Tumor mutation burden

Abstract

Providing tumor mutation burden. [Solution] The present invention encompasses the finding that the likelihood of a favorable response to cancer immunotherapy for a wide range of different cancers can be predicted through the definition of tumor mutational burden thresholds for tumors (and / or appropriate immunotherapy). Furthermore, in some embodiments, the present invention establishes that the likelihood of a sustained response to cancer immunotherapy (and / or effective immunotherapy agents and / or regimens) can be predicted for tumors already treated with prior immunotherapy.

Description

[Background technology]

[0001] Cancer immunotherapy involves the patient's immune system attacking cancer cells. The regulation and activation of T lymphocytes also depend on signaling by T cell receptors, as well as co-signaling to receptors that deliver positive or negative signals for activation. The T cell immune response is regulated by a balance of co-stimulatory and inhibitory signals known as immune checkpoints. Global cancer spending is projected to exceed $150 billion by 2020, with a significant portion attributed to the development of immunotherapy drugs. [Overview of the project] [Means for solving the problem]

[0002] In recent years, immune checkpoint modulators have revolutionized the treatment of patients with advanced solid tumors. These drugs include antibodies that act as CTLA-4 inhibitors or PD-1 / PD-L1 inhibitors, which can modulate immune regulatory signals. 1

[0003] This disclosure recognizes the causes of potential problems that may arise with immunotherapy regimens. In particular, it has been observed that sustained benefits are often achieved in only a subset of patients.

[0004] Recent studies have found that the likelihood of a favorable response to cancer immunotherapy can often be predicted. 2See Chan et al., Memorial Sloan Kettering Cancer Center, International Patent Application No. WO2016 / 081947, incorporated herein by reference. In particular, it has been shown that tumor mutational burden may correlate with responsiveness to certain therapies (e.g., immunotherapy, and especially immune checkpoint modifier therapy) for certain cancers, that certain cancer cells may possess somatic mutations that produce neoepitopes that can be recognized as non-self by the patient's immune system, and that the presence and / or identity of such neoepitopes may correlate with responsiveness to certain therapies. Furthermore, the ability to present neoepitopes to the immune system, particularly through diverse HLA molecules, may correlate with responsiveness to certain therapies. Mutational "signatures" that can be detected to predict certain characteristics and / or responsiveness to immunotherapy are defined and specifically include lung cancer (e.g., small cell or non-small cell carcinoma) and melanoma.

[0005] The present invention encompasses the finding that the likelihood of a favorable response to cancer immunotherapy for a wide range of different cancers can be predicted through the definition of a tumor mutational burden threshold for the tumor (and / or appropriate immunotherapy). In some embodiments, the present disclosure provides techniques for defining such thresholds and / or achieving such definitions.

[0006] Furthermore, in some embodiments, the present invention establishes that the potential for sustained response to cancer immunotherapy (and / or effective immunotherapy agents and / or regimens) can be predicted for tumors already treated with prior immunotherapy. In particular, the disclosure shows that tumor mutational loading thresholds can be defined for tumors that have already received prior immunotherapy and predict the potential for response to continued (and / or additional, extended, or modified) immunotherapy.

[0007] The present invention encompasses the finding that the likelihood of a favorable response to cancer immunotherapy for a wide range of different cancers can be predicted through HLA atypia. In some embodiments, HLA atypia alone is sufficient to determine the likelihood of a favorable response to cancer immunotherapy. In some embodiments, HLA atypia and tumor mutational load may be used in combination to determine the likelihood of a favorable response to cancer immunotherapy.

[0008] In particular, in some embodiments, the Disclosure provides techniques for defining tumor mutational load thresholds (and / or other features—e.g., the nature, level, and / or frequency of neoantigen mutations) that predict the ongoing responsiveness and / or persistence of the response to cancer immunotherapy. In some embodiments, the Disclosure defines such thresholds. Furthermore, in some embodiments, the Disclosure provides techniques for treating tumors that have been exposed to cancer immunotherapy by administering cancer immunotherapy to these tumors that exhibit, for example, the mutational load features described herein (i.e., tumor mutational load and / or the nature, level, and / or frequency of neoantigens exceeding the defined thresholds) (e.g., continuing, supplementing, and / or newly initiating). In many embodiments, tumors that exhibit a tumor mutational load exceeding a threshold correlated with a statistically significant probability of responding to cancer immunotherapy are treated with such immunotherapy. In some embodiments, the tumors have been previously exposed to (the same or different) immunotherapy.

[0009] In some embodiments, the Disclosure provides techniques for treating tumors in subjects having a specific HLA class I genotype or HLA class I atypia. Additionally, in some embodiments, the Disclosure provides techniques for treating tumors that have been exposed to cancer immunotherapy by administering cancer immunotherapy to these tumors present in subjects with a specific HLA class I genotype or HLA class I atypia, exhibiting, for example, the mutaloading characteristics described herein (i.e., tumor mutaloading and / or neoantigen properties, levels, and / or frequency) above a defined threshold.

[0010] In some embodiments, tumor mutational load features may include the properties (e.g., identity or type), level, and / or frequency of neoepitopes that can be recognized as non-self by the patient's immune system (e.g., in addition to or in place of tumor mutational load). This disclosure defines certain characteristics of specific tumor cells (e.g., cells previously treated with cancer immunotherapy) that can be detected to predict responsiveness (e.g., sustained responsiveness and / or persistence of responsiveness) to immunotherapy, particularly therapy with immune checkpoint modulators. In particular, this disclosure provides tools and techniques that can be practically applied to define, characterize, and / or detect one or more tumor mutational load features (e.g., tumor mutational load features, neoepitope identity, type, level, and / or frequency, etc.).

[0011] In some embodiments, HLA class I heterozygosity can include heterozygosity in a single HLA class I locus, two HLA class I locuses, or three HLA class I locuses. In some embodiments, the maximum heterozygosity is heterozygosity in three HLA class I locuses (i.e., A, B, and C).

[0012] In particular, this disclosure shows that appropriate tumor mutational burden can be determined and / or detected using targeted gene panel technologies (e.g., assessed by next-generation sequencing) and does not necessarily require whole exome sequencing. This disclosure recognizes that a problem associated with certain prior technologies for assessing tumor mutational burden is the extent to which they rely on and / or require whole exome sequencing, which is not typically performed widely as part of routine clinical care.

[0013] In some embodiments of the present invention, tumor mutational load is determined and / or detected by the use of a targeted sequence panel. In some embodiments, tumor mutational load is measured using next-generation sequencing. In some embodiments, tumor mutational load is measured using an actionable cancer target mutation profiling (MSK-IMPACT) assay. 8、17

[0014] In some embodiments, the determination step includes detecting at least one mutation by nucleic acid sequencing. In some embodiments, the nucleic acid sequencing is or includes whole exome sequencing. In some embodiments, the nucleic acid sequencing does not involve whole exome sequencing. In some embodiments, the nucleic acid sequencing is or includes next-generation sequencing.

[0015] In some embodiments, this disclosure relates to the administration of immunotherapy to a subject. In some embodiments, the administration includes the steps of detecting tumor mutational load characteristics (e.g., tumor mutational load levels relative to a threshold) in a cancer sample from the subject and considering the subject as a candidate for treatment (e.g., continued and / or extended or modified treatment). In some embodiments, the tumor mutational load threshold is used to determine whether the subject is a candidate for treatment with immunotherapy (e.g., continued and / or extended or modified treatment). In some embodiments, the present invention provides a method for detecting low tumor mutational load, or tumor mutational load below a defined tumor mutational load threshold, in a cancer sample from a subject and a method for considering the subject as an inadequate candidate for treatment with immune checkpoint modulators. In some embodiments, the detection step includes sequencing one or more exomes from the cancer sample. In some embodiments, the detection step does not involve sequencing one or more exomes.

[0016] In some embodiments, the present disclosure relates to the administration of immunotherapy to a subject. In some embodiments, such immunotherapy is, or includes, immune checkpoint modulation therapy. In some embodiments, the immunotherapy involves the administration of one or more immunomodulators. In some embodiments, the immunomodulator is, or includes, an immune checkpoint modulator. In some embodiments, the immune checkpoint modulator is an agent (e.g., an antibody agent) that targets (i.e., specifically interacts with) an immune checkpoint target. In some embodiments, the immune checkpoint target is one or more of CTLA-4, PD-1, PD-L1, GITR, OX40, LAG-3, KIR, TIM-3, CD28, CD40, and CD137, or includes one or more of CTLA-4, PD-1, PD-L1, GITR, OX40, LAG-3, KIR, TIM-3, CD28, CD40, and CD137. In some embodiments, the immune checkpoint modulator therapy is the administration of an antibody agent that targets one or more such checkpoint targets, or includes the administration of an antibody agent that targets one or more such checkpoint targets. In some embodiments, the immune checkpoint modulator interacts with cytotoxic T lymphocyte antigen 4 (CTLA4) or its ligand, and / or programmed death 1 (PD-1) or its ligand. In some embodiments, the antibody agent is a monoclonal antibody or an antigen-binding fragment thereof, or includes a monoclonal antibody or an antigen-binding fragment thereof. In some embodiments, the antibody is selected from the group consisting of atezolizumab, avelumab, durvalumab, ipilimumab, nivolumab, pembrolizumab, or tremelimumab, and combinations thereof.

[0017] In some embodiments, the cancer is selected from the group consisting of bladder cancer, bone cancer, breast cancer, cancer of unknown primary origin, esophageal gastric cancer, gastrointestinal cancer, glioma, head and neck cancer, hepatobiliary cancer, melanoma, mesothelioma, non-Hodgkin lymphoma, non-small cell lung cancer, pancreatic cancer, prostate cancer, renal cell cancer, skin cancer (non-melanoma), small cell lung cancer, soft tissue sarcoma, thyroid cancer, and combinations thereof.

[0018] In some embodiments, the cancer is selected from the group consisting of bladder cancer, breast cancer, esophageal gastric cancer, glioma, head and neck cancer, melanoma, non-small cell lung cancer, renal cell cancer, and combinations thereof.

[0019] The following figures are presented for illustrative purposes only and are not intended to be limiting.

