Using Tumor Mutation Burden as a Predictive Biomarker for the Efficacy of Immune Checkpoint Inhibitors vs. Chemotherapy in Cancer Treatment

Abstract

Disclosed herein are methods of treating, treating or identifying, or stratifying individuals with cancer for treatment based on an assessment of tumor mutational burden (TMB) score or TMB score and microsatellite instability.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Application No. 63 / 309,449, filed February 11, 2022, and U.S. Provisional Application No. 63 / 335,079, filed April 26, 2022, the contents of each of which are incorporated by reference in their entirety herein. [Technical field]

[0002] Provided herein are methods of selecting a treatment for an individual with cancer, treating or identifying an individual with cancer for treatment, or stratifying an individual with cancer for treatment based on a tumor mutation burden (TMB) score. [Background technology]

[0003] Cancer can be caused by genomic mutations, and cancer cells can accumulate mutations during cancer development and progression. These mutations can be the result of intrinsic dysfunction of DNA repair, copying, or modification functions, or can be the result of exposure to external mutagens. Certain mutations confer a growth advantage to cancer cells and are positively selected in the tissue microenvironment in which cancer develops. Detecting these mutations in patient samples using next-generation sequencing (NGS) or other genomic analysis techniques can provide important insights into cancer diagnosis, prediction, and treatment.

[0004] Immune checkpoint inhibitor (ICPI) therapy is increasingly being used to treat metastatic cancer. However, despite success, many clinical trials have failed to identify improved survival in patients treated with ICPI versus chemotherapy. Thus, there is a need in the art to identify patient groups with similar or better outcomes in ICPI (no chemotherapy), ICPI (first-line), and ICPI versus chemotherapy after chemotherapy (first-line) regimens. Summary of the Invention

[0005] Provided herein is a method for identifying an individual having cancer for treatment with immune checkpoint inhibitor therapy, comprising determining a tumor mutational burden (TMB) score of a tumor biopsy sample obtained from the individual, wherein the individual is identified for treatment with immune checkpoint inhibitor therapy if the TMB score is at least a threshold TMB score, wherein the cancer is metastatic urothelial carcinoma, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC).

[0006] Further provided herein is a method of selecting a treatment for an individual having cancer, comprising determining a tumor mutational burden (TMB) score of a tumor biopsy sample obtained from the individual, wherein a TMB score that is at least a threshold TMB score identifies the individual as one that may benefit from treatment with an immune checkpoint inhibitor therapy, and wherein the cancer is metastatic urothelial carcinoma, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC).

[0007] Further provided herein is a method of identifying one or more treatment options for an individual having cancer, the method comprising: (a) determining a tumor mutational burden (TMB) score of a tumor biopsy sample obtained from the individual; and (b) generating a report that includes the one or more treatment options identified for the individual, wherein a TMB score that is at least a threshold TMB score identifies the individual as one that may benefit from treatment with an immune checkpoint inhibitor therapy, and the cancer is metastatic urothelial carcinoma, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC).

[0008] Further provided herein is a method of stratifying an individual having cancer for treatment with a therapy, comprising: determining a tumor mutational burden (TMB) score of a tumor biopsy sample obtained from the individual; and (a) identifying the individual as a candidate for receiving immune checkpoint inhibitor therapy if the TMB score is at least a threshold TMB score, or (b) identifying the individual as a candidate for receiving a chemotherapy regimen if the TMB score is less than a threshold TMB score, wherein the cancer is metastatic urothelial carcinoma, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC).

[0009] In some embodiments of the foregoing methods, the method further comprises assessing microsatellite instability, and the identification is further based on the cancer being microsatellite instability high (MSI-H). In some embodiments, microsatellite instability is assessed by next generation sequencing (NGS).

[0010] In some embodiments of the foregoing methods, the individual is identified as having increased survival time as compared to treatment with the chemotherapy regimen.

[0011] Further provided herein is a method of predicting survival of an individual having cancer, comprising obtaining knowledge of a tumor mutation burden (TMB) score of a tumor biopsy sample obtained from the individual, wherein if the TMB score of the tumor biopsy sample obtained from the individual is at least a threshold TMB score, the individual is predicted to have increased survival when treated with an immune checkpoint inhibitor compared to treatment with a chemotherapy regimen, and wherein the cancer is metastatic urothelial carcinoma, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC). Further provided herein is a method of monitoring, evaluating, or screening an individual with cancer, comprising obtaining knowledge of a tumor mutation burden (TMB) score of a tumor biopsy sample obtained from the individual, wherein if the TMB score of the tumor biopsy sample obtained from the individual is at least a threshold TMB score, the individual is predicted to have an increased survival time when treated with an immune checkpoint inhibitor compared to treatment with a chemotherapy regimen, and the cancer is metastatic urothelial carcinoma, metastatic gastric adenocarcinoma, metastatic endometrial carcinoma, prostate cancer, or non-small cell lung cancer (NSCLC). In some embodiments of the aforementioned method, the method further comprises that the increased survival time is increased overall survival (OS). In some embodiments of the aforementioned method, the method further comprises that the increased survival time is increased progression-free survival (PFS). Further provided herein is a method of predicting survival of an individual having cancer, comprising obtaining knowledge of a tumor mutation burden (TMB) score of a tumor biopsy sample obtained from the individual, wherein if the TMB score of the tumor biopsy sample obtained from the individual is at least a threshold TMB score, the individual is predicted to have increased survival when treated with an immune checkpoint inhibitor compared to patients having a TMB score that is less than the threshold TMB score, and wherein the cancer is metastatic urothelial carcinoma, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC).Further provided herein is a method of monitoring, evaluating, or screening an individual with cancer, comprising obtaining knowledge of a tumor mutation burden (TMB) score of a tumor biopsy sample obtained from the individual, wherein if the TMB score of the tumor biopsy sample obtained from the individual is at least a threshold TMB score, the individual is predicted to have increased survival time when treated with an immune checkpoint inhibitor compared to patients with a TMB score that is less than the threshold TMB score, and the cancer is metastatic urothelial carcinoma, metastatic gastric adenocarcinoma, metastatic endometrial carcinoma, prostate cancer, or non-small cell lung cancer (NSCLC). In some embodiments, the increased survival time is increased overall survival (OS). In some embodiments, the increased survival time is increased progression-free survival (PFS).

[0012] Further provided herein is a method of predicting the duration of a therapeutic response for an individual having cancer, comprising obtaining knowledge of a tumor mutation burden (TMB) score of a tumor biopsy obtained from the individual, and comparing the TMB score of the sample to a threshold TMB score, where if the TMB score is equal to or greater than the threshold TMB score, the individual is predicted to have a longer duration of therapeutic response to an immune checkpoint inhibitor, and 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. In some embodiments, a longer duration of therapeutic response is one or more of an increased progression-free survival (PFS) and overall survival (OS) compared to the PFS or OS of an individual having the threshold TMB score, and a shorter duration of therapeutic response is one or more of a decreased PFS and OS compared to the PFS or OS of an individual having the threshold TMB score.

[0013] Further provided herein is a method for treating an individual having cancer, comprising: (a) determining a tumor mutational burden (TMB) score of 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 carcinoma, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC). In some embodiments, the method further comprises assessing microsatellite instability, and (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).

[0014] In some embodiments of the aforementioned methods, the methods further include treating the individual with chemotherapy if the TMB score is below a threshold TMB score.In some embodiments, chemotherapy is an alkylating agent, an alkylsulfonate, an aziridine, an ethylenimine, a methylameramine, an acetogenin, a camptothecin, a bryostatin, a kallistatin, a CC-1065, a cryptophycin, a dolastatin, a duocarmycin, an erytherobin, a pancratistatin, a sarcodictin, a spongiostatin, a nitrogen mustard, a nitrosourea, an antibiotic, a dynemicin, a bisphosphonate, an esperamicin, a neocarzinostatin chromophore or a related chromoprotein enediyne antibiotic chromophore. Groups, antimetabolites, folic acid analogues, purine analogues, pyrimidine analogues, androgens, antiadrenal agents, folic acid supplements, aldophosphamide glycosides, aminolevulinic acid, eniluracil, amsacrine, bestravcil, bisantrene, edatraxate, deformamine, demecolcine, diazicon, elformitin, elliptinium acetate, epothilone, etoglucide, gallium nitrate, hydroxyurea, lentinan, lonidainin, maytansinoids, mitoguazone, mitoxantrone, mopidamol, nitraelin, pentostatin, phenamet, pirarubicin cin, losoxantrone, podophyllic acid, 2-ethylhydrazide, procarbazine, PSK polysaccharide complex, razoxane, rhizoxin, schizophyllan, spirogermanium, tenuazonic acid, triazicon, 2,2',2"-trichlorotriethylamine, trichothecene, urethane, vindesine, dacarbazine, mannomustine, mitobronitol, mitolactol, pipobroman, gacitosine, arabinoside ("Ara-C"), cyclophosphamide, taxoids, 6-thioguanine, mercaptopurine, platinum coordination complexes, vinblastine, platinum, etoposide and / or any combination thereof.

[0015] In some embodiments of the aforementioned 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 aforementioned methods, the threshold TMB score is about 10 mutations / Mb. In some embodiments of the aforementioned methods, the threshold TMB score is about 20 mutations / Mb. In some embodiments of the aforementioned methods, the threshold TMB score is 20 mutations / Mb. In some embodiments of the aforementioned methods, the TMB score is determined based on about 100 kb to about 10 Mb of sequenced DNA. In some embodiments of the aforementioned methods, the TMB score is determined based on about 0.8 Mb to about 1.1 Mb of sequenced DNA.

[0016] In some embodiments of the aforementioned methods, the methods further include treating the individual with an immune checkpoint inhibitor if the TMB score is at least a threshold TMB score.

[0017] In some embodiments of the aforementioned methods, the cancer is prostate cancer that is metastatic castration-resistant prostate cancer.

[0018] In some embodiments of the aforementioned methods, the cancer is NSCLC, and the NSCLC is advanced NSCLC (aNSCLC).

[0019] In some embodiments of the aforementioned methods, the cancer is metastatic urothelial cancer.

[0020] In some embodiments of the aforementioned methods, the cancer is metastatic gastric adenocarcinoma.

[0021] In some embodiments of the aforementioned methods, the cancer is metastatic endometrial cancer.

[0022] In some embodiments of the aforementioned 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 proteolysis-targeting chimeric molecule (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 nivolumab, pembrolizumab, cemiplimab, or dostarlimab. In some embodiments, the immune checkpoint inhibitor is a PD-L1 inhibitor. In some embodiments, the immune checkpoint inhibitor comprises one or more of atezolizumab, avelumab, or durvalumab. In some embodiments, the immune checkpoint inhibitor is a CTLA-4 inhibitor. In some embodiments, the CTLA-4 inhibitor comprises ipilimumab.

[0023] In some embodiments of the foregoing methods, the individual has previously been treated with an anti-cancer therapy for the cancer, hi some embodiments, the anti-cancer therapy is one or more of 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-neoplastic agent, a growth inhibitory agent, a cytotoxic agent, or any combination thereof.

[0024] In some embodiments of the foregoing methods, the individual has not previously received a chemotherapy regimen for the cancer.

[0025] In some embodiments of the foregoing methods, the individual has previously undergone a chemotherapy regimen for the cancer.In some embodiments, the chemotherapy regimen comprises an alkylating agent, an alkylsulfonate, an aziridine, an ethylenimine, a methylameramine, an acetogenin, a camptothecin, a bryostatin, a kallistatin, a CC-1065, a cryptophycin, a dolastatin, a duocarmycin, an erytherobin, a pancratistatin, a sarcodictin, a spongiostatin, a nitrogen mustard, a nitrosourea, an antibiotic, a dynemicin, a bisphosphonate, an esperamicin, a neocarzinostatin chromophore or a related chromoprotein enediyne anti- Biochromophores, antimetabolites, folic acid analogues, purine analogues, pyrimidine analogues, androgens, antiadrenal agents, folic acid supplements, aldophosphamide glycosides, aminolevulinic acid, eniluracil, amsacrine, bestravcil, bisantrene, edatraxate, defoamin, demecolcine, diazicon, elformitin, elliptinium acetate, epothilone, etoglucide, gallium nitrate, hydroxyurea, lentinan, lonidainin, maytansinoids, mitoguazone, mitoxantrone, mopidamol, nitraelin, pentostatin, phenamet, Pirarubicin, losoxantrone, podophyllic acid, 2-ethylhydrazide, procarbazine, PSK polysaccharide complex, razoxane, rhizoxin, schizophyllan, spirogermanium, tenuazonic acid, triazicon, 2,2',2"-trichlorotriethylamine, trichothecenes, urethanes, vindesine, dacarbazine, mannomustine, mitobronitol, mitolactol, pipobroman, gacitosine, arabinoside ("Ara-C"), cyclophosphamide, taxoids, 6-thioguanine, mercaptopurine, platinum coordination complexes, vinblastine, platinum, etho and / or any combination thereof.

[0026] In some embodiments of the foregoing methods, the immune checkpoint inhibitor therapy is the only anti-cancer therapy designated or administered for the cancer.

[0027] In some embodiments of the foregoing methods, the immune checkpoint inhibitor therapy is a single active agent therapy.

[0028] In some embodiments of the aforementioned methods, the immune checkpoint inhibitor therapy comprises two or more active agents.

[0029] In some embodiments of the foregoing methods, the immune checkpoint inhibitor therapy comprises a first round of an immune checkpoint inhibitor and a subsequent round of therapy with a different immune checkpoint inhibitor.

[0030] In some embodiments of the aforementioned methods, the immune checkpoint inhibitor therapy is a first-line therapy for the cancer.

[0031] In some embodiments of the aforementioned methods, the immune checkpoint inhibitor therapy is a second line therapy for the cancer.

[0032] In some embodiments of the foregoing methods, the method further comprises treating the individual with an additional anti-cancer therapy, hi some embodiments, the additional anti-cancer therapy comprises one or more of 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-neoplastic agent, a growth inhibitory agent, a cytotoxic agent, or any combination thereof.

[0033] In some embodiments of the foregoing methods, the TMB score or microsatellite instability is determined by sequencing. In some embodiments, the sequencing comprises the use of 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. In some embodiments, the sequencing comprises: (a) providing a plurality of nucleic acid molecules obtained from a tumor biopsy sample, the plurality of nucleic acid molecules comprising a mixture of tumor and non-tumor nucleic acid molecules; (b) optionally ligating one or more adapters to one or more nucleic acid molecules from the plurality of nucleic acid molecules; (c) amplifying the nucleic acid molecules from the plurality of nucleic acid molecules; (d) capturing a nucleic acid molecule from the amplified nucleic acid molecules, the captured nucleic acid molecule being captured from the amplified nucleic acid molecules by hybridization to one or more bait molecules; and (e) sequencing at least a portion of the captured nucleic acid molecule by a sequencer to obtain a plurality of sequence reads corresponding to one or more genomic loci within the subgenomic interval in the sample. In some embodiments of the aforementioned method, the adapter comprises one or more of an amplification primer sequence, a flow cell adapter hybridization sequence, a unique molecular identifier sequence, a substrate adapter sequence, or a sample index sequence. In some embodiments, amplifying the nucleic acid molecule comprises performing a polymerase chain reaction (PCR) technique, a non-PCR amplification technique, or an isothermal amplification technique. In some embodiments, one or more bait molecules comprise one or more nucleic acid molecules, each nucleic acid molecule comprising a region complementary to a region of a captured nucleic acid molecule. In some embodiments, one or more bait molecules each comprise a capture molecule. In some embodiments, the capture molecule is biotin.

[0034] In some embodiments of the aforementioned methods, the individual is a human.

[0035] 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 (TTNT) when treated with an immune checkpoint inhibitor compared to chemotherapy.

[0036] Further provided herein are kits containing immune checkpoint inhibitors and instructions for use in accordance with any of the aforementioned methods. [Brief description of the drawings]

[0037] Various aspects of at least one example are described below with reference to the accompanying drawings, which are not drawn to scale. The drawings are included to provide illustration and further understanding of the various aspects and examples, and are incorporated into and constitute a part of this specification, but are not intended as a definition of the limits of the particular 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 figures, each identical or nearly identical component shown in the various figures is represented by a like numeral. For clarity, not every component is labeled in every figure.

[0038] [Figure 1A-1B] Propensity weights (pre- and post-adjusted balance) for urothelial cancer patients stratified by TMB <10 mutations / Mb ( Fig. 1A ) and TMB of at least 10 ( Fig. 1B ), showing bias toward chemotherapy (left bias) or immune checkpoint inhibitor therapy (right bias). [Figure 2A-2C] Series of Kaplan-Meier survival curves for patients with urothelial carcinoma receiving first-line single-agent immune checkpoint inhibitor therapy, stratified by tumor mutation burden, without weighting or adjustment, and assessed by progression-free survival (PFS) (Figure 2A), time to next treatment (TTNT) (Figure 2B), and overall survival (OS) (Figure 2C). X-axis is truncated at 36 months for PFS and TTNT, and 48 months for OS. Overall survival estimates are left truncated and at-risk tables are adjusted accordingly. [Figure 3A-3F] A series of Kaplan-Meier survival curves for patients with urothelial carcinoma showing treatment outcomes of first-line immune checkpoint inhibitors (ICPI) versus chemotherapy, adjusted for imbalance (i.e., propensity weighting applied), assessed by PFS (Figures 3A-3B), TTNT (Figures 3C-3D), and OS (Figures 3E and 3F), stratified by TMB less than 10 mutations / Mb and TMB of at least 10 mutations / Mb. The x-axis is truncated at 36 months for PFS and TTNT and 48 months for OS. Overall survival estimates are left truncated and at-risk tables are adjusted accordingly. ICPI curves reflect observed unadjusted PFS, TTNT, and OS, with chemotherapy arms adjusted by propensity weighting. [Figure 4A-4F] Series of Kaplan-Meier survival curves for patients with urothelial carcinoma showing treatment outcomes of first-line ICPI versus chemotherapy, unadjusted for imbalance (i.e., not propensity weighted), assessed by PFS (Figures 4A-4B), TTNT (Figures 4C-4D), and OS (Figures 4E-4F), stratified by TMB <10 mutations / Mb and TMB of at least 10 mutations / Mb. X-axis is truncated at 36 months for PFS and TTNT and 48 months for OS. Overall survival estimates are left-censored. ICPI curves reflect observed unadjusted PFS, TTNT, and OS, with chemotherapy arms adjusted by propensity weighting. [Figure 5A-5C] Evaluation of treatment outcomes of ICPI versus chemotherapy assessed by PFS (Figure 5A), TTNT (Figure 5B), and OS (Figure 5C) are shown with TMB and PL-D1. 64.3% of the analyzed cohort did not have evaluable PD-L1, and only the analyzed cohort with evaluable PD-L1 is represented. With respect to the central vertical axis, a left bias indicates in favor of ICPI and a right bias indicates in favor of chemotherapy. [Figures 6A-6C]Comparison of the real-world analysis cohort with three randomized controlled clinical trials (DANUBE, IMvigor130, and KEYNOTE-361) is shown. ECOG performance scores are shown in Figure 6A. The real-world analysis cohort and the three clinical trials are stratified by TMB (<10 mutations / Mb vs. at least 10 mutations / Mb) for patient outcomes assessed by PFS (Figure 6B) and OS (Figure 6C). [Figure 7] A flow chart of the analysis of ICPI versus chemotherapy for patients with metastatic gastric adenocarcinoma is shown. [Figure 8A-8D] Series of Kaplan-Meier survival curves for patients with metastatic gastric adenocarcinoma showing treatment outcomes of second-line ICPI versus chemotherapy, adjusted for imbalance (i.e., propensity weighting was applied), for time to next treatment (TTNT) with TMB <10 mut / Mb ( Fig. 8A ), TTNT with TMB at least 10 mut / Mb ( Fig. 8B ), OS with TMB <10 mut / Mb ( Fig. 8C ), and OS with TMB at least 10 mut / Mb ( Fig. 8D ). [Figure 9A-9D] Series of Kaplan-Meier survival curves for patients with metastatic gastric adenocarcinoma showing treatment outcomes of second-line ICPI versus chemotherapy, not adjusted for imbalance (i.e., no propensity weighting applied), for TTNT with TMB less than 10 mut / Mb (Figure 9A), TTNT with TM of at least 10 mut / Mb (Figure 9B), OS for TMB less than 10 mut / Mb (Figure 9C), and OS for TMB of at least 10 mut / Mb (Figure 9D). [Figure 10A-10D]Analysis of patients with metastatic gastric adenocarcinoma who received second-line ICPI after first-line chemotherapy. Figure 10A shows TTNT for individual patients by stacked horizontal bar plots by patient in consecutive cohorts with TMB less than 10 mut / Mb. Figure 10B shows TTNT for individual patients by stacked horizontal bar plots by patient with TMB at least 10 mut / Mb. MSI status is listed to the right of the bar. Figure 10C shows point estimates and confidence intervals from a Cox model comparing within-patient TTNT. Figure 10D shows unadjusted overall survival from first-line chemotherapy initiation by TMB. [Figures 11A-11C] Shown are point estimates and confidence intervals for patients with biomarker-defined metastatic gastric adenocarcinoma assessed by TTNT in the second-line ICPI vs. chemotherapy cohort (Figure 11A), OS in the second-line ICPI vs. chemotherapy cohort (Figure 11B), and within-patient TTNT (Figure 11C). [Figure 12A-12B] The KeyNote-061 and real-world analysis cohorts (2L comparative efficacy cohorts) are shown, which were compared for their patient ECOG score distribution (FIG. 12A) and overall survival by TMB subgroup (FIG. 12B). KN-061 had less than 1% as ECOG2, and the real-world analysis cohort had less than 1% ECOG0, which are not labeled. High TMB for the real-world analysis cohort is a TMB of at least 10 mut / Mb, and for KN-061, a whole exome sequencing assay with a "high" threshold is selected consistent with a TMB of at least 10 mut / Mb. [Figure 13A-13D]A series of Kaplan-Meier survival curves for patients with metastatic gastric adenocarcinoma showing treatment outcomes of first-line ICPI versus chemotherapy, adjusted for imbalance, for time to next treatment (TTNT) with TMB < 10 mut / Mb (Figure 13A), TTNT with TMB at least 10 mut / Mb (Figure 13B), OS with TMB < 10 mut / Mb (Figure 13C), and OS with TMB at least 10 Mb / Mb (Figure 13D). X-axis is truncated at 36 months for TTNT and 48 months for OS. Overall survival estimates are left truncated and at-risk tables are adjusted accordingly. Visualizations are adjusted by propensity weighting. [Figure 14A-14D] A series of Kaplan-Meier survival curves for patients with metastatic gastric adenocarcinoma showing treatment outcomes of first-line ICPI versus chemotherapy, not adjusted for imbalance (i.e., no propensity weighting applied), for time to next treatment (TTNT) with TMB < 10 mut / Mb (Figure 14A), TTNT with TMB at least 10 mut / Mb (Figure 14B), OS with TMB < 10 mut / Mb (Figure 14C), and OS with TMB at least 10 mut / Mb (Figure 14D). X-axis is truncated at 36 months for TTNT and 48 months for OS. Overall survival estimates are left truncated and at-risk tables are adjusted accordingly. [Figure 15] To present treatment outcomes in patients with metastatic castration-resistant prostate cancer (mCRPC) as assessed by prostate-specific antigen (PSA) change on single-agent taxanes and stratified by TMB less than 10 and TMB at least 10. [Figure 16] Shown are treatment outcomes for patients with mCRPC assessed by PSA change on single-agent anti-PD1 axis therapy and stratified by TMB <10 and TMB at least 10. [Figures 17A-17D]Series of Kaplan-Meier survival curves for mCRPC patients showing treatment outcomes of single-agent taxane vs. ICPI for time to next treatment (TTNT) with TMB <10 mut / Mb (Figure 17A), TTNT with TMB at least 10 mutations / Mb (Figure 17B), overall survival (OS) with TMB <10 mutations / Mb (Figure 17C), and OS with TMB at least 10 (Figure 17D). [Figure 18] 1 provides a flow chart showing the cohort selection scheme used in Example 4. [Figure 19A] Figure 19B provides an adjusted Kaplan-Meier plot of real-world progression-free survival (rwPFS) for NCLC patients treated with ICPI monotherapy. Figure 19B provides an adjusted Kaplan-Meier plot of rwPFS for NCLC patients treated with ICPI therapy + chemotherapy. Figure 19C provides an adjusted Kaplan-Meier plot of real-world overall survival (rwOS) for NCLC patients treated with ICPI monotherapy. Figure 19D provides an adjusted Kaplan-Meier plot of rwOS for NCLC patients treated with ICPI + chemotherapy. Outcomes were stratified by TMB<10 and TMB≧10. [Figure 20A] Figure 20B provides an adjusted Kaplan-Meier plot of real-world progression-free survival (rwPFS) for NCLC patients treated with ICPI monotherapy. Figure 20B provides an adjusted Kaplan-Meier plot of rwPFS for NCLC patients treated with ICPI therapy + chemotherapy. Figure 20C provides an adjusted Kaplan-Meier plot of real-world overall survival (rwOS) for NCLC patients treated with ICPI monotherapy. Figure 20D provides an adjusted Kaplan-Meier plot of rwOS for NCLC patients treated with ICPI therapy + chemotherapy. Outcomes were stratified by TMB<20 and TMB≧20. [Figure 21A]Figure 21B provides the Kaplan-Meier plot of rwPFS for patients treated with ICPI-containing regimens. Outcomes were stratified by TMB and PDL1 levels: PDL1<1% and TMB<10 (i.e., PDL1- / TMB-), PDL1>1% and TMB<10 (i.e., PDL1+ / TMB-), PDL1<1% and TMB≧10 (i.e., PDL1- / TBM+), and PDL1>1% and TMB≧10 (i.e., PDL1+ / TMB+). Figure 21B provides the results from a multivariate Cox Ph model to detect associations between clinical or genomic features and rwPFS. Figure 21C provides the Kaplan-Meier plot of rwOS for patients treated with ICPI-containing regimens. Outcomes were stratified by TMB and PDL1 levels: PDL1<1% and TMB<10 (i.e., PDL1- / TMB-), PDL1>1% and TMB<10 (i.e., PDL1+ / TMB-), PDL1<1% and TMB≧10 (i.e., PDL1- / TBM+), and PDL1>1% and TMB≧10 (i.e., PDL1+ / TMB+). Figure 21D provides results from a multivariate Cox Ph model detecting associations between clinical or genomic features and rwOS. [Figure 22A]Figure 22B provides the Kaplan-Meier plot of rwPFS for patients treated with ICPI-containing regimens. Outcomes were stratified by TMB and PDL1 levels: PDL1<1% and TMB<20 (i.e., PDL1- / TMB-), PDL1>1% and TMB<20 (i.e., PDL1+ / TMB-), PDL1<1% and TMB≧20 (i.e., PDL1- / TBM+), and PDL1>1% and TMB≧20 (i.e., PDL1+ / TMB+). Figure 22B provides the results from a multivariate Cox Ph model to detect associations between clinical or genomic features and rwPFS. Figure 22C provides the Kaplan-Meier plot of rwOS for patients treated with ICPI-containing regimens. Outcomes were stratified by TMB and PDL1 levels: PDL1<1% and TMB<20 (i.e., PDL1- / TMB-), PDL1>1% and TMB<20 (i.e., PDL1+ / TMB-), PDL1<1% and TMB≧20 (i.e., PDL1- / TBM+), and PDL1>1% and TMB≧20 (i.e., PDL1+ / TMB+). Figure 22D provides results from a multivariate Cox Ph model detecting associations between clinical or genomic features and rwOS. [Figure 23A] Figure 23B shows point estimates and 95% HR (hazard ratio) confidence intervals for biomarkers, and treatment interactions are shown for different TMB or PDL1 cutoffs for rwPFS. Figure 23B shows point estimates and 95% HR (hazard ratio) confidence intervals for biomarkers, and treatment interactions are shown for different TMB or PDL1 cutoffs for rwOS. Figure 23C provides a Kaplan-Meier plot of rwPFS for patients with a PD-L1 score between 1 and 49% treated with ICPI monotherapy or ICPI therapy + chemotherapy. Figure 23D provides a Kaplan-Meier plot of rwPFS for patients with a PD-L1 score ≧50% treated with ICPI monotherapy or ICPI therapy + chemotherapy. [Figure 24]The top 30 altered genes in the ICPI monotherapy cohort (-) and ICPI + chemotherapy cohort (+) are shown. Multi: multiple alterations in the specified gene, RE: rearrangement, CN: copy number alteration, SV: short variant mutation (substrate substitution or insertion / deletion). [Figure 25A] Figure 25B shows the adjusted Kaplan-Meier plot of rwPFS for patients treated with ICPI therapy alone. Figure 25B shows the adjusted Kaplan-Meier plot of rwPFS for patients treated with ICPI therapy + chemotherapy. Figure 25C shows the adjusted Kaplan-Meier plot of rwOS for patients treated with ICPI therapy alone. Figure 25D shows the adjusted Kaplan-Meier plot of rwOS for patients treated with ICPI therapy + chemotherapy. Outcomes were stratified by PDL1 TPS<1% and PDL1 TPS≧1%. [Figure 26A] Figure 26B shows the adjusted Kaplan-Meier plot of rwPFS for patients treated with ICPI therapy alone. Figure 26B shows the adjusted Kaplan-Meier plot of rwPFS for patients treated with ICPI therapy + chemotherapy. Figure 26C shows the adjusted Kaplan-Meier plot of rwOS for patients treated with ICPI therapy alone. Figure 26D shows the adjusted Kaplan-Meier plot of rwOS for patients treated with ICPI therapy + chemotherapy. Outcomes are stratified by PDL1 TC<50% and PDL1 TC≧50%. [Figure 27] 13 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. [Figure 28A]Figure 28B shows the Kaplan-Meier plot of rwPFS for patients treated with ICPI therapy alone. Figure 28B shows the Kaplan-Meier plot of rwPFS for patients treated with ICPI therapy + chemotherapy. Figure 28C shows the Kaplan-Meier plot of rwOS for patients treated with ICPI therapy alone. Figure 28D shows the Kaplan-Meier plot of rwOS for patients treated with ICPI therapy + chemotherapy. [Figure 29A-B] Figure 29 shows pan-tumor evaluation of the clinical relevance of TMB to determine outcome prognosis in single-agent ICPI. Stratified Cox proportional hazards (Cox PH model labeled "Estimate") was used to evaluate pan-cancer associations. Figure 29A shows the association of observed features with time to next treatment. Figure 29B shows the association of observed features with overall survival. [Fig. 30A-B] Figure 30 shows an assessment of the clinical relevance of TMB to determine outcome prognosis in single agent ICPI by tumor type. Cox models adjusted for ECOG score, choice of therapy, sex, age, and opioid use are shown for (Figure 30A) time to next treatment and (Figure 30B) overall survival by disease type. [Fig. 31A-B] Figure 31 shows an assessment of the clinical relevance of TMB to determine outcome prognostic in single-agent ICPI for patients with tumors with MSS status by tumor type. For the MSS group, outcomes of patients with MSS (microsatellite stable) and TMB > 10 tumors were compared with those with TMB < 10. Disease areas are shown for those with a minimum of 5 patients per group. Cox models adjusted for ECOG, treatment of choice, sex, age, and opioid use are shown by disease type for time to next treatment (Figure 31A) and overall survival (Figure 31B). [Fig. 32A-B]Figure 32 shows pan-tumor evaluation of the clinical relevance of TMB to determine outcome prognosis in ICPI combination therapy. Stratified Cox PH model was utilized to evaluate pan-tumor association of observed features. "Estimate" shows Cox proportional hazards. Figure 32A shows the association of observed features with time to next treatment. Figure 32B shows the association of observed features with overall survival. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0039] Described herein is a method, comprising: determining a tumor mutation burden (TMB) score of a sample obtained from an individual; and comparing the determined TMB score with a threshold TMB score.It has been found that the comparison of the determined TMB score with the threshold TMB score is useful for guiding treatment decisions, including the selection between chemotherapy regimens and immune checkpoint inhibitor (ICPI) therapy.

