not receive treatment with ICPI were also deleted from the analysis. Patients receiving ICPI as monotherapy were filtered out and patients receiving ICPI combination therapy were identified.

The risk ratio { HR, (95% CI) } relative to time to next treatment of TMB <5 across the whole queue was 0.92 (0.86 to 0.99) for TMB 5 to 10, 0.77 (0.71 to 0.84) for TMB 10 to 20, and 0.59 (0.52 to 0.67) for tmb20+ (fig. 32A).

The risk ratio { HR, (95% ci) } for total lifetime relative to TMB <5 across the whole queue was 1.05 (0.97 to 1.13) for TMBs 5 to 10, 0.91 (0.83 to 1.01) for TMBs 10 to 20, and 0.68 (0.60 to 0.78) for tmb20+ (fig. 32B).

Conclusion: across the heterogeneity cohort, using elevated TMB from FDA-approved test TMB measurements was associated with a more favorable survival for patients receiving combined ICPI than for similar patients with lower TMB levels. Similarly, using elevated TMB from FDA approved test TMB measurements correlates with a more favorable time to next treatment for patients receiving ICPI than for similar patients with lower TMB levels.

Claims (24)

1. A method for treating an individual suffering from cancer, the method comprising: (a) determining a tumor mutation burden (TMB) score for a tumor biopsy sample obtained from the individual; and (b) treating the individual with an immune checkpoint inhibitor therapy if the TMB score is at least a threshold TMB score; The cancer is metastatic urothelial carcinoma, metastatic gastric adenocarcinoma, metastatic endometrial carcinoma, prostate cancer or non-small cell lung cancer (NSCLC). 2. The method of claim 1, further comprising: assessing microsatellite instability, wherein (b) is further based on the cancer being microsatellite instability high (MSI-H), wherein microsatellite instability is assessed by next generation sequencing (NGS). 3. The method of claim 1, wherein the threshold TMB score is about 8 mutations/Mb, about 9 mutations/Mb, about 10 mutations/Mb, about 11 mutations/Mb, about 12 mutations/Mb, about 13 mutations/Mb, about 14 mutations/Mb, about 15 mutations/Mb, about 16 mutations/Mb, about 17 mutations/Mb, about 18 mutations/Mb, about 19 mutations/Mb, or about 20 mutations/Mb. 4. The method of claim 1, wherein the TMB score is determined based on sequenced DNA between about 100 kb to about 10 Mb. 5. The method of claim 1, wherein the TMB score is determined based on between about 0.8 Mb and about 1.1 Mb of sequenced DNA. 6. The method of claim 1, further comprising treating the individual with an immune checkpoint inhibitor if the TMB score is at least the threshold TMB score. 7. The method of claim 1, wherein the immune checkpoint inhibitor comprises a small molecule inhibitor, an antibody, a nucleic acid, an antibody-drug conjugate, a recombinant protein, a fusion protein, a natural compound, a peptide, a proteolysis targeting chimera (PROTAC), a cell therapy, a treatment for cancer being tested in a clinical trial, an immunotherapy, or any combination thereof. 8. The method of claim 1, wherein the immune checkpoint inhibitor is a PD-1 inhibitor, and the PD-1 inhibitor comprises one or more of the following: nivolumab, pembrolizumab, cemiplimab, or dotalimumab. 9. The method of claim 1, wherein the immune checkpoint inhibitor is a PD-L1 inhibitor, and the PD-L1 inhibitor comprises one or more of the following: atezolizumab, avelumab, or durvalumab. 10. The method of claim 1, wherein the immune checkpoint inhibitor is a CTLA-4 inhibitor, wherein the CTLA-4 inhibitor comprises ipilimumab. 11. The method of claim 1, wherein the individual has previously been treated with an anti-cancer therapy for the cancer. 12. The method of claim 11, wherein the anti-cancer therapy is one or more of the following: a small molecule inhibitor, a chemotherapeutic agent, a cancer immunotherapy, an antibody, a cell therapy, a nucleic acid, surgery, radiation therapy, an anti-angiogenic therapy, an anti-DNA repair therapy, an anti-inflammatory therapy, an anti-tumor agent, a growth inhibitory agent, a cytotoxic agent, or any combination thereof. 13. The method of claim 1, wherein the immune checkpoint inhibitor therapy is a single agent therapy. 14. The method of claim 1, wherein the immune checkpoint inhibitor therapy comprises two or more active agents. 15. The method of claim 1, wherein the immune checkpoint inhibitor therapy comprises a first round of an immune checkpoint inhibitor and subsequent rounds of therapy with a different immune checkpoint inhibitor. 16. The method of claim 1, wherein the immune checkpoint inhibitor therapy is a first-line therapy for the cancer. 17. The method of claim 1, wherein the immune checkpoint inhibitor therapy is a second-line therapy for the cancer. 18. The method of claim 1, further comprising: treating the individual with an additional anti-cancer therapy, wherein the additional anti-cancer therapy comprises one or more of the following: a small molecule inhibitor, a chemotherapeutic agent, a cancer immunotherapy, an antibody, a cell therapy, a nucleic acid, surgery, radiation therapy, an anti-angiogenic therapy, an anti-DNA repair therapy, an anti-inflammatory therapy, an anti-tumor agent, a growth inhibitory agent, a cytotoxic agent, or any combination thereof. 19. The method of claim 1, wherein the TMB score or microsatellite instability is determined by sequencing, wherein the sequencing comprises using massively parallel sequencing (MPS) technology, whole genome sequencing (WGS), whole exome sequencing (WES), targeted sequencing, direct sequencing, next generation sequencing (NGS) or Sanger sequencing technology. 20. The method of claim 1, wherein the individual is a human. 21. The method of claim 1, wherein if the TMB score is at least the threshold TMB score, the individual is predicted to have increased time to next treatment (TTNT), improved overall survival (OS), or improved progression-free survival (PFS) when treated with an immune checkpoint inhibitor compared to chemotherapy. 22. The method of claim 1, further comprising treating the individual with chemotherapy if the TMB score is less than the threshold TMB score. 23. The method of claim 1, wherein the threshold TMB score is about 10 mutations/Mb. 24. A method for identifying an individual having cancer to be treated with immune checkpoint inhibitor therapy, the method comprising: determining a tumor mutation burden (TMB) score for a tumor biopsy sample obtained from the individual, wherein if the TMB score is at least a threshold TMB score, the individual is identified as being treated with immune checkpoint inhibitor therapy, wherein the cancer is metastatic urothelial carcinoma, metastatic gastric adenocarcinoma, metastatic endometrial carcinoma, prostate cancer, or non-small cell lung cancer (NSCLC).