Brief Description of the Drawings

[0020] [Figure 1] Shows a Consolidated Standards of Reporting Trials (CONSORT) diagram showing the flow of patient selection for analysis. [Figure 2] Shows the effect of tumor mutation burden on overall survival after immune checkpoint modulator therapy. Kaplan-Meier curves are shown for the number of patients with the indicated number of mutations (1-15, 16-25, or >25) identified from the MSK-IMPACT assay. Overall survival is determined from the first dose of immune checkpoint modulator therapy. M, months. P < 0.05 for all pairwise comparisons. [Figure 3] Shows overall survival associated with (A) and without (B) pan-cancer tumor mutation burden thresholds with immune checkpoint modulator (ICM) therapy. Kaplan-Meier curves are shown for patients treated with or without ICM with the indicated number of normalized mutations identified by the MSK-IMPACT assay. Overall survival is determined starting from the first dose of ICM or the first dose of any chemotherapy. [Figure 4]The effect of tumor mutational burden on overall survival after ICM therapy (A) is shown for each cancer subtype and drug class. Forest plots are shown for all patients in the identified cohort ("all cancers") or individual cancer subtypes. Numbers for patients and hazard ratios are shown. Horizontal lines represent 95% confidence intervals. The threshold used for normalized tumor mutational burden from MSK-IMPACT for specific subtypes to select high tumor mutational burden is shown as well as the log-rank p-value for comparing high and low tumor mutational burden survival curves. All cancer types examined in a number of patients N>35 are shown. (B) shows the effect of tumor mutational burden on overall survival for each cancer subtype without ICM therapy. Forest plots are shown for all patients in the cohort of patients not receiving ICM ("all cancers") or individual cancer subtypes. Numbers for patients and hazard ratios are shown. Horizontal lines represent 95% confidence intervals. The threshold used is the optimal cutoff for that particular subtype in the ICM cohort. Log-rank p-values ​​are shown for comparisons of high and low tumor mutation burden survival curves. All cancer types examined are shown for a patient population of N > 35. In both panels A and B, the term “cutoff” is used to represent the tumor mutation burden threshold as defined herein. [Figure 5] The tumor mutation load threshold values ​​used for the analysis are shown. (A) shows the use of maximum chi-square analysis for the optimal threshold with individual cutpoints for normalized tumor mutation load on the x-axis and p-value. (B) shows the hazard ratio at each cutpoint. [Figure 6-1] The effect of tumor mutation burden on overall survival after ICM therapy is shown for each cancer subtype. The first column in panels A-H shows the distribution of normalized tumor mutation burden frequencies across subsets of tumor mutation burden. The second column in panels A-H shows Kaplan-Meier curves for patients treated with ICM therapy who have the indicated number of normalized mutations identified by MSK-IMPACT testing. Each panel represents a cancer subtype: (A) bladder cancer, (B) breast cancer, (C) esophageal and gastric cancer, (D) glioma, (E) head and neck cancer, (F) melanoma, (G) non-small cell lung cancer (NSCLC), and (H) renal cell carcinoma. [Figure 6-2] Same as above. [Figure 6-3] Same as above. [Figure 6-4] Same as above. [Figure 7] The funnel plots of hazard ratios for all cancer subtypes are shown. The funnel plots show the reciprocal of the number of patients as a continuous variable for a particular histology (y-axis) and the hazard ratio for normalized tumor mutation burden (x-axis). [Figure 8-1]This study demonstrates the effect of HLA class I asozygosity on survival in patients treated with immune checkpoint modulators. (A) Association between asozygosity at at least one HLA class I locus and reduced overall survival in Cohort 1, consisting of 369 patients with melanoma or NSCLC treated with ICM therapy. (B) Association between asozygosity at at least one HLA class I locus and reduced overall survival in Cohort 2, consisting of 1,166 patients representing different cancer types treated with ICM therapy. (C) Association between asozygosity at one or more class I loci and individual loci (HLA-A, HLA-B, and HLA-C) and reduced overall survival from all 1,535 patients. The number of patients and hazard ratios (HRs) are shown. Horizontal lines represent 95% confidence intervals. P-values ​​were calculated using the log-rank test. Patients were divided as follows: Individuals who were atypically conjugated in all three class I loci, individuals who were isozygous in one or more class I loci, individuals who were isozygous in the specified locus but atypically conjugated in both of the other two loci, and individuals who were isozygous in the specified locus and one of the other two loci but atypically conjugated in the other. Isozygosity in HLA-A and HLA-B, and isozygosity in HLA-A and HLA-C were rare in these patients, limiting the interpretability of analyses involving locus combinations. (D) Improved survival in cohort 1 patients with atypia in all HLA class I loci and high tumor mutation burden compared to patients with isozygosity in at least one HLA class I locus and low tumor mutation burden. Mutation burden was calculated from the total non-synonymous mutation count from whole exome sequencing. Here, high mutation burden is defined as a tumor with more than 113 mutations. (E) Improved survival in Cohort 2 patients with atypia in all HLA class I loci and high tumor mutation burden, compared to patients with isozygosity in at least one HLA class I locus and low tumor mutation burden. Mutation burden was calculated from the total non-synonymous mutation count from MSK-IMPACT. Here, high mutation burden is defined as tumors with mutations greater than 16.72.(F and G) Box plots illustrating the distribution of hazard ratios resulting from survival analyses using cutoff ranges to stratify patients based on their tumor mutational burden. This analysis shows that the combined effect of HLA class I atypeticity and mutational burden at all loci on improved survival was greater in cohorts 1 (F) and 2 (G) compared to simply considering tumor mutational burden alone. For this analysis, we used cutoff ranges between quartiles of mutational burden. We calculated p-values ​​using the Wilcoxon rank-sum test. (H) Survival analysis shows that LOH of atypetic germline HLA class I is associated with reduced overall survival in patients treated with ICM immunotherapy. The number of patients with atypetic germline at all HLA class I loci and no LOH is 199. The number of patients with atypetic germline at all HLA class I loci and LOH is 32. (I) Survival analysis demonstrating that the effect of LOH in atypical germline HLA class I is enhanced in tumors with low mutational burden compared to tumors with high mutational burden but without LOH. High mutational burden is defined here as in (D). The number of patients with tumors containing high mutational burden, being atypical germline and without LOH at each HLA class I locus is 142. The number of patients with tumors containing low mutational burden, being atypical germline and with LOH at all HLA class I loci is 8. [Figure 8-2] Same as above. [Figure 8-3] Same as above. [Figure 9-1]This study shows the effect of HLA B44 supertype on survival in patients with advanced melanoma treated with ICM. (A) Prevalence of different HLA supertypes in patients with melanoma from Cohort 1. (B) Prevalence of different HLA supertypes in patients with melanoma from Cohort 2. (C and D) Survival analysis showing overall survival of patients with advanced melanoma carrying the B44 supertype [B44(+)] treated with ICM therapy compared with patients without the B44 supertype [B44(-)] from Cohort 1 (C) and Cohort 2 (D). (E and F) Survival analysis of patients with the B44 supertype and high mutational burden versus patients without B44 and with low mutational burden from Cohort 1 (E) and Cohort 2 (F). (G and H) Box plots illustrating the distribution of hazard ratios resulting from survival analyses using different cutoffs to stratify patients based on their tumor mutational burden. This analysis shows that the combined effect of B44 and mutational burden on increased survival was greater than that of tumor mutational burden alone in patients with melanoma treated with ICM from cohorts 1(G) and 2(H). For this analysis, we used a cutoff range between the quartiles of mutational burden. We calculated the p-value using Wilcoxon rank-sum test. (I) Survival analysis of melanoma patients with and without B44 supertype from the TCGA cohort. (J) Left: Example of a common peptide motif among B44 HLA alleles docked in complex with HLA-B*44:02 based on available crystal structure (PDB:1M6O). Five common residues of the motif (E2, I3, P4, V6, and Y9) were reported in (45). Peptide residues are colored according to their properties, such as basic, acidic, polar, or hydrophobic. Center: Close-up of exemplary peptides matching the B44 motif reported in the literature. The residues at positions 2 and 9 are particularly important for fixing the HLA peptide binding groove. Right: Known immunogenic neoantigens within the B44 supertype expressed by the B44 peptide motif and melanoma (Table 8). All neoepitopes are characterized by glutamate at position 2. Neoantigens are either identical or similar to the motif at one or two additional positions.A second neoantigen (FAM3C:TESPFEQHI) was identified in melanoma patients with a long-term response to anti-CTLA-4 from Cohort 1. Sequence similarity was determined using standard residue classes (GAVLI, FYW, CM, ST, KRH, DENQ, and P). [Figure 9-2] Same as above. [Figure 9-3] Same as above. [Figure 9-4] Same as above. [Figure 10] This study demonstrates the effect of HLA-B*15:01 on overall survival in patients with melanoma treated with ICM therapy. (A) Survival analysis showing reduced survival in ICM-treated melanoma patients from cohort 1 with and without the HLA-B*15:01 allele. (B) Schematic diagram of the three-dimensional structure of HLA-B*15:01, light purple; binding peptide, yellow; binding groove, light pink; peptide binding groove. (C) Side view of the bridge-sequestration effect across binding peptide residue positions P2 and P3. (D) MD simulation snapshots of both isolated HLA-B*15:01 molecules and their complex with the 9-mer peptide. Each trajectory was operated over a simulation time of 500 ns. (E) Observables from the MD simulation described in (D). The mean crosslinking distances in the HLA-B*15:01 molecule and the HLA-B*15:01 peptide complex are comparable. Residue position-root mean-squared fluctuation (RMSF) indicates that each cross-linking residue becomes more rigid in the presence of the peptide. [Figure 11] These figures represent the number of somatic coding mutations between patients who were isozygous at at least one HLA class I locus and patients who were heterozygous at each class I locus in Cohort 1 and Cohort 2, respectively. The p-value was calculated using the Wilcoxon rank-sum test. [Figure 12]Molecular dynamics simulations for HLA-B*07:02 and HLA-B*53:01 are shown. (A and C) MD simulation snapshots of both isolated HLA B*07:02 and HLA B*53:01 molecules and their complexes with 9-mer peptides, respectively. Each trajectory was operated over a simulation time of 300 ns. (B and D) Observables from the MD simulations described in (A and C). The mean crosslinking distance and crosslinking residue RMSF for HLA B*07:02 and HLA B*53:01 molecules and their corresponding HLA peptide complexes are shown. [Figure 13] This diagram shows the Consortium Criteria (CONSORT) for trial reporting, illustrating the patient selection flow for analysis of confirmatory cohorts. [Figure 14] This shows the effect of mutational burden on overall survival after ICI treatment. A. Kaplan-Meier curves for patients with tumors classified into drawn deciles of tumor mutational burden (TMB) within each histology. TMB is defined as normalized somatic mutations per MB identified by MSK-IMPACT testing. Overall survival is from the first dose of ICI. The log-rank p-values ​​for all patients are shown, along with the univariate Cox regression hazard ratios for the 10-20% and top 10% groups, which were 0.76 (95% CI 0.62-0.94) and 0.52 (95% CI 0.42-0.64), respectively, compared to the bottom 80% group. B. Cox regression hazard ratios for overall survival at drawn cutoffs of tumor mutational burden (TMB) measured by mutations per MB across all cancer subtypes. Black circles represent hazard ratios at p-value < 0.05. [Figure 15] Figure 14A shows the distribution of cancer types within the group. [Figure 16] This shows the overall survival of high-TMB patients by quantile across cancer types. Kaplan-Meier survival analysis of high versus low TMB is defined by the percentage of patients from each cancer type shown at the top. P-values ​​are shown using the log-rank test. [Figure 17]This shows the effect of non-synonymous mutation burden on overall survival after ICI treatment for each cancer type and drug class. Forest plots are shown for all patients in the identified cohort or individual cancer subtypes. The number of patients and hazard ratios are shown comparing overall survival after ICI for patients in the top 20 percentile TMB within each histology. Horizontal lines represent 95% confidence intervals. A cutoff defining the top 20% of normalized mutation burden from MSK-IMPACT for each cancer type is shown, as are log-rank p-values ​​for comparing high and low mutation burden survival curves. All cancer types in the analysis are shown. [Figure 18] Forest plots are shown for all patients in the cohort and individual cancer histologies. For each histology, the number of patients and hazard ratios are shown comparing overall survival after ICI in patients with a TMB of ≥10% (A) or 30% (B). Horizontal lines represent 95% confidence intervals. The cutoff used for normalized mutational loading from MSK-IMPACT for specific subtypes to select high mutational loading is shown, as well as the log-rank p-values ​​for comparing high and low mutational loading survival curves. [Figure 19-1] This shows the effect of non-synonymous mutation burden on overall survival for each cancer type, in patients treated with or without ICI. Individual plots are shown for all patients in the identified cohort ("all cancer types") or individual cancer subtypes. The first column shows the distribution of normalized mutational burden frequencies. The second column shows Kaplan-Meier curves for patients treated with ICI who have the top 20% TMB within each histology identified by MSK-IMPACT testing. The third column represents OS, comparing the top 20% of tumors in the cohort of patients who have not received any ICI treatment since the date of diagnosis. [Figure 19-2] Same as above. [Figure 19-3] Same as above. [Figure 19-4] Same as above. [Figure 19-5] Same as above. [Figure 19-6] Same as above. [Figure 20]A forest plot is shown illustrating the Cox proportional hazards model across all cancer types and individual histologies, with the hazard ratio for TMB as a continuous variable. [Figure 21] This shows TMB as a predictor of clinical response to ICI. A. Pie charts showing the relative proportion of patients with low and high TMB who have clinical utility (defined as a radiographic response or stable disease for ≥6 months) in NSCLC, B. head and neck, and C. esophageal and gastric cancer. Fisher's exact test p-values ​​are shown. Similar data on the association between TMB and tumor response in MSK-IMPACT-sequenced NSCLC patients have also been published separately. [Figure 22-1] TMB is shown to predict progression-free survival (A, B, C) or time to next treatment (D) in patients with high and low TMB (top 20%) tumors in the indicated cancer types. The indicated log-rank p-values ​​are shown. [Figure 22-2] Same as above. [Figure 23] This shows the effect of non-synonymous mutation burden on overall survival (OS) for each cancer subtype in patients not treated with ICI. Forest plots are presented for the cohort of patients not receiving ICI ("all cancer types") or for all metastatic patients in individual cancer subtypes. Numerical values ​​for patients and hazard ratios are shown. Horizontal lines represent 95% confidence intervals. The cutoff used is the top 20% in this cohort. Log-rank p-values ​​are shown for comparisons of high and low mutation burden survival curves. [Figure 24] Figures 17 and 23 are shown with a modified version using a TMB cutoff, which is instead defined as the top 20% of all patients in both ICI-treated and non-ICI-treated cohorts. [Figure 25-1]A modified version of Figure 19 is shown, with a TMB cutoff defined instead as the top 20% of all patients in both the ICI-treated and non-ICI-treated cohorts. The first column shows the distribution of normalized mutational burden frequencies across the combined ICI-treated and non-ICI-treated cohorts in their histology. The second column shows Kaplan-Meier curves for ICI-treated patients with the top 20% TMB (across the combined cohort) within each histology identified by MSK-IMPACT testing. The third column represents OS, comparing the top 20% TMB (across the combined cohort) in the cohort of patients who have not received any ICI treatment since the date of diagnosis. [Figure 25-2] Same as above. [Figure 25-3] Same as above. [Figure 25-4] Same as above. [Figure 25-5] Same as above. [Figure 25-6] Same as above. [Modes for carrying out the invention]

[0021] definition To make the present invention easier to understand, certain terms are defined below. Those skilled in the art will understand that definitions of certain terms may be provided elsewhere in the specification and / or will become apparent from the context.

[0022] Administration: As used herein, the term “administration” refers to the administration of the composition to a subject. Administration may be by any suitable route. For example, in some embodiments, administration may be by the bronchi (including by bronchial droplet), oral cavity, enteral, intercutaneous, intra-arterial, intradermal, intragastric, intramedullary, intramuscular, intranasal, intraperitoneal, intrathecal, intravenous, intraventricular, transmucosal, transnasal, oral, rectal, subcutaneous, sublingual, topical, trachea (including by intratracheal droplet), transdermal, vaginal, and vitreous humor.

[0023] Affinity: As is known to those skilled in the art, "affinity" is a measure of the strength of binding of a particular ligand to its partner. Affinity can be measured in various ways. In some embodiments, affinity is measured by quantitative assays. In some such embodiments, the binding partner concentration may be fixed above the ligand concentration to mimic physiological conditions. Alternatively or additionally, in some embodiments, the binding partner concentration and / or ligand concentration may be modified. In some such embodiments, affinity may be compared to a reference under equivalent conditions (e.g., concentration).