[0040] Thus, described herein is a method for identifying an individual having cancer for treatment with immune checkpoint inhibitor therapy, comprising determining a tumor mutational burden (TMB) score of a tumor biopsy sample obtained from the individual, where if the TMB score is at least a threshold TMB score, the individual is identified for treatment with immune checkpoint inhibitor therapy. Also described herein is a method for selecting a treatment for an individual having cancer, comprising determining a tumor mutational burden (TMB) score of a sample obtained from the individual, where a TMB score that is at least a threshold TMB score identifies the individual as an individual that may benefit from treatment with immune checkpoint inhibitor therapy. Also described herein is a method for identifying one or more treatment options for an individual having cancer, comprising (a) determining a tumor mutational burden (TMB) score of a tumor biopsy sample obtained from the individual, and (b) generating a report including one or more treatment options identified for the individual, where a TMB score that is at least a threshold TMB score identifies the individual as an individual that may benefit from treatment with immune checkpoint inhibitor therapy. Further described herein is a method of stratifying an individual having cancer for treatment with a therapy, comprising: determining a tumor mutational burden (TMB) score of a tumor biopsy sample obtained from the individual; and (a) identifying the individual as a candidate for receiving immune checkpoint inhibitor therapy if the TMB score is at least a threshold TMB score, or (b) identifying the individual as a candidate for receiving a chemotherapy regimen if the TMB score is less than a threshold TMB score. Further described herein is a method of predicting survival of an individual having cancer, comprising obtaining knowledge of a tumor mutational burden (TMB) score of a sample obtained from the individual, wherein the individual is predicted to have increased survival when treated with an immune checkpoint inhibitor compared to treatment with a chemotherapy regimen if the TMB score of a tumor biopsy sample obtained from the individual is at least a TMB score.Further described herein is a method of monitoring, evaluating, or screening an individual having cancer, comprising obtaining knowledge of a tumor mutational burden (TMB) score of a sample obtained from the individual, wherein if the TMB score of the sample obtained from the individual is at least a TMB score, the individual is predicted to have an increased survival time when treated with an immune checkpoint inhibitor compared to treatment with a chemotherapy regimen. Further described herein is a method for treating an individual having cancer, comprising (a) determining a tumor mutational burden (TMB) score of a 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. In any of the methods provided, in addition to determining the TMB score, the method may further comprise assessing microsatellite instability. It has been found that the assessment of microsatellite instability as microsatellite instability high (MSI-H) or not microsatellite instability high (MSI-Low (MSI-L) or microsatellite stable (MSS)) in combination with TMB being less than or at least a threshold TMB score can further help guide treatment decisions, including choosing between chemotherapy regimens and immune checkpoint inhibitor (ICPI) therapy 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.

[0041] Further described herein are methods that include assessing microsatellite instability in a tumor biopsy obtained from an individual with cancer. Assessment of microsatellite instability as frequent (i.e., MSI-H) or not MSI-H (MSI-L or MSS) can help guide treatment decisions, including choosing between chemotherapy regimens and immune checkpoint inhibitor (ICPI) therapy.

[0042] Thus, described herein is a method for identifying an individual having cancer for treatment with immune checkpoint inhibitor therapy, comprising assessing microsatellite instability in a sample obtained from the individual, where if the microsatellite instability is MSI-H, the individual is identified for treatment with immune checkpoint inhibitor therapy. Also described herein is a method for selecting a treatment for an individual having cancer, comprising assessing microsatellite instability in a sample obtained from the individual, where microsatellite instability that is MSI-H identifies the individual as an individual that may benefit from treatment with immune checkpoint inhibitor therapy. Also described herein is a method for identifying one or more treatment options for an individual having metastatic cancer, comprising (a) assessing microsatellite instability in a sample obtained from the individual, and (b) generating a report including the one or more treatment options identified for the individual, where microsatellite instability that is MSI-H identifies the individual as an individual that may benefit from treatment with immune checkpoint inhibitor therapy. Further described herein is a method of stratifying an individual having cancer for treatment with a therapy, comprising: assessing microsatellite instability of a tumor biopsy sample obtained from the individual; and (a) identifying the individual as a candidate for receiving immune checkpoint inhibitor therapy if the microsatellite instability is MSI-H, or (b) identifying the individual as a candidate for receiving a chemotherapy regimen if the microsatellite instability is not MSI-H. Further described herein is a method of predicting survival of an individual having cancer, comprising obtaining knowledge of microsatellite instability of a sample obtained from the individual, wherein if the microsatellite instability is MSI-H for the sample obtained from the individual, the individual is predicted to have increased survival when treated with an immune checkpoint inhibitor compared to treatment with a chemotherapy regimen.Further described herein are methods of monitoring, evaluating, or screening an individual having cancer, comprising obtaining knowledge of microsatellite instability of a sample obtained from the individual, wherein if the microsatellite instability is MSI-H for the sample obtained from the individual, the individual is predicted to have increased survival time 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, comprising (a) assessing microsatellite instability of a sample obtained from the individual, and (b) treating the individual with immune checkpoint inhibitor therapy if the 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 Techniques

[0043] The techniques and procedures described or referenced herein generally conform to conventional methodology, e.g., those described in Sambrook et al., Molecular Cloning: A Laboratory Manual 3rd edition (2001) Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY, Current Protocols in Molecular Biology (eds. FMA Usubel, et al., (2003)), the series Methods in Enzymology (Academic Press, Inc.): PCR 2: A Practical Approach (eds. MJ MacPherson, BD Hames and GR Taylor (1995)), Antibodies, A Laboratory Manual (eds. Harlow and Lane, 1988), and Animal Cell Culture (ed. R.I. Freshney (1987)), Oligonucleotide Synthesis (ed. M.J. Gait, 1984), Methods in Molecular Biology, Humana Press, Cell Biology: A Laboratory Notebook (ed. J.E. Cellis, 1998) Academic Press, Animal Cell Culture (RIFreshney), 1987), Introduction to Cell and Tissue Culture (JPMather and PE Roberts, 1998), Plenum Press, Cell and Tissue Culture: Laboratory Procedures (A.Doyle, JBGriffiths, and DGNewell, eds., 1993-8), J. Wiley and Sons, Handbook of Experimental Immunology (DMWeir and CC Blackwell, eds.), Gene Transfer. Vectors for Mammalian Cells(JMMiller and MPCalos, 1987), PCR: The Polymerase Chain Reaction, (Mullis et al., 1994), Current Protocols in Immunology (JEColigan et al., 1991), Short Protocols in Molecular Biology (Wiley and Sons, 1999), Immunobiology (CA Janeway and P. Travers, 1997), Antibodies (P. Finch, 1997), Antibodies: A Practical Approach (edited by D. Catty, IRL Press, 1988-1989), Monoclonal Antibodies: A Practical Approach (edited by P. Shepherd and C. Dean, Oxford University Press, 2000), Using Antibodies: A Laboratory Manual (E. Harlow and D. Lane (Cold Spring Harbor Laboratory Press, 1999), The Antibodies (edited by M. Zanetti and JD Capra, Harwood Academic Publishers, 1995), as well as Cancer: Principles and Practice of Oncology (eds. VT DeVita et al., J.B. Lippincott Company, 1993), and are well understood and commonly employed by those of skill in the art.

[0044] II. Definition Certain terms are defined: Additional terms are defined throughout the specification.

[0045] As used herein, the articles "a" and "an" refer to one or to more than one (eg, to at least one) of the grammatical object of the article.

[0046] "About" and "approximately" are generally intended to mean an acceptable degree of error of the quantity measured, given the nature or precision of the measurements. Exemplary degrees of error are within 20% (%), typically within 10%, and more typically within 5% of a given value or range of values.

[0047] It will be understood that aspects and embodiments of the invention described herein include "comprising," "consisting" and / or "consisting essentially of" aspects and embodiments.

[0048] The terms "cancer" and "tumor" are used interchangeably herein. These terms refer to the presence of cells that have characteristics typical of cancer-causing cells, such as uncontrolled proliferation, immortality, metastatic potential, rapid growth and proliferation rate, and certain characteristic morphological features. Cancer cells are often in the form of tumors, but such cells can exist alone in an animal or can 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 precancerous as well as malignant cancers.

[0049] As used interchangeably herein, "polynucleotide", "nucleic acid", or "nucleic acid molecule" refers to a polymer of nucleotides of any length, including DNA and RNA. The nucleotides can be deoxyribonucleotides, ribonucleotides, modified nucleotides or bases, and / or their analogs, 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-stranded and double-stranded DNA, DNA including single-stranded and double-stranded regions, single-stranded and double-stranded RNA, RNA including single-stranded and double-stranded regions, hybrid molecules including DNA and RNA that may be single-stranded or may typically be double-stranded or include single-stranded and double-stranded regions. In addition, the term "polynucleotide" as used herein refers to triple-stranded regions including RNA or DNA, or both RNA and DNA. The strands in such regions may be from the same molecule or from different molecules. A region may include all of one or more of the molecules, but more typically involves only some regions of the molecule. One of the molecules of the triple helix region is often an oligonucleotide. The term "polynucleotide" specifically includes cDNA.

[0050] A polynucleotide may comprise modified nucleotides, such as methylated nucleotides and their analogs. If present, modifications to the nucleotide structure may be imparted before or after assembly of the polymer. The sequence of nucleotides may be interrupted by non-nucleotide components. A polynucleotide may be further modified after synthesis, such as by conjugation with a label. Other types of modifications include, for example, substitution of one or more of the naturally occurring nucleotides with "caps", analogs, internucleotide modifications, such as those with uncharged linkages (e.g., methylphosphonates, phosphotriesters, phosphoamidates, carbamates, etc.) and those with charged linkages (e.g., phosphorothioates, phosphorodithioates, etc.), those containing pendant moieties, such as 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, metal oxides, etc.), those containing alkylators, those with modified linkages (e.g., alpha anomeric nucleic acids), as well as unmodified forms of polynucleotides. Additionally, any of the hydroxyl groups normally present in the sugar may be replaced, for example, by phosphonate groups, phosphate groups, protected by standard protecting groups, or activated to prepare additional linkages to additional nucleotides, or conjugated to solid or semi-solid supports. The 5' and 3' terminal OH may be phosphorylated or substituted with amines or organic capping group moieties of 1-20 carbon atoms. Other hydroxyls may also be derivatized to standard protecting groups. Polynucleotides may also contain analogous forms of ribose or deoxyribose sugars 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 sugars, furanose sugars, sedoheptulose, acyclic analogs, and abasic nucleoside analogs such as methyl riboside.One or more phosphodiester linkages may be replaced by alternative linking groups. These alternative linking groups include, but are not limited to, embodiments in which phosphate is replaced by P(0)S ("thioate"), P(S)S ("dithioate"), "(0)NR2 ("amidate"), P(0)R, P(0)OR', CO or CH2 ("formacetal"), where each R or R' is independently H or substituted or unsubstituted alkyl (1-20C) optionally containing an ether (-0-) linkage, aryl, alkenyl, cycloalkyl, cycloalkenyl, or araldyl. Not all linkages in a polynucleotide need be identical. A polynucleotide may contain one or more different types of modifications and / or multiple modifications of the same type described herein. The preceding description applies to all polynucleotides referred to herein, including RNA and DNA.

[0051] The term "detection" includes any means of detection, including direct and indirect detection. As used herein, the term "biomarker" refers to an indicator (e.g., preventative, diagnostic, and / or prognostic) that can be detected in a sample. A biomarker can serve as an indicator of a particular subtype of a disease or disorder (e.g., cancer) characterized by certain molecular, pathological, histological, and / or clinical features (responsiveness to therapy, e.g., checkpoint inhibitors). In one embodiment, a biomarker is a set of genes or a set number of mutations / alterations (e.g., somatic mutations) in a set of genes. Biomarkers include, but are not limited to, molecular markers of 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, modifications of polypeptides and polynucleotides (e.g., post-translational modifications), carbohydrates, and / or glycolipids.

[0052] As used herein, "amplification" generally refers to the process of producing multiple copies of a desired sequence. "Multiple copies" means at least two copies. A "copy" does not necessarily mean perfect sequence complementarity or identity to the template sequence. For example, a copy may contain nucleotide analogs such as deoxyinosine, deliberate sequence changes (e.g., sequence changes introduced by a primer that contains a sequence that is hybridizable to the template but is not complementary to the template), and / or sequence errors that occur during amplification.

[0053] As used herein, the technique of "polymerase chain reaction" or "PCR" generally refers to a procedure in which small amounts of specific nucleic acids, RNA, and / or DNA pieces are amplified, for example, as described in U.S. Pat. No. 4,683,195. Generally, sequence information from or beyond the ends of the region of interest must be available so that oligonucleotide primers can be designed that are identical or similar in sequence to opposite strands of the template to be amplified. The 5' terminal nucleotides of the two primers may coincide with the ends of the amplified material. PCR can be used to amplify specific RNA sequences, specific DNA sequences from total genomic DNA, cDNA transcribed from total cellular RNA, bacteriophage, or plasmid sequences, etc. See generally Mullis et al., Cold Spring Harbor Symp. Quant. Biol. 51:263 (1987), and Erlich, ed., PCR Technology (Stockton Press, NY, 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 that involves the use of known nucleic acids (DNA or RNA) as primers and a nucleic acid polymerase to amplify or generate a specific piece of nucleic acid, or a specific piece of nucleic acid that is complementary to a specific nucleic acid.

[0054] "Individual response" or "response" may be assessed using any endpoint that indicates benefit to an individual, including, but not limited to, (1) inhibition to some extent, including slowing or complete halt, of disease progression (e.g., cancer progression); (2) reduction in tumor size; (3) inhibition (i.e., reduction, slowing, or complete halt) of cancer cell invasion into adjacent peripheral organs and / or tissues; (4) inhibition (i.e., reduction, slowing, or complete halt) of metastasis; (5) alleviation to some extent of one or more symptoms associated with a disease or disorder (e.g., cancer); (6) increase or prolongation in length of survival, including overall survival and progression-free survival; and / or (7) reduced mortality at a given time point following treatment.

[0055] An "effective response" of a patient or "responsiveness" of a patient to treatment with a pharmaceutical agent, and similar expressions, refers to a clinical or therapeutic benefit conferred on a patient at risk for or suffering from a disease or disorder, e.g., cancer. In one embodiment, such benefit includes extending survival (including overall survival and / or progression-free survival), obtaining an objective response (including a complete or partial response), or ameliorating the signs or symptoms of cancer.

[0056] As used herein, "treatment" (and its grammatical variants, e.g., "treat" or "treating") refers to clinical intervention in an attempt to alter the natural course of the individual being treated, and may be performed either prophylactically or during the course of clinical pathology. Desirable effects of treatment include, but are not limited to, preventing the onset or recurrence of disease, alleviating symptoms, reducing any direct or indirect pathological consequences of the disease, preventing metastasis, reducing the rate of disease progression, ameliorating or alleviating the disease state, and remission or improved prognosis.

[0057] As used herein, the terms "individual," "patient," or "subject" are used interchangeably and refer to any single animal, e.g., mammals (including non-human animals, e.g., dogs, cats, horses, rabbits, zoo animals, cows, pigs, sheep, and non-human primates), for which treatment is desired. In certain embodiments, a patient herein is a human.

[0058] As used herein, "administering" refers to a method of giving a dosage of a drug or pharmaceutical composition (e.g., a pharmaceutical composition comprising a drug) to a subject (e.g., a patient). Administration may be by any suitable means for localized treatment, intralesional administration, including parenteral, intrapulmonary, and intranasal, and, if desired. Parenteral injections include, for example, intramuscular, intravenous, intraarterial, intraperitoneal, or subcutaneous administration. Administration may be by any suitable route, for example, by injection (e.g., intravenous or subcutaneous injection), depending in part on whether administration is temporary or chronic. Various dosing schedules are contemplated herein, including, but not limited to, single or multiple administrations over various time points, bolus administration, and pulse infusion.

[0059] As used herein, the terms "concurrently" or "in combination" are used to refer to the administration of two or more therapeutic agents, where at least a portion of the administration overlaps in time. Thus, concurrent administration includes dosing regimens where the administration of one or more agents continues after the administration of one or more other agents is discontinued.

[0060] As used herein, "obtain" or "obtaining" refers to gaining possession of a physical entity or value, e.g., a numerical value, by "directly obtaining" or "indirectly obtaining" the physical entity or value. "Directly obtaining" means performing a process (e.g., performing a synthetic or analytical method) to obtain the physical entity or value. "Indirectly obtaining" refers to receiving a physical entity or value from another entity or source (e.g., a third-party laboratory that directly obtained the physical entity or value). Obtaining a physical entity directly includes performing a process that involves a physical change of a physical substance, e.g., a starting material. Exemplary changes include making a physical entity from two or more starting materials, shearing or fragmenting a material, separating or purifying a material, combining two or more separate entities into a mixture, and performing a chemical reaction that involves breaking or forming a covalent or non-covalent bond. Obtaining a value directly includes performing a process involving a physical change of a sample or another substance, including, for example, performing an analytical process involving a physical change of a substance, e.g., a sample, an analyte, or a reagent (sometimes referred to herein as a "physical analysis"); performing an analytical method, e.g., separating or purifying a substance, e.g., an analyte, or a fragment or other derivative thereof, from another substance; combining the analyte, or a fragment or other derivative thereof, with another substance, e.g., a buffer, a solvent, or a reactant; or modifying the structure of the analyte, or a fragment or other derivative thereof, e.g., by breaking or forming a covalent or non-covalent bond between a first atom and a second atom of the analyte, or by modifying the structure of a reagent, or a fragment or other derivative thereof, e.g., by breaking or forming a covalent or non-covalent bond between a first atom and a second atom of the reagent.

[0061] "Obtaining a sequence" or "obtaining a read", as the term is used herein, refers to obtaining possession of a nucleotide or amino acid sequence by "directly obtaining" or "indirectly obtaining" a sequence or read. "Directly obtaining" a sequence or read means performing a process (e.g., performing a synthesis or analytical method) to obtain a sequence, such as performing a sequencing method (e.g., a next generation sequencing (NGS) method). "Indirectly obtaining" a sequence or read refers to receiving sequence information or knowledge from another party or source (e.g., a third party laboratory that directly obtained the sequence) or receiving a sequence. The obtained sequence or read need not be a complete sequence, e.g., sequencing of at least one nucleotide, or obtaining information or knowledge that identifies one or more of the alterations disclosed herein as present in a sample, biopsy, or subject constitutes obtaining a sequence.

[0062] Obtaining sequences or reads directly includes performing a process that involves a physical change of a starting material, such as a physical material, e.g., a sample, as described herein. Exemplary changes include creating a physical entity from two or more starting materials, shearing or fragmenting a material, such as genomic DNA fragments, separating or purifying a material (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 a covalent or non-covalent bond. Obtaining a value directly includes performing a process that involves a physical change of a sample or another material, as described above. The size of the fragments (e.g., the average size of the fragments) can be 2500 bp or less, 2000 bp or less, 1500 bp or less, 1000 bp or less, 800 bp or less, 600 bp or less, 400 bp or less, or 200 bp or less. In some embodiments, the size of the fragments (e.g., cfDNA) is about 150 bp to about 200 bp (e.g., about 160 bp to about 170 bp). In some embodiments, the size of the fragments (e.g., DNA fragments from a liquid biopsy sample) is about 150 bp to about 250 bp. In some embodiments, the size of the fragments (e.g., cDNA fragments obtained from RNA in a liquid biopsy sample) is about 100 bp to about 150 bp.

[0063] 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 a mutation, e.g., a mutation, in a gene or gene product that affects the integrity, sequence, structure, amount or activity of the gene or gene product compared to a normal or wild-type gene. The alteration may be the amount, structure and / or activity in a cancer tissue or cell compared to its amount, structure and / or activity in a normal or healthy tissue or cell (e.g., a control) and is associated with a disease state such as cancer. For example, an alteration associated with cancer or predicting responsiveness to anti-cancer therapy may have an altered nucleotide sequence (e.g., a mutation), amino acid sequence, chromosomal translocation, chromosomal inversion, copy number, expression level, protein level, protein activity, epigenetic modification (e.g., methylation or acetylation status, or post-translational modification) in a cancer tissue or cell 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, duplications, amplifications, translocations, inter- and intra-chromosomal rearrangements. Mutations may be present in coding or non-coding regions of genes. In certain embodiments, the alterations are detected as rearrangements, e.g., genomic rearrangements, including one or more introns or fragments thereof (e.g., one or more rearrangements in the 5'-UTR and / or 3'-UTR). In certain aspects, the alterations are associated (or not) with a phenotype, e.g., a cancerous phenotype (e.g., one or more of cancer risk, cancer progression, cancer treatment, or resistance to cancer treatment). In one embodiment, the alterations (or tumor mutation burden) are associated with one or more of a genetic risk factor, a positive treatment response predictor, a negative treatment response predictor, a positive prognostic factor, a negative prognostic factor, or a diagnostic factor for cancer.

[0064] As used herein, the term "indel" refers to an insertion, deletion, or both of one or more nucleotides in the nucleic acid of a cell. In certain embodiments, an indel includes both an insertion and deletion of one or more nucleotides, where both the insertion and deletion are nearby on the nucleic acid. In certain embodiments, an indel results in a net change in the total number of nucleotides. In certain embodiments, an indel results in a net change of about 1 to about 50 nucleotides.

[0065] "Subgenomic interval", as the term is used herein, refers to a portion of a genomic sequence. In one embodiment, a subgenomic interval can be a single nucleotide position, e.g., a variant at that position is associated (positively or negatively) with a tumor phenotype. In one embodiment, a subgenomic interval includes two or more nucleotide positions. Such embodiments include sequences that are at least 2, 5, 10, 50, 100, 150, or 250 nucleotides in length. A subgenomic interval can include an entire gene or a portion thereof, e.g., a coding region (or a portion thereof), an intron (or a portion thereof), or an exon (or a portion thereof). A subgenomic interval can include all or a portion of a naturally occurring, e.g., genomic DNA, fragment of a nucleic acid. For example, a subgenomic interval can correspond to a fragment of genomic DNA that is subjected to a sequencing reaction. In one embodiment, a subgenomic interval is a contiguous sequence from a genomic source. In one embodiment, a subgenomic interval includes sequences that are not contiguous in a genome, e.g., a subgenomic interval in a cDNA can include an exon-exon junction formed as a result of splicing. In one embodiment, the subgenomic interval comprises a tumor nucleic acid molecule. In one embodiment, the subgenomic interval comprises a non-tumor nucleic acid molecule.

[0066] In one embodiment, the subgenomic interval may comprise a single nucleotide position; an intragenic or intergenic region; an exon or intron, or a fragment thereof, typically an exonic sequence or a fragment thereof; a coding or non-coding region, such as a promoter, enhancer, 5' untranslated region (5'UTR), or 3' untranslated region (3'UTR), or a fragment thereof; a cDNA or a fragment thereof; a SNP; a somatic mutation, a germline mutation, or both, an alteration, such as a point or single mutation; a deletion mutation (e.g., an in-frame deletion, an intragenic deletion, a complete gene deletion); The term "gene copy number" includes or consists of: an insertion mutation (e.g., intragenic insertion); an inversion mutation (e.g., intrachromosomal inversion); an inverted duplication mutation; a tandem duplication (e.g., intrachromosomal tandem duplication); a translocation (e.g., chromosomal translocation, non-reciprocal translocation); a rearrangement (e.g., a genomic rearrangement (e.g., rearrangement of one or more introns, rearrangement of one or more exons, or combinations and / or fragments thereof; a rearranged intron can include the 5' and / or 3'-UTR); a change in gene copy number; a change in gene expression; a change in RNA levels; or a combination thereof. "Genetic copy number" refers to the number of DNA sequences in a cell that code for a particular gene product. Generally, for a given gene, a mammal has two copies of each gene. Copy number can be increased, for example, by gene amplification or duplication, or decreased by deletion.

[0067] "Interval of interest" as that term is used herein refers to a subgenomic interval or an expressed subgenomic interval. In one embodiment, the subgenomic interval and the expressed subgenomic interval correspond, meaning that the expressed subgenomic interval contains sequences expressed from the corresponding subgenomic interval. In one embodiment, the subgenomic interval and the expressed subgenomic interval are non-corresponding, meaning that the expressed subgenomic interval does not contain sequences expressed from the non-corresponding subgenomic interval, but rather corresponds to a different subgenomic interval. In one embodiment, the subgenomic interval and the expressed subgenomic interval are partially corresponding, meaning that the expressed subgenomic interval contains sequences expressed from the corresponding subgenomic interval and sequences expressed from a different corresponding subgenomic interval.

[0068] As used herein, the term "library" refers to a collection of nucleic acid molecules. In one embodiment, a library comprises a collection of nucleic acid molecules, e.g., a collection of whole genomes, subgenomic fragments, cDNA, cDNA fragments, RNA, e.g., mRNA, RNA fragments, or combinations thereof. Typically, the nucleic acid molecules are DNA molecules, e.g., genomic DNA or cDNA. The nucleic acid molecules can be fragmented, e.g., sheared or enzymatically prepared genomic DNA. The nucleic acid molecules include sequences derived from the subject and can also include sequences not derived from the subject, e.g., adapter sequences, primer sequences, or other sequences that allow for identification, e.g., "barcode" sequences. In one embodiment, some or all of the library nucleic acid molecules include adapter sequences. The adapter sequences can be located at one or both ends. The adapter sequences can be useful, for example, for sequencing methods (e.g., NGS methods), amplification, reverse transcription, or cloning into vectors. A library can comprise a collection of nucleic acid molecules, e.g., target nucleic acid molecules (e.g., tumor nucleic acid molecules, reference nucleic acid molecules, or combinations thereof). The nucleic acid molecules of the library can be derived from a single individual. In embodiments, a library can include 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 from different subjects can be combined to form a library that includes nucleic acid molecules from two or more subjects. In one embodiment, the subject is a human having or at risk of having cancer or a tumor.

[0069] "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 an adenine residue of a first nucleic acid strand can form specific hydrogen bonds ("base pairing") with a residue of a second nucleic acid strand that is antiparallel to the first strand if the residue is thymine or uracil. Similarly, it is known that a cytosine residue of a first nucleic acid strand can base pair with a residue of a second nucleic acid strand that is antiparallel to the first strand if the residue is guanine. A first region of a nucleic acid is complementary to a second region of the same or different nucleic acid if at least one nucleotide residue of the first region can base pair with a residue of the second region when the two regions are arranged in antiparallel. In certain embodiments, the first region comprises a first portion and the second region comprises a second portion, and when the first and second portions are arranged in an antiparallel manner, 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 can base pair with nucleotide residues of the second portion. In other embodiments, all nucleotide residues of the first portion can base pair with nucleotide residues of the second portion.

[0070] As used herein, "likely" or "likely" refers to a high probability that an item, object, thing, or person will occur. Thus, in one example, a subject that is likely to respond to a treatment has a higher probability of responding to the treatment compared to a reference subject or group of subjects.

[0071] "Low likelihood" refers to a decreased probability of an event, item, object, thing, or person occurring relative to a standard. Thus, a subject who is unlikely to respond to a treatment has a reduced probability of responding to the treatment compared to a reference subject or group of subjects.

[0072] As used herein, "next generation sequencing" or "NGS" or "NG sequencing" refers to the determination of the nucleotide sequence of individual nucleic acid molecules (e.g., in single molecule sequencing) or clonally expanded proxies of individual nucleic acid molecules (e.g., in single molecule sequencing). 3 , 10 4 , 10 5Next-generation sequencing refers to any sequencing method that identifies in a high-throughput manner (more than 100 or more molecules are sequenced 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 cognate sequences in the data generated by the sequencing experiment. Next-generation sequencing methods are known in the art and are described, for example, in Metzker, M. (2010) Nature Biotechnology Reviews 11:31-46, 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 a sample.

[0073] A "nucleotide value" as referred to herein represents the identity of a nucleotide occupying or assigned to a nucleotide position. Exemplary nucleotide values ​​include absence (e.g., deletion), addition (e.g., insertion of one or more nucleotides, which may or may not include the identity), or presence (occupancy), A, T, C, or G. Other values ​​may be, for example, A or X (where X is one or two of T, G, or C), T or X (where X is one or two of A, G, or C), G or X (where X is one or two of T, A, or C), C or X (where X is one or two of T, G, or A), a pyrimidine nucleotide, or a purine nucleotide, where the nucleotide value may be the frequency of one or more, e.g., two, three, or four bases (or other values ​​described herein, e.g., missing or additional) at a nucleotide position. For example, a nucleotide value can include a frequency for A and a frequency for G at a nucleotide position.

[0074] "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 any place herein does not imply that the use of the term "or" is not interchangeable with the term "and / or," unless the context clearly indicates otherwise.

[0075] As used herein, a "control nucleic acid" or "reference nucleic acid" refers to a nucleic acid molecule from a control or reference sample. Typically, it is a DNA, e.g., genomic DNA, or cDNA derived from RNA, that does not contain alterations or mutations of genes or gene products. 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 derived from a blood control, a normal adjacent tissue (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 somatic alterations, e.g., serves as a negative control.

[0076] A "threshold" as used herein is a value that is a function of the number of reads that need to be present to assign a nucleotide value to a target interval (e.g., a subgenomic or expressed subgenomic interval). For example, it is a function of the number of reads with a particular nucleotide value, e.g., "A", at a nucleotide position that is required to assign that nucleotide value to that nucleotide position within the subgenomic interval. The threshold can be expressed, for example, as a number of reads, e.g., an integer (or a function thereof), or as a percentage of reads with that value. As an example, if the threshold is X and there are X+1 reads with a nucleotide value of "A", then a value of "A" is assigned to the position within the target interval (e.g., a subgenomic or expressed subgenomic interval). The threshold can also be expressed as a function of a mutation or variant expectation, mutation frequency, or Bayesian prior. In one embodiment, a mutation frequency would require the number or percentage of reads with a nucleotide value, e.g., A or G, at a position to call that nucleotide value. In an embodiment, the threshold can be a function of mutation expectation, e.g., mutation frequency, and tumor type. For example, a variant at a nucleotide position can have a first threshold value if the patient has a first tumor type and a second threshold value if the patient has a second tumor type.