[0024] Amino Acids: As used herein, the term “amino acid” means, in its broadest sense, any compound and / or substance that can be incorporated into a polypeptide chain. In some embodiments, an amino acid has the general structure H2N-C(H)(R)-COOH. In some embodiments, an amino acid is a naturally occurring amino acid. In some embodiments, an amino acid is a synthetic amino acid. In some embodiments, an amino acid is a d-amino acid. In some embodiments, an amino acid is an l-amino acid. “Standard amino acid” means any of the 20 standard l-amino acids commonly found in naturally occurring peptides. “Non-standard amino acid” means any amino acid other than a standard amino acid, whether it is synthetically prepared or obtained from a natural source. As used herein, “synthetic amino acid” includes, but is not limited to, salts, amino acid derivatives (such as amides), and / or substitutions of chemically modified amino acids. Amino acids containing carboxyl and / or amino-terminal amino acids in a peptide may be modified by methylation, amidation, acetylation, substitution with protecting groups, and / or other chemical groups, which can alter the cyclic half-life of the peptide without adversely affecting their activity. Amino acids can be involved in disulfide bonds. Amino acids can contain one or more chemical entities (e.g., methyl group, acetate group, acetyl group, phosphate group, formyl moiety, isoprenoid group, sulfate group, polyethylene glycol moiety, lipid moiety, carbohydrate moiety, biotin moiety, etc.) or post-translational modifications. The term “amino acid” is used interchangeably with “amino acid residue” and can refer to free amino acids and / or amino acid residues of peptides. Whether the term “amino acid” refers to free amino acids or peptide residues should be clear from the context in which the term is used.

[0025] Antibody Drugs: As used herein, the term “antibody drug” refers to a drug that specifically binds to a particular antigen. In some embodiments, the term encompasses any polypeptide having sufficient immunoglobulin structural elements to confer specific binding. Preferred antibodies include, but are not limited to, human antibodies, primate-like antibodies, chimeric antibodies, bispecific antibodies, humanized antibodies, conjugated antibodies (i.e., antibodies conjugated or fused to other proteins, radiolabeled, or cytotoxins), Small Modular Immuno Pharmaceuticals ("SMIP" trademark), single-chain antibodies, camelid antibodies, and antibody fragments. As used herein, the term “antibody drug” also includes intact monoclonal antibodies, polyclonal antibodies, single-domain antibodies formed from at least two intact antibodies (e.g., IgNAR or a fragment thereof), multispecific antibodies formed from at least two intact antibodies (e.g., bispecific antibodies), and antibody fragments, insofar as they exhibit the desired biological activity. In some embodiments, the term encompasses stapled peptides. In some embodiments, the term encompasses one or more antibody-like conjugated peptide mimetics. In some embodiments, the term encompasses one or more antibody-like binding scaffold proteins. In some embodiments, the term encompasses monobodies or adnectins. In many embodiments, the antibody drug is a polypeptide comprising one or more structural elements whose amino acid sequence is recognized by those skilled in the art as complementarity-determining regions (CDRs), or comprises a polypeptide comprising one or more structural elements whose amino acid sequence is recognized by those skilled in the art as complementarity-determining regions (CDRs). In some embodiments, the antibody drug is a polypeptide comprising at least one CDR (e.g., at least one heavy-chain CDR and / or at least one light-chain CDR) whose amino acid sequence is substantially identical to that found in a reference antibody, or comprises a polypeptide comprising at least one CDR (e.g., at least one heavy-chain CDR and / or at least one light-chain CDR) whose amino acid sequence is substantially identical to that found in a reference antibody.In some embodiments, the included CDR is substantially identical to the reference CDR in that it is either sequence-identical or contains 1 to 5 amino acid substitutions when compared to the reference CDR. In some embodiments, the included CDR is substantially identical to the reference CDR in that it exhibits 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or 100% sequence identity with the reference CDR. In some embodiments, the included CDR is substantially identical to the reference CDR in that it exhibits 96%, 96%, 97%, 98%, 99%, or 100% sequence identity with the reference CDR. In some embodiments, the included CDR is substantially identical to the reference CDR in that at least one amino acid in the included CDR is deleted, added, or substituted compared to the reference CDR, but the included CDR has an amino acid sequence that is otherwise identical to that of the reference CDR. In some embodiments, the included CDR is substantially identical to the reference CDR in that at least one amino acid in the included CDR is substituted compared to the reference CDR, but the included CDR has an amino acid sequence that is otherwise identical to that of the reference CDR. In some embodiments, the included CDR is substantially identical to the reference CDR in that at least one amino acid in the included CDR is substituted compared to the reference CDR, but the included CDR has an amino acid sequence that is otherwise identical to that of the reference CDR. In some embodiments, the included CDR is substantially identical to the reference CDR in that at least one amino acid in the included CDR is substituted compared to the reference CDR, but the included CDR has an amino acid sequence that is otherwise identical to that of the reference CDR. In some embodiments, the antibody drug is a polypeptide comprising a structural element whose amino acid sequence is recognized by those skilled in the art as an immunoglobulin variable domain, or comprises a polypeptide comprising a structural element whose amino acid sequence is recognized by those skilled in the art as an immunoglobulin variable domain.In some embodiments, the antibody drug is a polypeptide protein having a binding domain that is homologous or highly homologous to the immunoglobulin binding domain.

[0026] Antibody polypeptide: As used herein, the terms “antibody polypeptide” or “antibody” or “its antigen-binding fragment” can be used interchangeably and refer to a polypeptide capable of binding to an epitope. In some embodiments, the antibody polypeptide is a full-length antibody, and in some embodiments, less than full-length but containing at least one binding site (containing at least one, and preferably at least two, sequences together with the antibody “variable region”). In some embodiments, the term “antibody polypeptide” encompasses any protein having a binding domain that is homologous or highly homologous to an immunoglobulin-binding domain. In certain embodiments, the “antibody polypeptide” encompasses a polypeptide having a binding domain that exhibits at least 99% identity with an immunoglobulin-binding domain. In some embodiments, the “antibody polypeptide” is any protein having a binding domain that exhibits at least 70%, 80%, 85%, 90%, or 95% identity with an immunoglobulin-binding domain, e.g., a reference immunoglobulin-binding domain. The included “antibody polypeptide” may have the same amino acid sequence as that of an antibody found in natural sources. Antibody polypeptides according to the present invention can be prepared by any available means, including, for example, isolation from natural sources or antibody libraries, recombinant production in or by a host system, chemical synthesis, or a combination thereof. Antibody polypeptides may be monoclonal or polyclonal. Antibody polypeptides may be members of any immunoglobulin, including any of the human classes: IgG, IgM, IgA, IgD, and IgE. In certain embodiments, the antibody may be a member of the IgG immunoglobulin class. As used herein, the terms “antibody polypeptide” or “characteristic portion of an antibody” are used interchangeably and refer to any derivative of an antibody that possesses the ability to bind to the epitope of interest. In certain embodiments, “antibody polypeptide” is an antibody fragment that retains at least a significant portion of the specific binding ability of a full-length antibody. Examples of antibody fragments include, but are not limited to, Fab, Fab', F(ab')2, scFv, Fv, dsFv bispecific antibodies, and Fd fragments.Alternatively or additionally, the antibody fragment may include multiple chains linked together, for example, by disulfide bonds. In some embodiments, the antibody polypeptide may be a human antibody. In some embodiments, the antibody polypeptide may be humanized. A humanized antibody polypeptide may include a chimeric immunoglobulin, an immunoglobulin chain, or an antibody polypeptide (such as Fv, Fab, Fab', F(ab')2, or other antigen-binding subsequences of the antibody) containing minimal sequences derived from a non-human immunoglobulin. Generally, a humanized antibody is a human immunoglobulin (recipient antibody) in which residues in the complementarity-determining region (CDR) of the recipient are replaced with residues from the CDR of a non-human species (donor antibody), such as mouse, rat, or rabbit, having the desired specificity, affinity, and ability. In certain embodiments, the antibody polypeptide for use according to the present invention binds to a specific epitope on an immune checkpoint molecule.

[0027] Antigen: An "antigen" is a molecule or entity to which an antibody binds. In some embodiments, an antigen is a polypeptide or a portion thereof, or comprises a polypeptide or a portion thereof. In some embodiments, an antigen is part of an infectious agent recognized by an antibody. In some embodiments, an antigen is a drug that elicits an immune response, and / or (ii) a drug bound by a T cell receptor (e.g., when presented by an MHC molecule), or an antibody (e.g., produced by a B cell) when exposed to or administered to an organism. In some embodiments, an antigen elicits a humoral response in an organism (e.g., including the production of antigen-specific antibodies). Alternatively or additionally, in some embodiments, an antigen elicits a cellular response (e.g., including T cells whose receptors specifically interact with the antigen). Those skilled in the art will understand that a particular antigen may elicit an immune response in one or more members of a target organism (e.g., mouse, rabbit, primate, human), but not in all members of a target species. In some embodiments, the antigen elicits an immune response in at least about 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, and 99% of members of the target species. In some embodiments, the antigen may or may not bind to antibodies and / or T cell receptors to induce a specific physiological response in the organism. In some embodiments, for example, the antigen may bind to antibodies or T cell receptors in vitro, regardless of whether such interaction occurs in vivo or not. In general, an antigen may be any chemical entity such as a low molecular weight, nucleic acid, polypeptide, carbohydrate, lipid, polymer [in some embodiments, other than biomacromolecules (e.g., other than nucleic acid or amino acid polymers)], or may contain any chemical entity such as a low molecular weight, nucleic acid, polypeptide, carbohydrate, lipid, polymer [in some embodiments, other than biomacromolecules (e.g., other than nucleic acid or amino acid polymers)]. In some embodiments, the antigen is a polypeptide or comprises a polypeptide.In some embodiments, the antigen is or contains a glycan. Those skilled in the art will understand that the antigen may generally be provided in an isolated or pure form, or alternatively in a crude form (e.g., together with other materials, such as cell extracts or other relatively crude preparations of the antigen-containing source). In some embodiments, the antigen utilized according to the present invention is provided in a crude form. In some embodiments, the antigen is or contains a recombinant antigen.

[0028] Approximately: As used herein, the terms “approximately” or “about” refer to a value similar to the reference value stated, when applied to one or more values ​​of interest. In certain embodiments, the terms “approximately” or “about” refer to a range of values ​​that fall within 25%, 20%, 19%, 18%, 17%, 16%, 15%, 14%, 13%, 12%, 11%, 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, or less in either direction (above or below) the reference value stated, unless otherwise stated or evident from the content (except where such number exceeds 100% of the possible value).

[0029] "Inhibitor": As used herein, the term "inhibitor" refers to an entity or event whose presence or level correlates with a decrease in the level and / or activity of a target. Thus, for example, a "PD-1 inhibitor" is a drug or event whose presence correlates with a decrease in the level and / or activity of PD-1. In some such embodiments, adequate activity of PD-1 may be, or may include, interaction with its ligand (e.g., PD-L1 and / or PD-L2) and / or one of its many downstream effects. In some embodiments, a PD-1 inhibitor may be achieved by administering a drug, such as an antibody drug, that targets PD-1 and / or PD-1 ligands (e.g., PD-L1 and / or PD-L2) and / or their complexes. In some specific embodiments, a PD-1 inhibitor may be achieved through the administration of an antibody drug that binds to PD-1. In some embodiments, PD-1 inhibitory action can be achieved through the administration of one or more of nivolumab, pembrolizumab, atezolizumab, avelumab, and / or durvalumab. Similarly, a CTL4 inhibitor is a drug or event whose presence correlates with a decrease in the level and / or activity of CTLA-4. In some such embodiments, adequate activity of CTLA-4 may be or may include interaction with its ligand (e.g., CD80 and / or CD86) and / or one of many of its downstream effects. In some embodiments, a CTLA-4 inhibitor may be achieved by administering a drug such as an antibody drug that targets the CTLA-4 ligand (e.g., CD80 and / or CD86) and / or their complex. In some specific embodiments, a CTLA-4 inhibitor may be achieved through the administration of an antibody drug that binds to CTLA-4. In some embodiments, a CTLA-4 inhibitor may be achieved through the administration of one or more of ipilimumab and / or tremelimumab.

[0030] Combination therapy: As used herein, the term “combination therapy” refers to situations in which two or more different pharmaceutical agents are administered in overlapping regimens so that the subject is simultaneously exposed to both agents. When used in combination therapy, two or more different agents may be administered simultaneously or separately. This combined administration may include simultaneous administration of two or more agents in the same dosage form, simultaneous administration in separate dosage forms, and separate administrations. That is, two or more agents may be formulated together in the same dosage form and administered simultaneously. Alternatively, two or more agents may be administered simultaneously, with the agents present in separate formulations. Another alternative is that the first agent may be administered immediately before one or more additional agents. In separate administration protocols, two or more agents may be administered at intervals of minutes, hours, or days.

[0031] Equivalent: The term “equivalent” is used herein to describe two (or more) sets of conditions, situations, individuals, or populations that are sufficiently similar to one another to enable comparison of the results obtained or the phenomena observed. In some embodiments, equivalent sets of conditions, situations, individuals, or populations are characterized by several substantially identical features and one or a few modified features. A person skilled in the art will understand that sets of situations, individuals, or populations are equivalent to one another when they are characterized by a sufficient number and variety of substantially identical features to ensure a reasonable conclusion that differences in the results obtained or the phenomena observed under or with different sets of situations, individuals, or populations are caused by or indicate variations in these modified features. A person skilled in the art will understand that relative language used herein (e.g., enhanced, activated, reduced, suppressed, etc.) typically refers to comparisons made under equivalent conditions.

[0032] Consensus Sequence: As used herein, the term “consensus sequence” refers to a core sequence that induces or causes a physiological phenomenon (e.g., an immune response). It will be understood by those skilled in the art that cancer cells sharing a “consensus sequence” with an infectious agent antigen share a portion of an amino acid sequence that affects MHC molecules (directly or allosterically) and / or facilitates recognition by T cell receptors. In some embodiments, the consensus sequence is a tetrapeptide. In some embodiments, the consensus sequence is a nonapeptide. In some embodiments, the consensus sequence is 4 to 9 amino acids long. In some embodiments, the consensus sequence is longer than 9 amino acids.

[0033] Diagnostic Information: As used herein, diagnostic information or information for use in diagnosis is any information useful in determining whether a patient has a disease or condition and / or classifying a disease or condition into a phenotypic category or any category meaningful for the prognosis of a likely response to treatment of the disease or condition. Similarly, diagnosis means providing any type of diagnostic information, including but not limited to information relating to whether a subject is likely to have a disease or condition (such as cancer), the appearance, stage or characteristics of the disease or condition as expressed in the subject, the nature or classification of the tumor, and information useful in selecting a prognosis or appropriate treatment. Treatment selection may include choices relating to specific therapeutic agents (e.g., chemotherapy) or other therapeutic modalities such as surgery or radiation, choices about whether to withhold or deliver therapy, and drug regimens (e.g., the frequency or level of one or more doses of a particular therapeutic agent or combination of therapeutic agents).

[0034] Medication regimen: A “medication regimen” (or “treatment regimen”), as the term is used herein, is a set of unit doses (typically two or more) administered individually to a subject, typically separated by time periods. In some embodiments, a given therapeutic agent has a recommended medication regimen in which one or more doses can be involved. In some embodiments, a medication regimen comprises multiple doses, each separated from the others by time periods of equal length. In some embodiments, a medication regimen comprises multiple doses and at least two distinct time periods separating the individual doses. In some embodiments, the medication regimen, when administered across a population of patients, was or correlated with a desired treatment outcome.

[0035] Sustained Clinical Benefit: As used herein, the term “Sustained Clinical Benefit” (DCB) means a clinical benefit that has the meaning understood by those skilled in the art and lasts for a suitable period of time. In some embodiments, such clinical benefit is a reduction in tumor size, an increase in progression-free survival, an increase in overall survival, a decrease in overall tumor burden, and a reduction in symptoms caused by tumor growth, such as pain, organ failure, bleeding, skeletal damage, and other associated sequelae of metastatic cancer, and combinations thereof, or includes a reduction in tumor size, an increase in progression-free survival, an increase in overall survival, a decrease in overall tumor burden, and a reduction in symptoms caused by tumor growth, such as pain, organ failure, bleeding, skeletal damage, and other associated sequelae of metastatic cancer, and combinations thereof. In some embodiments, a suitable period is at least one month, two months, three months, four months, five months, six months, seven months, eight months, nine months, ten months, eleven months, one year, two years, three years, four years, five years, or longer. In some specific embodiments, a suitable period is six months.

[0036] Exome: As used herein, the term “exome” is used in accordance with the meaning understood by those skilled in the art and refers to the set of exon sequences found in a particular genome.

[0037] Preferred Response: As used herein, the term “preferred response” refers to a reduction in the frequency and / or intensity of one or more symptoms in the pathophysiology of a disease, a reduction in tumor burden, complete or partial remission, or other improvement. A symptom is reduced when one or more symptoms of a particular disease, disorder, or condition are reduced in magnitude (e.g., intensity, severity, etc.) and / or frequency. For the purposes of clarity, a delay in the onset of a particular symptom is considered one form of reducing the frequency of that symptom. Many cancer patients with smaller tumors have no symptoms. The present invention is not intended to be limited to cases where symptoms disappear. The present invention specifically aims to treat one or more symptoms so that they are reduced, if not completely eliminated (and the condition in question is thus “improved”). In some embodiments, a preferred response is established when a particular treatment regimen is administered across an appropriate population and shows a statistically significant effect. Proof of specific results in specific individuals cannot be required. Thus, in some embodiments, a particular treatment regimen is determined to have a preferred response when its administration correlates with an appropriate desired effect.

[0038] Homology: As used herein, the term “homology” refers to the overall relationship between polymerizable molecules, for example, nucleic acid molecules (e.g., DNA molecules and / or RNA molecules) and / or polypeptide molecules. In some embodiments, polymerizable molecules are considered “homological” to each other if their sequences are at least 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, or 99% identical. In some embodiments, polymerizable molecules are considered “homological” to each other if their sequences are at least 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, or 99% similar.

[0039] Identity: As used herein, the term “identity” refers to the overall relationship between polymerizable molecules, such as nucleic acid molecules (e.g., DNA molecules and / or RNA molecules) and / or polypeptide molecules. The calculation of the identity percentage of two nucleic acid sequences can be performed by aligning the two sequences for the best possible comparison (e.g., gaps can be introduced in one or both of the first and second nucleic acid sequences for the best possible alignment, and non-identical sequences can be ignored for the comparison). In certain embodiments, the length of the aligned sequences for the comparison is at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, at least 95%, or substantially 100% of the reference sequence. Next, nucleotides at the corresponding nucleotide positions are compared. The molecules are identical at a given position when the position in the first sequence is occupied by the same nucleotide as the corresponding position in the second sequence. The percentage of identity between two sequences is a function of the number of gaps and the number of identical positions shared by the sequences, taking into account the length of each gap that needs to be introduced for optimal alignment of the two sequences. Sequence comparison and determination of the percentage of identity between two sequences can be achieved using mathematical algorithms. For example, the percentage identity between two nucleotide sequences can be determined using the algorithm of Meyers and Miller (CABIOS, 1989, 4:11-17), which was incorporated into the ALIGN program (version 2.0) using the PAM120 weight residual table, a gap length penalty of 12, and a gap penalty of 4. Alternatively, the percentage of identity between two nucleotide sequences can be determined using the GAP program in the GCG software package, which uses the NWSgapdna.CMP matrix.

[0040] Immune checkpoint modulators: As used herein, the term “immune checkpoint modulator” refers to agents that directly or indirectly interact with immune checkpoints. In some embodiments, immune checkpoint modulators increase immune effector responses (e.g., cytotoxic T cell responses) by, for example, stimulating positive signals for T cell activation. In some embodiments, immune checkpoint modulators increase immune effector responses (e.g., cytotoxic T cell responses) by, for example, suppressing (deinhibiting) negative signals for T cell activation. In some embodiments, immune checkpoint modulators interfere with signals for T cell anergy. In some embodiments, immune checkpoint modulators reduce, eliminate, or prevent immune tolerance to one or more antigens.

[0041] Long-term benefit: Generally, the term “long-term benefit” refers to a desirable clinical outcome observed after administration of a specific treatment or both of the above, maintained for a clinically appropriate period. For example, in some embodiments, the long-term benefit of cancer therapy is (1) no evidence of disease (“NED,” e.g., against radiographic assessment) and / or (2) stable or reduced disease volume, or (1) no evidence of disease (“NED,” e.g., against radiographic assessment) and / or (2) stable or reduced disease volume. In some embodiments, the clinically appropriate period is at least one month, at least two months, at least three months, at least four months, at least five months, or longer. In some embodiments, the clinically appropriate period is at least six months. In some embodiments, the clinically appropriate period is at least one year.

[0042] Marker: As used herein, a marker refers to a drug whose presence or level is characteristic of a particular tumor or its metastatic disease. For example, in some embodiments, the term refers to a gene expression product that is characteristic of a particular tumor, tumor subclass, tumor stage, etc. Alternatively or additionally, in some embodiments, the presence or level of a particular marker correlates with the activity (or level of activity) of a particular signaling pathway that may be a particular class of tumor, for example. The statistical significance of the presence or absence of a marker may vary depending on the particular marker. In some embodiments, the detection of a marker is highly specific in that it reflects a high probability that the tumor is a particular subclass. Such specificity may come at the expense of sensitivity (i.e., negative results may occur even if the tumor is one that is expected to express the marker). Conversely, a highly sensitive marker may be less specific and have lower sensitivity. According to the present invention, a useful marker does not need to distinguish a particular subclass of tumor with 100% accuracy.

[0043] Modulator: The term “modulator” is used to refer to an entity whose presence in a system where a desired activity is observed correlates with a change in the level and / or properties of that activity compared to what is observed under other equivalent conditions in the absence of the modulator. In some embodiments, a modulator is an activator in that its activity increases compared to what is observed under other equivalent conditions in the absence of the modulator. In some embodiments, a modulator is an inhibitor in that its activity decreases compared to other equivalent conditions in the absence of the modulator. In some embodiments, a modulator directly interacts with the target entity whose activity is of interest. In some embodiments, a modulator indirectly interacts with the target entity whose activity is of interest (i.e., directly with an intermediate agent that interacts with the target entity). In some embodiments, a modulator affects the level of the target entity of interest. Alternatively or additionally, in some embodiments, a modulator affects the activity of the target entity of interest without affecting the level of the target entity. In some embodiments, the modulator affects both the level and activity of the target entity of interest, so that the observed difference in activity is not entirely explained by or equal to the observed difference in level.

[0044] Mutation: As used herein, the term “mutation” refers to a permanent change in the DNA sequence that makes up a gene. In some embodiments, mutations range in size from a single DNA building block (DNA base) to a large fragment of a chromosome. In some embodiments, mutations can include missense mutations, frameshift mutations, duplications, insertions, nonsense mutations, deletions, and repeat extensions. In some embodiments, a missense mutation is a change of one DNA base pair that results in the substitution of one amino acid in a protein produced by a gene with another. In some embodiments, a nonsense mutation is also a change of one DNA base pair. However, instead of substituting one amino acid with another, the altered DNA sequence signals the cell to stop assembling the protein. In some embodiments, an insertion changes the number of DNA bases in a gene by adding a piece of DNA. In some embodiments, a deletion changes the number of DNA bases in a gene by removing a piece of DNA. In some embodiments, a small deletion may remove one or a few base pairs in a gene, while a large deletion may remove an entire gene or multiple adjacent genes. In some embodiments, replication consists of a piece of DNA that has been abnormally copied one or more times. In some embodiments, frameshift mutations occur when the addition or deletion of DNA bases alters the reading frame of a gene. The reading frame consists of a group of three bases, each encoding a single amino acid. In some embodiments, frameshift mutations shift the grouping of these bases, altering the encoding of an amino acid. In some embodiments, insertions, deletions, and duplications can all be frameshift mutations. In some embodiments, repeat elongation is another type of mutation. In some embodiments, a nucleotide repeat is a short DNA sequence that is repeated a certain number of times in succession. For example, a trinucleotide repeat consists of a 3-base pair sequence, and a tetranucleotide repeat consists of a 4-base pair sequence. In some embodiments, repeat elongation is a mutation that increases the number of times a short DNA sequence is repeated.

[0045] "Mutational Load": The term "mutational load" is used herein to refer to the number of mutations detected in a sample (e.g., a tumor sample) at a given point in time. Those skilled in the art will understand that "mutational load" may also be referred to as "mutational burden." In some embodiments, the tumors included in the evaluation of mutational load are neoantigen tumors (i.e., tumors that produce neoantigens). In some embodiments, the samples from which mutational load is evaluated are from a single tumor. In some embodiments, the samples are pooled from multiple tumors and are either from a single individual subject or from multiple subjects.

[0046] Neoepitope: "Neoepitope" is understood by those skilled in the art to mean an epitope that develops or develops in a subject after exposure to or occurrence of a particular event (e.g., the onset or progression of a particular disease, disorder, or condition, e.g., infection, cancer, or stage of cancer). As used herein, a neoepitope is one whose presence and / or level correlates with exposure to or occurrence of an event. In some embodiments, a neoepitope elicits an immune response against cells expressing it (e.g., at an appropriate level). In some embodiments, a neopepitope elicits an immune response that kills or otherwise destroys cells expressing it (e.g., at an appropriate level). In some embodiments, an appropriate event eliciting a neoepitope is or includes somatic mutations in cells. In some embodiments, the neoepitope is not expressed in non-cancer cells to a level and / or manner sufficient to induce and / or support an immune response (e.g., an immune response sufficient to target cancer cells expressing the neoepitope). In some embodiments, the neoepitope is a neoantigen.

[0047] No usefulness: As used herein, the phrase “no usefulness” is used to mean the absence of detectable clinical usefulness (e.g., in response to administration of a particular therapy or treatment of interest). In some embodiments, the absence of clinical usefulness means the absence of a statistically significant change in any particular symptom or feature of a particular disease, disorder, or condition. In some embodiments, the absence of clinical usefulness means a change in one or more symptoms or features of a disease, disorder, or condition that lasts only for a short period of time, such as less than about 6 months, less than about 5 months, less than about 4 months, less than about 3 months, less than about 2 months, less than about 1 month, or less. In some embodiments, no usefulness means the absence of sustained usefulness.