[0077] As used herein, a "target nucleic acid molecule" refers to a nucleic acid molecule that one wishes to isolate from a nucleic acid library. In one embodiment, the target nucleic acid molecule may be a tumor nucleic acid molecule, a reference nucleic acid molecule, or a control nucleic acid molecule, as described herein.

[0078] As used herein, a "tumor nucleic acid molecule" or other similar terms (e.g., "tumor or cancer-associated nucleic acid molecule") refers to a nucleic acid molecule having a sequence derived from a tumor cell. The terms "tumor nucleic acid molecule" and "tumor nucleic acid" may be used interchangeably herein. In one embodiment, the tumor nucleic acid molecule comprises a target section having a sequence (e.g., a nucleotide sequence) having an alteration (e.g., a mutation) associated with a cancerous phenotype. In other embodiments, the tumor nucleic acid molecule comprises a target section having a wild-type sequence (e.g., a wild-type nucleotide sequence). For example, a target section from a heterozygous or homozygous wild-type allele present in a cancer cell. The tumor nucleic acid molecule may comprise a reference nucleic acid molecule. Typically, it is DNA from the sample, e.g., genomic DNA, or cDNA 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 a CTC.

[0079] "Variant" as used herein refers to a structure that can exist in more than one structure, for example a subgenomic interval that can have alleles of a polymorphic locus.

[0080] An "isolated" nucleic acid molecule is one 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 does not contain 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 may contain less than about 5 kB, less than about 4 kB, less than about 3 kB, less than about 2 kB, less than about 1 kB, less than about 0.5 kB, or less than about 0.1 kB of nucleotide sequences that naturally flank the nucleic acid molecule in the genomic DNA of the cell from which the nucleic acid is derived. 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., if produced by recombinant techniques, or may be substantially free of chemical precursors or other chemicals, e.g., if chemically synthesized.

[0081] III. TREATMENT, ASSESSMENT, AND IDENTIFICATION The methods of the disclosure, in certain embodiments, relate to an individual having cancer and / or a sample (biopsy and / or blood sample) obtained from the individual having cancer. In some embodiments, the methods provide improved treatments for the individual based on determining a TMB score and / or assessing microsatellite instability in a sample obtained from the individual. In some embodiments, the methods provide improved methods of selecting a treatment, identifying one or more treatment options, stratifying an individual for treatment with a therapy, predicting an individual's survival time, and / or monitoring, evaluating, or screening an individual, each based at least in part on determining a TMB score and / or microsatellite instability in a sample obtained from the individual.

[0082] In some embodiments, the individual has cancer. In some embodiments, the individual has been treated or is being treated for cancer. In some aspects, the individual is in need of being monitored for progression or regression of cancer, e.g., after being treated with a cancer therapy. In some embodiments, the individual is in need of being monitored for recurrence of cancer. In some embodiments, the individual is at risk of having cancer. In some embodiments, the individual is suspected of having cancer. In some embodiments, the individual is being tested for cancer. In some embodiments, the individual has a genetic predisposition to cancer (e.g., having a mutation that increases the baseline risk for developing cancer). In some embodiments, the individual has been exposed to an environment (e.g., radiation or chemicals) that increases the risk of developing cancer. In some embodiments, the individual is in need of being monitored for the development 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 second line treatment for cancer.

[0083] In certain embodiments, the sample is from an individual with cancer. Exemplary cancers include, but are not limited to, B-cell cancers, such as 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, kidney cancer, testicular cancer, biliary tract cancer, small intestine or adnexal cancer, and the like. Cancer of the salivary gland, thyroid cancer, adrenal adenocarcinoma, osteosarcoma, chondrosarcoma, cancer of the blood tissue, adenocarcinoma, inflammatory myofibroblastic tumor, gastrointestinal stromal tumor (GIST), colon cancer, multiple myeloma (MM), myelodysplastic syndrome (MDS), myeloproliferative disorder (MPD), acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), chronic myelogenous leukemia (CML), chronic lymphocytic leukemia (CLL), polycythemia vera, Hodgkin's lymphoma, non-Hodgkin's lymphoma Lymphoma (NHL), soft tissue sarcoma, fibrosarcoma, myxosarcoma, liposarcoma, osteogenic sarcoma, chordoma, angiosarcoma, endothelial sarcoma, synovium, mesothelioma, Ewing's tumor, leiomyosarcoma, rhabdomyosarcoma, squamous cell carcinoma, basal cell carcinoma, adenocarcinoma, sweat gland carcinoma, sebaceous gland carcinoma, papillary carcinoma, papillary adenocarcinoma, medullary carcinoma, bronchogenic carcinoma, renal cell carcinoma, hepatocellular carcinoma, bile duct carcinoma, choriocarcinoma, seminoma, embryonal carcinoma, Wilms' tumor, bladder cancer, epithelial carcinoma, glioma, astrocytoma These include cell tumors, medulloblastomas, craniopharyngiomas, ependymoma, pinealomas, hemangioblastomas, acoustic neuromas, oligodendroglioma, meningiomas, neuroblastomas, retinoblastomas, cell lymphomas, mantle cell lymphomas, hepatocellular carcinoma A, thyroid cancer, gastric cancer, head and neck cancer, small cell carcinoma, essential thrombocythemia, agnogenic myeloid metaplasia, hypereosinophilic syndrome, systemic mastocytosis, the familiar hypereosinophilia, chronic eosinophilic leukemia, neuroendocrine carcinoma, and cancer-like tumors. In some embodiments, the cancer is NSCLC (advanced NSCLCL or "aNSCLC"), colorectal cancer, cholangiocarcinoma, breast cancer, gastric cancer, melanoma, pancreatic cancer, prostate cancer, ovarian cancer, esophageal cancer, or cancer of unknown primary. In some embodiments, the cancer is metastatic urothelial carcinoma. 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 cancer is melanoma. In some embodiments, the cancer is non-small cell lung cancer (NSCLC). In some embodiments, the NSCLC is advanced NSCLC (aNSCLC).

[0084] In certain embodiments, the sample is from an individual with a solid tumor, hematological cancer, or metastatic forms thereof. In certain embodiments, the sample is obtained from a subject who has cancer or is at risk of having cancer. In certain embodiments, the sample is obtained from a subject who has not undergone therapy to treat cancer, who is undergoing therapy to treat cancer, or who has undergone therapy to treat cancer, as described herein.

[0085] In some embodiments, the cancer is a hematological malignancy (or pre-malignancy). As used herein, hematological malignancy refers to a tumor of hematopoietic or lymphatic tissue, e.g., a tumor affecting the blood, bone marrow, or lymph nodes. Exemplary hematological malignancies include leukemia (e.g., acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), chronic lymphocytic leukemia (CLL), chronic myelogenous leukemia (CML), hairy cell leukemia, acute monocytic leukemia (AMoL), chronic myelomonocytic leukemia (CMML), juvenile myelomonocytic leukemia (JMML), or large granular lymphocytic leukemia), lymphoma (e.g., AIDS-related lymphoma, cutaneous T-cell lymphoma, Hodgkin's lymphoma (e.g., classical Hodgkin's lymphoma or nodular lymphocyte-predominant Hodgkin's lymphoma), mycosis fungoides, non-Hodgkin's lymphoma, and / or leukemia (e.g., leukemia ... Examples of lymphomas include, but are not limited to, B-cell non-Hodgkin's lymphoma (e.g., Burkitt's lymphoma, small lymphocytic lymphoma (CLL / SLL), diffuse large B-cell lymphoma, follicular lymphoma, immunoblastic 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. As used herein, a premalignant tumor refers to tissue that is not yet malignant, but is preparing to become malignant.

[0086] In some embodiments, the individual has been previously treated with an anti-cancer therapy, e.g., one or more cancer therapies (e.g., any of the disclosed anti-cancer therapies). For example, the sample may be from an individual who has been treated with an anti-cancer therapy, including one or more of 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-neoplastic agent, a growth inhibitory agent, or a cytotoxic agent. In some embodiments, the individual has been previously treated with a chemotherapy or immuno-oncology therapy. In some aspects, a post-anti-cancer therapy sample, e.g., a specimen, is obtained, e.g., collected, for a patient who has been previously treated with an anti-cancer therapy. In some aspects, the post-anti-cancer therapy sample is a sample obtained, e.g., collected, after completion of the targeted therapy.

[0087] 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.

[0088] In some embodiments, the individual has previously undergone or is currently undergoing treatment for cancer. In some embodiments, the individual has previously undergone a chemotherapy regimen. In some embodiments, the individual has previously undergone chemotherapy for cancer.

[0089] In some embodiments, the individual is in need of a first line therapy for cancer. In some embodiments, the individual is in need of a second line therapy for cancer.

[0090] In some embodiments, the individual is a human. In some embodiments, the individual is a non-human mammal.

[0091] IV. Samples and Processing The methods of the disclosure, in certain embodiments, include 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 related to the cancer being treated or assessed. In some embodiments, the sample is derived from a solid tumor (e.g., a tumor biopsy sample). In some embodiments, the sample is derived from a liquid sample (e.g., a liquid biopsy sample). In some embodiments, the sample is derived from a blood sample.

[0092] In some embodiments, the sample is cancer of any cancer type, including, but 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, Cancer, biliary tract cancer, small intestine or adnexal cancer, salivary gland cancer, thyroid cancer, adrenal adenocarcinoma, osteosarcoma, chondrosarcoma, cancer of blood tissue, adenocarcinoma, inflammatory myofibroblastic tumor, gastrointestinal stromal tumor (GIST), colon cancer, multiple myeloma (MM), myelodysplastic syndrome (MDS), myeloproliferative disorder (MPD), acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), chronic myelogenous leukemia (CML), chronic lymphocytic leukemia (CLL), polycythemia vera, Hodgkin's lymphoma Lymphoma, Non-Hodgkin's lymphoma (NHL), Soft tissue sarcoma, Fibrosarcoma, Myxosarcoma, Liposarcoma, Osteosarcoma, Chordoma, Angiosarcoma, Endothelioma, Synovium, Mesothelioma, Ewing's tumor, Leiomyosarcoma, Rhabdomyosarcoma, Squamous cell carcinoma, Basal cell carcinoma, Adenocarcinoma, Sweat gland carcinoma, Sebaceous gland carcinoma, Papillary carcinoma, Papillary adenocarcinoma, Medullary carcinoma, Bronchogenic carcinoma, Renal cell carcinoma, Hepatocellular carcinoma, Cholangiocarcinoma, Choriocarcinoma, Seminoma, Embryonic carcinoma, Wilms' tumor, Bladder cancer, Epithelial carcinoma, Glioma, Astrocyte In some embodiments, the cancer is associated with a tumor biopsy sample from a tumor-specific tumour, a medulloblastoma, a craniopharyngioma, an ependymoma, a pinealoma, a hemangioblastoma, an acoustic neuroma, an oligodendroglioma, a meningioma, a neuroblastoma, a retinoblastoma, a diffuse large B-cell lymphoma, a mantle cell lymphoma, a hepatocellular carcinoma, a thyroid cancer, a gastric cancer, a head and neck cancer, a small cell carcinoma, an essential thrombocythemia, an agnogenic myeloid metaplasia, a hypereosinophilic syndrome, a systemic mastocytosis, a familial hypereosinophilia, a chronic eosinophilic leukemia, a neuroendocrine carcinoma, a carcinoma-like tumour, or the like. In some embodiments, the cancer is NSCLC (e.g., advanced NSCLC), a colorectal cancer, a cholangiocarcinoma, a breast cancer, a gastric cancer, a melanoma, a pancreatic cancer, a prostate cancer, an ovarian cancer, an esophageal cancer, or a cancer of unknown primary. In some embodiments, the tumor biopsy sample is associated with a metastatic urothelial carcinoma. In some embodiments, the sample is associated with a gastric adenocarcinoma. In some embodiments, the sample is associated with a 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.

[0093] In some embodiments, the sample comprises nucleic acid, such as DNA, RNA, or both. In certain embodiments, the sample comprises one or more nucleic acids from a cancer. In certain aspects, the sample further comprises one or more non-nucleic acid components from a tumor, such as cells, proteins, carbohydrates, or lipids. In certain embodiments, the sample further comprises one or more nucleic acids from a non-tumor cell or tissue.

[0094] In some embodiments, the sample comprises one or more nucleic acids, e.g., DNA, RNA, or both, from pre-malignant or malignant cells, cells from a solid tumor, a soft tissue tumor, or a metastatic lesion, cells from a hematological cancer, histologically normal cells, circulating tumor cells (CTCs), or a combination thereof. In some embodiments, the sample comprises one or more cells selected from pre-malignant or malignant cells, cells from a solid tumor, a soft tissue tumor, or a metastatic lesion, hematological cancer, histologically normal cells, circulating tumor cells (CTCs), or a combination thereof.

[0095] In some embodiments, the sample comprises RNA (e.g., mRNA), DNA, circulating tumor DNA (ctDNA), cell-free DNA, or cell-free RNA (cfRNA) from the cancer. In some embodiments, the sample comprises cell-free DNA (cfDNA). In some embodiments, the cfDNA comprises DNA from healthy tissue, e.g., non-diseased cells, or tumor tissue, e.g., tumor cells. In some embodiments, the cfDNA from tumor tissue comprises circulating tumor DNA (ctDNA). In some embodiments, the sample further comprises non-nucleic acid components, e.g., from the tumor, e.g., cells, proteins, carbohydrates, or lipids.

[0096] 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 peritoneal fluid. In certain embodiments, the sample comprises urine.

[0097] In some embodiments, the sample comprises or is derived from a blood sample, e.g., a peripheral whole blood sample. In some embodiments, the peripheral whole blood sample is collected, e.g., in two tubes, e.g., with about 8.5 ml of blood per tube. In some aspects, 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, e.g., by gentle inversion, e.g., about 8-10 times. In some embodiments, the inversion is performed, e.g., by a full, e.g., complete, 180° rotation of the wrist. In some embodiments, the blood sample is shipped the same day as collection, e.g., at ambient temperature, e.g., 43-99° F. or 6-37° C. In some embodiments, the blood sample is not frozen or refrigerated. In some embodiments, the collected blood sample is maintained, e.g., stored, at 43-99° F. or 6-37° C.

[0098] In some embodiments of the methods described herein, the method further comprises isolating nucleic acid from the sample described herein. In some embodiments of the methods described herein, the method comprises isolating nucleic acid from the sample to provide an isolated nucleic acid sample. In one embodiment, the method comprises isolating nucleic acid from a control to provide an isolated control nucleic acid sample. In one embodiment, the method further comprises rejecting samples that do not contain detectable nucleic acid.

[0099] In some embodiments of the methods described herein, the method further comprises obtaining a value of nucleic acid yield in the sample and comparing the obtained value to a reference standard, e.g., if the obtained value is less than the reference standard, amplifying the nucleic acid prior to library construction. In one embodiment, the method further comprises obtaining a value of size of nucleic acid fragments in the sample and comparing the obtained value to a reference standard, e.g., a size of at least 300, 600 or 900 bps, e.g., an average size. The parameters described herein can be adjusted or selected accordingly.

[0100] In some embodiments, nucleic acids are isolated when they are partially purified or substantially purified, hi some embodiments, nucleic acids are isolated when they are purified from other cellular components (e.g., proteins, carbohydrates, or lipids) by standard techniques.

[0101] Protocols for DNA isolation from samples are known in the art, for example, as provided in Example 1 of International Patent Application Publication No. WO2012 / 092426. Additional methods for isolating nucleic acids (e.g., DNA) from formaldehyde-fixed or paraformaldehyde-fixed, paraffin-embedded (FFPE) tissues are described, for example, in Cronin M. et al., (2004) Am J Pathol. 164(1):35-42; Masuda, et al., (1999) Nucleic Acids Res. 27(22):4436-4443; Specht, et al., (2001) Am J Pathol. 158(2):419-429; Ambion RecoverAll™ Total Nucleic Acid Isolation Protocol (Ambion, Cat. No. AM1975, September 2008); Maxwell® 16 FFPE Plus LEV DNA Purification Kit Technical Manual (Promega Literature #TM349, February 2011); EZNA® FFPE DNA Kit Handbook (OMEGA bio-tek, Norcross, GA, product numbers D3399-00, D3399-01, and D3399-02, June 2009), as well as the QIAamp® DNA FFPE Tissue Handbook (Qiagen, Cat. No. 37625, October 2007). The RecoverAll™ Total Nucleic Acid Isolation Kit uses xylene at high temperature to solubilize paraffin-embedded samples and apply to glass fiber filters to capture nucleic acids. The Maxwell® 16 FFPE Plus LEV DNA Purification Kit is used with the Maxwell® 16 Instrument to purify genomic DNA from 1 to 10 μm sections of FFPE tissue. DNA is purified using silica-clad paramagnetic particles (PMPs) and eluted in low elution volumes.The EZNA® FFPE DNA Kit uses spin columns and a buffer system for the isolation of genomic DNA. The QIAamp® DNA FFPE Tissue Kit uses QIAamp® DNA Micro technology for the purification of genomic and mitochondrial DNA. Protocols for DNA isolation from blood are disclosed, for example, in the Maxwell® 16 LEV Blood DNA Kit and Maxwell 16 Buccal Swab LEV DNA Purification Kit Technical Manual (Promega Literature #TM333, January 1, 2011).

[0102] Protocols for RNA isolation are disclosed, for example, in the Maxwell® 16 Total RNA Purification Kit Technical Bulletin (Promega Literature #TB351, August 2009).

[0103] The isolated nucleic acid (e.g., genomic DNA) can be fragmented or sheared by implementing routine techniques. For example, genomic DNA can be fragmented by physical shearing, enzymatic cleavage, chemical cleavage, and other methods well known to those skilled in the art. The nucleic acid library can contain all or substantially all of the complexity of a genome. The term "substantially all" in this context actually refers to the possibility that there may be some undesired loss of genomic complexity during the initial steps of the procedure. The methods described herein are also useful when the nucleic acid library is a portion of a genome, for example, when 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.

[0104] In certain embodiments, the method further comprises isolating nucleic acid from the sample to provide a library (e.g., a nucleic acid library described herein). In certain embodiments, the sample comprises a whole genome, a subgenomic fragment, or both. The isolated nucleic acid can be used to prepare a nucleic acid library. Protocols for isolating and preparing libraries from whole genomes or subgenomic fragments are known in the art (e.g., Illumina's genomic DNA sample preparation kit). In certain embodiments, genomic or subgenomic DNA fragments are isolated from a sample of a subject (e.g., a sample described herein).

[0105] In yet other embodiments, the nucleic acid used to generate the library comprises RNA or cDNA derived from RNA. In some aspects, the RNA comprises total cellular RNA. In other embodiments, certain abundant RNA sequences (e.g., ribosomal RNA) are depleted. In some embodiments, poly(A)-tailed mRNA fragments are enriched in total RNA preparations. In some embodiments, cDNA is produced by random primed cDNA synthesis. In other embodiments, cDNA synthesis is initiated at the poly(A) tail of mature mRNA by priming with oligo(dT)-containing oligonucleotides. Methods for depletion, poly(A) enrichment, and cDNA synthesis are well known to those of skill in the art.

[0106] In other embodiments, the nucleic acids are fragmented or sheared by physical or enzymatic methods, optionally or ligated to synthetic adaptors, size selected (e.g., by preparative gel electrophoresis), and amplified (e.g., by PCR). Alternative methods for DNA shearing 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., degraded FFPE samples). Alternative DNA shearing methods may also be used to avoid the ligation step during library preparation.

[0107] In other embodiments, the isolated DNA (e.g., genomic DNA) is fragmented or sheared. In some embodiments, the library contains less than 50% genomic DNA, e.g., a fraction of genomic DNA that is a reduced representation or defined portion of the genome that has been fragmented by other means. In other embodiments, the library contains all or substantially all genomic DNA.

[0108] In other embodiments, fragmented and adaptor-linked nucleic acids are used without explicit size selection or amplification prior to hybrid selection. In some embodiments, the nucleic acids are amplified by specific or non-specific nucleic acid amplification methods well known to those of skill in the art. In some embodiments, the nucleic acids are amplified by whole genome amplification methods such as, for example, random primed strand displacement amplification.

[0109] The methods described herein can be performed using small amounts of nucleic acid, for example, when the amount of source DNA or RNA is limiting (e.g., even after whole genome amplification). In one embodiment, the nucleic acid comprises about 5 μg, 4 μg, 3 μg, 2 μg, 1 μg, 0.8 μg, 0.7 μg, 0.6 μg, 0.5 μg or 400 ng, 300 ng, 200 ng, 100 ng, 50 ng, 10 ng, 5 ng, 1 ng or less of the nucleic acid sample. For example, one can typically start with 50-100 ng of genomic DNA. However, one can start with smaller amounts if one amplifies the genomic DNA (e.g., using PCR) prior to the hybridization step, e.g., solution hybridization. Thus, it is possible, but not necessary, to amplify the genomic DNA prior to hybridization, e.g., solution hybridization.

[0110] In some embodiments, the sequencing comprises providing a plurality of nucleic acid molecules obtained from the sample, amplifying a nucleic acid molecule from the plurality of nucleic acid molecules, capturing a nucleic acid molecule from the amplified nucleic acid molecules, and sequencing the captured nucleic acid molecule with a sequencer to obtain a plurality of sequence reads corresponding to one or more genomic loci within a genomic interval in the sample. In some embodiments, the plurality of nucleic acid molecules comprises a mixture of tumor and non-tumor nucleic acid molecules.

[0111] In some embodiments, amplification of nucleic acid molecules is performed by polymerase chain reaction (PCR) amplification techniques, non-PCR amplification techniques, or isothermal amplification techniques.

[0112] In some embodiments, the sequencing further comprises ligating one or more adaptors to one or more nucleic acids from the plurality of nucleic acid molecules, in some embodiments, the adaptors comprise one or more of an amplification primer sequence, a flow cell adaptor hybridization sequence, a unique molecular identifier sequence, a substrate adaptor sequence, or a sample index sequence.

[0113] In some embodiments, nucleic acid molecules from the library are isolated, for example using solution hybridization, thereby providing a library catch. The library catch or a subgroup thereof can be sequenced. Thus, the methods described herein can further include analyzing the library catch. In some embodiments, the library catch is analyzed by a sequencing method, for example a next generation sequencing method described herein. In some embodiments, the method includes isolating the library catch by solution hybridization and subjecting the library catch to nucleic acid sequencing. In certain embodiments, the library catch is resequenced.

[0114] In some embodiments, the captured nucleic acid molecule is captured from the amplified nucleic acid molecule by hybridization to one or more bait molecules. In some embodiments, the one or more bait molecules comprise one or more nucleic acid molecules, each nucleic acid molecule 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 molecule. In some embodiments, the capture molecule is biotin.

[0115] Any sequencing method known in the art can be used. For example, the sequencing of the nucleic acid 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. 2012 / 092426. In some embodiments, sequencing is performed 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.

[0116] In some embodiments, sequencing involves detecting alterations present within the genome, whole exome, or transcriptome of an individual. In some embodiments, sequencing involves DNA and / or RNA sequencing, e.g., targeted DNA and / or RNA sequencing. In some embodiments, sequencing involves detecting alterations (e.g., increases or decreases) in the levels of genes or gene products, e.g., alterations in the expression of genes or gene products described herein.

[0117] Sequencing optionally includes enriching the sample for target RNA. In other embodiments, sequencing includes depleting certain high abundance RNAs, such as ribosomal RNA or globin RNA. RNA sequencing methods can be used alone or in combination with DNA sequencing methods described herein. In one embodiment, sequencing includes a DNA sequencing step and an RNA sequencing step. The method can be performed in any order. For example, the method can include confirming the expression of the alterations described herein by RNA sequencing, e.g., confirming the expression of the mutations or fusions detected by the DNA sequencing method of the present invention. In other embodiments, sequencing includes performing an RNA sequencing step followed by a DNA sequencing step.

[0118] In some embodiments, the sample is associated with a cancer that has not been previously treated with an anti-cancer therapy. In some embodiments, the sample is associated with a cancer that has not been previously 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.

[0119] 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.

[0120] V. Methods for Determining Tumor Mutational Burden Tumor mutation burden (TMB) is generally the number of somatic mutations per megabase of a genomic region. TMB score (e.g., can be expressed as mutations per megabase, i.e., mutations / Mb) can inform treatment decisions in some embodiments, including whether to administer immune checkpoint inhibitor therapy to a patient if the TMB score is at least a threshold TMB score, or administer a chemotherapy regimen if the TMB score is less than a threshold TMB score. TMB score can be determined using a variety of techniques, including next-generation sequencing (NGS).

[0121] In some embodiments, the disclosed methods include determining a tumor mutational burden (TMB) score in a sample, such as a tumor sample. In some embodiments, the TMB score is a blood TMB (bTMB) score. In some embodiments, the TMB score is a tissue TMB score (tTMB score).

[0122] In some embodiments, the TMB score is determined by sequencing. In some embodiments, the TMB score is determined by sequencing using high-throughput sequencing technology, 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 profiling (CGP). In some embodiments, the sequencing includes sequencing a panel of cancer genes. In some embodiments, the TMB score reflects the number of non-synonymous mutations, such as missense or nonsense mutations. In some embodiments, the TMB score is normalized to the matched tumor biopsy sample sequence with germline sequences to exclude inherited germline mutations.

[0123] A "threshold TMB score" as used herein refers to a predetermined TMB score that is compared to a measured TMB score (i.e., a TMB score determined in a sample from an individual with cancer). Comparison of the determined TMB score to the threshold TMB score is used in certain embodiments to inform treatment decisions or identify treatment options for an individual. In some embodiments, the threshold TMB score is at least 8 mutations / Mb, e.g., at least 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 26 mutations / Mb, about 27 mutations / Mb, about 28 mutations / Mb, about 30 mutations / Mb, about 32 mutations / Mb, about 34 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, about 50 mutations / Mb, about 51 mutations / Mb, about 52 mutations / Mb, about 53 mutations / 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 at least about 8 mutations / Mb, e.g., at least 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 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, about 50 mutations / Mb, about 51 mutations / Mb, about 52 mutations / Mb, about 53 mutations / Mb, about 54 mutations / Mb, about 55 mutations / Mb, about 56 mutations / Mb, about 57 In some embodiments, the threshold TMB score is about 10 mutations / Mb. In some embodiments, the threshold TMB score is about 10 mutations / Mb. In some embodiments, the threshold TMB score is about 10 mutations / Mb. In some embodiments, the threshold TMB score is a "high tumor mutation burden score", e.g., a TMB score of at least about 10 mutations / Mb or more, e.g., 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 or more.

[0124] 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). The tTMB score can be measured, for example, based on the entire genome or exome, or based on a subset of the genome or exome (e.g., a set of predefined genes). In some embodiments, the tTMB score can be measured based on intergenic sequences. In some embodiments, the tTMB score measured based on a subset of the genome or exome can be extrapolated to determine the tTMB of the entire genome or exome. In certain embodiments, the set of predefined genes does not include the entire genome or exome. In other embodiments, the set of subgenomic intervals does not include the entire genome or exome. In some embodiments, the set of predefined genes includes multiple genes that, in mutant form, are associated with an effect on cell division, proliferation, or survival, or are associated with cancer. In some embodiments, the set of predefined genes includes 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 400 or more, about 450 or more, or about 500 or more genes. In some embodiments, the set of predefined genes covers about 1 Mb (e.g., about 1.1 Mb, e.g., about 1.125 Mb). In some embodiments, the tTMB score is 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 insertion deletion mutations counted. In some embodiments, the tTMB score refers to the number of accumulated somatic mutations in the tumor.

[0125] As used herein, the terms "blood tumor mutational 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). The bTMB score can be measured, for example, based on the entire genome or exome, or based on a subset of the genome or exome (e.g., a set of predefined genes). In certain embodiments, the bTMB score may be measured based on intergenic sequences. In some embodiments, a bTMB score measured based on a subset of the genome or exome may be extrapolated to determine a bTMB score for the entire genome or exome. In certain embodiments, the set of predefined genes does not include the entire genome or exome. In other embodiments, the set of subgenomic intervals does not include the entire genome or exome. In some embodiments, the set of predefined genes includes multiple genes that, in mutant form, are associated with an effect on cell division, proliferation, or survival, or are associated with cancer. In some embodiments, the set of predefined genes includes 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 set of predefined genes covers about 1 Mb (e.g., about 1.1 Mb, e.g., about 1.125 Mb). In some embodiments, the bTMB score is 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 insertion deletion mutations counted.In some embodiments, the bTMB score refers to the number of accumulated somatic mutations in a tumor.

[0126] In some embodiments, tumor mutational burden (e.g., bTMB or solid tumor TMB) is measured using any suitable method known in the art. For example, tumor mutational burden can be measured using whole exome sequencing (WES), next generation sequencing, whole exome sequencing, whole genome sequencing, gene targeted sequencing, or sequencing of a panel of genes (e.g., a panel including cancer-related genes). 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.

[0127] In some embodiments, the tumor mutational burden is measured according to the method provided in WO2017 / 151524(A1), which is incorporated herein by reference in its entirety. In some embodiments, the 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, the tumor mutational burden is measured according to the method described in Chalmers et al., "Analysis of 100,00 human cancer genomes reveals the landscape of tumor mutational burden," Genome Med. 2017;9(1):34). In some embodiments, the 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 Quintanilha, J., et al., “Comparative Effectiveness of Immune 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.

[0128] In some embodiments, tumor mutational burden is assessed based on the number of non-driver somatic coding mutations / megabase (mut / Mb) of the sequenced genome.