[0048] Success: As used herein, the term “success” refers to a reduction in the size of a cancerous mass by a defined amount. In some embodiments, the cancerous mass is a tumor. In some embodiments, a confirmed success is a response confirmed at least four weeks after treatment.

[0049] Response Rate: As used herein, the term “Response Rate” (“ORR”) has the meaning understood by those skilled in the art and refers to the proportion of patients who have a tumor size reduction of a predetermined amount and minimum duration. In some embodiments, the duration of the response is measured typically from the time of the initial response to recorded tumor progression. In some embodiments, the ORR comprises the sum of partial and complete responses.

[0050] Patient: As used herein, the terms “patient” or “subject” refer to any organism to which the provided composition is administered or may be administered for, for example, experimental, diagnostic, prophylactic, cosmetic, and / or therapeutic purposes. Typical patients include animals (e.g., mice, rats, rabbits, non-human primates, and / or humans). In some embodiments, the patient is human. In some embodiments, the patient suffers from or is susceptible to the effects of one or more disorders or conditions. In some embodiments, the patient exhibits one or more symptoms of a disorder or condition. In some embodiments, the patient is diagnosed with one or more disorders or conditions. In some embodiments, the disorder or condition is the presence of cancer or one or more tumors, or includes the presence of cancer or one or more tumors. In some embodiments, the disorder or condition is metastatic cancer.

[0051] Polypeptide: As used herein, “polypeptide” is, generally speaking, a string of at least two amino acids linked to one another by peptide bonds. In some embodiments, a polypeptide may contain at least three to five amino acids, each linked to the others by at least one peptide bond. Those skilled in the art will understand that polypeptides sometimes contain “non-natural” amino acids or other subjects that can nevertheless be incorporated into a polypeptide chain.

[0052] Prognostic and Predictive Information: As used herein, the terms prognostic and predictive information are used interchangeably to refer to any information that may be used to indicate any aspect of the course of a disease or condition, either in the absence or in the presence of treatment. Such information may include, but is not limited to, the patient's life expectancy, the patient's likelihood of surviving for a given amount of time (e.g., 6 months, 1 year, 5 years), the patient's likelihood of recovering from the disease, or the patient's likelihood of responding to a particular therapy (response may be defined in any of several ways). Prognostic and predictive information is included in a broad category of diagnostic information.

[0053] Progression-Free Survival: As used herein, the term “progression-free survival” (PFS) has the meaning understood by those skilled in the art and relates to the length of time during and after treatment for a disease such as cancer in which a patient survives with the disease but does not experience disease progression. In some embodiments, measuring progression-free survival is used as an assessment of how well a new treatment is working. In some embodiments, PFS is determined in a randomized clinical trial. In some such embodiments, PFS refers to the time from randomization to tumor progression and / or death.

[0054] Protein: As used herein, the term “protein” means polypeptide (i.e., a string of at least two amino acids linked together by peptide bonds). Proteins may contain non-amino acid portions (e.g., glycoproteins, proteoglycans, etc.) and / or may be separately processed or modified. Those skilled in the art will understand that “protein” may be a complete polypeptide chain or a characteristic portion thereof when produced by a cell. Those skilled in the art will understand that a protein may contain two or more polypeptide chains linked, for example, by one or more disulfide bonds or associated by other means. Polypeptides may contain L-amino acids, D-amino acids, or both, and may contain various amino acid modifications or analogs known to those skilled in the art. Useful modifications include, for example, terminal acetylation, amidation, methylation, etc. In some embodiments, proteins may contain native amino acids, non-native amino acids, synthetic amino acids, and combinations thereof. The term “peptide” is generally used to refer to polypeptides having a length of less than about 100 amino acids, less than about 50 amino acids, less than about 20 amino acids, or less than about 10 amino acids.

[0055] Reference: Those skilled in the art will understand that in many embodiments described herein, the determined value or feature of interest is compared to a suitable reference. In some embodiments, the reference value or feature is determined for an equivalent cohort, individual, population, or sample. In some embodiments, the reference value or feature is examined and / or determined substantially concurrently with the examination or determination of the feature or value of interest. In some embodiments, the reference feature or value is, at the option of, a historical reference embodied in a tangible medium, or includes a historical reference. Typically, as can be understood by those skilled in the art, the reference value or feature is determined under circumstances equivalent to those used to determine or analyze the feature or value of interest.

[0056] Response: As used herein, the term “response” may refer to a change in a subject’s condition that occurs as a result of or correlates with a treatment. In some embodiments, a response is or includes a beneficial response. In some embodiments, a beneficial response may include stabilization of the condition (e.g., prevention or delay of an exacerbation that was expected or typically observed to occur in the absence of treatment), recovery of one or more symptoms of the condition (e.g., reduction in frequency and / or intensity), and / or improvement in the prospect of recovery of the condition. In some embodiments, “response” may refer to a response of an organism, organ, tissue, cell, or cellular component, or a response in an in vitro system. In some embodiments, a response is or includes a clinical response. In some embodiments, the presence, degree, and / or nature of a response may be measured and / or characterized according to certain criteria. In some embodiments, such criteria may include clinical criteria and / or objective criteria. In some embodiments, techniques for evaluating the response may include, but are not limited to, clinical trials, positron emission tomography, chest X-ray CT scans, MRI, ultrasound, endoscopy, laparoscopy, the presence or level of specific markers in a sample, cytology, and / or histology. Where the response of interest is a tumor response to therapy or includes a tumor response to therapy, those skilled in the art will know of various established techniques for evaluating such responses, including, for example, those for determining tumor load, tumor size, tumor stage, etc.For example, certain techniques for evaluating the response to treatment of solid tumors are discussed in Therasse et al., “New guidelines to evaluate the response to treatment in solid tumors”, European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada, J.Natl.CancerInst., 2000, 92(3):205-216. Those skilled in the art will, in light of this disclosure, be aware of strategies for determining specific response criteria for individual tumors, tumor types, patient populations, or cohorts, and for determining appropriate references.

[0057] Sample: As used herein, the term “sample” typically refers to a biological sample obtained from or derived from a source of interest, as described herein. In some embodiments, the source of interest includes an animal or a living organism such as a human. In some embodiments, the biological sample is or includes cytological tissue or fluid. In some embodiments, the biological sample may be or may include bone marrow, blood, blood cells, ascites, tissue or fine-needle biopsy specimens, cell-containing fluids, suspended nucleic acids, sputum, saliva, urine, cerebrospinal fluid, peritoneal fluid, pleural fluid, feces, lymph, gynecological fluids, skin swabs, vaginal swabs, oral swabs, nasal swabs, washes or lavages such as mammary duct lavages or bronchoalveolar lavages, aspirates, scrapes, bone marrow specimens, tissue biopsy specimens, surgical specimens, feces, other body fluids, secretions, and / or excretions, and / or cells therefrom. In some embodiments, the biological sample is cells obtained from an individual or includes cells obtained from an individual. In some embodiments, the obtained cells are cells from the individual from which the sample was obtained or include cells from the individual from which the sample was obtained. In some embodiments, the sample is a “primary sample” obtained directly from the source of interest by any suitable means. For example, in some embodiments, the primary biological sample is obtained by a method selected from the group consisting of biopsy (e.g., fine-needle aspiration or tissue biopsy), surgery, collection of bodily fluids (e.g., blood, lymph, feces, etc.). In some embodiments, as is evident from the context, the term “sample” refers to a preparation obtained by processing the primary sample (e.g., removing one or more components and / or adding one or more agents). For example, filtration using a semipermeable membrane. Such a “processed sample” may include nucleic acids or proteins extracted from the sample or obtained by exposing the primary sample to techniques such as mRNA amplification or reverse transcription, isolation and / or purification of certain components, etc.

[0058] Specific: When the term “specific” is used herein in relation to active drugs, it will be understood by those skilled in the art to mean that the drug is distinct among potential target entities or aspects. For example, in some embodiments, a drug is said to bind “specifically” to a target if it preferentially binds to that target in the presence of one or more competing alternative targets. In many embodiments, a particular interaction depends on the presence of specific structural features of the target entity (e.g., epitopes, cavities, binding sites). It should be understood that specificity does not have to be absolute. In some embodiments, specificity may be evaluated in comparison to that of a binder for one or more other potential target entities (e.g., competitors). In some embodiments, specificity is evaluated in comparison to that of a reference specific binder. In some embodiments, specificity is evaluated in comparison to that of a reference nonspecific binder. In some embodiments, a drug or entity does not directly bind to competing alternative targets under conditions that it binds to its target entity. In some embodiments, the binder binds to its target entity with a higher on-rate, lower off-rate, increased affinity, decreased dissociation, and / or increased stability compared to competing alternative targets.

[0059] Specific Binding: As used herein, the terms “specific binding,” “specific to,” or “specific to” refer to the interaction between a target entity (e.g., a target protein or polypeptide) and a binder (e.g., a provided antibody). As will be understood by those skilled in the art, an interaction is considered “specific” if the interaction is advantageous in the presence of alternative interactions. In many embodiments, the interaction typically depends on the presence of a specific structural feature of the target molecule, such as an antigenic determinant or epitope recognized by the binding molecule. For example, if an antibody is specific to epitope A, the presence of a polypeptide containing epitope A or, in a reaction containing both advantageously labeled A and an antibody against it, advantageously unlabeled A reduces the amount of labeled A that binds to the antibody. It should be understood that specificity does not have to be absolute. For example, it is well known in the art that many antibodies cross-react with other epitopes in addition to those present on the target molecule. Such cross-reactivity may be acceptable depending on the application in which the antibody is used. In certain embodiments, antibodies specific to receptor tyrosine kinases exhibit less than 10% cross-reactivity with receptor tyrosine kinases bound to protease inhibitors (e.g., ACT). Those skilled in the art will be able to select antibodies with a sufficient degree of specificity to perform well in a given application (e.g., for the detection of a target molecule, for therapeutic purposes, etc.). Specificity can be evaluated in the context of additional factors such as the affinity of the binding molecule to the target molecule versus the affinity of the binding molecule to other targets (e.g., competitors). If the binding molecule exhibits high affinity for the target molecule, detection is desirable, and if it exhibits low affinity for the target molecule, detection is desirable.

[0060] Cancer Stage: As used herein, the term “cancer stage” refers to a qualitative or quantitative assessment of the level of cancer progression. Criteria used to determine cancer stage include, but are not limited to, tumor size and the extent of metastasis (e.g., localized or distant).

[0061] Subject: As used herein, the terms “subject” or “patient” refer to any organism to which embodiments of the present invention may be used or administered, for example, for experimental, diagnostic, preventive, and / or therapeutic purposes. Typical subjects include animals (e.g., mice, rats, rabbits, non-human primates, and humans, insects, worms, etc.).

[0062] Substantially: As used herein, the term “substantially” refers to a quantitative state indicating the total or near-total degree or extent of a particular feature or attribute. Those skilled in the art of biology will understand that biological and chemical phenomena rarely, if ever, proceed toward completion and / or reach completion or achieve or avoid absolute results. Thus, the term “substantially” is used to capture the potential lack of completion inherent in many biological and chemical phenomena.

[0063] Having a disease, disorder, or condition (e.g., cancer) is an individual who has been diagnosed with and / or exhibits one or more symptoms of the disease, disorder, or condition. In some embodiments, an individual having cancer has cancer but does not exhibit any symptoms of cancer and / or has not been diagnosed with cancer.

[0064] Susceptible to: A person who is "susceptible to" a disease, disorder, or condition (e.g., cancer) is at risk of developing the disease, disorder, or condition. In some embodiments, a person who is susceptible to a disease, disorder, or condition does not exhibit any symptoms of the disease, disorder, and / or condition. In some embodiments, a person who is susceptible to a disease, disorder, and / or condition has not been diagnosed with the disease, disorder, and / or condition. In some embodiments, a person who is susceptible to a disease, disorder, or condition is a person who exhibits a condition associated with the development of the disease, disorder, or condition. In some embodiments, the risk of developing a disease, disorder, and / or condition is a population-based risk.

[0065] Target Cells or Target Tissues: As used herein, the terms “target cells” or “target tissues” refer to any cells, tissues, or organisms that are affected by and treated under the conditions described herein, or any cells, tissues, or organisms that express proteins involved under the conditions described herein. In some embodiments, target cells, target tissues, or target organisms include these cells, tissues, or organisms that have detectable immune checkpoint signals and / or activity. In some embodiments, target cells, target tissues, or target organisms include cells, tissues, or organisms that exhibit disease-related pathology, symptoms, or characteristics.

[0066] Therapeutic regimen: As used herein, the term “therapeutic regimen” means any method used to partially or completely alleviate, restore, reduce, suppress, prevent, delay the onset, reduce the severity, or reduce the incidence of one or more symptoms or characteristics of a particular disease, disorder, and / or condition. A therapeutic regimen includes treatment or a series of treatments designed to achieve a particular effect, for example, reduction or elimination of an adverse condition or disease such as cancer. Treatment may include administration of one or more compounds in the same or different amounts for the same or different amounts of time, simultaneously, sequentially, or in different numbers. Alternatively or additionally, treatment may include exposure to radiation, chemotherapeutic agents, hormone therapy, or surgery. In addition, a “therapeutic regimen” may include genetic methods such as gene therapy, gene ablation, or other methods known to reduce the translation of a particular gene or gene-derived mRNA.