[0129] In some embodiments, the tumor mutation burden is measured in the sample by next generation sequencing. In some embodiments, the tumor mutation burden is measured in the sample by whole exome sequencing. In some embodiments, the tumor mutation burden is measured in the sample using whole genome sequencing. In some embodiments, the tumor mutation burden is measured in the sample by gene targeted sequencing. In some embodiments, the tumor mutation burden is measured for about 0.83 Mb to about 1.3 Mb of sequenced DNA. In some embodiments, the tumor mutation burden is measured for about 0.8 Mb, about 0.81 Mb, about 0.82 Mb, about 0.83 Mb, about 0.84 Mb, about 0.85 Mb, about 0.86 Mb, about 0.87 Mb, about 0.88 Mb, about 0.89 Mb, about 0.9 Mb, about 0.91 Mb, about 0.92 Mb, about 0.93 Mb, about 0.94 Mb, about 0. In some embodiments, the tumor mutation burden is measured for about 0.95 Mb, about 0.96 Mb, about 0.97 Mb, about 0.98 Mb, about 0.99 Mb, about 1 Mb, about 1.01 Mb, about 1.02 Mb, about 1.03 Mb, about 1.04 Mb, about 1.05 Mb, about 1.06 Mb, about 1.07 Mb, about 1.08 Mb, about 1.09 Mb, about 1.1 Mb, about 1.2 Mb, or about 1.3 Mb of sequenced DNA. In some embodiments, the tumor mutation burden is measured for about 0.8 Mb of sequenced DNA. In some embodiments, the tumor mutation burden is evaluated for about 0.83 Mb to about 1.14 Mb of sequenced DNA. In some embodiments, the tumor mutation burden is measured for up to about 1.24 Mb of sequenced DNA. In some embodiments, the tumor mutation burden is measured for up to about 1.1 Mb of sequenced DNA. In some embodiments, the tumor mutational burden is assessed for about 0.79 Mb of sequenced DNA.

[0130] 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 burden, for example, at least about 10 mut / 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 from about 10 mut / Mb to about 15 mut / Mb, from about 15 mut / Mb to about 20 mut / Mb, from about 20 mut / Mb to about 25 mut / Mb, from about 25 mut / Mb to about 30 mut / Mb, from about 30 mut / Mb to about 35 mut / Mb, from about 35 mut / Mb to about 40 mut / Mb, from about 40 mut / Mb to about 45 mut / Mb, from about 45 mut / Mb to about 50 mut / Mb, from about 50 mut / Mb to about 55 mut / Mb, about 55 mut / Mb to about 60 mut / Mb, about 60 mut / Mb to about 65 mut / Mb, about 65 mut / Mb to about 70 mut / Mb, about 70 mut / Mb to about 75 mut / Mb, about 75 mut / Mb to about 80 mut / Mb, about 80 mut / Mb to about 85 mut / Mb, about 85 mut / Mb to about 90 mut / Mb, about 90 mut / Mb to about 95 mut / Mb, or about 95 mut / Mb to about 100 mut / Mb.In some embodiments, the TMB score is from about 100 mut / Mb to about 110 mut / Mb, from about 110 mut / Mb to about 120 mut / Mb, from about 120 mut / Mb to about 130 mut / Mb, from about 130 mut / Mb to about 140 mut / Mb, from about 140 mut / Mb to about 150 mut / Mb, from about 150 mut / Mb to about 160 mut / Mb, from about 160 mut / Mb to about 170 mut / Mb, ut / Mb, approx. 170mut / Mb ~ approx. 180mut / Mb, approx. 180mut / Mb ~ approx. 190mut / Mb, approx. 190mut / Mb ~ approx. 200mut / Mb, approx. 210mut / Mb ~ approx. 220mut / Mb, approx. 220mut / Mb ~ approx. 230mut / Mb, approx. 230mut / Mb ~ approx. 240mut / Mb, approx. 240mut / Mb ~ approx. 250mut / Mb, approx. 250mut / M b ~ approx. 260mut / Mb, approx. 260mut / Mb ~ approx. 270mut / Mb, approx. 270mut / Mb ~ approx. 280mut / Mb, approx. 280mut / Mb ~ approx. 290mut / Mb, approx. 290m ut / Mb ~ approx. 300mut / Mb, approx. 300mut / Mb ~ approx. 310mut / Mb, approx. 310mut / Mb ~ approx. 320mut / Mb, approx. 320mut / Mb ~ approx. 330mut / Mb, approx. 3 30 mut / Mb to about 340 mut / Mb, about 340 mut / Mb to about 350 mut / Mb, about 350 mut / Mb to about 360 mut / Mb, about 360 mut / Mb to about 370 mut / Mb, about 370 mut / Mb to about 380 mut / Mb, about 380 mut / Mb to about 390 mut / Mb, about 390 mut / Mb to about 400 mut / Mb, or more than 400 mut / Mb. In some embodiments, the TMB score is at least about 100 mut / Mb, at least about 110 mut / Mb, at least about 120 mut / Mb, at least about 130 mut / Mb, at least about 140 mut / Mb, at least about 150 mut / Mb, or more. In some embodiments, the TMB score is determined based on about 0.8 Mb to about 1.1 Mb.

[0131] VI. Methods for Determining Microsatellite Instability Some aspects of the present disclosure provide further analysis of microsatellite instability (MSI) status. In some embodiments, it has been found that assessment of microsatellite instability can inform treatment decisions, including 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 (MSI-L or MSS) in a sample obtained from an individual with cancer. Microsatellites are sequences of 1-6 nucleotides that are typically repeated 5-50 times in the genome. Microsatellite instability can be classified into categories of degree, such as high (MSI-H), low (MSI-L), or stable (MSS). MSS refers to a microsatellite status that does not show somatic changes in the number of repeated nucleotide sequences. MSI-L refers to a microsatellite status that has an intermediate phenotype between MSS and MSI-H.

[0132] Microsatellite instability may be assessed using any suitable method known in the art. For example, microsatellite instability may be measured using next-generation sequencing (see, e.g., Hempelmann et al., J Immunother 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., Malaysia J Pathol (2019) 41(2):91-100), or single molecule molecular inversion probes (smMIPs, 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 intron homopolymer repeat loci for length variability. In some embodiments, microsatellite instability is assessed based on DNA sequencing (e.g., next generation sequencing) of about 114 intron homopolymer repeat loci for length variability. In some embodiments, microsatellite instability status (e.g., high frequency microsatellite instability) is defined as described in Trabucco et al., J Mol Diagn. 2019 Nov; 21 (6): 1053-1066.

[0133] VII. Immune Checkpoint Inhibitors In certain embodiments, the methods described herein relate to predicting the efficacy of immune checkpoint inhibitor (ICPI) therapy and / or administering ICPI to an individual with cancer. In some embodiments, the efficacy of ICPI therapy is predicted as a first-line treatment. 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 specified. In some embodiments, ICPI therapy consists of a single active agent, such as a single immune checkpoint inhibitor. In some embodiments, ICPI therapy is administered as a second-line therapy for cancer. In some embodiments, ICPI therapy is administered or is indicated to be administered with another treatment, such as a non-ICPI therapy. In some embodiments, ICPI therapy includes a combination ICPI therapy that includes two or more ICPIs, i.e., two or more different active agents that target checkpoints. In some embodiments, the two or more different active agents each target a different immune checkpoint protein.

[0134] As is known in the art, checkpoint inhibitors target at least one immune checkpoint protein to alter the regulation of the immune response. 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, MHC class I, MHC class II, GALS, adenosine, TGFR, CSF1R, MICA / B, arginase, CD160, gp49B, PIR-B, KIR family receptors, TIM-1, TIM-3, TIM-4, LAG-3, BTLA, SIRP alpha (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 regulating immune checkpoints include, but are not limited to, PD-1 (CD279), PD-L1 (B7-H1, CD274), PD-L2 (B7-CD, CD273), CTLA-4 (CD152), HVEM, BTLA (CD272), killer cell immunoglobulin-like receptors (KIR), LAG-3 (CD223), TIM-3 (HAVCR2), CEACAM, CEACAM-1, CEACAM-3, CEACAM-5, GAL9, VISTA (PD-1H), TIGIT, LAIR1, CD160, 2B4, TGFR beta, A2AR, GITR (CD357), CD80 (B7-1), CD86 (B7 -2), CD276 (B7-H3), VTCNI (B7-H4), MHC class I, MHC class II, GALS, adenosine, 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., to enhance T cell activation and / or anti-cancer immune responses. In other embodiments, a checkpoint inhibitor enhances the activity of a checkpoint protein that positively regulates immune cell function, e.g., to enhance T cell activation and / or anti-cancer immune responses. In some embodiments, a checkpoint inhibitor is an antibody. Examples of checkpoint inhibitors include, but are not limited to, a PD-1 axis binding antagonist, a PD-L1 axis binding antagonist (e.g., an anti-PD-L1 antibody, e.g., atezolizumab (MPDL3280A)), an antagonist against a co-inhibitory molecule (e.g., a CTLA4 antagonist (e.g., an anti-CTLA4 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, immune checkpoint inhibitors include drugs such as small molecules, recombinant forms of ligands or receptors, or antibodies (e.g., human antibodies) (see, e.g., International Patent Publication No. WO2015 / 016718; Pardoll, Nat Rev Cancer, 12(4):252-64, 2012). In some embodiments, known inhibitors of immune checkpoint proteins or analogs thereof can be used, in particular chimeric, humanized, or human forms of antibodies.

[0135] In some embodiments according to any of the embodiments described herein, the immune checkpoint inhibitor comprises a PD-1 antagonist / inhibitor or a PD-L1 antagonist / inhibitor.

[0136] 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 referred to in the art as "programmed cell death 1", "PDCD1", "CD279", and "SLEB2". An exemplary human PD-1 is set forth in UniProtKB / Swiss-Prot Accession No. Q15116. PD-L1 (programmed death ligand 1) is also referred to in the art as "programmed cell death 1 ligand 1", "PDCD1 LG1", "CD274", "B7-H", and "PDL1". An exemplary human PD-L1 is set forth in UniProtKB / Swiss-Prot Accession No. Q9NZQ7.1. PD-L2 (Programmed Death Ligand 2) is also referred to in the art as "Programmed Cell Death 1 Ligand 2", "PDCD1 LG2", "CD273", "B7-DC", "Btdc", and "PDL2". An exemplary human PD-L2 is set forth in UniProtKB / Swiss-Prot Accession No. Q9BQ51. In some instances, PD-1, PD-L1, and PD-L2 are human PD-1, PD-L1, and PD-L2.

[0137] In some cases, the PD-1 binding antagonist / inhibitor is a molecule that inhibits the binding of PD-1 to its ligand binding partner. In certain embodiments, the PD-1 ligand binding partner is PD-L1 and / or PD-L2. In another example, the PD-L1 binding antagonist / inhibitor is a molecule that inhibits the binding of PD-L1 to its binding ligand. In certain embodiments, the PD-L1 binding partner is PD-1 and / or B7-1. In another example, the PD-L2 binding antagonist is a molecule that inhibits the binding of PD-L2 to its ligand binding partner. In certain embodiments, the PD-L2 binding ligand partner is PD-1. The antagonist may be an antibody, an antigen-binding fragment thereof, an immunoadhesin, a fusion protein, or an 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.

[0138] In some cases, the PD-1 binding antagonist is an anti-PD-1 antibody (e.g., a human antibody, a humanized antibody, or a chimeric antibody), such as those described below. In some examples, the anti-PD-1 antibody is MDX-1 106 (nivolumab), MK-3475 (pembrolizumab, Keytruda®), cemiplimab, dostallimab, MEDI-0680 (AMP-514), PDR001, REGN2810, MGA-012, JNJ-63723283, BI 754091, or BGB-108. In other examples, the PD-1 binding antagonist is an immunoadhesin (e.g., an immunoadhesin that includes 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. Other examples of anti-PD-1 antibodies include MEDI-0680 (AMP-514; AstraZeneca), PDR001 (CAS Registry Number 1859072-53-9; Novartis), REGN2810 (LIBTAYO® or cemiplimab-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), ENUM244C8 (Enumeral Biomedical In some embodiments, the PD-1 axis binding antagonist is tislelizumab (BGB-A317), BGB-108, STI-A1110, AM0001, BI754091, sintilimab (IBI308), cetrelimab (JNJ-63723283), toripalimab (JS-001), camrelizumab (SHR-1210, INCSHR-1210, HR-301210), MEDI-0680 (AMP-514), MGA-012 (INCMGA0012), nivolumab (BMS-9365 58, MDX1106, ONO-4538), spartalizumab (PDR00l), pembrolizumab (MK-3475, SCH900475, Keytruda®), PF-06801591, cemiplimab (REGN-2810, REGEN2810), dostallimab (TSR-042, ANB011), FITC-YT-16 (PD-1 binding peptide), APL-501 or CBT-501 or genolimuzumab (GB-226), AB-122, AK105, AMG404, BCD-100, F520, HLX10, HX008, JTX-4014, LZM009, Sym021, PSB205, AMP-224 (fusion protein targeting PD-1 (protein), CX-188 (PD-1 probody), 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 EISCOI11-003, IKT-202, MCLA-134, MT-17000, PEGMP-7, PRS-332, RXI-762, STI-1110, VXM-10, XmA b-23104, AK-112, HLX-20, SSI-361, AT-16201, SNA-01, AB122, PD1-PIK, PF-06936308, RG-7769, CAB PD-1 Abs, 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.

[0139] 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. In some embodiments, the PD-L1 binding antagonist is a small molecule that inhibits PD-L1 and VISTA or PD-L1 and TIM3. 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 is capable of binding to human PD-L1, e.g., human PD-L1 as set forth in UniProtKB / Swiss-Prot Accession No. 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.

[0140] In some cases, the PD-L1 binding antagonist is an anti-PD-L1 antibody, such as those described below. In some cases, the anti-PD-L1 antibody can inhibit the binding between PD-L1 and PD-1 and / or the binding 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 a Fab, Fab'-SH, Fv, scFv, or (Fab')2 fragment. 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 (atezolizumab), MDX-1 105, MEDI4736 (durvalumab), or MSB0010718C (avelumab).In some embodiments, the PD-L1 axis binding antagonist is atezolizumab, avelumab, durvalumab (Imfinzi), BGB-A333, SHR-1316 (HTI-1088), CK-301, BMS-936559, embafolimab (KN035, ASC22), CS1001, MDX-1105 (BMS-936559), LY330 0054, STI-A1014, FAZ053, CX-072, INCB086550, GNS-1480, CA-170, CK-301, M-7824, HTI-1088(H TI-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, AP L-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.

[0141] In some embodiments, the checkpoint inhibitor is an antagonist / inhibitor of CTLA4. In some embodiments, the checkpoint inhibitor is a small molecule antagonist of CTLA4. In some embodiments, the checkpoint inhibitor is an anti-CTLA4 antibody. CTLA4 is part of the CD28-B7 immunoglobulin superfamily of immune checkpoint molecules and acts to negatively regulate T cell activation, particularly CD28-dependent T cell responses. CTLA4 competes for binding to ligands common to CD28, such as CD80 (B7-1) and CD86 (B7-2), and binds these ligands with higher affinity than CD28. Blocking CTLA4 activity (e.g., using an anti-CTLA4 antibody) is believed to enhance CD28-mediated costimulation (resulting in increased T cell activation / priming), affect T cell development, and / or deplete Tregs, e.g., intratumoral Tregs. In some embodiments, the CTLA4 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 embodiments, the CTLA-4 inhibitor comprises ipilimumab (IBI310, BMS-734016, MDX010, MDX-CTLA4, MEDI4736), tremelimumab (CP-675, CP-675, 206), APL-509, AGEN1884, CS1002, AGEN1181, abatacept (Orencia, BMS-188667, RG2077), BCD-145, ONC-392, ADU-1604, REGN4659, ADG116, KN044, KN046, or a derivative thereof.

[0142] In some embodiments, the anti-PD-1 antibody or antibody fragment is MDX-1106 (nivolumab), MK-3475 (pembrolizumab, Keytruda®), cemiplimab, dostallimab, 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, ENUM244C8, or ENUM388D4. 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 (atezolizumab), MDX-1105, MEDI4736 (durvalumab), MSB0010718C (avelumab), LY3300054, STI-A1014, KN035, FAZ053, or CX-072.

[0143] In some embodiments, the immune checkpoint inhibitor comprises a LAG-3 inhibitor (e.g., an antibody, an antibody conjugate, or an antigen-binding fragment thereof). In some embodiments, the LAG-3 inhibitor comprises a small molecule, a nucleic acid, a polypeptide (e.g., an antibody), a carbohydrate, a lipid, a metal, or a toxin. 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, an antibody conjugate, or an antigen-binding fragment thereof. In some embodiments, the LAG-3 inhibitor comprises eftiragimob alfa (IMP321, IMP-321, EDDP-202, EOC-202), leratolimab (BMS-986016), GSK2831781 (IMP-731), LAG525 (IMP701), 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 antibody, Arcus Biosciences LAG-3 antibody, Sym022, a derivative thereof, or an antibody competing with any of the foregoing.

[0144] In some embodiments, the immune checkpoint inhibitor is monovalent and / or monospecific, hi some embodiments, the immune checkpoint inhibitor is multivalent and / or multispecific.

[0145] In some embodiments, immune checkpoint inhibitors may be administered in combination with immunomodulatory molecules or cytokines. An immunomodulatory profile is necessary to elicit an efficient immune response and balance the immunity of a subject. 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 TNFβ), erythropoietin (EPO), FLT-3 ligand, gIp10, TCA-3, MCP-1, MIF, MIP-1α, MIP-1β, 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., a 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-2 Groα, Gro-β, Nap-2, Ena-78, Ip-10, MIG, I-Tac, SDF-1, or BCA-1 (Blc), as well as functional fragments thereof. In some embodiments, an immunomodulatory molecule is included in any of the treatments provided herein.

[0146] In some embodiments, the immune checkpoint inhibitor is a first-line immune checkpoint inhibitor (e.g., a first-line therapy for cancer). In some embodiments, the immune checkpoint inhibitor is a second-line immune checkpoint inhibitor (e.g., a second-line therapy for cancer). In some embodiments, the immune checkpoint inhibitor is administered in combination with one or more additional anti-cancer therapies or treatments.

[0147] VIII.Chemotherapy The methods described herein, in certain embodiments, relate to predicting the efficacy of a chemotherapy regimen and / or administering a chemotherapy regimen to an individual with cancer. For example, in some embodiments, if the TMB score of a tumor is determined to be less than a threshold level, such as less than 10 mut / megabase or less than 20 mut / megabase, the tumor is not designated as a suitable candidate for ICPI therapy, but is instead identified for therapy with a chemotherapy regimen.

[0148] In some embodiments, the methods provided herein include administering chemotherapy to the individual. Exemplary chemotherapeutic agents include alkylating agents (e.g., thiotepa and cyclophosphamide), alkylsulfonates (e.g., busulfan, improsulfan, piposulfan), aziridines (e.g., benzodopa, carboquone, meturedopa, and uredopa), ethylenimines and methylameramines (including altretamine, triethylenemelamine, triethylenephosphoramide, triethylenethiophosphoramide, and trimethylolmelamine), acetogenins (particularly bullatacin and bullatasinone), camptothecin, cyclosulfamide ... Tothecins (including the synthetic analogue topotecan), bryostatins, kallistatins, CC-1065 (including the synthetic analogues adozelesin, carzelesin, and bizelesin), cryptophycins (particularly cryptophycin 1 and cryptophycin 8), dolastatins, duocarmycins (including the synthetic analogues KW-2189 and CB1-TM1), erytherobin, pancratistatins, sarcodictins, spongiostatins, nitrogen mustards (e.g., chlorambucil, chromafazine, chlorophosphamide, estradiol ... ramustine, ifosfamide, mechlorethamine, mechlorethamine oxide hydrochloride, melphalan, nobembitine, phenesterine, prednimustine, trofosfamide, and uracil mustard), nitrosoureas (carmustine, chlorozotocin, fotemustine, lomustine, nimustine, and ranimustine), antibiotics (e.g., enediyne antibiotics such as calicheamicins, especially calicheamicin gamma ll and calicheamicin omega ll), dynemicins (including, for example, dynemicin A), bisphosphatase inhibitors (e.g., dynemicin A), bisphosphatase inhibitors (e.g., bisphosphatase inhibitors ... phonates (e.g., clodronate), esperamicin, and neocarzinostatin chromophores and related chromoprotein enediyne antibiotic chromophores, aclacinomycin, actinomycin, autramycin, azaserine, bleomycin, cactinomycin, carabicin, carminomycin, carzinophilin, chromomycin, dactinomycin, daunorubicin, detorubicin, 6-diazo-5-oxo-L-norleucine, doxorubicin (morpholinodoxorubicin, cyanomorpholinodoxorubicin,2-pyrrolino-doxorubicin and deoxydoxorubicin), epirubicin, esorubicin, idarubicin, marcelomycin, mitomycins (e.g., mitomycin C), mycophenolic acid, nogalamycin, olivomycin, peplomycin, potfilomycin, puromycin, keramycin, rodorubicin, streptonigrin, streptozocin, tubercidin, ubenimex, zinostatin, and zorubicin), antimetabolites (e.g., methotrexate and 5-fluorouracil (5-FU)), folic acid analogs (e.g., denopterin, pteropterin, trimetrexate), purine analogs (e.g., fludarabine, 6-mercaptopurine, thiamiprine, thioguanine), pyrimidine analogs (e.g., ancitabine, azacitidine, 6-azauridine, carmofur, cytarabine, dideoxyuridine, doxifluridine, enocitabine, and floxuridine), androgens (e.g., calsterone, dromostanolone propionate, epithiostanol, mepitiostane, and testolactone), antiadrenal agents (e.g., mitotane and trilostane). , folic acid supplements (e.g., folic acid), aceglatone, aldophosphamide glycosides, aminolevulinic acid, eniluracil, amsacrine, bestravcil, bisantrene, edatraxate, defoamin, demecolcine, diazicon, elformitin, elliptinium acetate, epothilone, etoglucide, gallium nitrate, hydroxyurea, lentinan, lonidainin, maytansinoids (e.g., maytansine and ansamitocin), mitoguazone, mitoxantrone, mopidamol, nitraelin, pentostatin, phenameth, pirarubicin Syn, losoxantrone, podophyllic acid, 2-ethylhydrazide, procarbazine, PSK polysaccharide complex, razoxane, rhizoxin, schizophyllan, spirogermanium, tenuazonic acid, triazicon, 2,2',2"-trichlorotriethylamine, trichothecenes (especially T-2 toxin, veracrine A, roridin A, and anguidin), urethane, vindesine, dacarbazine, mannomustine, mitobronitol, mitolactol, pipobroman, gacytosine, arabinoside ("Ara-C"), cyclophosphamide, taxoids (e.g.,paclitaxel and docetaxel gemcitabine), 6-thioguanine, mercaptopurine, platinum coordination complexes (e.g., cisplatin, oxaliplatin, and carboplatin), vinblastine, platinum, etoposide (VP-16), ifosfamide, mitoxantrone, vincristine, vinorelbine, novantrone, teniposide, edatrexate, daunomycin, aminopterin, xeloda, ibandronate, irinotecan (e.g., CPT-11), topoisomerase inhibitors RFS2000, difluoromethylornithine (DMFO), retinoids (e.g., retinoic acid), capecitabine, carboplatin, procarbazine, plicomycin, gemcitabine, navelbine, farnesyl protein transferase inhibitors, transplatinum, and pharma- ceutical acceptable salts, acids, or derivatives of any of the above.

[0149] Some non-limiting examples of chemotherapeutic agents of the present disclosure include carboplatin (Paraplatin), cisplatin (Platinol, Platinol-AQ), cyclophosphamide (Cytoxan, Neosar), docetaxel (Taxotere), doxorubicin (Adriamycin), erlotinib (Tarceva), etoposide (VePesid), fluorouracil (5-FU), gemcitabine (Gemzar), imatinib mesylate (Gleevec), irinotecan (Camptosar), methotrexate (Folex, Mexate, Amethopterin), paclitaxel (Taxol, Abraxane), sorafinib (Nexavar), sunitinib (Sutent), topotecan (Hycamtin), vincristine (Oncovin, Vincasar). PFS), and vinblastine (Velban).

[0150] IX. Additional Anticancer Agents In some embodiments, the additional anti-cancer agent is administered in addition to a treatment as otherwise described (e.g., in addition to a chemotherapy regimen as described in Section VIII or in addition to an ICPI as described in Section VII). If a tumor is determined to be a suitable candidate for ICPI therapy using the methods described herein, such as the tumor is found to have a TMB score of at least 10 mut / megabase or at least 20 mut / megabase, the subject having the tumor may, in some embodiments, further benefit from treatment with an additional anti-cancer agent in addition to ICPI therapy. Similarly, if a tumor is determined to be a suitable candidate for a chemotherapy regimen, such as the tumor is found to have a TMBV score of less than 10 mut / megabase, the subject having the tumor may, in some embodiments, further benefit from treatment with an additional anti-cancer agent in addition to a chemotherapy regimen.

[0151] In some embodiments, the additional anti-cancer therapy comprises a kinase inhibitor. In some embodiments, the methods provided herein include administering a kinase inhibitor to an individual in combination with another therapy, such as, for example, an immune checkpoint inhibitor. Examples of kinase inhibitors include those that target one or more receptor tyrosine kinases (e.g., 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), those that target one or more cytoplasmic tyrosine kinases (e.g., c-SRC, c-YES, Abl, or JAK-2), those that target one or more serine / threonine kinases (e.g., ATM, Aurora A and B, CDK, mTOR, PKCi, PLK, b-Raf, S6K, or STK11 / LKB1), or those that target one or more lipid kinases (e.g., PI3K or SKI). Small molecule kinase inhibitors include PHA-739358, nilotinib, dasatinib, PD166326, NSC743411, lapatinib (GW-572016), canertinib (CI-1033), semaxinib (SU5416), vatalanib (PTK787 / ZK222584), sutent (SU1 1248), sorafenib (BAY43-9006), or leflunomide (SU101). Additional non-limiting examples of tyrosine kinase inhibitors include imatinib (Gleevec / Glivec) and gefitinib (Iressa).

[0152] In some embodiments, the additional anti-cancer therapy comprises an anti-angiogenic agent. In some embodiments, the methods provided herein comprise administering an anti-angiogenic agent to an individual in combination with another therapy, such as an immune checkpoint inhibitor. Angiogenesis inhibitors prevent the extensive growth of blood vessels (angiogenesis) that tumors need to survive. Non-limiting examples of angiogenesis mediating molecules or angiogenesis inhibitors that can be used in the methods of the present disclosure include soluble VEGF (e.g., VEGF isoforms, e.g., VEGF121 and VEGF165; VEGF receptors, e.g., VEGFR1, VEGFR2; and co-receptors, e.g., neuropilin 1 and neuropilin 2), NRP-1, angiopoietin 2, TSP-1 and TSP-2, angiostatin and related molecules, endostatin, vasostatin, calreticulin, platelet factor 4, TIMPs and CDAI, Meth-1 and Meth-2, IFNα, IFN-β and IFN-γ, CXCL10, IL-4, IL-12, and IL-18, prothrombin time-dependent inflammatory cytokines (e.g., IL-1, IL-2, and IL-3), and / or co-receptors such as IL-1, IL-2, IL-3, IL-4, IL-5, and IL-6. bin (kringle domain 2), antithrombin III fragment, prolactin, VEGI, SPARC, osteopontin, maspin, canstatin, proliferin-related protein, restin, and drugs such as bevacizumab, itraconazole, carboxyamidotriazole, TNP-470, CM101, IFN-a platelet factor 4, suramin, SU5416, thrombospondin, VEGFR antagonists, antiangiogenic steroids, and heparin, cartilage-derived angiogenesis inhibitor, matrix metalloproteinase inhibitor, 2-methoxyestradiol, tecogalan, tetrathiomolybdate, thalidomide, thrombospondin, prolactin ν β3 inhibitor, linomide, or tasquinimod. 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, potential therapeutic agents that may be used according to the methods of the present disclosure include specific inhibitors of endothelial cell proliferation, such as, but not limited to, TNP-470, thalidomide, and interleukin-12.Still other antiangiogenic agents that may be used according to the methods of the present disclosure include, but are not limited to, those that neutralize angiogenic molecules, including antibodies against fibroblast growth factor, antibodies against vascular endothelial growth factor, antibodies against platelet-derived growth factor, or antibodies or other types of inhibitors of receptors for EGF, VEGF, or PDGF. In some embodiments, antiangiogenic agents that may be used according to the methods of the present disclosure include, but are not limited to, suramin and its analogs, and tecogalan. In other embodiments, antiangiogenic agents that may be used according to the methods of the present disclosure include, but are not limited to, agents that neutralize receptors for angiogenic factors or agents that disrupt vascular basement membranes and extracellular matrices, including, but are not limited to, metalloprotease inhibitors and angiogenic inhibitory steroids. Another group of antiangiogenic compounds that may be used according to the methods of the present disclosure includes anti-adhesion molecules, such as, but not limited to, antibodies against integrin alpha v beta 3. Still other antiangiogenic compounds or compositions that may be used according to the methods of the present disclosure include kinase inhibitors, thalidomide, itraconazole, carboxyamidotriazole, CM101, IFN-α, IL-12, SU5416, thrombospondin, cartilage-derived angiogenesis inhibitor, 2-methoxyestradiol, tetrathiomolybdate, thrombospondin, prolactin, and linomide. In one particular embodiment, an antiangiogenic compound that may be used according to the methods of the present disclosure is an antibody against VEGF, such as Avastin® / bevacizumab (Genentech).

[0153] In some embodiments, the additional anti-cancer therapy comprises an anti-DNA repair therapy. In some embodiments, the methods provided herein comprise administering an anti-DNA repair therapy to an individual 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., talazoparib, rucaparib, olaparib), a RAD51 inhibitor (e.g., RI-1), or an inhibitor of DNA damage response kinase (e.g., CHCK1 (e.g., AZD7762), ATM (e.g., KU-55933, KU-60019, NU7026, or VE-821), and ATR (e.g., NU7026)).

[0154] In some embodiments, the additional anti-cancer therapy comprises a radiosensitizer. In some embodiments, the methods provided herein include administering a radiosensitizer to an individual in combination with another therapy, such as, for example, an immune checkpoint inhibitor. Exemplary radiosensitizers include hypoxia radiosensitizers (e.g., misonidazole, metronidazole) and trans-sodium crocetinate, a compound that helps increase the diffusion of oxygen to hypoxic tumor tissue. Radiosensitizers can also be DNA damage response inhibitors that interfere with base excision repair (BER), nucleotide excision repair (NER), mismatch repair (MMR), including homologous recombination (HR) and non-homologous end joining (NHEJ) and direct repair mechanisms. Single-strand break (SSB) repair mechanisms include the BER, NER, or MMR pathways, while double-strand break (DSB) repair mechanisms are composed of the HR and NHEJ pathways. Radiation causes DNA breaks that are lethal if not repaired. SSBs are repaired via a combination of BER, NER, and MMR mechanisms, using intact DNA strands as templates. The primary pathway for SSB repair is BER, which utilizes a family of related enzymes called poly(ADP-ribose) polymerases (PARPs). Radiosensitizers can therefore include DNA damage response inhibitors, such as PARP inhibitors.