[0067] Therapeutic agent: As used herein, the term “therapeutic agent” means any agent that, when administered to a subject, has a therapeutic effect and induces a desired biological and / or pharmacological effect.

[0068] Therapeutic Dose: As used herein, the term “therapeutic dose” refers to the amount of an agent (e.g., an immune checkpoint modulator) that confers a therapeutic effect to a treated subject in a reasonable benefit-risk ratio applicable to any medical treatment. Therapeutic effect may be objective (i.e., measurable by several tests or markers) or subjective (i.e., the subject is an indicator of or perceives the effect). In particular, “therapeutic dose” refers to a therapeutic agent or composition that is effective in treating, restoring, or preventing a desired disease or condition, or in restoring disease-related symptoms, preventing or delaying the onset of the disease, and / or reducing the severity or frequency of disease symptoms. Therapeutic doses are generally administered in a dosing regimen that may contain multiple unit doses. For any particular therapeutic agent, the therapeutic dose (and / or appropriate unit dose in an effective dosing regimen) may vary depending, for example, the route of administration, and combinations with other pharmaceutical agents. Furthermore, a specific therapeutically effective dose (and / or unit dose) for any particular patient may depend on a variety of factors, including the disorder being treated and its severity, the activity of the specific pharmaceutical agent employed, the specific composition employed, the patient's age, weight, general health, sex, diet, time of administration, route of administration, and / or frequency of excretion or metabolism of the specific fusion protein employed, continuation of treatment, and factors well known to those skilled in the art of the medical field.

[0069] Treatment: As used herein, the term “treatment” (and also “to treat” or “treatment”) means any administration of a substance (e.g., a provided composition) that partially or completely alleviates, restores, reduces, suppresses, delays the onset, reduces the severity, or reduces the occurrence of one or more symptoms, characteristics, and / or causes of a particular disease, disorder, and / or condition (e.g., cancer). Such treatment may relate to a subject that does not show signs of the disease, disorder, and / or condition in question, and / or a subject that shows only initial signs of the disease, disorder, and / or condition. Alternatively or additionally, such treatment may relate to a subject that shows one or more established signs of the disease, disorder, and / or condition in question. In some embodiments, the treatment may be a subject diagnosed with the disease, disorder, and / or condition in question. In some embodiments, the treatment may be a subject known to have one or more susceptibility factors that statistically correlate with an increased risk of developing the disease, disorder, and / or condition in question.

[0070] Wild-type: As used herein, the term “wild-type” has the meaning understood by those skilled in the art, referring to an entity having the structure and / or activity found in nature in its “normal” form or context (as opposed to mutants, diseased, modified, etc.). Those skilled in the art will understand that wild-type genes and polypeptides often exist in multiple different forms (e.g., alleles). [Modes for carrying out the invention]

[0071] cancer In some embodiments, the present invention relates to the treatment of cancer. In some embodiments, certain exemplary cancers that can be treated according to this disclosure include, for example, adrenocortical carcinoma, astrocytoma, basal cell carcinoma, carcinoid, cardiac, cholangiocarcinoma, chordoma, chronic myeloproliferative neoplasm, craniopharyngeal carcinoma, ductal carcinoma in situ, ependymoma, intraocular melanoma, gastrointestinal carcinoid, gastrointestinal stromal tumor (GIST), gestational trophoblastic disease, glioma, histiocytosis, leukemia (e.g., acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), chronic lymphocytic leukemia (CLL), chronic myeloid leukemia (CML), hairy cell leukemia, myeloid leukemia, and myeloid leukemia), lymphoma (e.g., Burkitt lymphoma (non-Hodgkin lymphoma), cutaneous T-cell lymphoma, Hodgkin lymphoma, mycosis fungoides, Sézary syndrome, AIDS-related lymphoma, follicular lymphoma, diffuse lymphoma) Large B-cell lymphoma), melanoma, Merkel cell carcinoma, mesothelioma, myeloma (e.g., multiple myeloma), myelodysplastic syndrome, papillomatosis, paraganglioma, pheochromocytoma, pleuroblastoma, retinoblastoma, sarcoma (e.g., Ewing's sarcoma, Kaposi's sarcoma, osteosarcoma, rhabdomyosarcoma, uterine sarcoma, vascular sarcoma), Wilms' tumor, and / or adrenal cortex, anus, appendix, bile duct, bladder, bone, brain, breast, bronchi, This includes cancers of the central nervous system, cervix, colon, endometrium, esophagus, eye, fallopian tube, gallbladder, digestive tract, germ cells, head and neck, heart, intestines, kidneys (e.g., Wilms' tumor), larynx, liver, lungs (e.g., non-small cell lung cancer, small cell lung cancer), mouth, nasal cavity, oral cavity, ovaries, pancreas, rectum, skin, stomach, testes, throat, thyroid, penis, pharynx, peritoneum, pituitary gland, prostate, rectum, salivary glands, ureters, urethra, uterus, vagina, or vulva.

[0072] In some embodiments, cancer can involve one or more tumors. In some embodiments, tumors include solid tumors. In some embodiments, solid tumors include, but are not limited to, tumors of the bladder, breast, central nervous system, cervix, colon, esophagus, endometrium, head and neck, kidney, liver, lung, ovary, pancreas, skin, stomach, uterus, or upper respiratory tract.

[0073] In some embodiments, cancer is selected from the group consisting of bladder cancer, bone cancer, breast cancer, cancer of unknown primary origin, esophageal and gastric cancer, gastrointestinal cancer, glioma, head and neck cancer, hepatobiliary tract cancer, melanoma, mesothelioma, non-Hodgkin lymphoma, non-small cell lung cancer, pancreatic cancer, prostate cancer, renal cell carcinoma, skin cancer (non-melanoma), small cell lung cancer, soft tissue sarcoma, thyroid cancer, and combinations thereof.

[0074] In some embodiments, the cancer is selected from the group consisting of bladder cancer, breast cancer, esophageal and gastric cancer, glioma, head and neck cancer, melanoma, non-small cell lung cancer, renal cell carcinoma, and combinations thereof.

[0075] In some embodiments, the cancer that can be treated in accordance with this disclosure is one that has been exposed to the immunotherapy described herein.

[0076] In some embodiments, cancers that can be treated in accordance with this disclosure are those that have been exposed to an immunotherapy that, in some embodiments, includes a therapy with one or more immune checkpoint inhibitor modulators, or an immunotherapy that may include a therapy with one or more immune checkpoint inhibitor modulators.

[0077] In some embodiments, cancers that can be treated according to this disclosure are characterized by high tumor mutational load (i.e., tumor mutational load exceeding an appropriate threshold) as described herein. Alternatively or additionally, cancers that can be treated according to this disclosure are characterized by neoantigens.

[0078] In some embodiments, cancers that can be treated in accordance with this disclosure are characterized by exposure to immunotherapy that includes both immune checkpoint modulators and high tumor mutational burden. In some such embodiments, the cancer exhibits a higher tumor mutational burden that was present prior to its exposure to immunotherapy. immunotherapy

[0079] In some embodiments, this disclosure relates to the administration of immunotherapy to a subject. In some embodiments, the immunotherapy is or comprises immune checkpoint modulation therapy. In some embodiments, the immunotherapy involves the administration of one or more immunomodulators. In some embodiments, the immunomodulator is or comprises an immune checkpoint modulator. In some embodiments, the immune checkpoint modulator is a drug (e.g., an antibody drug) that targets (i.e., specifically interacts with) an immune checkpoint target. In some embodiments, the immune checkpoint target is one or more of CTLA-4, PD-1, PD-L1, GITR, OX40, LAG-3, KIR, TIM-3, CD28, CD40, and CD137, or comprises one or more of CTLA-4, PD-1, PD-L1, GITR, OX40, LAG-3, KIR, TIM-3, CD28, CD40, and CD137. In some embodiments, immune checkpoint modulator therapy is the administration of an antibody drug that targets one or more such checkpoint targets, or includes the administration of an antibody drug that targets one or more such checkpoint targets.

[0080] In some embodiments, immune checkpoints refer to suppressive pathways of the immune system responsible for maintaining self-tolerance and regulating the continuation and amplitude of physiological immune responses. Certain cancer cells thrive by utilizing immune checkpoint pathways as a major mechanism of immune resistance, particularly with respect to tumor antigen-specific T cells. For example, certain cancer cells may overexpress one or more immune checkpoint proteins responsible for suppressing cytotoxic T cell responses. Therefore, immune checkpoint modulators, among other things, may be administered to overcome suppressive signals and allow and / or increase immune attacks against cancer cells. Immune checkpoint modulators can promote immune cell responses against cancer cells by reducing, suppressing, or inhibiting signaling by negative immune response regulators (e.g., CTLA-4), or they can stimulate or enhance signaling by positive immune response regulators (e.g., CD28).

[0081] Advances in understanding the molecular mechanisms of T cell activation and inhibition, as well as immune homeostasis, have enabled the rational development of immunologically targeted therapies for cancer. Among these, the best known are immune checkpoint modulator monoclonal antibodies that suppress the CTLA-4 and PD-1 pathways, representing inhibitory checkpoints that suppress T cells from complete and sustained activation and proliferation under normal physiological conditions. Inhibitors of the CTLA-4 and / or PD-1 pathways can produce sustained relief for patients with a broad spectrum of malignancies. In some embodiments, immunotherapy is an administration of one or more PD-1 or PD-L1 inhibitors, or comprises an administration of one or more PD-1 or PD-L1 inhibitors. In some embodiments, immunotherapy is an administration of one or more CTLA-4 inhibitors, or comprises an administration of one or more CTLA-4 inhibitors. In some embodiments, the immunotherapy may include ipilumimab and tremelimumab targeting CTLA-4, pembrolizumab, nivolumab, avelumab, durvalumab, and atezolizumab targeting PD-1, or any combination thereof.

[0082] The teachings of this disclosure predict, among other things, responsiveness to immune checkpoint modulators, particularly to therapeutic modalities or regimens targeting immune checkpoint modulators. The disclosure shows, among other things, that tumor mutational loading thresholds correlate with responsiveness to immune checkpoint modulators. In some embodiments, the disclosure shows that tumor mutational loading thresholds correlate with an increased probability of clinical efficacy from immune checkpoint modulators for these cancers that are responsive to immunotherapy (e.g., to PD-1 inhibitors and / or CTLA-4). In some embodiments, immunotherapy (e.g., immune checkpoint modulator therapy) involves the administration of a drug that acts as an inhibitor of cytotoxic T lymphocyte-associated protein 4 (CTLA-4). In certain embodiments, immunotherapy involves treatment with a drug that interferes with interactions involving CTLA-4 (e.g., CD80 or CD86). In some embodiments, immunotherapy involves the administration of one or more of tremelimumab and / or ipilimumab. In some embodiments, immunotherapy (e.g., immune checkpoint modifier therapy) involves the administration of a drug (e.g., an antibody drug) that acts as an inhibitor of programmed cell death 1 (PD-1). In certain embodiments, immunotherapy involves treatment with a drug that interferes with interactions involving PD-1 (e.g., with PD-L1). In some embodiments, immunotherapy involves the administration of a drug (e.g., an antibody drug) that specifically interacts with PD-1 or PD-L1. In some embodiments, immunotherapy (e.g., immune checkpoint modifier therapy) involves the administration of one or more of nivolumab, pembrolizumab, atezolizumab, avelumab, and / or durvalumab. CTLA-4

[0083] CTLA-4 is a member of the immunoglobulin superfamily that is expressed by activated T cells and transmits inhibitory signals to T cells. CTLA-4 is structurally similar to the T cell costimulatory protein CD28, and both molecules bind to CD80 and CD86 on antigen-presenting cells. 18CTLA-4 binds to CD80 and CD86 with greater affinity than CD28, and therefore CTLA-4 outperforms CD28 for its ligand. 18 CTLA-4 transmits inhibitory signals to T cells, while CD28 transmits stimulating signals. T cell activation via the T cell receptor and CD28 leads to increased expression of CTLA-4.

[0084] The mechanism by which CTLA-4 acts on T cells remains somewhat unclear. Biochemical evidence suggests that CTLA-4 recruits phosphatases to T cell receptors, thereby attenuating signaling. It has also been suggested that CTLA-4 functions in vivo by capturing and removing CD80 and CD86 from the membrane of antigen-presenting cells, thus preventing these antigens from being used to induce CD28.

[0085] The CTLA-4 protein contains an extracellular V domain, a transmembrane domain, and a cytoplasmic tail. CTLA-4 has an intracellular domain similar to that of CD28, in that it lacks intrinsic catalytic activity and contains one YVKM motif capable of binding PI3K, PP2A, and SHP-2, as well as one proline-rich motif capable of binding SH3-containing proteins. One role of CTLA-4 in repressing T cell responses appears to be its direct involvement in the dephosphorylation of SHP-2 and PP2A of T cell receptor proximal signaling proteins such as CD3 and LAT. CTLA-4 may also indirectly influence signaling through competition with CD28 for CD80 and / or CD86.