[0155] In some embodiments, the additional anti-cancer therapy comprises an anti-inflammatory agent. In some embodiments, the methods provided herein include administering an anti-inflammatory agent to an individual 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 signaling from an inflammatory signaling pathway. In some embodiments, the anti-inflammatory agent inhibits or reduces the activity of any one or more of the following: 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, interferon (IFN) (e.g., IFNα, IFNβ, IFNγ, IFN-γ)-inducing factor (IGIF), transforming growth factor-β, (TGF-β), transforming growth factor-alpha (TGF-α), tumor necrosis factor (e.g., 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, TLR5, TLR6, TLR7, TLR8, TLR9, and / or their cognate receptors. In some embodiments, the anti-inflammatory agent is IL-1 or an IL-1 receptor antagonist, such as anakinra (Kineret®), rilonacept, or canakinumab. In some embodiments, the anti-inflammatory agent is an IL-6 or IL-6 receptor antagonist, such as an anti-IL-6 antibody or an anti-IL-6 receptor antibody (such as tocilizumab (ACTEMRA®), olokizumab, clazakizumab, sarilumab, sirumab, siltuximab, or ALX-0061). In some embodiments, the anti-inflammatory agent is a TNF-α antagonist, such as an anti-TNFα antibody (such as infliximab (Remicade®), golimumab (Simponi®), adalimumab (Humira®), certolizumab pegol (Cimzia®), or etanercept). In some embodiments, the anti-inflammatory agent is a corticosteroid.Examples of corticosteroids include cortisone (hydrocortisone, hydrocortisone sodium phosphate, hydrocortisone sodium succinate, Ala-Cort®, Hydrocort Acetate®, hydrocortone phosphate Lanacort®, Solu-Cortef®), Decadron (dexamethasone, dexamethasone acetate, dexamethasone sodium phosphate, Dexasone®, Diodex®, Hexadrol®, Maxidex®), methylprednisolone (6-methylprednisolone, methylprednisolone acetate, methylprednisolone sodium succinate, Duralone®, Medralone®, Medrol®, M-Prednisol®, Solu-Medrol®), prednisolone (Delta-Cortef®, ORAPRED®, Pediapred®, Prezone®), and prednisone (Deltasone®, Liquid Pred®, Meticorten®, Orasone®), and bisphosphonates (e.g., pamidronate (Aredia®), and zoledronic acid (Zometac®)).

[0156] In some embodiments, the additional anti-cancer therapy comprises an anti-hormonal agent. In some embodiments, the methods provided herein comprise administering to an individual an anti-hormonal agent in combination with another therapy, such as an immune checkpoint inhibitor. An anti-hormonal agent is an agent that acts to regulate or inhibit hormone action on tumors. Examples of antihormonal agents include antiestrogens and selective estrogen receptor modulators (SERMs), such as tamoxifen (including NOLVADEX® tamoxifen), raloxifene, droloxifene, 4-hydroxytamoxifen, trioxyphene, ketoxifene, LY117018, onapristone, and FARESTON®, toremifene, aromatase inhibitors (which inhibit the enzyme aromatase, which regulates estrogen production in the adrenal glands) (e.g., 4(5)-imidazole, aminoglutethimide, MEGACE® megestrol acetate, AROMASIN® exemestane, formestane, fadrozole, RIVISOR® vorozole, FEMARA® letrozole, and ARIMIDEX® (anastrozole). ), antiandrogens (e.g., flutamide, nilutamide, bicalutamide, leuprolide, goserelin), troxacitabine (a 1,3-dioxolane nucleoside cytosine analog); antisense oligonucleotides (particularly oligonucleotides that inhibit the expression of genes in signal transduction pathways involved in abnormal cell proliferation, such as, for example, PKC-alpha, Raf, H-Ras, and epidermal growth factor receptor (EGF-R)), vaccines such as gene therapy vaccines (e.g., ALLOVECTIN® vaccine, LEUVECTIN® vaccine, and VAXID® vaccine), PROLEUKIN® rIL-2, LURTOTECAN® topoisomerase 1 inhibitors, ABALELIX® rmRH, and pharma- ceutically acceptable salts, acids, or derivatives of any of the above.

[0157] In some embodiments, the anti-cancer therapy comprises an antimetabolite chemotherapeutic agent. In some embodiments, the methods provided herein comprise administering an antimetabolite chemotherapeutic agent to an individual in combination with another therapy, such as an immune checkpoint inhibitor. An antimetabolite chemotherapeutic agent is a drug that is structurally similar to a metabolite, but cannot be productively used in the body. Many antimetabolite chemotherapeutic agents interfere with the production of RNA or DNA. Examples of antimetabolite chemotherapeutic agents include gemcitabine (GEMZAR®), 5-fluorouracil (5-FU), capecitabine (XELODA™), 6-mercaptopurine, methotrexate, 6-thioguanine, pemetrexed, raltitrexed, arabinosylcytosine, ARA-C, cytarabine (CYTOSAR-U®), dacarbazine (DTIC-DOMED), azocytosine, deoxycytosine, pyridomidene, fludarabine (FLUDARA®), cladrabine, and 2-deoxy-D-glucose. In some embodiments, the antimetabolite chemotherapeutic agent is gemcitabine. Gemcitabine HCl is sold under the trademark GEMZAR® by Eli Lilly.

[0158] In some embodiments, the additional anti-cancer therapy comprises a platinum-based chemotherapeutic agent. In some embodiments, the methods provided herein comprise administering to an individual a platinum-based chemotherapeutic agent in combination with another therapy, such as an immune checkpoint inhibitor. A platinum-based chemotherapeutic agent is a chemotherapeutic agent that comprises an organic compound that contains platinum as an integral part of the 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, triplatin tetranitrate, phenanthriplatin, picoplatin, or satraplatin.

[0159] In some embodiments, the additional anti-cancer therapy comprises a cancer immunotherapy, such as a cancer vaccine, a cell-based therapy, a T cell receptor (TCR)-based therapy, an adjuvant immunotherapy, a cytokine immunotherapy, and an oncolytic virus therapy. In some embodiments, the methods provided herein comprise administering to an individual a cancer immunotherapy, such as a cancer vaccine, a cell-based therapy, a T cell receptor (TCR)-based therapy, an adjuvant immunotherapy, a cytokine immunotherapy, and an oncolytic virus therapy, in combination with a therapy, such as an immune checkpoint inhibitor. In some embodiments, the cancer immunotherapy comprises a small molecule, a nucleic acid, a polypeptide, a carbohydrate, a toxin, a cell-based agent, or a cell-binding agent. Examples of cancer immunotherapies are described in more detail herein, but are not intended to be limiting. In some embodiments, the cancer immunotherapy activates one or more aspects of the immune system to attack cells (e.g., tumor cells) that express neo-antigens (e.g., neo-antigens expressed by a cancer of the present disclosure). The cancer immunotherapies of the present disclosure are contemplated for use as a monotherapy or in a combination approach including any combination or number of two or more, subject to medical judgment. Any of the cancer immunotherapies (optionally as a monotherapy or in combination with another cancer immunotherapy or other therapeutic agent described herein) can be used in any of the methods described herein.

[0160] In some embodiments, the cancer immunotherapy comprises a cancer vaccine. Various cancer vaccines using different approaches to promote immune response against cancer have been tested (see, for example, Emens LA, Expert Opin Emerg Drugs 13(2):295-308(2008) and US2019 / 0367613). Approaches have been designed to enhance the response of B cells, T cells, or professional antigen presenting cells against tumors. Exemplary types of cancer vaccines include, but are not limited to, DNA-based vaccines, RNA-based vaccines, viral transduction 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 can 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, vaccine compositions can include naked cDNA in cationic lipid formulations, lipopeptides (e.g., Vitiello, A. et al, J. Clin. Invest. 95:341, 1995), naked cDNA or peptides encapsulated in, e.g., poly(DL-lactide-co-glycolide) ("PLG") microspheres (see, e.g., Eldridge, et al, Molec. 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 immune stimulating complexes (ISCOMS) (see, e.g., Takahashi et al, Nature 344:873-875, 1990; Hu et al, Nature 344:873-875, 1990), and the like. al, Clin. Exp. Immunol. 113:235-243, 1998), or multiple antigen peptide systems (MAP) (see, e.g., Tam, JP, Proc. Natl Acad. Sci. USA 85:5409-5413, 1988; Tam, JP, 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 the 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 a personalized peptide vaccine. In some embodiments, the cancer vaccine is a multivalent long peptide, multiple peptide, 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.

[0161] In some embodiments, the cancer vaccine comprises a polynucleotide encoding a neo-antigen (e.g., a neo-antigen expressed by a cancer of the present disclosure). In some embodiments, the cancer vaccine comprises DNA or RNA encoding the neo-antigen. In some embodiments, the cancer vaccine comprises a polynucleotide encoding the neo-antigen. In some embodiments, the cancer vaccine further comprises one or more additional antigens, neo-antigens, or other sequences that promote antigen presentation and / or immune response. In some embodiments, the polynucleotide is complexed with one or more additional agents, such as liposomes or lipoplexes. In some embodiments, the polynucleotide is taken up and translated by antigen presenting cells (APCs), which then present the neo-antigen via MHC class I on the APC cell surface.

[0162] In some embodiments, the cancer vaccine is selected from sipuleucel-T (Provenge®, Dendreon / Valeant Pharmaceuticals), which is approved for the treatment of asymptomatic or minimally symptomatic metastatic castration-resistant (hormone refractory) prostate cancer, and talimogene laherparepvec (Imlygic®, BioVex / Amgen, formerly known as T-VEC), which is a genetically modified oncolytic virus therapy approved for the treatment of unresectable cutaneous, subcutaneous, and lymph node lesions in melanoma. In some embodiments, the cancer vaccine is an oncolytic virotherapy, e.g., PexaVec / JX-594, a thymidine kinase (TK)-deficient vaccinia virus engineered to express GM-CSF, for hepatocellular carcinoma (NCT02562755) and melanoma (NCT00429312); colorectal cancer (NCT01622543), prostate cancer (NCT01619813), head and neck squamous cell carcinoma (NCT01166542), pancreatic adenocarcinoma (NCT00998322), and non-small cell lung cancer (NSCLC) (NCT Reolysin® (Oncolytics 00861627), a variant of respiratory enteric orphan virus (reovirus) that does not replicate in cells without RAS activation, has been shown to be effective in treating multiple cancers, including ovarian cancer, ovarian cancer, and ovarian cancer. Enadenotsilieff (NG-348, formerly known as PsiOxus as ColoAdl), an adenovirus engineered to express full-length CD80 and an antibody fragment specific for the T-cell receptor CD3 protein, in ovarian cancer (NCT02028117), metastatic or advanced epithelial tumors such as colorectal cancer, bladder cancer, head and neck squamous cell carcinoma, and salivary gland cancer (NCT02636036); ONCOS-102 (Targovax / formerly Oncos), an adenovirus engineered to express GM-CSF, in melanoma (NCT03003676), and peritoneal disease, colorectal cancer, or ovarian cancer (NCT02963831);GL-ONC1 (GLV-1h68 / GLV-1h153, Genelux GmbH), a vaccinia virus engineered to express beta-galactosidase (beta-gal) / beta-glucoronidase, or beta-gal / human sodium iodide symporter (hNIS), respectively, studied in peritoneal carcinomatosis (NCT01443260), fallopian tube cancer, and ovarian cancer (NCT 02759588); or CG0070 (Cold Genesys), an adenovirus engineered to express GM-CSF, in bladder cancer (NCT02365818); anti-gp100; STINGVAX; GVAX; DCVaxL;and DNX-2401. In some embodiments, the cancer vaccine is selected from JX-929 (SillaJen / formerly Jennerex Biotherapeutics), which is a TK-deficient 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 / formerly Oncos), which are peptide-based immunotherapeutics targeting difficult-to-treat RAS mutations; TILT-123 (TILT Biotherapeutics), which is an engineered adenovirus designated Ad5 / 3-E2F-delta24-hTNFα-IRES-hIL20; VSV-GP (ViraTherapeutics), which is a vesicular stomatitis virus (VSV) engineered to express the glycoprotein (GP) of lymphocytic choriomeningitis virus (LCMV), which can be further engineered to express antigens designed to elicit 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 method to provide a steady supply of antigens to stimulate anti-tumor immune responses. In some embodiments, a vector encoding a tumor antigen is injected into an individual (possibly with other inducers such as pro-inflammatory agents or GM-CSF) and taken up by cells in vivo to produce the specific antigen, which then elicits the desired immune response. In some embodiments, a vector can be used to deliver more than one tumor antigen at a time to increase the immune response. In addition, recombinant viral, bacterial, or yeast vectors can themselves trigger an immune response, which can also enhance the overall immune response.;

[0163] In some embodiments, the cancer vaccine comprises a DNA-based vaccine. In some embodiments, a DNA-based vaccine can be used to stimulate an anti-tumor response. The ability to directly inject DNA encoding an antigen protein to induce a protective immune response has been demonstrated in a number of experimental systems. Vaccination by directly injecting DNA encoding an antigen protein to induce a protective immune response often provokes both cellular and humoral responses. Also, reproducible immune responses to DNA encoding various antigens have been reported in mice that persist essentially throughout the life of the animal (see, e.g., Yankauckas et al. (1993) DNA Cell Biol., 12:771-776). In some embodiments, a plasmid (or other vector) DNA containing a protein-encoding sequence 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, the cells of the individual take up the administered DNA and the coding sequence is expressed. In some embodiments, the antigen so produced becomes a target against which an immune response is directed.

[0164] In some embodiments, the cancer vaccine comprises an RNA-based vaccine. In some embodiments, the RNA-based vaccine can be used to stimulate anti-tumor responses. In some embodiments, the RNA-based vaccine comprises a self-replicating RNA molecule. In some embodiments, the self-replicating RNA molecule can be an RNA replicon derived from an alphavirus. Self-replicating RNA (or "SAM") molecules are well known in the art and can be produced, for example, by using replication elements derived from alphaviruses to replace structural viral proteins with nucleotide sequences that code for a protein of interest. Self-replicating RNA molecules are typically +-strand molecules that can be directly translated after delivery to a cell, and this translation provides an RNA-dependent RNA polymerase that produces both antisense and sense transcripts from the delivered RNA. Thus, the delivered RNA leads to the production of multiple daughter RNAs. These daughter RNAs, as well as collinear subgenomic transcripts, can themselves be translated to provide in situ expression of the encoded polypeptide or can be transcribed to provide further transcripts of the same sense strand as the delivered RNA, which are translated to provide in situ expression of the antigen.

[0165] In some embodiments, the 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 an adoptive therapy (e.g., an adoptive T cell-based therapy). In some embodiments, the T cells are autologous or allogeneic to the recipient. In some embodiments, the T cells are CD8+ T cells. In some embodiments, the T cells are CD4+ T cells. Adoptive immunotherapy refers to a therapeutic approach for treating cancer or infectious diseases in which immune cells are administered to a host with the goal that the cells mediate direct or indirect specific immunity against (i.e., mount an immune response against) the cancer cells. In some embodiments, the immune response results in inhibition of growth and / or proliferation of tumor cells and / or metastatic cells, and in related embodiments, death and / or resorption of tumor cells. The immune cells can be derived from a different organism / host (exogenous immune cells) or can be cells obtained from the subject organism (autologous immune 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, invariant NK cells, or NKT cells) may be genetically engineered to express an antigen receptor, such as an engineered TCR and / or chimeric antigen receptor (CAR). For example, host cells (e.g., autologous or allogeneic T cells) are modified to express a T cell receptor (TCR) with antigen specificity for a cancer antigen. In some embodiments, NK cells are engineered to express a TCR. NK cells may be further engineered to express a CAR. Multiple CARs and / or TCRs, such as for different antigens, can be added to a single cell type, such as a T cell or NK cell. In some embodiments, the cells comprise one or more nucleic acids / expression constructs / vectors introduced via genetic engineering that encode one or more antigen receptors, and the genetically engineered products of such nucleic acids. In some embodiments, the nucleic acids are heterologous. That is, it is not normally present in a cell or a sample obtained from a cell, such as one obtained from another organism or cell, and is not normally found, for example, in the cell being manipulated and / or the organism from which such a cell is derived.In some embodiments, the nucleic acid is not naturally occurring, e.g., a nucleic acid not found in nature (e.g., chimeric). In some embodiments, the population of immune cells can be obtained from a subject in need of therapy or from a subject suffering from a disease associated with reduced activity of immune cells. Thus, the cells are autologous to the subject in need of therapy. In some embodiments, the population of immune cells can be obtained from a donor (e.g., a histocompatibility-matched donor). In some embodiments, the immune cell population can be harvested from peripheral blood, umbilical cord blood, bone marrow, spleen, or any other organ / tissue in which immune cells are present in the subject or donor. In some embodiments, the immune cells can be isolated from a pool of subjects and / or donors (e.g., pooled umbilical cord blood). In some embodiments, if the population of immune cells is obtained from a donor different from the subject, the donor can be allogeneic, so long as the obtained cells are subject-compatible in that they can 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, the allogeneic cells can be treated to reduce immunogenicity in order to be subject-compatible.

[0166] In some embodiments, cell-based treatments include T cell-based therapy, including autologous cells, e.g., tumor infiltrating lymphocytes (TILs); T cells activated ex vivo using autologous DCs, lymphocytes, artificial antigen presenting cells (APCs) or beads coated with T cell ligands and activating antibodies, or cells isolated by capturing target cell membranes; allogeneic cells that naturally express 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 TCRs or chimeric TCR molecules (known as "T bodies" and exhibiting antibody-like tumor recognition capabilities). Several approaches for the isolation, induction, engineering or modification, activation, and expansion of functional anti-tumor effector cells have been described in the past 20 years and can 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 cells are human cells. In some embodiments, the cells are primary cells, such as cells isolated directly from a subject and / or cells isolated and frozen from a subject. In some embodiments, the cells include T cells or other cell types, such as those defined by function, activation state, maturity, differentiation potential, proliferation, recirculation, localization, and / or persistence, antigen specificity, type of antigen receptor, presence in a particular organ or compartment, marker or cytokine secretion profile, and / or degree of differentiation, such as one or more subsets of the total T cell population, CD4+ cells, CD8+ cells, and subpopulations thereof. In some embodiments, the cells may be allogeneic and / or autologous. In some embodiments, such as off-the-shelf technologies, the cells are pluripotent and / or multipotent, such as stem cells, such as induced pluripotent stem cells (iPSCs).

[0167] In some embodiments, the T cell-based therapy includes chimeric antigen receptor (CAR)-T cell-based therapy. This approach involves engineering a CAR. The CAR specifically binds to an antigen of interest and contains one or more intracellular signaling domains for T cell activation. The CAR is then expressed on the surface of engineered T cells (CAR-T) and administered to a patient, resulting in a T cell-specific immune response against cancer cells expressing the antigen.

[0168] In some embodiments, T cell-based therapy involves T cells expressing recombinant T cell receptors (TCRs). This approach involves identifying a TCR that specifically binds to an antigen of interest. This is then used to replace the endogenous or natural TCR on the surface of engineered T cells. When administered to a patient, this results in a T cell-specific immune response against cancer cells expressing the antigen.

[0169] In some embodiments, the T cell-based therapy includes tumor infiltrating lymphocytes (TILs). For example, TILs can be isolated from a tumor or cancer of the present disclosure, and then isolated and expanded in vitro. Some or all of these TILs can specifically recognize antigens expressed by the tumor or cancer of the present disclosure. In some embodiments, the TILs are exposed to one or more neo-antigens (e.g., one neo-antigen) after being isolated in vitro. The TILs are then administered to the patient (optionally in combination with one or more cytokines or other immune stimulants).

[0170] In some embodiments, the cell-based therapy comprises natural killer (NK) cell-based therapy. Natural killer (NK) cells are a subpopulation of lymphocytes that have spontaneous cytotoxicity against various tumor cells, virus-infected cells, and some normal cells in bone marrow and thymus. NK cells are important effectors of early innate immune responses against transformed and virus-infected cells. NK cells can be detected by specific surface markers such as CD16, CD56, CD8 in humans. NK cells do not express T cell antigen receptor, pan-T marker CD3, or surface immunoglobulin B cell receptor. In some embodiments, NK cells are obtained from human peripheral blood mononuclear cells (PBMCs), unstimulated leukapheresis 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.

[0171] In some embodiments, the cell-based therapy includes dendritic cell (DC)-based therapy (e.g., dendritic cell vaccines). In some embodiments, the DC vaccine includes antigen-presenting cells capable of inducing specific T cell immunity, harvested from a patient or donor. In some embodiments, the DC vaccine can then be exposed to peptide antigens in vitro, for which T cells are generated in the patient. In some embodiments, the antigen-loaded dendritic cells are then injected back into the patient. In some embodiments, immunization can be repeated multiple times, as needed. Methods for harvesting, expanding, and administering dendritic cells are known in the art (see, e.g., WO2019 / 178081). Dendritic cell vaccines (e.g., Sipuleucel-T, also known as APC8015 and PROVENGE®) are vaccines that involve administration of dendritic cells that function 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.

[0172] In some embodiments, the cancer immunotherapy comprises a TCR-based therapy. In some embodiments, the cancer immunotherapy comprises administration of one or more TCRs or TCR-based therapeutics that specifically bind to an antigen expressed by the cancer of the present disclosure. In some embodiments, the TCR-based therapeutic 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-CD3 antibody or antibody fragment).

[0173] In some embodiments, the immunotherapy comprises adjuvant immunotherapy, which comprises the use of one or more agents that activate components of the innate immune system, such as HILTONOL® (imiquimod), which targets the TLR7 pathway.

[0174] 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, aldesleukin (PROLEUKIN®, interleukin-2), interferon alpha-2a (ROFERON®-A), interferon alpha-2b (INTRON®-A), and PEG-interferon alpha-2b (PEGINTRON®).

[0175] In some embodiments, the immunotherapy comprises oncolytic virotherapy, in which genetically modified viruses are used to replicate in and kill cancer cells, releasing antigens that stimulate the immune response. In some embodiments, the replication-competent oncolytic virus expressing a tumor antigen comprises any naturally occurring (e.g., from a "field source") or modified replication-competent oncolytic virus. In some embodiments, the oncolytic virus, in addition to expressing a tumor antigen, may be modified to increase the selectivity of the virus for cancer cells. In some embodiments, the replication-competent oncolytic viruses include, but are not limited to, Myoviridae, Siphoviridae, Podoviridae, Tesiviridae, Corticoviridae, Plasmaviridae, Liposthrixviridae, Fuselloviridae, Poxyiridae, Iridoviridae, Phycodnaviridae, Baculoviridae, Herpesviridae, Adnoviridae, Papovaviridae, Polydnaviridae, Inoviridae, Microviridae, Geminiviridae, Circoviridae, Parvoviridae, Hepadnaviruses, Oncolytic viruses include those that are members of the following families: Retroviridae, Cytoviridae, Reoviridae, Birnaviridae, Paramyxoviridae, Rhabdoviridae, Filoviridae, Orthomyxoviridae, Bunyaviridae, Arenaviridae, Leviviridae, Picornaviridae, Sequiviridae, Comoviridae, Potyviridae, Caliciviridae, Astroviridae, Nodaviridae, Tetraviridae, Tombusviridae, Coronaviridae, Graviviridae, Togaviridae, and Barnaviridae. In some embodiments, replication-competent oncolytic viruses include adenoviruses, retroviruses, reoviruses, rhabdoviruses, Newcastle disease virus (NDV), polyomaviruses, vaccinia viruses (VacV), herpes simplex viruses, picornaviruses, coxsackieviruses, and parvoviruses. In some embodiments, replicative oncolytic vaccinia viruses expressing tumor antigens may be engineered to lack one or more functional genes to enhance the 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 may be engineered to lack vaccinia virus growth factor (VGF). In some embodiments, the oncolytic vaccinia virus may be engineered to lack both VGF and TK activity. In some embodiments, the oncolytic vaccinia virus may be engineered to lack one or more genes involved in evading the host interferon (IFN) response, such as E3L, K3L, B18R, or B8R. In some embodiments, the replicative oncolytic vaccinia virus is a 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 that lacks a functional B18R and / or B8R gene. In some embodiments, a replicating oncolytic vaccinia virus expressing a tumor antigen can be administered to a subject locally or systemically, for example, via intratumoral, intraperitoneal, intravenous, intraarterial, intramuscular, intradermal, intracranial, subcutaneous, or intranasal administration.

[0176] In some embodiments, the anti-cancer therapy comprises a nucleic acid molecule, such as a dsRNA, siRNA, or shRNA. In some embodiments, the methods provided herein comprise administering to an individual a nucleic acid molecule, such as a dsRNA, siRNA, or shRNA, for example, in combination with another anti-cancer therapy. As is known in the art, dsRNA having a double-stranded structure is effective in inducing RNA interference (RNAi). In some embodiments, the anti-cancer therapy comprises a short interfering RNA (siRNA). dsRNA and siRNA can be used to suppress gene expression in mammalian cells (e.g., human cells). In some embodiments, the dsRNA of the present disclosure comprises any of about 5 to about 10 base pairs, about 10 to about 12 base pairs, about 12 to about 15 base pairs, about 15 to about 20 base pairs, about 20 to 23 base pairs, about 23 to about 25 base pairs, about 25 to about 27 base pairs, or about 27 to about 30 base pairs. As known in the art, siRNA is a small dsRNA that optionally includes an overhang. In some embodiments, the double-stranded region of the siRNA is about 18-25 nucleotides (e.g., any of 18, 19, 20, 21, 22, 23, 24, or 25 nucleotides). siRNA can also be a short hairpin RNA (shRNA), such as one with a stem of approximately 29 base pairs and a 2-nucleotide 3' overhang. Methods for designing, optimizing, producing, and using dsRNA, siRNA, or shRNA are known in the art.

[0177] X. Treatment and Therapeutic Effects The methods described herein provide improved therapy and / or therapeutic efficacy. The improved therapy and / or therapeutic efficacy is based at least in part on stratifying individuals having cancers with TMB scores below a threshold TMB score and individuals having cancers with TMB scores of at least a threshold TMB score, stratifying individuals having cancers that are MSI-H and individuals having cancers that are not MSI-H (such as MSI-L or MSS), or both. Once the TMB score is determined and / or microsatellite instability status is assessed, the individual can receive the appropriate therapy, resulting in improved clinical outcomes, including improved survival (such as improved progression-free survival and / or improved overall survival) and / or increased time to next treatment (TTNT). The individual can be any of the individuals described in Section III above.

[0178] Thus, in some embodiments, the methods include administering an immune checkpoint inhibitor (such as an ICPI described in Section VII) if the TMB score in the sample from the individual with cancer is at least a threshold TMB score. In some embodiments, the methods include administering a chemotherapy (such as a chemotherapy described in Section VIII) if the TMB score is less than a threshold TMB score. In some embodiments, the methods include administering an ICPI (such as an ICPI described in Section VII) if the sample from the individual is assessed as MSI-H, and the methods include administering a chemotherapy (such as a chemotherapy described in Section VIII) if the sample from the individual is not MSI-H (such as MSS or MSI-L).

[0179] In some embodiments, the methods of treatment described herein provide a clinical benefit and / or improved clinical benefit to individuals with cancer. In some embodiments, the methods provide an improved clinical benefit compared to alternative therapies. For example, in some embodiments, the methods include administering an ICPI, and the individual is expected to benefit from the ICPI therapy compared to treatment with a chemotherapy regimen. In some embodiments, the methods include administering a chemotherapy regimen, and the individual is expected to benefit from the chemotherapy regimen compared to treatment with an ICPI therapy.

[0180] In some embodiments, the clinical benefit is improved survival (such as improved PFS and / or improved OS). In some embodiments, the treatment improves PFS for at least 1 month, e.g., at least 2 months, at least 3 months, at least 4 months, at least 5 months, at least 6 months, at least 7 months, at least 8 months, at least 9 months, at least 10 months, at least 11 months, at least 12 months, at least 18 months, at least 2 years, at least 3 years, at least 4 years, or more, after administration. In some embodiments, the treatment improves OS for at least 1 month, e.g., at least 2 months, at least 3 months, at least 4 months, at least 5 months, at least 6 months, at least 7 months, at least 8 months, at least 9 months, at least 10 months, at least 11 months, at least 12 months, at least 18 months, at least 2 years, at least 3 years, at least 4 years, or more, after administration. In some embodiments, the treatment methods provide an objective response that is improved by at least 20%, e.g., 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%.

[0181] XI. Cancer being evaluated or treated The methods described herein relate to individuals with cancer and the assessment of the cancer (by evaluating a sample, such as a blood sample or tumor biopsy sample) to identify an appropriate treatment for the individual. Exemplary cancers to be treated or evaluated 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, and liver cancer. , kidney cancer, testicular cancer, biliary tract cancer, small intestine or adnexal cancer, salivary gland cancer, thyroid cancer, adrenal adenocarcinoma, osteosarcoma, chondrosarcoma, cancer of blood tissue, adenocarcinoma, inflammatory myofibroblastic tumor, gastrointestinal stromal tumor (GIST), colon cancer, multiple myeloma (MM), myelodysplastic syndrome (MDS), myeloproliferative disorder (MPD), acute lymphoblastic leukemia (ALL), acute myeloid 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, synovium, mesothelioma, Ewing's tumor, leiomyosarcoma, rhabdomyosarcoma, squamous cell carcinoma, basal cell carcinoma, adenocarcinoma, sweat gland carcinoma, sebaceous gland carcinoma, papillary carcinoma, papillary adenocarcinoma, medullary carcinoma, bronchogenic carcinoma, renal cell carcinoma, hepatocellular carcinoma, cholangiocarcinoma, choriocarcinoma, seminoma, embryonal carcinoma, Wilms' tumor, bladder cancer, epithelial carcinoma, glioma , astrocytoma, medulloblastoma, craniopharyngioma, ependymoma, pinealoma, hemangioblastoma, acoustic neuroma, oligodendroglioma, meningioma, neuroblastoma, retinoblastoma, diffuse large B-cell lymphoma, mantle cell lymphoma, hepatocellular carcinoma, thyroid cancer, gastric cancer, head and neck cancer, small cell carcinoma, essential thrombocythemia, agnogenic myeloid metaplasia, hypereosinophilic syndrome, systemic mastocytosis, familial hypereosinophilia, chronic eosinophilic leukemia, neuroendocrine carcinoma, carcinoma-like tumors, 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 cancer of unknown primary. In some embodiments, the cancer is metastatic urothelial carcinoma.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 (aNSCLC). In some embodiments, the cancer is melanoma. In some embodiments, the cancer is a hematological malignancy (or pre-malignancy). As used herein, hematological malignancy refers to a tumor of the hematopoietic or lymphatic tissues, e.g., a tumor affecting the blood, bone marrow, or lymph nodes. Exemplary hematological malignancies include leukemia (e.g., acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), chronic lymphocytic leukemia (CLL), chronic myelogenous leukemia (CML), hairy cell leukemia, acute monocytic leukemia (AMoL), chronic myelomonocytic leukemia (CMML), juvenile myelomonocytic leukemia (JMML), or large granular lymphocytic leukemia), lymphoma (e.g., AIDS-related lymphoma, cutaneous T-cell lymphoma, Hodgkin's lymphoma (e.g., classical Hodgkin's lymphoma or nodular lymphocyte-predominant Hodgkin's lymphoma), mycosis fungoides, non-Hodgkin's lymphoma, and the like). Examples of lymphomas include, but are not limited to, B-cell non-Hodgkin's lymphoma (e.g., Burkitt's lymphoma, small lymphocytic lymphoma (CLL / SLL), diffuse large B-cell lymphoma, follicular lymphoma, immunoblastic 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. As used herein, a premalignant tumor refers to tissue that is not yet malignant, but is preparing to become malignant.

[0182] In some embodiments, the cancer being treated or evaluated has never been treated with an anti-cancer therapy. In some embodiments, the cancer being treated or evaluated has never been treated or is not currently being treated with a chemotherapy regimen. In some embodiments, the cancer being treated or evaluated has been previously treated with an anti-cancer therapy. In some embodiments, the cancer being treated or evaluated has been previously treated with a chemotherapy regimen.

[0183] In some embodiments, the cancer being treated or evaluated has a TMB score of at least 8 mutations / Mb, e.g., 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 being treated or evaluated has a TMB score of at least 10 mutations / Mb. In some embodiments, the cancer being treated or evaluated has a TMB score of less than 12 mutations / Mb, e.g., 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 being treated or evaluated has a TMB score of less than 10 mutations / Mb.

[0184] In some embodiments, the cancer being treated or evaluated is MSI-H. In some embodiments, the cancer being treated or evaluated is MSI-L. In some embodiments, the cancer being treated or evaluated is MSS.

[0185] In some embodiments, the cancer being treated or evaluated has a TMB score of at least 10 mutations / Mb and is MSI-H. In some embodiments, the cancer being treated or evaluated has a TMB score of at least 10 mutations / Mb and is MSI-L or MSS. In some embodiments, the cancer being treated or evaluated has a TMB score of less than 10 mutations / Mb and is MSI-H. In some embodiments, the cancer being treated or evaluated has a TMB score of less than 10 mutations / Mb and is MSI-H or MSS.

[0186] XII. Exemplary Embodiments The following embodiments are illustrative and are not intended to limit the scope of the present invention.

[0187] Embodiment 1. A method for identifying an individual having cancer for treatment with immune checkpoint inhibitor therapy, comprising determining a tumor mutational burden (TMB) score of a sample obtained from the individual, wherein if the TMB score is at least a threshold TMB score, the individual is identified for treatment with immune checkpoint inhibitor therapy.

[0188] Embodiment 2. A method of selecting a treatment for an individual having cancer, comprising determining a tumor mutational burden (TMB) score of a sample obtained from the individual, wherein a TMB score that is at least a threshold TMB score identifies the individual as one that may benefit from treatment with an immune checkpoint inhibitor therapy.

[0189] Embodiment 3. A method of identifying one or more treatment options for an individual having cancer, comprising: (a) determining a tumor mutational burden (TMB) score of a sample obtained from the individual; and (b) generating a report including the one or more treatment options identified for the individual, wherein a TMB score that is at least a threshold TMB score identifies the individual as one that may benefit from treatment with an immune checkpoint inhibitor therapy.

[0190] Embodiment 4. A method of stratifying an individual having cancer for treatment with a therapy, comprising: determining a tumor mutational burden (TMB) score of a sample obtained from the individual; and (a) identifying the individual as a candidate for receiving immune checkpoint inhibitor therapy if the TMB score is at least a threshold TMB score, or (b) identifying the individual as a candidate for receiving a chemotherapy regimen if the TMB score is less than a threshold TMB score.

[0191] Embodiment 5. The method of any one of embodiments 1 to 4, further comprising assessing microsatellite instability, wherein the identification is further based on the cancer being microsatellite instability high (MSI-H).

[0192] Embodiment 6. The method of any one of embodiments 1-5, wherein the individual is identified as having increased survival time compared to treatment with a chemotherapy regimen.

[0193] Embodiment 7. A method of predicting survival of an individual having cancer, comprising obtaining knowledge of a tumor mutational burden (TMB) score of a sample obtained from the individual, wherein if the TMB score of the sample obtained from the individual is at least a threshold TMB score, the individual is predicted to have increased survival when treated with an immune checkpoint inhibitor compared to treatment with a chemotherapy regimen.

[0194] Embodiment 8. A method of monitoring, assessing or screening an individual having cancer, comprising obtaining knowledge of a tumor mutational burden (TMB) score of a sample obtained from the individual, wherein if the TMB score of the sample obtained from the individual is at least a TMB score, the individual is predicted to have increased survival when treated with an immune checkpoint inhibitor compared to treatment with a chemotherapy regimen.

[0195] Embodiment 9. The method of any one of embodiments 6 to 8, wherein the increased survival is increased overall survival (OS).

[0196] Embodiment 10. The method of any one of embodiments 6 to 8, wherein the increased survival is increased progression-free survival (PFS).

[0197] Embodiment 11. A method for treating an individual having cancer, comprising: (a) determining a tumor mutational burden (TMB) score of a 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.

[0198] Embodiment 12. The method of embodiment 11, further comprising assessing microsatellite instability, wherein (b) is further based on the cancer being microsatellite instability high (MSI-H).

[0199] Embodiment 13. The method of any one of embodiments 1-12, further comprising treating the individual with chemotherapy if the TMB score is below a threshold TMB score.

[0200] Embodiment 14.The chemotherapy is an alkylating agent, an alkylsulfonate, an aziridine, an ethylenimine, a methylameramine, an acetogenin, a camptothecin, a bryostatin, a kallistatin, a CC-1065, a cryptophycin, a dolastatin, a duocarmycin, an erytherobin, a pancratistatin, a sarcodictin, a spongiostatin, a nitrogen mustard, a nitrosourea, an antibiotic, a dynemicin, a bisphosphonate, an esperamicin, a neocarzinostatin chromophore or a related chromoprotein enediyne antibiotic chromophore, an antimetabolite, a folic acid analogue body, purine analogues, pyrimidine analogues, androgens, antiadrenal agents, folic acid supplements, aldophosphamide glycosides, aminolevulinic acid, eniluracil, amsacrine, bestravcil, bisantrene, edatraxate, deformamine, demecolcine, diazicon, elformitin, elliptinium acetate, epothilone, etoglucide, gallium nitrate, hydroxyurea, lentinan, lonidainin, maytansinoids, mitoguazone, mitoxantrone, mopidamol, nitraelin, pentostatin, phenamet, pirarubicin, rosoxantrone, Podophyllic acid, 2-ethylhydrazide, procarbazine, PSK polysaccharide complex, razoxane, rhizoxin, schizophyllan, spirogermanium, tenuazonic acid, triazicon, 2,2',2"-trichlorotriethylamine, trichothecene, urethane, vindesine, dacarbazine, mannomustine, mitobronitol, mitolactol, pipobroman, gacitosine, arabinoside ("Ara-C"), cyclophosphamide, taxoids, 6-thioguanine, mercaptopurine, platinum coordination complex, vinblastine, platinum, etoposide (VP-16), ifosf 14. The method of embodiment 13, comprising one or more of the following: amides, mitoxantrone, vincristine, vinorelbine, novantrone, teniposide, edatrexate, daunomycin, aminopterin, xeloda, ibandronate, irinotecan, topoisomerase inhibitor RFS2000, difluoromethylornithine (DMFO), retinoids, capecitabine, carboplatin, procarbazine, plicomycin, gemcitabine, navelbine, farnesyl protein transferase inhibitors, transplatinum, or any combination thereof.

[0201] 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.

[0202] Embodiment 16. The method of any one of embodiments 1 to 15, wherein the threshold TMB score is about 10 mutations / Mb.

[0203] Embodiment 17. The method of any one of embodiments 1 to 16, wherein the threshold TMB score is 10 mutations / Mb.

[0204] Embodiment 18. The method of any one of embodiments 1 to 17, wherein the TMB score is determined based on about 100 kb to about 10 MB of sequenced DNA.

[0205] Embodiment 19. The method of any one of embodiments 1 to 18, wherein the TMB score is determined based on about 0.8 Mb to about 1.1 MB of sequenced DNA.

[0206] Embodiment 20. A method of identifying an individual having cancer for treatment with immune checkpoint inhibitor therapy, comprising assessing microsatellite instability in a sample obtained from the individual, and if the microsatellite instability is MSI-H, then the individual is identified for treatment with immune checkpoint inhibitor therapy.

[0207] Embodiment 21. A method of selecting a treatment for an individual having cancer, comprising assessing microsatellite instability in a sample obtained from the individual, wherein microsatellite instability that is MSI-H identifies the individual as one that may benefit from treatment with immune checkpoint inhibitor therapy.

[0208] Embodiment 22. A method of identifying one or more treatment options for an individual having metastatic cancer, comprising: (a) assessing microsatellite instability of a sample obtained from the individual; and (b) generating a report including one or more treatment options identified for the individual, wherein microsatellite instability that is MSI-H identifies the individual as one that may benefit from treatment with immune checkpoint inhibitor therapy.

[0209] Embodiment 23. A method of stratifying an individual having cancer for treatment with a therapy, comprising: assessing microsatellite instability in a sample obtained from the individual; and (a) identifying the individual as a candidate for receiving immune checkpoint inhibitor therapy if the microsatellite instability is MSI-H, or (b) identifying the individual as a candidate for receiving a chemotherapy regimen if the microsatellite instability is not MSI-H.

[0210] Embodiment 24. The method of any one of embodiments 20-23, wherein the individual is identified as having increased survival time compared to treatment with a chemotherapy regimen.

[0211] Embodiment 25. A method for predicting survival of an individual having cancer, comprising obtaining knowledge of microsatellite instability of a sample obtained from the individual, wherein if the microsatellite instability is MSI-H for the sample obtained from the individual, the individual is predicted to have increased survival when treated with an immune checkpoint inhibitor compared to treatment with a chemotherapy regimen.

[0212] Embodiment 26. A method for monitoring, evaluating or screening an individual having cancer, comprising obtaining knowledge of microsatellite instability of a sample obtained from the individual, wherein if the microsatellite instability is MSI-H for the sample obtained from the individual, the individual is predicted to have an increased survival time when treated with an immune checkpoint inhibitor compared to treatment with a chemotherapy regimen.

[0213] Embodiment 27. The method of any one of embodiments 20 to 26, wherein the increased survival time is increased overall survival (OS).

[0214] Embodiment 28. The method of any one of embodiments 20 to 26, wherein the increased survival is increased progression-free survival (PFS).

[0215] Embodiment 29. The method of any one of embodiments 1 to 28, further comprising treating the individual with an immune checkpoint inhibitor.

[0216] Embodiment 30. A method for treating an individual having cancer, comprising: (a) assessing microsatellite instability in a sample obtained from the individual; and (b) treating the individual with immune checkpoint inhibitor therapy if the microsatellite instability is assessed as MSI-H.

[0217] Embodiment 31 The method of any one of embodiments 20 to 30, wherein microsatellite instability is assessed by NGS.

[0218] Embodiment 32 The method of any one of embodiments 20 to 31, further comprising treating the individual with chemotherapy if microsatellite instability is not assessed as MSI-H.

[0219] EMBODIMENT 33.The chemotherapy is an alkylating agent, an alkylsulfonate, an aziridine, an ethylenimine, a methylameramine, an acetogenin, a camptothecin, a bryostatin, a kallistatin, a CC-1065, a cryptophycin, a dolastatin, a duocarmycin, an erytherobin, a pancratistatin, a sarcodictin, a spongiostatin, a nitrogen mustard, a nitrosourea, an antibiotic, a dynemicin, a bisphosphonate, an esperamicin, a neocarzinostatin chromophore or a related chromoprotein enediyne antibiotic chromophore, an antimetabolite, a folic acid analogue body, purine analogues, pyrimidine analogues, androgens, antiadrenal agents, folic acid supplements, aldophosphamide glycosides, aminolevulinic acid, eniluracil, amsacrine, bestravcil, bisantrene, edatraxate, deformamine, demecolcine, diazicon, elformitin, elliptinium acetate, epothilone, etoglucide, gallium nitrate, hydroxyurea, lentinan, lonidainin, maytansinoids, mitoguazone, mitoxantrone, mopidamol, nitraelin, pentostatin, phenamet, pirarubicin, rosoxantrone, Podophyllic acid, 2-ethylhydrazide, procarbazine, PSK polysaccharide complex, razoxane, rhizoxin, schizophyllan, spirogermanium, tenuazonic acid, triazicon, 2,2',2"-trichlorotriethylamine, trichothecene, urethane, vindesine, dacarbazine, mannomustine, mitobronitol, mitolactol, pipobroman, gacitosine, arabinoside ("Ara-C"), cyclophosphamide, taxoids, 6-thioguanine, mercaptopurine, platinum coordination complex, vinblastine, platinum, etoposide (VP-16), ifosf 33. The method of embodiment 32, comprising one or more of the following: amides, mitoxantrone, vincristine, vinorelbine, novantrone, teniposide, edatrexate, daunomycin, aminopterin, xeloda, ibandronate, irinotecan, topoisomerase inhibitor RFS2000, difluoromethylornithine (DMFO), retinoids, capecitabine, carboplatin, procarbazine, plicomycin, gemcitabine, navelbine, farnesyl protein transferase inhibitors, transplatinum, or any combination thereof.

[0220] Embodiment 34. The method of any one of embodiments 1 to 33, wherein the cancer is a metastatic cancer.

[0221] Embodiment 35. The cancer is B-cell cancer, melanoma, breast cancer, lung cancer, bronchial cancer, colorectal 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, endometrial cancer, oral cavity cancer, pharyngeal cancer, liver cancer, kidney cancer, testicular cancer, biliary tract cancer, small intestine cancer, appendix cancer, salivary gland cancer, thyroid cancer, adrenal cancer, osteosarcoma, chondrosarcoma, cancer of the blood tissue, adenocarcinoma, inflammatory myoma, myeloma, leukemia ... Fibroblastoma, gastrointestinal stromal tumor (GIST), colon cancer, multiple myeloma (MM), myelodysplastic syndrome (MDS), myeloproliferative disorder (MPD), acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), chronic myeloid leukemia (CML), chronic lymphocytic leukemia (CLL), polycythemia vera, Hodgkin's lymphoma, non-Hodgkin's lymphoma (NHL), soft tissue sarcoma, fibrosarcoma, myxosarcoma, liposarcoma, osteosarcoma, chordoma, angiosarcoma, endothelial sarcoma, lymphoma Pangiosarcoma, lymphangioendothelial sarcoma, synovium, mesothelioma, Ewing's tumor, leiomyosarcoma, rhabdomyosarcoma, squamous cell carcinoma, basal cell carcinoma, adenocarcinoma, sweat gland carcinoma, sebaceous gland carcinoma, papillary carcinoma, papillary adenocarcinoma, medullary carcinoma, bronchogenic carcinoma, renal cell carcinoma, hepatic cancer, bile duct carcinoma, choriocarcinoma, seminoma, embryonal carcinoma, Wilms' tumor, bladder cancer, epithelial carcinoma, glioma, astrocytoma, medulloblastoma, craniopharyngioma, ependymoma, pineal cell tumor, hemangioblastoma, acoustic neuroblastoma, oligodendroglioma, The method according to any one of embodiments 1 to 34, wherein the cancer is meningioma, neuroblastoma, retinoblastoma, follicular lymphoma, diffuse large B-cell lymphoma, mantle cell lymphoma, hepatocellular carcinoma, thyroid cancer, gastric cancer, non-small cell lung cancer (NSCLC), head and neck cancer, small cell carcinoma, essential thrombocythemia, primary myelofibrosis, hypereosinophilic syndrome, systemic mastocytosis, familial eosinophilia, chronic eosinophilic leukemia, neuroendocrine carcinoma, or carcinoid tumor.

[0222] Embodiment 36. The method of any one of embodiments 1 to 35, wherein the cancer is metastatic urothelial carcinoma.

[0223] Embodiment 37. The method of any one of embodiments 1 to 35, wherein the cancer is metastatic gastric adenocarcinoma.

[0224] Embodiment 38. The method of any one of embodiments 1 to 35, wherein the cancer is breast cancer.

[0225] Embodiment 39. The method of any one of embodiments 1 to 35, wherein the cancer is prostate cancer.

[0226] Embodiment 40. The method of embodiment 39, wherein the cancer is metastatic castration-resistant prostate cancer.

[0227] Embodiment 41 The method of any one of embodiments 1 to 35, wherein the cancer is colorectal cancer.

[0228] Embodiment 42. The method of any one of embodiments 1 to 35, wherein the cancer is lung cancer.

[0229] Embodiment 43. The method of embodiment 42, wherein the lung cancer is non-small cell lung cancer (NSCLC).

[0230] Embodiment 44 The method of embodiment 43, wherein the NSCLC is advanced NSCLC (aNSCLC).

[0231] Embodiment 45. The method of any one of embodiments 1 to 35, wherein the cancer is endometrial cancer.

[0232] Embodiment 46. The method of any one of embodiments 1 to 35, wherein the cancer is melanoma.

[0233] 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 proteolysis-targeting chimeric molecule (PROTAC), a cell therapy, a treatment for cancer being tested in a clinical trial, an immunotherapy, or any combination thereof.

[0234] Embodiment 48. The method of embodiment 47, wherein the immune checkpoint inhibitor is a PD-1 inhibitor.

[0235] Embodiment 49. The method of embodiment 47, wherein the checkpoint inhibitors comprise one or more of nivolumab, pembrolizumab, cemiplimab, or dostarlimab.

[0236] Embodiment 50. The method of embodiment 47, wherein the immune checkpoint inhibitor is a PD-L1 inhibitor.

[0237] Embodiment 51. The method of embodiment 47, wherein the checkpoint inhibitors comprise one or more of atezolizumab, avelumab, or durvalumab.

[0238] Embodiment 52. The method of embodiment 47, wherein the immune checkpoint inhibitor is a CTLA-4 inhibitor.

[0239] Embodiment 53. The method of embodiment 52, wherein the CTLA-4 inhibitor comprises ipilimumab.

[0240] Embodiment 54. The method of any one of embodiments 1 to 53, wherein the individual has not previously undergone a chemotherapy regimen for the cancer.

[0241] Embodiment 55. The method of any one of embodiments 1 to 53, wherein the individual has previously undergone a chemotherapy regimen for the cancer.

[0242] Embodiment 56. The aforementioned chemotherapy regimen is selected from the group consisting of alkylating agents, alkylsulfonates, aziridines, ethylenimines, methylameramines, acetogenins, camptothecins, bryostatins, kallistatins, CC-1065, cryptophycins, dolastatins, duocarmycins, erytherobins, pancratistatins, sarcodictins, spongiostatins, nitrogen mustards, nitrosoureas, antibiotics, dynemicins, bisphosphonates, esperamicins, neocarzinostatin chromophores or related chromoprotein enediyne antibiotic chromophores, antimetabolites, folic acid analogs, purine analogs, pyrimidine analogs, androgens, antiadrenal agents, and folic acid supplements. , aldophosphamide glycoside, aminolevulinic acid, eniluracil, amsacrine, bestravcil, bisantrene, edatraxate, defoamin, demecolcine, diazicon, elformitin, elliptinium acetate, epothilone, etoglucide, gallium nitrate, hydroxyurea, lentinan, lonidain, maytansinoids, mitoguazone, mitoxantrone, mopidamol, nitraelin, pentostatin, phenamet, pirarubicin, losoxantrone, podophyllic acid, 2-ethylhydrazide, procarbazine, PSK polysaccharide complex, razoxane, rhizoxin, schizofiran, spirogermanium, tenuazonic acid, triazicon, 2,2',2"-Trichlorotriethylamine, Trichothecenes, Urethanes, Vindesine, Dacarbazine, Mannomustine, Mitobronitol, Mitolactol, Pipobroman, Gacytosine, Arabinoside ("Ara-C"), Cyclophosphamide, Taxoids, 6-Thioguanine, Mercaptopurine, Platinum Coordination Complexes, Vinblastine, Platinum, Etoposide (VP-16), Ifosfamide, Mitoxantrone, Vincristine, Vinorelbine, Novantrone, Teniposide, Etoposide (VP-16), 56. The method of embodiment 55, comprising one or more of datlexate, daunomycin, aminopterin, xeloda, ibandronate, irinotecan, topoisomerase inhibitor RFS2000, difluoromethylornithine (DMFO), retinoids, capecitabine, carboplatin, procarbazine, plicomycin, gemcitabine, navelbine, farnesyl protein transferase inhibitors, transplatinum, or any combination thereof.

[0243] Embodiment 57. The method of any one of embodiments 1 to 56, wherein immune checkpoint inhibitor therapy is the only anti-cancer therapy indicated or administered for the cancer.

[0244] Embodiment 58. The method of any one of embodiments 1 to 56, wherein the immune checkpoint inhibitor therapy is a single active agent therapy.

[0245] Embodiment 59. The method of any one of embodiments 1 to 56, wherein the immune checkpoint inhibitor therapy comprises two or more active agents.

[0246] Embodiment 60. The method of any one of embodiments 1 to 56, wherein the immune checkpoint inhibitor therapy comprises a first round of an immune checkpoint inhibitor and a subsequent round of therapy with a different immune checkpoint inhibitor.

[0247] Embodiment 61. The method of any one of embodiments 1 to 60, wherein the immune checkpoint inhibitor therapy is a first-line therapy for cancer.

[0248] Embodiment 62. The method of any one of embodiments 1 to 56, further comprising treating the individual with an additional anti-cancer therapy.

[0249] Embodiment 63. The method of embodiment 62, wherein the anti-cancer therapy comprises one or more of 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-neoplastic agent, a growth inhibitory agent, a cytotoxic agent, or any combination thereof.

[0250] Embodiment 64. The method of any one of embodiments 1 to 63, wherein the sample is a solid tumor biopsy sample obtained from an individual.

[0251] Embodiment 65. The method of any one of embodiments 1 to 63, wherein the sample is a liquid biopsy sample obtained from the individual.

[0252] Embodiment 66 The method of embodiment 65, wherein the liquid biopsy sample comprises blood, plasma, cerebrospinal fluid, sputum, stool, urine or saliva.

[0253] 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 derived from the cancer.

[0254] Embodiment 68. The method of any one of embodiments 1 to 67, wherein the TMB score or microsatellite instability is determined by sequencing.

[0255] Embodiment 69. The method of embodiment 68, wherein the sequencing comprises the use of massively parallel sequencing (MPS) technology, whole genome sequencing (WGS), whole exome sequencing, targeted sequencing, direct sequencing, or Sanger sequencing technology.

[0256] 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, the plurality of nucleic acid molecules comprising a mixture of tumor and non-tumor nucleic acid molecules; (b) optionally ligating one or more adapters to one or more nucleic acids from the plurality of nucleic acid molecules; (c) amplifying the nucleic acid molecules from the plurality of nucleic acid molecules; (d) capturing a nucleic acid molecule from the amplified nucleic acid molecules, the captured nucleic acid molecule being captured from the amplified nucleic acid molecules by hybridization to one or more bait molecules; and (e) sequencing the captured nucleic acid molecule by a sequencer to obtain a plurality of sequence reads corresponding to one or more genomic loci within a subgenomic interval in the sample.

[0257] Embodiment 71 The method of embodiment 70, wherein the adapter comprises one or more of an amplification primer sequence, a flow cell adapter hybridization sequence, a unique molecular identifier sequence, a substrate adapter sequence, or a sample index sequence.

[0258] Embodiment 72. The method of embodiment embodiment 70 or embodiment 71, wherein amplifying the nucleic acid molecule comprises performing a polymerase chain reaction (PCR) amplification technique, a non-PCR amplification technique, or an isothermal amplification technique.

[0259] Embodiment 73. The method of any one of embodiments 70 to 72, wherein the one or more bait molecules comprise one or more nucleic acid molecules, each nucleic acid molecule comprising a region complementary to a region of a captured nucleic acid molecule.

[0260] Embodiment 74. The method of embodiment 73, wherein the one or more bait molecules each comprise a capture molecule.

[0261] Embodiment 75. The method of embodiment 74, wherein the capture molecule is biotin.

[0262] Embodiment 76. The method of any one of embodiments 1 to 75, wherein the individual is a human.

[0263] Embodiment 77. A kit comprising an immune checkpoint inhibitor and instructions for use according to the method of any one of embodiments 1 to 76.

[0264] Embodiment 1A. A method for identifying an individual having cancer for treatment with immune checkpoint inhibitor therapy comprising determining a tumor mutational burden (TMB) score of a tumor biopsy sample obtained from the individual, wherein the individual is identified for treatment with immune checkpoint inhibitor therapy if the TMB score is at least a threshold TMB score, and wherein the cancer is metastatic urothelial carcinoma, metastatic gastric adenocarcinoma, metastatic endometrial carcinoma, prostate cancer, or non-small cell lung cancer (NSCLC).

[0265] Embodiment 2A. A method of selecting a treatment for an individual having cancer, comprising determining a tumor mutational burden (TMB) score of 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 one who may benefit from treatment with an 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).

[0266] Embodiment 3A. A method of identifying one or more treatment options for an individual with cancer, comprising: determining a tumor mutation burden (TMB) score of a tumor biopsy sample obtained from the individual; generating a report including one or more treatment options identified for the individual, wherein a TMB score that is at least a threshold TMB score identifies the individual as an individual that may benefit from treatment with immune checkpoint inhibitor therapy, and the cancer is metastatic urothelial carcinoma, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC).

[0267] Embodiment 4A. A method of stratifying an individual having cancer for treatment with a therapy, comprising determining a tumor mutational burden (TMB) score of a tumor biopsy sample obtained from the individual; Identifying the individual as a candidate for receiving immune checkpoint inhibitor therapy if the TMB score is at least a threshold TMB score; or identifying the individual as a candidate for receiving the chemotherapy regimen if the TMB score is a threshold TMB score; The method, wherein the cancer is metastatic urothelial carcinoma, metastatic gastric adenocarcinoma, metastatic endometrial carcinoma, prostate cancer, or non-small cell lung cancer (NSCLC).

[0268] Embodiment 5A. The method of any one of embodiments 1A-4A, further comprising assessing microsatellite instability, wherein the identification is further based on the cancer being microsatellite instability high (MSI-H).

[0269] Embodiment 6A. The method of embodiment 5A, wherein microsatellite instability is assessed by next generation sequencing (NGS).

[0270] Embodiment 7A. The method of any one of embodiments 1A-6A, wherein the individual is identified as having increased survival time as compared to treatment with a chemotherapy regimen.

[0271] Embodiment 8A. A method of predicting survival of an individual having cancer, comprising obtaining knowledge of a tumor mutation burden (TMB) score of a tumor biopsy sample obtained from the individual, wherein if the TMB score of the tumor biopsy sample obtained from the individual is at least a threshold TMB score, the individual is predicted to have increased survival when treated with an immune checkpoint inhibitor compared to treatment with a chemotherapy regimen, and wherein the cancer is metastatic urothelial carcinoma, metastatic gastric adenocarcinoma, metastatic endometrial carcinoma, prostate cancer, or non-small cell lung cancer (NSCLC).

[0272] Embodiment 9A. A method of monitoring, evaluating, or screening an individual having cancer, comprising obtaining knowledge of a tumor mutation burden (TMB) score of a tumor biopsy sample obtained from the individual, wherein if the TMB score of the tumor biopsy sample obtained from the individual is at least a threshold TMB score, the individual is predicted to have increased survival when treated with an immune checkpoint inhibitor compared to treatment with a chemotherapy regimen, and the cancer is metastatic urothelial carcinoma, metastatic gastric adenocarcinoma, metastatic endometrial carcinoma, prostate cancer, or non-small cell lung cancer (NSCLC).

[0273] Embodiment 10A. A method of predicting survival of an individual having cancer, comprising obtaining knowledge of a tumor mutation burden (TMB) score of a tumor biopsy sample obtained from the individual, wherein if the TMB score of the tumor biopsy sample obtained from the individual is at least a threshold TMB score, the individual is predicted to have increased survival when treated with an immune checkpoint inhibitor compared to patients having a TMB score that is less than the threshold TMB score, wherein the cancer is metastatic urothelial carcinoma, metastatic gastric adenocarcinoma, metastatic endometrial carcinoma, prostate cancer, or non-small cell lung cancer (NSCLC).

[0274] Embodiment 11A. A method of monitoring, evaluating, or screening an individual having cancer, comprising obtaining knowledge of a tumor mutation burden (TMB) score of a tumor biopsy sample obtained from the individual, wherein if the TMB score of the tumor biopsy sample obtained from the individual is at least a threshold TMB score, the individual is predicted to have increased survival when treated with an immune checkpoint inhibitor compared to patients having a TMB score that is less than the threshold TMB score, wherein the cancer is metastatic urothelial carcinoma, metastatic gastric adenocarcinoma, metastatic endometrial carcinoma, prostate cancer, or non-small cell lung cancer (NSCLC).

[0275] Embodiment 12A. The method of any one of embodiments 7A-11A, wherein the increased survival is increased overall survival (OS).

[0276] Embodiment 13A. The method of any one of embodiments 7A-11A, wherein the increased survival is increased progression-free survival (PFS).

[0277] Embodiment 14A. A method of predicting duration of therapeutic response for an individual having cancer, comprising obtaining knowledge of a Tumor Mutational Burden (TMB) score of a tumor biopsy obtained from the individual, and comparing the TMB score of the sample to a threshold TMB score, wherein if the TMB score is equal to or greater than the threshold TMB score, the individual is predicted to have a longer duration of therapeutic response to an immune checkpoint inhibitor, and 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.

[0278] 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 overall survival (OS), and the shorter duration of the therapeutic response is one or more of decreased PFS and decreased OS.

[0279] Embodiment 16A. A method for treating an individual with cancer, comprising: determining a tumor mutation burden (TMB) score of a tumor biopsy sample obtained from the individual; and treating the individual with an immune checkpoint inhibitor therapy if the TMB score is at least a threshold TMB score; The method, wherein the cancer is metastatic urothelial carcinoma, metastatic gastric adenocarcinoma, metastatic endometrial carcinoma, prostate cancer, or non-small cell lung cancer (NSCLC).

[0280] Embodiment 17A. The method of embodiment 16A, further comprising assessing microsatellite instability, wherein (b) is further based on the cancer being microsatellite instability high (MSI-H).

[0281] Embodiment 18A. The method of embodiment 17A, wherein microsatellite instability is assessed by next generation sequencing (NGS).

[0282] Embodiment 19A. The method of any one of embodiments 1A-18A, further comprising treating the individual with chemotherapy if the TMB score is a threshold TMB score.