[0086] The first clinical evidence that regulating T cell activation can lead to effective anticancer therapies stemmed from the development of the CTLA-4 inhibitor antibody ipilimumab. 18 In some embodiments, ipilimumab is a human IgG1 antibody with specificity for CTLA-4. In some embodiments, another CTLA-4 inhibitory therapy, tremelimumab, is a human IgG2 antibody. PD-1

[0087] PD-1 is expressed on T cells, B cells, and certain myeloid cells. However, its role is most characteristically characterized on T cells. PD-1 expression on T cells is induced by antigen stimulation. Unlike CTLA-4, which limits initial T cell activation, PD-1 primarily exerts its inhibitory effect on T cells in the peripheral regions where T cells encounter PD-1 ligands. Two ligands for PD-1 have been identified to date: PD-L1 and PD-L2, which are expressed by a wide range of cell types, including tumor cells, monocyte-derived myeloid dendritic cells, T cells, and B cells. 18 In cancer, tumor cells and myeloid cells are considered to be the major cell types that mediate T cell suppression via PD-1 ligation. However, it remains unclear whether the effects of PD-L1 and PD-L2 on PD-1 downstream signaling depend on the cell type expressing a given ligand. Furthermore, differences exist between PD-L1 and PD-L2 induction effects, and these remain largely unexplained.

[0088] Several mechanisms of PD-1-mediated T cell suppression have been proposed. 18One mechanism suggests that PD-1 ligation suppresses T cell activation only upon T cell receptor engagement. PD-1 has an intracellular "immunoreceptor tyrosine-based inhibitory motif" or (ITIM) and an immunoreceptor tyrosine-based switch motif. PD-1 ligation has been shown to cause recruitment to the immunoreceptor tyrosine-based switch motifs of phosphatases called "src homology 2 domain-containing tyrosine phosphatases" or SHP-1 and SHP-2. Moreover, PD-1 ligation has been shown to interfere with signaling molecules such as phosphatidylinositol-4,5-bisphosphate 3-kinase and Ras, which are important for T cell proliferation, cytokine secretion, and metabolism. Analysis of human immunodeficiency virus (HIV)-specific T cells has also shown upregulation of PD-1-dependent basic leucine zipper transcription factors that suppress T cell function. Ligation of PD-1 has been shown to induce metabolic changes in T cells. Metabolic reprogramming of T cells from glycolysis to lipolysis is a result of PD-1-mediated impairment of T cell effector function. Furthermore, PD-1-induced defects in mitochondrial respiration and glycolysis cause impaired T cell effector function that can be reversed by mammalian target of rapamycin inhibition. Since most of the identified mechanisms of PD-1-mediated T cell suppression are based on in vitro or ex vivo experiments, it remains unshown that these same mechanisms are responsible for T cell exhaustion in vivo.

[0089] PD-1 is a 288 amino acid type I membrane protein and a member of the extended CD28 / CTLA-4 family of T cell regulators. 19The PD-1 protein structure includes an extracellular IgV domain in front of the transmembrane and intracellular tail, and contains two phosphorylation sites located at the immunoreceptor tyrosine-based inhibitory motif (ITIM) and the immunoreceptor tyrosine-based switch motif, suggesting that PD-1 negatively regulates T cell receptor signaling. This is consistent with the binding of the PD-1 cytoplasmic tail to the ligand binding of SHP-1 and SHP-2 phosphatases. In addition, PD-1 ligation upregulates the E3 ubiquitin ligases CBL-b and c-CBL, which induce T cell receptor downregulation. PD-1 is expressed on activated T cells, B cells, and macrophages, suggesting that PD-1 negatively regulates the immune response more broadly than CTLA-4.

[0090] Combined CTLA-4 and PD-1 While monotherapy with CTLA-4 or PD-1 blocking antibodies has significantly extended survival in several patients with certain cancers, there are cases where several patients do not respond to therapy. Previous studies have shown that combination therapy with ipilimumab (a CTLA-4 inhibitor) and nivolumab (a PD-1 inhibitor) induced a better response than either monotherapy. 18、20 In some embodiments, immunotherapy includes both PD-1 inhibitor therapy and CTLA-4 inhibitor therapy in accordance with this disclosure. In certain embodiments, immunotherapy (e.g., immune checkpoint modulator therapy) involves treatment with a drug (e.g., an antibody drug) that interferes with interactions involving CTLA-4 and / or PD-1. In some embodiments, immunotherapy (e.g., immune checkpoint modulator therapy) involves administration of a drug (e.g., an antibody drug) that specifically interacts with one or more of CTLA-4, CD80, CD86, PD-1, or PD-L1. In some embodiments, such therapy involves administration of one or more of atezolizumab, avelumab, durvalumab, ipilimumab, nivolumab, pembrolizumab, and / or tremelimumab.

[0091] Tumor mutation burden In particular, this disclosure shows that tumor mutational burden can predict the clinical efficacy of immunotherapy for certain cancers. In particular, this disclosure establishes that, in certain cases, individuals with a higher tumor mutational burden are more likely to respond positively to immunotherapy than individuals with a significantly lower tumor mutational burden. In particular, this disclosure establishes that, in certain cases, individuals with a higher tumor mutational burden who have already received immunotherapy are more likely to respond positively to immunotherapy than individuals with a significantly lower tumor mutational burden.

[0092] In some embodiments, tumor mutation loading includes several somatic mutations within a region of the tumor genome. In some embodiments, somatic mutations include DNA modifications in non-germline cells and commonly occur in cancer cells. In some embodiments, somatic mutations give rise to neoantigens or neoepitopes. Certain somatic mutations in cancer cells have been found to result in the expression of neoepitopes, in some embodiments, which shift a sequence of amino acids from being recognized as "self" to "non-self." Cancer cells harboring "non-self" antigens are typically more likely to elicit an immune response against cancer cells. Identifying multiple mutations in cancer samples described herein may be useful in determining which cancer patients are likely to respond favorably to immunotherapy (e.g., continued and / or extended immunotherapy). In some embodiments, such identification may be useful in determining which cancer patients are particularly likely to respond to treatment with immune checkpoint modulators and / or other PD-1 and / or CTLA-4 inhibitors.

[0093] This disclosure, in particular, shows that patients with a large number of somatic mutations or a high tumor mutagenesis burden for a particular cancer are likely to benefit from immune checkpoint modulators more than patients with a lower tumor mutagenesis burden. In some embodiments, patients with a high tumor mutagenesis burden respond better to PD-1 (programmed cell death 1) inhibitors than these patients with a significantly lower tumor mutagenesis burden. In some embodiments, individuals with a high tumor mutagenesis burden respond better to treatment with anti-PD-1 antibodies than these individuals with a low tumor mutagenesis burden. In some embodiments, individuals with a high tumor mutagenesis burden respond better to treatment with CTLA-4 inhibitors than these individuals with a low tumor mutagenesis burden. In some embodiments, individuals with a high tumor mutagenesis burden respond better to treatment with anti-CTLA-4 antibodies than these individuals with a low tumor mutagenesis burden.

[0094] Tumor mutation loading threshold This disclosure, in particular, encompasses the insight that meaningful limitations can be imposed on mutational analysis of cancer cells, and moreover, that the use of such limitations unexpectedly provides a tumor mutational loading threshold that effectively predicts responsiveness to treatment (e.g., continued and / or extended or modified immunotherapy). In some embodiments, the tumor mutational loading threshold described herein correlates with and / or predicts the response to immunotherapy (e.g., immune checkpoint modifier therapy, e.g., PD-1 inhibitor or CTLA-4 inhibitor).

[0095] Furthermore, the disclosure particularly encompasses the finding that tumor mutational burden thresholds can be defined for tumors that have already received prior immunotherapy to predict the likelihood of a response to cancer immunotherapy (and / or specific immunomodulators and / or regimens). In some embodiments, the number of mutations in a given tumor correlates with and / or is a prediction of a positive response to immunotherapy. Moreover, the disclosure shows that tumor mutational burden levels relative to thresholds can be detected and effectively used to predict tumor responsiveness in a wide variety of cancers.

[0096] In some embodiments, as described herein, the Disclosure provides techniques for defining tumor mutational loading thresholds that predict responsiveness to immunotherapies (e.g., continued and / or extended or modified), and in particular to immune checkpoint modifier therapies. In some embodiments, effective uses of such thresholds for predicting therapeutic responsiveness are described and / or established.

[0097] This disclosure shows that the mutation landscape and / or tumor mutation loading threshold of a particular tumor can predict the potential clinical utility from immunotherapy (e.g., PD-1 inhibitors or CTLA-4 inhibitors). This disclosure also teaches that the tumor mutation loading threshold can predict the potential positive response to immunotherapy with immune checkpoint modulators. Furthermore, the nature of the somatic mutations present can predict the response to immunotherapy with immune checkpoint modulators.

[0098] In some embodiments, the tumor mutational burden level relative to the threshold can be determined and / or detected using targeted gene panel techniques (e.g., evaluated by next-generation sequencing), without necessarily requiring whole exome sequencing.

[0099] Therefore, in particular, this disclosure establishes that appropriate thresholds for these cancers are, for example, the following: [Table A]

[0100] Detection of tumor mutations and / or neoepitopes Cancers may be screened to detect mutations and / or neoepitopes described herein (e.g., tumor mutational load and / or neoepitope load and / or neoantigen identity, and / or the nature, level, and / or frequency of neoepitopes) using any of the various known techniques. In some embodiments, specific mutations or neoepitopes, or their expression, are detected at the nucleic acid level (e.g., in DNA or RNA). Those skilled in the art will recognize that mutations or neoepitopes, or their expression, may be detected in a sample containing DNA or RNA from cancer cells. Furthermore, those skilled in the art will understand that a sample containing DNA or RNA from cancer cells includes, but is not limited to, circulating tumor DNA (ctDNA), free cell DNA (cfDNA), cells, tissues, or organs. In some embodiments, mutations or neoepitopes, or their expression, are detected at the protein level (e.g., in a sample containing polypeptides from cancer cells, where the sample is a polypeptide complex or other higher-order structure including, but not limited to, cells, tissues, or organs).

[0101] In some specific embodiments, detection is involved in nucleic acid sequencing. In some embodiments, detection is involved in whole exome sequencing. In some embodiments, detection is involved in immunoassays. In some embodiments, detection is involved in microassays. In some embodiments, detection is involved in large-scale parallel exome sequencing. In some embodiments, detection is involved in genome sequencing. In some embodiments, detection is involved in RNA sequencing. In some embodiments, detection is involved in standard DNA or RNA sequencing. In some embodiments, detection is involved in mass spectrometry.

[0102] In some embodiments, detection involves next-generation sequencing (DNA and / or RNA). In some embodiments, detection involves genome sequencing, genome resequencing, targeted sequencing panels, transcriptome profiling (RNA-Seq), DNA-protein interaction (ChIP sequencing), and / or epigenomic characterization. In some embodiments, resequencing of a patient's genome may be used, for example, to detect genomic variation.

[0103] In some embodiments, detection involves using techniques such as ELISA, Western transfer, immunoassay, mass spectrometry, and microarray analysis.

[0104] In some embodiments, detection involves next-generation sequencing (DNA and / or RNA). In some embodiments, detection involves next-generation sequencing of a targeted gene panel (e.g., MSK-IMPACT or FoundationOne®). In some embodiments, detection involves genomic profiling. In some embodiments, detection involves genomic profiling using integrated actionable cancer target mutation profiling (MSK-IMPACT). 8、17 MSK-IMPACT is a comprehensive molecular profiling assay that engages in hybridization capture and deep sequencing of all exons and selected introns of multiple oncogenes and tumor suppressor genes, enabling point mutations, small and large insertions or deletions, and rearrangements. MSK-IMPACT also captures single nucleotide polymorphisms between genes and introns, occupying intergeneric and intercellular spaces across the genome and aiding in accurate assessment of copy numbers across the genome. In some embodiments, the probe can target megabases.

[0105] In some embodiments, detection can be involved in sequencing exon and / or intron sequences from at least 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 800, 850, 900, 950, 1000 or more genes (e.g., oncogenes and / or tumor suppressor genes). For example, literature reports have shown that MSK-IMPACT was used to achieve deep sequencing of all exons and selected introns of 468 oncogenes and tumor suppressor genes.

[0106] Alternatively or additionally, in some embodiments, detection can be involved in sequencing intergenetic and / or intronic single nucleotide polymorphisms. For example, literature reports indicate that MSK-IMPACT has been used to achieve deep sequencing of more than 1000 intergenetic and intronic single nucleotide polymorphisms.

[0107] In some embodiments, administering immunotherapy to subjects who have previously received immunotherapy displays a threshold length tumor mutation burden correlated with a statistically significant probability of responding to immunotherapy.

[0108] In some embodiments, administering immunotherapy to a subject includes a further step of measuring the tumor mutational burden level relative to a threshold in the subject, the measurement step being performed at a time selected from the group consisting of pre-administration, during administration, post-administration, and combinations thereof.

[0109] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art. Methods and materials similar to or equivalent to those described herein may be used in the practice or examination of the present invention, but preferred methods and materials are described herein. Human leukocyte antigen

[0110] Prior to this disclosure, there was little understanding of how host genetics influences the response to cancer immunotherapy. One factor repeatedly associated with modulating the immune response in bacterial or viral infections, inflammatory conditions, and autoimmune diseases is the HLA class I genotype (21–29). Human leukocyte antigen (HLA) complexes are gene complexes that encode major histocompatibility complex (MHC) proteins. In humans, the major histocompatibility complex (MHC) class I coding region is central to the immune response. Each HLA class I molecule-binding specific peptide originates from intracellular proteins that are processed and transported into the endoplasmic reticulum by TAP proteins, and they bind to MHC class I molecules for presentation on the cell surface (30).