[0283] Embodiment 20A.The chemotherapy is selected from the group consisting of alkylating agents, alkylsulfonates, aziridines, ethylenimines, methylameramines, acetogenins, camptothecins, bryostatins, kallistatins, CC-1065, cryptophycins, dolastatins, duocarmycins, erytherobins, pancratistatins, sarcodictins, spongiostatins, nitrogen mustards, nitrosoureas, antibiotics, dynemicins, bisphosphonates, esperamicins, neocarzinostatin chromophores or related chromoprotein enediyne antibiotic chromophores, antimetabolites, and folic acid analogs. , purine analogues, pyrimidine analogues, androgens, antiadrenal agents, folic acid supplements, aldophosphamide glycosides, aminolevulinic acid, eniluracil, amsacrine, bestravcil, bisantrene, edatraxate, deformamine, demecolcine, diazicon, elformitin, elliptinium acetate, epothilone, etoglucide, gallium nitrate, hydroxyurea, lentinan, lonidainin, maytansinoids, mitoguazone, mitoxantrone, mopidamol, nitraelin, pentostatin, phenamet, pirarubicin, rosoxantrone, po Dofilinic acid, 2-ethylhydrazide, procarbazine, PSK polysaccharide complex, razoxane, rhizoxin, schizophyllan, spirogermanium, tenuazonic acid, triazicon, 2,2',2"-trichlorotriethylamine, trichothecenes, urethanes, vindesine, dacarbazine, mannomustine, mitobronitol, mitolactol, pipobroman, gacitosine, arabinoside ("Ara-C"), cyclophosphamide, taxoids, 6-thioguanine, mercaptopurine, platinum coordination complexes, vinblastine, platinum, etoposide (VP-16), ifospha The method of embodiment 19A, comprising one or more of the following: ribavirin, ...

[0284] Embodiment 21A. The method of any one of embodiments 1A to 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.

[0285] Embodiment 22A. The method of any one of embodiments 1A-21A, wherein the threshold TMB score is about 10 mutations / Mb.

[0286] Embodiment 23A. The method of any one of embodiments 1A-22A, wherein the threshold TMB score is 10 mutations / Mb.

[0287] The method of any one of embodiments 1A-22A, wherein the threshold TMB score is about 20 mutations / Mb.The method of any one of embodiments 1A-24A, wherein the TMB score is determined based on about 100 kb to about 10 Mb of sequenced DNA.

[0288] Embodiment 26A. A method according to any one of embodiments 1A to 25A, wherein the TMB score is determined based on about 0.8 Mb to about 1.1 Mb of sequenced DNA.

[0289] Embodiment 27A. The method of any one of embodiments 1A-26A, further comprising treating the individual with an immune checkpoint inhibitor if the TMB score is at least a threshold TMB score.

[0290] Embodiment 28A. The method of any one of embodiments 1A-27A, wherein the cancer is prostate cancer that is metastatic castration-resistant prostate cancer.

[0291] Embodiment 29A. The method of any one of embodiments 1A-27A, wherein the cancer is metastatic urothelial carcinoma.

[0292] Embodiment 30A. The method of any one of embodiments 1A-27A, wherein the cancer is metastatic gastric adenocarcinoma.

[0293] Embodiment 31A. The method of any one of embodiments 1A-27A, wherein the cancer is metastatic endometrial cancer.

[0294] Embodiment 32A. The method of any one of embodiments 1A to 27A, wherein the cancer is NSCLC or advanced NSCLC (aNSCLC).

[0295] Embodiment 33A. The method of any one 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 proteolysis-targeting chimeric molecule (PROTAC), a cell therapy, a treatment for cancer being tested in a clinical trial, an immunotherapy, or any combination thereof.

[0296] Embodiment 34A. The method of embodiment 33A, wherein the immune checkpoint inhibitor is a PD-1 inhibitor.

[0297] Embodiment 35A. The method of embodiment 33A, wherein the checkpoint inhibitors comprise one or more of nivolumab, pembrolizumab, cemiplimab, or dostarlimab.

[0298] Embodiment 36A. The method of embodiment 33A, wherein the immune checkpoint inhibitor is a PD-1 inhibitor.

[0299] Embodiment 37A. The method of embodiment 33A, wherein the checkpoint inhibitor comprises one or more of atezolizumab, avelumab, or durvalumab.

[0300] Embodiment 38A. The method of embodiment 33A, wherein the immune checkpoint inhibitor is a CTLA-4 inhibitor.

[0301] Embodiment 39A. The method of embodiment 38A, wherein the CTLA-4 inhibitor comprises ipilimumab.

[0302] Embodiment 40A. The method of any one of embodiments 1A-39A, wherein the individual has previously been treated for cancer with an anti-cancer therapy.

[0303] Embodiment 41A. The method of embodiment 40A, wherein the anti-cancer therapy is one or more of 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-neoplastic agent, a growth inhibitory agent, a cytotoxic agent, or any combination thereof.

[0304] Embodiment 42A. The method of any one of embodiments 1A-41A, wherein the individual has not previously undergone a chemotherapy regimen for the cancer.

[0305] Embodiment 43A. The method of any one of embodiments 1A-41A, wherein the individual has previously undergone a chemotherapy regimen for the cancer.

[0306] Embodiment 44A. The aforementioned chemotherapy regimen comprises an alkylating agent, an alkylsulfonate, an aziridine, an ethylenimine, a methylameramine, an acetogenin, a camptothecin, a bryostatin, a kallistatin, a CC-1065, a cryptophycin, a dolastatin, a duocarmycin, an erytherobin, a pancratistatin, a sarcodictin, a spongiostatin, a nitrogen mustard, a nitrosourea, an antibiotic, a dynemicin, a bisphosphonate, an esperamicin, a neocarzinostatin chromophore or a related chromoprotein enediyne antibiotic chromophore, an antimetabolite, a folic acid analog, a purine analog, a pyrimidine analog, an androgen, an antiadrenal agent, a folic acid supplement , aldophosphamide glycoside, aminolevulinic acid, eniluracil, amsacrine, bestravcil, bisantrene, edatraxate, defoamin, demecolcine, diazicon, elformitin, elliptinium acetate, epothilone, etoglucide, gallium nitrate, hydroxyurea, lentinan, lonidain, maytansinoids, mitoguazone, mitoxantrone, mopidamol, nitraelin, pentostatin, phenamet, pirarubicin, losoxantrone, podophyllic acid, 2-ethylhydrazide, procarbazine, PSK polysaccharide complex, razoxane, rhizoxin, schizofiran, spirogermanium, tenuazonic acid, triazicon, 2,2',2"-Trichlorotriethylamine, Trichothecenes, Urethanes, Vindesine, Dacarbazine, Mannomustine, Mitobronitol, Mitolactol, Pipobroman, Gacytosine, Arabinoside ("Ara-C"), Cyclophosphamide, Taxoids, 6-Thioguanine, Mercaptopurine, Platinum Coordination Complexes, Vinblastine, Platinum, Etoposide (VP-16), Ifosfamide, Mitoxantrone, Vincristine, Vinorelbine, Novantrone, Teniposide, Etoposide (VP-16), The method of embodiment 43A, comprising one or more of datlexate, daunomycin, aminopterin, xeloda, ibandronate, irinotecan, topoisomerase inhibitor RFS2000, difluoromethylornithine (DMFO), retinoids, capecitabine, carboplatin, procarbazine, plicomycin, gemcitabine, navelbine, farnesyl protein transferase inhibitors, transplatinum, or any combination thereof.

[0307] Embodiment 45A. The method of any one of embodiments 1A-44A, wherein immune checkpoint inhibitor therapy is the only anti-cancer therapy indicated or administered for the cancer.

[0308] Embodiment 46A. The method of any one of embodiments 1A-45A, wherein the immune checkpoint inhibitor therapy is a single active agent therapy.

[0309] Embodiment 47A. The method of any one of embodiments 1A-45A, wherein the immune checkpoint inhibitor therapy comprises two or more active agents.

[0310] Embodiment 48A. The method of any one of embodiments 1A-47A, wherein the immune checkpoint inhibitor therapy comprises a first round of an immune checkpoint inhibitor and a subsequent round of therapy with a different immune checkpoint inhibitor.

[0311] Embodiment 49A. The method of any one of embodiments 1A to 48A, wherein the immune checkpoint inhibitor therapy is a first-line therapy for cancer.

[0312] Embodiment 50A. The method of any one of embodiments 1A-48A, wherein the immune checkpoint inhibitor therapy is a second line therapy for cancer.

[0313] Embodiment 51A. The method of any one of embodiments 1A-50A, further comprising treating the individual with an additional anti-cancer therapy.

[0314] Embodiment 52A. The method of embodiment 51A, wherein the additional anti-cancer therapy comprises one or more of 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-neoplastic agent, a growth inhibitory agent, a cytotoxic agent, or any combination thereof.

[0315] Embodiment 53A. The method of any one of embodiments 1A to 52A, wherein the TMB score or microsatellite instability is determined by sequencing.

[0316] Embodiment 54A. The method of embodiment 53A, wherein the sequencing comprises the use of 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.

[0317] Embodiment 55A. Sequencing comprises: providing a plurality of nucleic acid molecules obtained from a tumor biopsy sample, the plurality of nucleic acid molecules comprising a mixture of tumor and non-tumor nucleic acid molecules; Optionally, ligating one or more adaptors to one or more nucleic acids from the plurality of nucleic acid molecules; amplifying a nucleic acid molecule from the plurality of nucleic acid molecules; capturing a nucleic acid molecule from the amplified nucleic acid molecules, wherein the captured nucleic acid molecule is captured from the amplified nucleic acid molecules by hybridization to one or more bait molecules; The method of embodiment 53A or embodiment 54A, comprising sequencing at least a portion of the captured nucleic acid molecules with a sequencer to obtain a plurality of sequence reads corresponding to one or more genomic loci within the genomic interval in the sample.

[0318] Embodiment 56A. The method of embodiment 55A, wherein the adapter comprises one or more of an amplification primer sequence, a flow cell adapter hybridization sequence, a unique molecular identifier sequence, a substrate adapter sequence, or a sample index sequence.

[0319] Embodiment 57A. The method of embodiment 55A or embodiment 56A, wherein amplifying the nucleic acid molecule comprises performing a polymerase chain reaction (PCR) amplification technique, a non-PCR amplification technique, or an isothermal amplification technique.

[0320] Embodiment 58A. The method of any one of embodiments 55A-57A, wherein the one or more bait molecules comprise one or more nucleic acid molecules, each nucleic acid molecule comprising a region complementary to a region of a captured nucleic acid molecule.

[0321] Embodiment 59A. The method of embodiment 58A, wherein one or more bait molecules each comprise a capture molecule.

[0322] Embodiment 60A. The method of embodiment 59A, wherein the capture moiety is biotin.

[0323] Embodiment 61A. The method of any one of embodiments 1A-60A, wherein the individual is a human.

[0324] Embodiment 62A. The method of any one of embodiments 1A to 61A, wherein the individual is predicted to have an increased time to next treatment (TTNT) when treated with an immune checkpoint inhibitor compared to chemotherapy if the TMB score is at least a threshold TMB score.

[0325] Embodiment 63A. A kit comprising an immune checkpoint inhibitor and instructions for use according to the method of any one of embodiments 1A to 62A. EXAMPLES

[0326] Example 1: Tumor mutational burden as a predictive biomarker for immune checkpoint inhibitor versus chemotherapy efficacy in first-line metastatic urothelial carcinoma. This example shows a comparison of real-world patient outcomes on immune checkpoint inhibitors (ICPIs) compared to patients on chemotherapy, using outcomes such as PFS and OS, relative to tumor mutation burden (TMB).

[0327] Study design and patient selection: The cohort included patients with a confirmed diagnosis of metastatic urothelial carcinoma (mUC) included in the de-identified ClinicoGenomics database. All patients underwent genomic testing using comprehensive genomic profiling (CGP) assays.

[0328] De-identified clinical data were derived from approximately 280 US cancer clinics (approximately 800 sites of care). Retrospective cross-sectional clinical data were derived from electronic health records (EHRs) and included patient-level structured or unstructured data curated via technology-enabled extraction of clinical notes and radiology / pathology reports, which were linked to study-derived genomic data by de-identified deterministic matching (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 included demographic, clinical, and laboratory characteristics, timing of treatment exposure, treatment progression, and survival.

[0329] Patients were included in the study if they received first-line single-agent anti-PD1 axis therapy (pembrolizumab, atezolizumab, nivolumab, durvalumab, or avelumab) or a carboplatin-based chemotherapy regimen and had TMB assessed via tissue biopsy. Patients who received concomitant ICPI and chemotherapy were not included. To reduce immortal time in the analysis, patients whose CGP report was received after discontinuation of first-line therapy were excluded.

[0330] Comprehensive genomic profiling. Hybrid capture-based next-generation sequencing (NGS) assays were performed on patient tumor samples in a Clinical Laboratory Improvement Amendments (CLIA)-certified and College of American Pathologists (CAP)-accredited laboratory. The assays interrogate exons from a minimum of 324 cancer-associated genes and select introns from a minimum of 28 genes for rearrangement detection. Samples were evaluated for alterations 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). Tumor mutational burden (TMB) was determined for up to 1.1 Mb of sequenced DNA (see Chalmers et al., “Analysis of 100,00 human cancer genomes reveals the landscape of tumor mutational burden,” Genome Med. 2017;9(1):34). MSI was determined for 95-114 loci as previously described (see Trabucco et al., “A Novel Next-Generation Sequencing Approach to Detecting Microsatellite Instability and Pan-Tumor Characterization of 1000 Microsatellite Instability-High Cases in 67,000 Patient Samples,” J. Mol. Diagn. 2019;21(6):1053-66).

[0331] Outcomes. PFS was calculated from the start of first-line treatment to a progression event (radiological, clinical, or pathological) or death. Patients without an observed record of a progression event or mortality were right-censored at the date of the last clinic visit. TTNT was calculated from the date of treatment initiation to the start of the next line of treatment (from any cause) or death. Patients who had not yet reached the next line of treatment or death were right-censored at the date of the last clinic visit or structure activity. OS was calculated from the start of first-line treatment to death from any cause, and patients without a record of mortality were right-censored at the date of the last clinic visit. Because patients are not entered into the database until the CGP report is delivered, the OS risk interval was left-truncated relative to the date of the CGP report to further account for immortal time. Censoring and independent truncation were assessed by Kendall's tau for both the ICPI and chemotherapy groups, separately or in combination, and p<0.05 was considered acceptable. The database mortality information is a composite of three sources: documents in the EHR, the Social Security Death Index, and commercial mortality datasets mined data from obituaries and funeral homes, with reported validation against the National Death Index (see Zhang et al., “Validation analysis of a composite real-world mortality endpoint for patients with cancer in the United States,” Health Services Research).

[0332] Statistical analysis. Differences in time-to-event outcomes were assessed by log-rank test and Cox proportional hazards (PH) model. Chi-square test and Wilcoxon rank sum test were used to assess differences between groups for dependent variables and between groups for continuous variables. No adjustment for multiple comparisons was performed, and p values ​​are reported to quantify the strength of association for biomarkers and each outcome, not for null hypothesis significance testing, with the commonly adopted interpretation being that the consistency of multiple outcome measures is associated (PFS, TTNT, OS) and that there are no independent outcome measures.

[0333] Missing values ​​were handled by simple imputation with base expectations determined using random forests with the R package "missForest." In subsequent analyses, imputed values ​​were treated identically to measured values.

[0334] The propensity analysis used a full matching technique (R package "MatchIt") so that no patients were excluded and chemotherapy was weighted. Weighting was capped at 10 equivalents to limit the influence of each observation. Among patients receiving chemotherapy, patients with characteristics most similar to the ICPI patient population were weighted more heavily and patients less similar to ICPI patients were weighted less. These weightings were included in all Kaplan-Meier visualizations and Cox PH models unless otherwise noted. Features included for adjustment of propensity models: age, ECOG performance score, eGFR, stage at diagnosis, and TMB. Standardized mean difference (SMD) was used to assess balance, and within 10% is considered acceptable (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," StatMed. 2015;34(28):3661-79).

[0335] For a 10mut / Mb (10 mutations per megabase) threshold, propensity weights were generated separately for the TMB≧10 and TMB<10 groups for best within-group balance. Predictive biomarker associations (see Ballman, “Biomarker: Predictive or Prognostic?” J. Clin. Oncol. 2015;33(33):3968-71) used propensity-weighted multivariate Cox proportional hazards regression models containing the following variables: drug class (ICPI or taxane), TMB (high vs. low), and interaction terms between drug class and biomarker. Hazard ratios for subgroup analyses were generated from the Cox models stratified by group (i.e., TMB high vs. low). R version 3.6.3 software was used for all statistical analyses.

[0336] Results - Characteristics of the Analysis Cohort. After selection, the cohort consisted of 401 unique patients treated in the first-line setting, with 245 patients receiving ICPI and 156 patients receiving carboplatin-based chemotherapy (see Table 1 below). When assessing differences in patients treated with ICPI vs. carboplatin-based chemotherapy, there were no major imbalances in gender, TMB, eGFR, practice setting, primary cancer anatomic site, smoking status, race, or PD-L1 staining (although only 30% of the cohort had PD-L1 staining available). Patients who received ICPI were older (median 69, IQR 63-76 vs. median 73, IQR 66-80, p<0.001), less likely to be stage IV at diagnosis (p<0.001), and have a higher ECOG score (p<0.001). Patients who received chemotherapy had very different subsequent treatments (p<0.001), including a very high frequency of ICPI use (41.7% vs. 3.7%). 122 of 401 patients (30.4%) had a TMB ≥ 10, and this subgroup showed a similar imbalance (see Table 2 below). [Table 1-1] [Table 1-2] [Table 2-1] [Table 2-2]

[0337] Propensity weighting. After propensity weighting in the TMB < 10 group, there were no features with the characteristics of > 10% SMD. After propensity weighting in the TMB ≥ 10 group, there was a residual imbalance of > 10% SMD such that patients receiving ICPI versus chemotherapy were more likely to be in stage I-III at initial diagnosis and more likely to have an ECOG score of ≥ 3 (Figures 1A-1B).

[0338] Patients with a TMB of at least 10 had more favorable PFS, TTNT, and OS in first-line single-agent ICPI. PFS, TTNT, and OS by ICPI were stratified by whether patients had a TMB<10 or TMB≥10. Compared with patients with TMB<10, patients with TMB≥10 had more favorable PFS (HR: 0.59, 95% CI: 0.41-0.85, p=0.0048), TTNT (HR: 0.59, 95% CI: 0.43-0.83, p=0.0020), and OS (HR: 0.47, 95% CI: 0.32-0.68, p=0.0001) (Figures 2A-2C).

[0339] Comparing outcomes for patients receiving first-line ICPI versus carboplatin-based chemotherapy, adjusting for imbalance in treatment assignment by propensity weighting (Figures 1A-1B), patients with TMB ≥ 10 had more favorable estimates for PFS (HR: 0.51, 95% CI: 0.32-0.82, p = 0.0058), TTNT (HR: 0.56, 95% CI: 0.35-0.91, p = 0.0197), and OS (HR: 0.56, 95% CI: 0.29-1.08, p = 0.084). whereas patients with TMB<10 had similar or less favorable PFS (HR: 1.26, 95% CI: 0.89-1.80, p=0.20), TTNT (HR: 0.89, 95% CI: 0.68-1.18, p=0.42) and OS (HR: 1.11, 95% CI: 0.79-1.59, p=0.54) (Figures 3A-3F). ICPI vs chemotherapy assessments unadjusted for treatment allocation imbalance show similar associations in total (Figures 4A-4F).

[0340] We further compared outcomes in patient subgroups identified by TMB or PD-L1. PD-L1 staining was available for only 35.7% of the cohort. Confidence intervals were unexpectedly wider in the PD-L1 group than in the TMB group, but the main effect estimates for PD-L1 CPS ≥ 10 were weaker than those for TMB ≥ 10 for PFS, TTNT, and OS (Figures 5A-5C).

[0341] The analytical cohort was compared to a randomized controlled trial population. First-line patients in the analytical cohort were compared to first-line patients in the randomized controlled trial for patient characteristics, using ECOG score as a proxy for patient frailty (Figure 6A). DANUBE, IMvigor130, and KEYNOTE-361 studies reported that 53.2%, 52.2%, and 44.8% of patients had an ECOG score of 0, while 0.3% of the real-world analytical cohort had an ECOG score of 0, respectively. DANUBE, IMvigor130, and KEYNOTE-361 studies reported that 0%, 10.8%, and 6.9% of patients had an ECOG score of 2, while 42.3% of the real-world analytical cohort had an ECOG score of 2, respectively. None of the first-line phase III trials included patients with an ECOG score of 3 or higher, and 19.2% of the real-world analysis cohort had an ECOG score of 3 or higher.

[0342] The combined real-world and study outcomes of ICPI versus carboplatin-based chemotherapy with TMB were next evaluated. There was consistent enrichment for benefit of ICPI versus carboplatin-based chemotherapy in the TMB ≥ 10 subgroup across both randomized controlled trial (RCT) and real-world analyses (Figures 6B-6C).

[0343] Conclusions: A high TMB cutoff (e.g., 10 mut / Mb) has clinical validity in the first-line setting for identifying patients with mUC who are more likely to have improved outcomes in single-agent ICPI compared with chemotherapy (e.g., non-cisplatin chemotherapy).

[0344] Example 2: Real-world validation of tumor mutation burden as a predictive biomarker for efficacy of immune checkpoint inhibitors versus chemotherapy in metastatic gastric adenocarcinoma across diverse patients and clinical practices This example shows a real-world comparison of patient outcomes in immune checkpoint inhibitors (ICPIs) versus chemotherapy, stratified by biomarkers including tumor mutational burden (TMB) score.

[0345] Real-world analysis design. Two complementary techniques were used to evaluate biomarker validity and drug efficacy using observational data: propensity analysis and crossover analysis, with interpretation placed on the consistency of observations across different cohorts and evaluation methods, similar to previous real-world analyses in 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). The efficacy of ICPI versus I chemotherapy was first evaluated among patients in the second-line setting, stratified by TMB, and then patients with TMB ≥ 10mut / Mb enhanced the relative efficacy of second-line ICPI when used after first-line chemotherapy within the same patients (flowchart in Figure 7). Finally, outcomes of patients who received first-line ICPI compared with first-line chemotherapy were evaluated (Figure 7).

[0346] Patient Selection. The study included patients with a confirmed diagnosis of gastric adenocarcinoma. All patients underwent genomic testing using a comprehensive genomic profiling (CGP) assay. De-identified clinical data were derived from approximately 280 US cancer clinics (approximately 800 care sites). Retrospective cross-sectional clinical data were derived from electronic health records (EHRs) and included patient-level structured or flight-augmented data curated via technology-enabled extraction of clinical notes and radiology / pathology reports, which were linked to genomic data by de-identified deterministic matching (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,” JAMA321;1391-1399, 2019). Clinical data included demographic, clinical, and laboratory characteristics, timing of treatment exposure, and survival.

[0347] Patient records were included in the study if they received first- or second-line single-agent anti-PD1 axis therapy or standard chemotherapy (platinum regimen in first-line and non-platinum regimen in second-line) and had TMB assessed via tissue specimen. Patients who received concomitant ICPI and chemotherapy were not included. Patients were required to additionally test negative for ERBB2 amplification and not receive anti-HER2 agents. The analysis was performed in three cohorts after the aforementioned exclusions:

[0348] 2L comparative efficacy cohort: patients who received platinum chemotherapy in first-line, patients who received platinum chemotherapy in second-line, and patients who received single-agent ICPI or non-platinum chemotherapy in second-line.

[0349] Consecutive cohorts: patients who received platinum chemotherapy in first-line, patients who received platinum chemotherapy in second-line, and patients who received single-agent ICPI in second-line.

[0350] 1L comparative efficacy cohort: Patients who received either a single-agent ICPI or a platinum-containing chemotherapy regimen in first-line.

[0351] Comprehensive genomic profiling: Hybrid capture-based next-generation sequencing (NGS) assays were performed on patient tumor samples in a Clinical Laboratory Improvement Amendments (CLIA)-certified and College of American Pathologists (CAP)-accredited laboratory. The assays interrogate exons from a minimum of 324 cancer-associated genes and select introns from a minimum of 28 genes for rearrangement detection. Samples were evaluated for alterations as previously described (Frampton et al., “Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing,” Nat Biotechnol 31:1023-31, 2013). Tumor mutational burden (TMB) was determined for up to 1.1 Mb of sequenced DNA (Chalmers et al., “Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden,” Genome Med 9:34, 2017). MSI was determined for 95–114 loci as previously described (Trabucco et al., “A Novel Next-Generation Sequencing Approach to Detecting Microsatellite Instability and Pan-Tumor Characterization of 1000 Microsatellite Instability-High Cases in 67,000 Patient Samples,” J. Mol. Diagn 21:1053-1066, 2019).

[0352] Outcomes: Time to next treatment (TTNT), such as PFS, is a time-to-event proxy for the clinical effect of a drug (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). TTNT was calculated from the date of treatment initiation to initiation of the next line of treatment (from any cause) or death. Patients who had not yet reached the next line of treatment or death were right-censored at the date of last clinic visit or structure activity. Overall survival (OS) was calculated from the date of first-line treatment initiation to death from any cause, and patients without documented mortality were right-censored at the date of last clinic visit or structure activity. Because patients cannot be entered into the database until the CGP report is delivered, OS risk intervals were left truncated relative to the date of the CGP report to account for immortal 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 mortality information is a composite of three sources: documentation within electronic health records (EHRs), the Social Security Death Index, and commercial mortality dataset mining data from obituaries and funeral homes.This mortality information has been externally validated against the National Death Index (Zhang et al., “Validation analysis of a composite real-world mortality endpoint for patients with cancer in the United States,” Health Services Research).

[0353] Statistical Analysis: Differences in time-to-event outcomes were assessed by log-rank tests and Cox proportional hazards (PH) models. Chi-square and Wilcoxon rank-sum tests were used to assess differences between groups for dependent variables and between groups for continuous variables, respectively. No adjustment for multiple comparisons was performed, and p-values ​​are reported to quantify the strength of association for biomarkers and each outcome, not for null hypothesis significance testing, and the widely adopted interpretation is that the consistency of multiple outcome measures across defined cohorts (between vs. within patients) is considered to be coordinated (TTNT, OS) and not independent outcome measures. The default interpretation is that biomarkers that correlate with OS but not TTNT within a cohort are likely confounding artifacts, and biomarkers that correlate with TTNT but not OS are likely not significant. In addition, effect size estimates may vary by cohort, and the default assumption is that biomarker effects should not be specific to any of the cohorts being evaluated.

[0354] Missing values ​​were handled by simple imputation with expected values ​​determined using random forests with the R package "missForest." In subsequent analyses, imputed values ​​were treated identically to measured values.

[0355] Propensity analysis used a full matching technique (R package "MatchIt") so that no patients were excluded and chemotherapy was weighted. Weighting was capped at 10 equivalents to limit the influence of each observation. Among patients receiving chemotherapy, patients with characteristics most similar to the ICPI patient population were weighted more heavily and patients less similar to ICPI patients were weighted less. These weightings were included in all Kaplan-Meier visualizations and Cox PH models unless otherwise noted. Available characteristics related to ICPI treatment assignment to chemotherapy were included for adjustment in the propensity models: ECOG (0-2 vs. 3+), abnormal labs (bilirubin above ULN and / or albumin below ULN), PD-L1 (CPS5 vs. none), stage at diagnosis (stage IV vs. none), surgery (yes vs. no) and TMB (continuous). To assess balance, standardized mean differences (SMDs) are used, with a difference within 10% considered acceptable (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).

[0356] For the 10 mut / Mb threshold, propensity weights were generated separately for the TMB ≥ 10 and TMB < 10 groups for best within-group balance. Predictive biomarker associations (see Ballman, “Biomarker: Predictive or Prognostic?” J Clin Oncol 33:3968-71, 2015) used propensity-weighted multivariate Cox proportional hazards regression models containing the following variables: drug class (ICPI or taxane), TMB (high vs. low), and interaction terms between drug class and biomarker. Models assessing patient-treatment interactions in continuous cohorts additionally utilize robust variables calculated by general estimating equations within an independent structure clustered and operating on individual patients. Hazard ratios were then generated from the adjusted Cox models stratified by group (i.e., TMB high vs. low). R version 3.6.3 software was used for all statistical analyses.

[0357] Results. 2L comparative efficacy cohort: After selection, 263 patients received second-line non-platinum chemotherapy after first-line platinum chemotherapy, and 99 patients received second-line ICPI after first-line platinum chemotherapy. No p<0.05 differences were observed by treatment group for age, sex, stage at diagnosis, smoking status, previous surgery, ECOG, albumin, or bilirubin. However, patients receiving ICPI had higher TMB (p<0.001), PD-L1 CPS score (p<0.001), and more frequent MSI-H (p<0.001). See Table 3 below. [Table 3-1] [Table 3-2]

[0358] Consecutive cohort: After selection, 65 patients received first-line platinum chemotherapy followed by second-line ICPI. Of these, 17 had TMB≧10 and 48 had TMB<10. No p<0.05 differences were observed by TMB group for age, sex, stage at diagnosis, smoking status, previous surgery, ECOG, albumin, bilirubin, or PD-L1. However, TMB and MSI were highly correlated (p<0.001), and in the TMB≧10 group, 14 had MSI-H, 2 had MSS, and 1 had unknown MSI status. In the TMB<10 group, 0 had MSI-H, 37 had MSS, and 11 had unknown MSI. See Table 4 below. [Table 4-1] [Table 4-2]

[0359] 1L Comparative Efficacy Cohort: After selection, 659 patients received first-line platinum chemotherapy and 33 patients received first-line ICPI. Compared to patients receiving chemotherapy, patients receiving ICPI were older (66 vs. 70, p=0.038), less likely to be stage IC at diagnosis (66.5% vs. 27.3%, p<0.001), more likely to have prior surgery (20% vs. 69.7%, p<0.001), and more likely to have PD-L1 testing available (p<0.001). See Table 5 below. [Table 5-1] [Table 5-2]

[0360] By adjusting for known treatment allocation imbalances, patients receiving second-line ICPI versus chemotherapy had more favorable outcomes if they had TMB ≥ 10 mut / Mb but not TMB < 10 (Figures 8A-8D). In the TMB < 10 subgroup, all features had SMB < 10% after weighting. In the TMB ≥ 10 subgroup, the imbalance was greatly reduced, but residual imbalance of SMD ≥ 10% existed, such that patients receiving ICPI were more likely to have had surgery, have PD-L1 CPS ≥ 5, be older, have abnormal test results, and have high TMB. Among patients treated with single-agent ICPI versus non-platinum chemotherapy in the second line (after prior platinum chemotherapy in the first line), patients with TMB<10 had comparable TTNT (HR: 0.96, 95% CI: 0.69-1.34, p=0.81) and OS (HR: 1.1, 95% CI: 0.73-1.64, p=0.66). However, patients with TMB≥10 had more favorable TTNT (HR: 0.16, 95% CI: 0.07-0.35, p=0.0001) and OS (HR: 0.21, 95% CI: 0.09-0.49, p=0.0004). Sensitivity analyses unadjusted for imbalance show similar results (Figures 9A-9D).

[0361] Patients who received second-line ICPI after first-line chemotherapy had more favorable outcomes in second-line ICPI compared to first-line chemotherapy when TMB ≥ 10 but not TMB < 10. TTNT of first-line chemotherapy was visualized for those with TMB < 10 (Figure 10A) and those with TMB ≥ 10 (Figure 10B), with bars colored by MSI status. MSI status was significantly correlated with TMB threshold in this cohort, but no patients had MSI-H with TMB < 10, and 14 of 17 with TMB ≥ 10 had MSI-H (2 had MSS, 1 had MSI unknown). Two with MSS and TMB ≥ 10 had no record of next treatment until 9.7 and 16.0 months after starting ICPI. Median TTNT of second-line ICPI in the TMB < 10 group was 3.3 months (95% CI: 2.2-8.0). Point estimates and confidence intervals from the Cox model comparing within-patient TTNT are shown in Figure 10C. Unadjusted overall survival from the start of first-line chemotherapy with TMB is shown in Figure 10D.

[0362] TMB≧10 and MSI-H are stronger predictive biomarkers for ICPI vs. chemotherapy efficacy than PD-L1 CPS≧5. Although MSI-H status correlates strongly with increasing TMB values ​​(FIGS. 11A-11B), PD-L1 CPS≧5 does not have a specific enrichment in patients with high TMB (Table 6 below), suggesting a degree of independence in these cohorts. PD-L1 scoring was not available for 47% of the second-line comparative efficacy cohort and 40% of the sequential cohorts. However, the prevalence of patients with PD-L1 CPS≧5 was much higher than TMB>10 or MSI-H. In the 2L ICPI vs. chemotherapy cohorts as well as in the sequential analysis, patients identified by TMB≧10 and / or MSI-H had similar prevalence, with enrichment for observed outcomes favoring ICPI vs. chemotherapy (FIGS. 11A-11C). For TTNT but not OS, there was a slight enrichment for the observed outcome favoring ICPI versus chemotherapy in patients identified by PD-L1 CPS ≥5. [Table 6]

[0363] The KeyNote-061 and real-world cohorts have very different patient populations and drug-class-specific TMB associations. Using the ECOG performance score as a proxy for overall patient frailty across cohorts, KeyNote-061, a phase III randomized, controlled trial comparing second-line pembrolizumab to ECOG in the second-line comparative efficacy cohort, shows a broad range of characteristics from paclitaxel (Shitara et al., “Pembrolizumab versus paclitaxel for previously treated, advanced gastric or gastro-oesophageal junction cancer (KEYNOTE-061): a randomized, open-label, controlled, phase 3 trial,” Lancet 392:123-133, 201812A). Overall survival subgroup analysis for high TMB in KeyNote-061 was reported as a post-hoc analysis by the FDA (Marcus et al., “FDA Approval Summary: Pembrolizumab for the Treatment of Tumor Mutational Burden-High Solid Tumors,” Clin Cancer Res, 2021) and is shown together with the in-patient OS assessment of the second-line comparative efficacy cohort (Figure 12B). The clinical trial assay used for KeyNote-061 TMB assessment was a whole exome sequencing assay, and “high” TMB was defined as a TMB ≥ 10 6 The most consistent cut-point was determined for the FDA-approved assay.

[0364] Adjusting for known treatment allocation imbalances, patients receiving first-line ICPI versus chemotherapy had more favorable outcomes when TMB ≥ 10 but not TMB < 10 (Figures 13A-13D). In the TMB < 10 subgroup, residual imbalances remained such that patients receiving ICPI were more likely to have no PD-L1 score and were more likely to have abnormal labs. In the TMB ≥ 10 subgroup, patients receiving ICPI were more likely to have stage IV disease at diagnosis. Among patients treated with single-agent ICPI versus non-platinum chemotherapy in first-line, patients with TMB < 10 had inferior TTNT (HR: 2.42, 95% CI: 1.29-4.57, p = 0.0062) and comparable or worse OS (HR: 1.71, 95% CI: 0.82-3.57, p = 0.16). However, patients with TMB ≥ 10 had a more favorable TTNT (HR: 0.14, 95% CI: 0.04-0.52, p = 0.0034) and similar to favorable OS (HR: 0.45, 95% CI: 0.11-1.82, p = 0.26). Sensitivity analyses not adjusted for imbalance show similar results (Figures 14A-14D).

[0365] In conclusion, the results indicate that the clinical validity of TMB ≥ 10 in a diverse real-world patient population does not qualify for clinical trials. By using two complementary approaches for comparative validity that partially overcome their respective limitations, consistent and strong enrichment was observed for ICPI versus chemotherapy effect in both inter- and intra-patient assessments for TMB ≥ 10, as well as in NGS-assessed MSI. Consistent results of the same magnitude were not observed for PD-L1 CPS ≥ 5. TMB ≥ 10 robustly identifies metastatic gastric patients with favorable outcomes in second-line single-agent ICPI compared with chemotherapy, and more diverse treatment settings than in registration clinical trials, in the patient population. The effect in the first-line data is consistent with the second-line observations. The results suggest that first-line trials of ICPI versus chemotherapy (without chemotherapy) may be successful if selected with TMB ≥ 10.

[0366] Example 3: Tumor mutational burden as a predictive biomarker for immune checkpoint inhibitor versus taxane chemotherapy efficacy in metastatic castration-resistant prostate cancer: a real-world biomarker analysis. This example shows a comparison of treatment class-specific outcomes for patients with metastatic castration-resistant prostate cancer (mCRPC) on ICPI versus taxane chemotherapy, stratified by TMB score.

[0367] Genomic data were linked to clinical variables and outcomes in a cohort of patients with mCRPC. De-identified cross-sectional clinical data from approximately 280 US academic- or community-based cancer clinics were derived from electronic health records, curated via technology-enabled extraction, and linked to genomic testing with comprehensive genomic assays. Forty-five patients (14 with a TMB of at least 10 and 31 with a TMB of less than 10) received single-agent anti-PD-1 axis ICPI. 696 patients (30 with a TMB of at least 10 and 666 with a TMB of less than 10) received a single-agent taxane at physician's option without randomization. For time to next treatment (TTNT) and overall survival (OS) assessments, imbalances between treatment arms were adjusted with propensity weighting.

[0368] 741 patients were identified and included in the analysis. Patients who received ICPI for taxanes had higher TMB (median 2.5 vs. 3.5, p<0.001), higher ECOG score (p=0.057), and more prior taxane use (53.7% vs. 73.3%, p=0.01). Baseline patient characteristics (overall and within ICPI for taxane subgroups), as well as comparison of characteristics between subgroups, are provided in Table 7 below. [Table 7]

[0369] Figure 15 shows PSA response of patients evaluable for PSA response receiving single-agent taxane therapy and stratified by TMB less than 10 and TMB at least 10. Figure 16 shows PSA response of patients evaluable for PSA response receiving single-agent anti-PD1 axis therapy. Most patients with a TMB of at least 10 responded to single-agent anti-PD1 axis therapy, and most patients with a TMB of less than 10 did not respond. No difference was observed in TMB levels for taxanes among patients with evaluable PSA response. No patients had a PSA decline of 50% or more to ICPI when TMB was less than 10. Four of nine patients with a TMB of at least 10 had a PSA decline of 50% or more.

[0370] Figures 17A-17D show TTNT and OS stratified by TMB less than 10 or at least 10. Patients with TMB less than 10 undergoing ICPI for taxanes had worse TTNT (median 4.1 months vs. 2.4 months, HR: 2.7, 95% CI, 1.7-4.0, p<0.001) and numerically worse OS (median 6.0 months vs. 4.2 months, HR: 1.08, 95% CI, 0.68-1.7, p=0.73). In contrast, ICPI of at least 10 TMB versus taxane use was associated with more favorable TTNT (median 2.4 vs. 8.0 months, HR: 0.37, 95% CI: 0.15-0.87, p=0.022) and OS (median 4.2 vs. 19.9 months, HR: 0.23, 95% CI: 0.10-0.57, p=0.0014). Of all 741 patients, 44 had at least 10 TMB, 22 had microsatellite instability-high (MSI-H), and 20 had both. The treatment interaction with at least 10 TMB (TTNT: p<0.001, OS: p=0.021) was stronger than that with MSI-H (TTNT: p=0.0038, OS: p=0.080).

[0371] In conclusion, these data indicate that ICPI is a viable alternative to taxane chemotherapy for patients with mCRPC with a TMB of at least 10.

[0372] Example 4A: Clinical and genomic characteristics of patients with durable benefit from immune checkpoint inhibitors (ICPIs) in advanced non-small cell lung cancer (aNSCLC) Materials and Methods Patient Selection Patients with a confirmed diagnosis of advanced NSCLC included in the de-identified Clinicogenomics database were selected for evaluation.

[0373] All patients underwent genomic testing using a comprehensive genomic profiling (CGP) assay. Additionally, some patients received PD-L1 DAKO 22C3 or Ventana SP142 IHC assays. De-identified clinical data were derived from approximately 280 US cancer clinics (approximately 800 care sites). Retrospective cross-sectional clinical data were derived from electronic health records (EHRs) and included patient-level structured or unstructured data curated via technology-enabled extraction of clinical notes and radiology / pathology reports, which were linked to genomic data by de-identified deterministic matching (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. Jama 2019;321:1391-1399). Clinical data included demographic, clinical, and laboratory characteristics, timing of treatment exposure, and survival time.

[0374] Patients were included in this study if they received first-line single-agent anti-PD1 (pembrolizumab) or anti-PD1 (pembrolizumab) + chemotherapy and had tumor mutation burden (TMB) assessed via tissue samples collected before the start of first-line (1L) therapy. Patients should have additionally tested negative for EGFR mutations and ALK / ROS1 / RET rearrangements via comprehensive genomic profiling (CGP). Patients who were diagnosed with advanced NSCLC more than 90 days before their first structural activity or who received a CGP report more than 60 days after their last structural activity date were excluded in order to (a) capture all therapies received before CGP and (b) exclude patients who left the network before CGP. Before the study described in this example began, the study protocol was approved by the Institutional Review Board.

[0375] Comprehensive Genomic Profiling Comprehensive genomic profiling (CGP) was performed on hybridization-captured, adaptor ligation-based libraries using DNA and / or RNA extracted from FFPE samples in a Clinical Laboratory Improvement Amendments (CLIA)-certified and College of American Pathologists (CAP)-accredited laboratory. Samples were sequenced for up to 406 cancer-associated genes 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 mutational burden (TMB) was determined for up to 1.24 Mb of sequenced DNA (Compared to standard process results in Chalmers ZR, Connelly CF, Fabrizio D et al. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med 2017;9:34).

[0376] 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 the VENTANA SP142 assay, i.e., in parallel with the CGP. The results of the DAKO 22C3 PD-L1 IHC and VENTANA SP142 assays were interpreted according to the manufacturer's instructions for TPS and TC, respectively. The DAKO 22C3 PD-L1 IHC and VENTANA SP142 assays were interpreted using the DAKO Tumor Proportion Scoring (TPS) method, in which tumor expression of PD-L1 is quantified. The DAKO TPS scoring method is: TPS=#PD-L1 positive tumor cells / (total#of PD-L1 positive+PD-L1 negative tumor cells) (DAKO.PD-L1 IHC 22C3 pharmDx Interpretation Manual-NSCLC). The Ventana SP142 assay, like the DAKO assay, also assessed the tumor cell score (TC) (PD-L1 positive tumor cells / (total number of PD-L1 positive tumor cells + PD-L1 negative tumor cells)).

[0377] Outcomes Overall survival (OS) was calculated from the start of first-line treatment to death from any cause, and patients without documented mortality were right-censored at the date of last clinic visit or structure activity. Because patients are not entered into the database until the CGP report is delivered, OS risk intervals were left-truncated relative to the date of the CGP report to account for immortal time (McGough SF, Incerti D, Lyalina S et al. Penalized regression for left-truncated and right-censored survival data. Stat Med 2021; Brown S, Lavery JA, Shen R et al. Implications of Selection Bias Due to Delayed Study Entry in Clinical Genomic Studies. JAMA Oncology 2021). Database mortality information is a composite of three sources: documentation in electronic health records (EHRs), the Social Security Death Index, and commercial mortality dataset mining data from obituaries and funeral homes. This mortality information was externally validated against the National Death Index with >90% accuracy (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 Dec;56(6):1281-1287). Progression-free survival (PFS) was calculated from the start of treatment to the date of first progression >14 days after the start of treatment or until death. Patients were censored at the date of last clinic visit if no progression or death was observed. Median PFS and OS values ​​were estimated in months with 95% confidence intervals.

[0378] Statistical analysis and interpretation Differences in time-to-event outcomes were assessed by log-rank tests and Cox proportional hazards (PH) models. Chi-square and Wilcoxon rank-sum tests were used to assess differences between groups for dependent variables and between groups for continuous variables. P values ​​were corrected for multiple testing. Multivariate Cox proportional hazards models were fitted for PFS and OS to estimate adjusted hazard ratios and their significance. Characteristics included in the Cox models were TMB status, PDL1 status, age at treatment initiation, Eastern Cooperative Oncology Group (ECOG) performance score (0–1, 2+, and unknown), metastatic status, smoking history, disease histology, stage at initial diagnosis, and STK11 mutation status. For interaction analyses, the same multivariate Cox models incorporated interaction terms between therapy class and biomarkers.

[0379] Propensity analysis was achieved with the R package "MatchIt" using inverse probability of treatment weighting targeting the mean treatment effect when comparing outcomes between biomarker-positive vs. -negative cohorts. Features used in the propensity model were: ECOG (0-1, 2+, and unknown), age at initiation of therapy, PD-L1 (TPS ≥ 1 vs. none), stage at diagnosis (stage IV vs. none), metastatic status, and smoking history. Standardized mean differences (SMDs) were used to assess balance, with a difference within 10% 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).

[0380] Predictive biomarker associations (see Ballman KV. Biomarker: Predictive or Prognostic? J Clin Oncol 2015;33:3968-3971) used propensity-weighted multivariate Cox proportional hazards regression models containing the following variables: drug class (ICPI or ICPI + chemotherapy), TMB (high vs. low), and interaction terms between drug class and biomarker. Models assessing patient-treatment interactions in a continuous cohort additionally use robust variables calculated by general estimating equations within an independent construct clustered and operating on individual patients. Hazard ratios were then generated from the adjusted Cox models stratified by group (i.e., TMB high vs. low). R version 3.6.3 software was used for all statistical analyses.

[0381] Non-proportional hazards over time between treatment groups may limit the interpretability of the hazard ratio as a valid criterion. For this reason, a prespecified method of hazard ratio estimation was augmented with the analysis of 3-year bounded mean survival time (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. Interpretability of Cancer Clinical Trial Results Using Restricted Mean Survival Time as an Alternative to the Hazard Ratio. JAMA Oncol 2017;3:1692-1696).

[0382] result Patient cohort A total of 15149 unique NSCLC patients were in the Clinicogenomics database, and 10139 patients had information on prior line therapy. See Figure 18. Of the 10139 patients, 2344 received immune checkpoint inhibitor (ICPI) therapy or immune checkpoint inhibitor therapy in combination with chemotherapy in the first line. Patients without PD-L1 immunohistochemistry results, patients with samples collected after the start of immune checkpoint inhibitor therapy, and patients with EGFR mutations or ALK / ROS1 / RET rearrangements were excluded. A total of 1722 patients remained in the analysis. Of the 1722, 630 received ICPI monotherapy and 1092 received ICPI therapy + chemotherapy. When comparing patient characteristics between ICPI monotherapy and ICPI + chemotherapy, it was observed that patients in ICPI monotherapy were more likely to be older, smoker, female, have higher ECOG score, be diagnosed at earlier stage, have higher TMB score, and have PD-L1 tumor proportion score (TPS) / PD-L1 stained tumor cells (TC) than patients in ICPI + chemotherapy.See Tables 8A and 8B. [Table 8] [Table 9]

[0383] Figures 19A and 19B provide adjusted Kaplan-Meier plots of real-world progression-free survival (rwPFS), and Figures 19C and 19D provide real-world overall survival (rwOS) for patients treated with ICPI monotherapy (Figures 19A and 19C) or ICPI therapy plus chemotherapy (Figures 19B and 19D). Outcomes were stratified by TMB<10 and TMB>10, with a TMB of 10 being the cutoff for high TMB. To adjust for imbalances, full matching was performed between TMB<10 vs. TMB>10 cohorts. Variables included for matching: age at start of therapy, ECOG PS (0-1, 2+, and unknown), metastasis, smoking history, stage at diagnosis. The results shown in Figures 19A-D suggest that tumor mutation burden is prognostic for ICPI-containing regimens. Figures 20A and 20B provide Kaplan-Meier plots of rwPFS, and Figures 20C and 20D provide rwOS for patients treated with ICPI monotherapy (Figures 20A and 20C) or ICPI plus chemotherapy (Figures 20B and 20D). Outcomes were stratified by TMB<10, TMB10-19, and TMB>20. The results shown in Figures 20A-D suggest that tumor mutation burden is prognostic for first-line ICPI-containing regimens.

[0384] Figure 21A provides a Kaplan-Meier plot of rwPFS for patients treated with ICPI-containing regimens. Outcomes were stratified by TMB and PDL1 levels: PDL1<1% and TMB<10 (i.e., PDL1- / TMB-), PDL1>1% and TMB<10 (i.e., PDL1+ / TMB-), PDL1<1% and TMB≧10 (i.e., PDL1- / TBM+), and PDL1>1% and TMB≧10 (i.e., PDL1+ / TMB+). Figure 21B provides results from a multivariate Cox Ph model to detect associations between clinical or genomic features and rwPFS. Figure 21C provides a Kaplan-Meier plot of rwOS for patients treated with ICPI-containing regimens. Outcomes were stratified by TMB and PDL1 levels: PDL1<1% and TBM<10 (i.e., PDL1- / TBM-), PDL1>1% and TBM<10 (i.e., PDL1+ / TBM-), PDL1<1% and TMB≧10 (i.e., PDL1- / TBM+), and PDL1>1% and TMB≧10 (i.e., PDL1+ / TMB+). Figure 21D provides results from a multivariate Cox Ph model to detect associations between clinical or genomic features and rwOS. Figure 22A provides a Kaplan-Meier plot of rwPFS for patients treated with ICPI-containing regimens. Outcomes were stratified by TMB and PDL1 levels: PDL1<1% and TBM<20 (i.e., PDL1- / TBM-), PDL1>1% and TBM<20 (i.e., PDL1+ / TBM-), PDL1<1% and TMB≧20 (i.e., PDL1- / TBM+), and PDL1>1% and TMB≧20 (i.e., PDL1+ / TMB+). Figure 22B provides results from a multivariate Cox Ph model to detect associations between clinical or genomic features and rwPFS. Figure 22C provides a Kaplan-Meier plot of rwOS for patients treated with ICPI-containing regimens.Outcomes were stratified by TMB and PDL1 levels: PDL1<1% and TMB<20 (i.e., PDL1- / TMB-), PDL1>1% and TBM<20 (i.e., PDL1+ / TMB-), PDL1<1% and TMB≧20 (i.e., PDL1- / TBM+), and PDL1>1% and TMB≧20 (i.e., PDL1+ / TMB+). Figure 22D provides results from a multivariate Cox Ph model to detect associations between clinical or genomic features and rwOS. Results from 21A-D and 22A-D suggest that TMB and PD-L1 expression are independent markers of ICPI outcomes.

[0385] Figure 23A shows the point estimates and 95% HR (hazard ratio) confidence intervals for the biomarkers, and treatment interactions are shown for different TMB or PDL1 cutoffs for rwPFS. Figure 23B shows the point estimates and 95% HR (hazard ratio) confidence intervals for the biomarkers, and treatment interactions are shown for different TMB or PDL1 cutoffs for rwOS. Figure 23C provides a Kaplan-Meier plot of rwPFS for patients with 1-49% PD-L1 score treated with ICPI monotherapy or ICPI therapy + chemotherapy. Figure 23D provides a Kaplan-Meier plot of rwPFS for patients with ≥ 50% PD-L1 score treated with ICPI monotherapy or ICPI therapy + chemotherapy. The results shown in Figures 23A-23D suggest that PD-L1 is a predictive biomarker for ICPI monotherapy vs. ICPI therapy + chemotherapy efficacy.

[0386] Figure 24 shows the top 30 altered genes in the ICPI monotherapy cohort (-) and the ICPI + chemotherapy cohort (+). Multi: multiple alterations in the specified gene, RE: rearrangement, CN: copy number alteration, SV: short variant mutation (substrate substitution or insertion / deletion).

[0387] Figure 25A shows adjusted Kaplan-Meier plots of rwPFS for patients treated with ICPI monotherapy. Figure 25B shows adjusted Kaplan-Meier plots of rwPFS for patients treated with ICPI therapy + chemotherapy. Figure 25C shows adjusted Kaplan-Meier plots of rwOS for patients treated with ICPI monotherapy. Figure 25D shows adjusted Kaplan-Meier plots of rwOS for patients treated with ICPI therapy + chemotherapy. In Figures 25A-25D, outcomes were stratified by PDL1 TPS<1% and PDL1 TPS≧1%. To adjust for imbalance, full matching was performed between the PDL1<1% vs. PDL1≧1% cohorts. Variables included for matching: age at start of therapy, ECOG PS (0-1, 2+, and unknown), metastasis, smoking history, stage at diagnosis. Figure 26A shows adjusted Kaplan-Meier plots of rwPFS for patients treated with ICPI monotherapy. Figure 26B shows adjusted Kaplan-Meier plots of rwPFS for patients treated with ICPI therapy plus chemotherapy. Figure 26C shows adjusted Kaplan-Meier plots of rwOS for patients treated with ICPI monotherapy. Figure 26D shows adjusted Kaplan-Meier plots of rwOS for patients treated with ICPI therapy plus chemotherapy. In Figures 26A-26D, outcomes were stratified by PDL1 TC<50% and PDL1 TC≧50%. To adjust for imbalance, full matching was performed between PDL1<50% vs. PDL1≧50% cohorts. Variables included for matching: age at start of therapy, ECOG PS (0-1, 2+, and unknown), metastasis, smoking history, stage at diagnosis. The results shown in Figures 25A-D and 26A-D suggest that PDL1 is prognostic for ICPI-containing treatment regimens.

[0388] Figure 27 provides a box plot 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 for comparing nested models. [Table 10] [Table 11]

[0389] Figure 28A shows the Kaplan-Meier plot of rwPFS for patients treated with ICPI monotherapy. Figure 28B shows the Kaplan-Meier plot of rwPFS for patients treated with ICPI therapy + chemotherapy. Figure 28C shows the Kaplan-Meier plot of rwOS for patients treated with ICPI monotherapy. Figure 28D shows the Kaplan-Meier plot of rwOS for patients treated with ICPI therapy + chemotherapy. Outcomes were stratified by TMB and PDL1 levels: PDL1<1% and TBM<10 (i.e., PDL1- / TBM-), PDL1>1% and TBM<10 (i.e., PDL1+ / TBM-), PDL1<1% and TMB≧10 (i.e., PDL1- / TBM+), and PDL1>1% and TMB≧10 (i.e., PDL1+ / TMB+).

[0390] Figures 27 and 28A-28D and Tables 9A and 9B suggest that TMB and PD-L1 expression are independent markers for ICPI outcome.

[0391] Consideration In this study, TMB and PD-L1 immunohistochemistry (IHC) were shown to be independent biomarkers for first-line NSCLC patients treated with ICPI-containing regimens (e.g., ICPI monotherapy or ICPI + chemotherapy). Specifically, single biomarker positivity (high TMB / PD-L1 neg and low TMB / PD-L1 pos ) groups were dual biomarker positive (low TMB / PD-L1 neg ) had a higher rwPFS than the other three groups (i.e., low TMB / PD-L1 pos , low TMB / PD-L1 neg , and high TMB / PD-L1 neg) with a survival of 10.5 to 12 months pos A very high median rwOS (20.1 months) was observed in 1L NSCLC patients. In summary, in addition to TMB and PD-L1 IHC being independent biomarkers for predicting outcome to ICPI-containing regimens, combined positivity of both biomarkers predicts the strongest response to ICPI-containing regimens. The data here suggest that in addition to PD-L1 IHC, TMB testing should also be performed for 1L NSCLC patients.

[0392] As an independent biomarker, high TMB was highly prognostic for 1L NSCLC in both ICPI monotherapy and ICPI + chemotherapy groups. This is exemplified by the near doubling of both rwPFS and rwOS in the high TMB group when compared with the TMB group in the ICPI monotherapy cohort. The same trend was observed in the ICPI + chemotherapy group, where a median rwPFS of 10 months was observed in the high TMB group versus 6.8 months in the low TMB group, with a less pronounced but significant difference in rwOS. TMB has been approved as a companion diagnostic in patients who have progressed after prior therapy, and real-world evidence shown in urothelial carcinoma reveals that TMB has predictive value in the first-line setting. Overall, these real-world data suggest that TMB is a highly prognostic biomarker for ICPI-containing regimens in multiple tumor types. PD-L1 is also an independent prognostic biomarker for first-line NSCLC at both TPS>1 and TPS>50 cutoffs (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).

[0393] The most widely used TMB cutoff is currently 10mut / Mb, but a higher cutoff at TMB≧20mut / Mb may help select patients who are exceptional responders to ICPI. In this example, patients with TMB≧20 in both the ICPI monotherapy group and the ICPI therapy + chemotherapy group responded very well to both. Specifically, in rwOS in both ICPI monotherapy groups, the TMB≧20 cohort (median 33.7 months) had more than three times the survival time when compared to the <10mut / Mb group (median 9.4 months). This same trend was observed when TMB and PD-L1 defined groups were tested. Double positive (PD-L1 pos / TMB pos ) group had a rwOS of 11.2 months. neg / TMB neg ) group had a median rwOS of 33.7 months. Finally, patients with a durable response >2 years after initiation of ICPI therapy in NSCLC represent a unique population of immune survivors with a median OS of approximately 5 years, with 41% of patients stopping ICPI before the 2-year mark. Based on these data, further investigation of TMB at higher cutoffs such as 20mut / Mb as a biomarker for long-term response to ICPI in NSCLC is warranted.

[0394] The predictive value of TMB and PD-L1 for ICPI + chemotherapy versus ICPI monotherapy was evaluated. In this cohort, it was observed that TMB (at 10 and 20mut / MB) could predict more favorable rwPFS or rwOS in ICPI monotherapy versus ICPI + chemotherapy. However, patients with PD-L1 IHC at TPS of 1-49 had significantly higher rwPFS in ICPI + chemotherapy compared to the ICPI monotherapy group (median rwPFS: 2.9 vs. 7.3 months), suggesting that PD-L1 IHC may be a useful biomarker to guide the decision in ICPI monotherapy versus ICPI + chemotherapy. The same trend was seen in rwOS and is consistent with the aforementioned FDA pooled analysis (Akinboro O, Vallejo JJ, Mishra-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). Overall, the data suggest that further clinical trials should be conducted to better evaluate the predictive power of PD-L1 in this co...

Claims

1. 1. A kit for treating an individual with cancer, the kit comprising: (a) determining a tumor mutational burden (TMB) score of a tumor biopsy sample obtained from said individual; (b) determining to treat the individual with immune checkpoint inhibitor therapy if the TMB score is at least a threshold TMB score; and The method includes the steps of: The kit, wherein the cancer is metastatic urothelial cancer, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC).

2. 2. The kit of claim 1, further comprising a means for assessing microsatellite instability, wherein (b) is further based on the cancer being microsatellite instability high (MSI-H), and wherein microsatellite instability is assessed by next-generation sequencing (NGS).

3. 2. The kit 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. 2. The kit of claim 1, wherein the TMB score is determined based on about 100 kb to about 10 Mb of sequenced DNA.

5. 2. The kit of claim 1, wherein the TMB score is determined based on about 0.8 Mb to about 1.1 Mb of sequenced DNA.

6. 10. The kit of claim 1, wherein the individual is treated with an immune checkpoint inhibitor if the TMB score is at least the threshold TMB score.

7. The kit 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 chimeric molecule (PROTAC), a cell therapy, a treatment for cancer being tested in a clinical trial, an immunotherapy, or any combination thereof.

8. The kit of claim 1, wherein the immune checkpoint inhibitor is a PD-1 inhibitor, and the PD-1 inhibitor comprises one or more of nivolumab, pembrolizumab, cemiplimab, or dostarlimab.

9. The kit described in claim 1, wherein the immune checkpoint inhibitor is a PD-L1 inhibitor, and the PD-L1 inhibitor includes one or more of atezolizumab, avelumab, or durvalumab.

10. The kit described in claim 1, wherein the immune checkpoint inhibitor is a CTLA-4 inhibitor, and the CTLA-4 inhibitor comprises ipilimumab.

11. 10. The kit of claim 1, wherein the individual has previously been treated with an anti-cancer therapy for the cancer.

12. 12. The kit of claim 11, wherein the anti-cancer therapy is one or more of 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-neoplastic agent, a growth inhibitory agent, a cytotoxic agent, or any combination thereof.

13. The kit described in claim 1, wherein the immune checkpoint inhibitor therapy is a single active agent therapy.

14. The kit described in claim 1, wherein the immune checkpoint inhibitor therapy comprises two or more active agents.

15. The kit of claim 1, wherein the immune checkpoint inhibitor therapy comprises a first round of an immune checkpoint inhibitor and a subsequent round of therapy with a different immune checkpoint inhibitor.

16. The kit described in claim 1, wherein immune checkpoint inhibitor therapy is a first-line therapy for the cancer.

17. The kit described in claim 1, wherein immune checkpoint inhibitor therapy is a second-line therapy for the cancer.

18. 10. The kit of claim 1, wherein the individual is treated with an additional anti-cancer therapy, wherein the additional anti-cancer therapy comprises one or more of 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-neoplastic agent, a growth inhibitory agent, a cytotoxic agent, or any combination thereof.

19. 2. The kit of claim 1, wherein the TMB score or microsatellite instability is determined by sequencing, and the sequencing comprises the use of 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 kit of claim 1 , wherein the individual is a human.

21. 2. The kit of claim 1, wherein 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 if the TMB score is at least the threshold TMB score.

22. 10. The kit of claim 1, wherein if the TMB score is less than the threshold TMB score, the individual is treated with chemotherapy.

23. 2. The kit of claim 1, wherein the threshold TMB score is about 10 mutations / Mb.

24. 1. A kit for identifying an individual having cancer for treatment with immune checkpoint inhibitor therapy, comprising: a means for determining a tumor mutational burden (TMB) score of a tumor biopsy sample obtained from the individual, wherein the individual is identified for treatment with immune checkpoint inhibitor therapy if the TMB score is at least a threshold TMB score, and the cancer is metastatic urothelial carcinoma, metastatic gastric adenocarcinoma, metastatic endometrial cancer, prostate cancer, or non-small cell lung cancer (NSCLC).

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