[0111] MHC molecules are highly polymorphic, with over a thousand allele variants already described within class IA and B loci. Most of the polymorphisms are located in the peptide-binding region, and as a result, each variant is believed to bind a unique repertoire of peptide ligands. Despite this polymorphism, HLA class I molecules can be clustered into groups referred to as supertypes (also known as superfamilies), representing sets of molecules that largely share overlapping peptide-binding specificity. Exemplary supertypes include, but are not limited to, A02, A24, A03, B07, B27, and B44, and each supertype can be described by a supermotif that reflects a broad main anchor motif recognized by molecules within the corresponding supertype. For example, the A02 supertype molecule shares specificity for peptides with aliphatic hydrophobic residues at position 2 and at the C-terminus, while the A03 supertype molecule recognizes peptides with a small or aliphatic residue at position 2 and a basic residue at the C-terminus.

[0112] Typically, in the case of human leukocyte antigen (HLA) class I, the primary binding energy is provided by the interaction of residues at position 2 and the C-terminus of the peptide with the B and F binding pockets of the MHC molecule, respectively, although the side chains of the entire ligand can have a positive or negative influence on binding ability. When pathogen or tumor-derived epitopes are presented on the cell surface, CD8+ T cells should be able to recognize them to subsequently trigger an immune response and eliminate cells bearing these same epitopes (31, 32). Some tumor cells have a reduced ability to present epitopes on their surface due to genetic modifications that result in loss of atypical zygosity (LOH) at HLA loci. LOH is a gross chromosomal event that results in the loss of an entire gene and surrounding chromosomal region. The antitumor activity of immune checkpoint therapy has been shown to depend on CD8+ T cell, MHC class I-dependent immune activity (33-35).

[0113] In particular, this disclosure shows that HLA class I genotypes can influence the clinical efficacy of immunotherapy for certain cancers. This disclosure establishes, among other things, that atypia at one or more HLA class I loci (e.g., A, B, or C) can influence the clinical efficacy of immunotherapy. In some embodiments, atypia at all three HLA class I loci (i.e., maximum atypia) can influence the clinical efficacy of immunotherapy.

[0114] This disclosure, in particular, establishes that, in certain cases, individuals with atypia at one or more HLA class I loci (e.g., A, B, or C) are more likely to respond positively to immunotherapy. In some embodiments, individuals with atypia at all three HLA class I loci (i.e., maximum atypia) are more likely to respond positively to immunotherapy.

[0115] In some embodiments, the disclosure establishes that individuals having a particular HLA class I superfamily allele are more likely to respond positively to immunotherapy. In some embodiments, individuals having the HLA class IB44 allele are more likely to respond positively to immunotherapy. In some embodiments, individuals having the HLA class IB62 allele are more likely to respond positively to immunotherapy.

[0116] Furthermore, this disclosure establishes, in particular, that in certain cases, individuals having atypia at one or more HLA class I loci (e.g., A, B, or C) and a higher tumor mutational burden as described herein are more likely to respond positively to immunotherapy than individuals with a significantly lower tumor mutational burden and / or no or less atypia at any HLA class I loci. In some embodiments, individuals having atypia at all three HLA class I loci and a higher tumor mutational burden as described herein are more likely to respond positively to immunotherapy than individuals with a significantly lower tumor mutational burden and / or no or less atypia at any HLA class I loci.

[0117] In some embodiments, the HLA class I genotype of interest may be determined by sequencing. Sequencing may be performed by methods known in the art. In some embodiments, for example, the HLA class I genotype may be determined by exome sequencing. In some embodiments, the HLA class I genotype of interest may be determined using a clinically proven HLA typing assay. treatment

[0118] In some embodiments, the present invention relates to the treatment of tumors exhibiting a tumor mutational burden exceeding a suitable threshold. In some embodiments, such tumors have previously received immunotherapy. In some embodiments, such immunotherapy is an immune checkpoint modulator. Administration of an immune checkpoint modulator

[0119] According to a particular method of the present invention, an immunomodulator (e.g., an immune checkpoint regulator) is administered to an individual or has been administered to an individual. In some embodiments, treatment with an immunomodulator (e.g., an immune checkpoint regulator) is used as monotherapy. In some embodiments, treatment with an immunomodulator (e.g., an immune checkpoint regulator) is used in combination with one or more other therapies.

[0120] Those skilled in the art will understand that appropriate formulations, indications, and dosing regimens are typically analyzed and approved by government regulatory authorities, such as the Food and Drug Administration in the United States. For example, Examples 4 and 5 present certain FDA-approved dosing information for PD-1 and CTLA-4 inhibitor regimens, respectively. In some embodiments, immunomodulators (e.g., immune checkpoint modulators) are administered according to the present invention in accordance with such approved protocols. However, this disclosure provides, among other things, certain techniques for identifying, characterizing, and / or selecting specific patients to whom immunomodulators (e.g., immune checkpoint modulators) may be desirablely administered. In some embodiments, the insights provided by this disclosure enable the administration of a given immunomodulator (e.g., immune checkpoint modulator) at a greater frequency and / or larger individual dose (e.g., due to reduced sensitivity to undesirable effects and / or occurrence or intensity of undesirable effects) compared to those recommended or approved based on population studies including both the identified individuals described herein (e.g., those expressing neoepitopes or having tumor mutational burdens above a threshold) and other individuals. In some embodiments, the insights provided by this disclosure enable the administration of a given immunomodulator (e.g., an immune checkpoint modulator) at a reduced frequency and / or reduced individual dose (e.g., by increased responsiveness) compared to those recommended or approved based on community studies involving both identified individuals described herein (e.g., those expressing a neoepitope or having a tumor mutational burden exceeding a threshold) and other individuals.

[0121] In some embodiments, immunomodulators (e.g., immune checkpoint regulators) are also administered in pharmaceutical compositions that include physiologically acceptable carriers or excipients. In some embodiments, the pharmaceutical compositions are sterile. In many embodiments, the pharmaceutical compositions are formulated for a specific mechanism of administration.

[0122] In some embodiments, suitable pharmaceutically acceptable carriers include, but are not limited to, water, saline solutions (e.g., NaCl), physiological saline, buffered physiological saline, alcohol, glycerol, ethanol, gum arabic, vegetable oil, benzyl alcohol, polyethylene glycol, gelatin, carbohydrates such as lactose, amylose or starch, sugars such as mannitol, sucrose, or other sugars, dextrose, magnesium stearate, talc, silicic acid, viscous paraffin, fragrance oils, fatty acid esters, hydroxymethylcellulose, polyvinylpyrrolidone, and combinations thereof. In some embodiments, the pharmaceutical composition may optionally include one or more adjuvants (e.g., lubricants, preservatives, stabilizers, wetting agents, emulsifiers, salts, buffers, colorants, fragrances, and / or aromatics) that do not react harmfully with or interfere with the activity of the active compound. In some embodiments, water-soluble carriers suitable for intravenous administration are used.

[0123] In some embodiments, the pharmaceutical composition or drug may contain, if desired, amounts (typically small amounts) of wetting agents or emulsifiers and / or pH buffers. In some embodiments, the pharmaceutical composition may be a liquid solution, suspension, emulsion, tablet, pill, capsule, sustained-release formulation, or powder. In some embodiments, the pharmaceutical composition may be formulated as a suppository with conventional binders and carriers such as triglycerides. In some embodiments, the oral formulation may include standard carriers such as pharmaceutical grades, including mannitol, lactose, starch, magnesium stearate, polyvinylpyrrolidone, sodium saccharin, cellulose, and magnesium carbonate.

[0124] In some embodiments, the pharmaceutical composition may be formulated according to standard procedures as a pharmaceutical composition suitable for administration to humans. For example, in some embodiments, the composition for intravenous administration is typically a solution in a sterile isotonic aqueous buffer. In some embodiments, if necessary, the composition may include a solubilizer and a local anesthetic to relieve pain at the injection site. In some embodiments, the components are generally supplied either separately as a dry, lyophilized powder or a water-free concentrate in an airtight container such as an ampoule or sachet indicating the amount of the active agent, or mixed together in a unit dosage form. In some embodiments, when the composition is administered by infusion, the composition may be dispensed in an infusion bottle containing sterile pharmaceutical-grade water, saline, or glucose / water. In some embodiments, when the composition is administered by injection, an ampoule of sterile water or saline for injection may be provided so that the components can be mixed before administration.

[0125] In some embodiments, immunomodulators (e.g., immune checkpoint regulators) may be formulated in a neutral form. In some embodiments, immunomodulators may be formulated in the form of salts. In some embodiments, pharmaceutically acceptable salts include those formed with free amino groups, such as those derived from hydrochloric acid, phosphoric acid, acetic acid, oxalic acid, tartaric acid, etc., and those formed with free carboxyl groups, such as those derived from sodium, potassium, ammonium, calcium, ferric hydroxide, isopropylamine, triethylamine, 2-ethylaminoethanol, procaine, etc.

[0126] The pharmaceutical compositions for use according to the present invention may be administered by any suitable route. In some embodiments, the pharmaceutical composition is administered intravenously. In some embodiments, the pharmaceutical composition is administered subcutaneously. In some embodiments, the pharmaceutical composition is administered by direct administration to target tissue such as the heart or muscle (e.g., intramuscularly) or the nervous system (e.g., direct injection into the brain, ventricle, intrathecal cavity). Alternatively or additionally, in some embodiments, the pharmaceutical composition is administered parenterally, transdermally, or transmucosally (e.g., orally or nasally). If desired, two or more routes may be used simultaneously.

[0127] In some embodiments, an immunomodulator (e.g., an immune checkpoint modulator (or a composition or drug containing an immune checkpoint modulator)) may be administered alone or in conjunction with other immunomodulators. The term “in conjunction with” indicates that the first immune checkpoint modulator is administered before, at the same time as, or after another immune checkpoint modulator. In some embodiments, the first immunomodulator (e.g., an immune checkpoint modulator) may be mixed with a composition containing one or more different immunomodulators (e.g., immune checkpoint modulators) and administered simultaneously. Alternatively, in some embodiments, the drugs may be administered simultaneously without mixing (e.g., by “piggyback” delivery of the drug over an intravenous line in which the immunomodulator (e.g., immune checkpoint modulator) is also administered, or vice versa). In some embodiments, the immunomodulators (e.g., immune checkpoint modulators) may be administered separately (e.g., without mixing) but within a short time frame (e.g., within 24 hours) of the administration of another immunomodulator (e.g., immune checkpoint modulator).

[0128] In some embodiments, the subject treated with an immunomodulator (e.g., an immune checkpoint modulator) is one or more immunosuppressants administered. In some embodiments, one or more immunosuppressants are administered to reduce, suppress, or prevent an unwanted autoimmune response (colitis, hepatitis, dermatitis (including toxic epidermal necrolysis), neurological disorders, and / or endocrine disorders), such as hypothyroidism. In some embodiments, exemplary immunosuppressants include steroids, antibodies, immunoglobulin fusion proteins, etc. In some embodiments, the immunosuppressant inhibits B cell activity (e.g., rituximab). In some embodiments, the immunosuppressant is a decoy polypeptide antigen.

[0129] In some embodiments, immunomodulators (e.g., immune checkpoint modulators (or compositions or drugs containing immune checkpoint modulators)) are administered in therapeutically effective doses (e.g., according to dosages and / or drug regimens shown to be sufficient to treat cancer when administered to an appropriate population, such as restoring cancer-related symptoms, preventing or delaying the onset of cancer, and / or reducing the severity or frequency of cancer symptoms). In some embodiments, long-term clinical utility is observed after treatment with immunomodulators (e.g., immune checkpoint modulators), including, for example, PD-1 inhibitors such as pembrolizumab, CTLA-4 inhibitors such as ipilimumab, and / or other agents. Those skilled in the art will understand that the therapeutically effective dose for cancer treatment in a given patient may depend, at least to some extent, on the nature and extent of the cancer and may be determined by standard clinical techniques. In some embodiments, one or more in vitro or in vivo assays may be employed to help identify the optimal dosage range at their discretion. In some embodiments, the specific dose employed in the treatment of a given individual may depend on one or more other factors that are deemed appropriate in the practitioner's judgment in light of the route of administration, the stage of cancer, and / or the patient's condition. In some embodiments, an effective dose may be extrapolated from dose-response curves derived from in vitro or animal model studies (e.g., as described by the U.S. Department of Health and Human Services, the Food and Drug Administration, and the Center for Drug Evaluation and Research in "Guidance for Industry: Estimating Maximum Safe Starting Dose in Initial Clinical Trials for Therapeutics in Adult Healthy Volunteers," Pharmacology and Toxicology, July 2005).

[0130] In some embodiments, the therapeutically effective dose of an immunomodulator (e.g., an immune checkpoint regulator) may be, for example, greater than about 0.01 mg / kg body weight, greater than about 0.05 mg / kg body weight, greater than about 0.1 mg / kg body weight, greater than about 0.5 mg / kg body weight, greater than about 1.0 mg / kg body weight, greater than about 1.5 mg / kg body weight, greater than about 2.0 mg / kg body weight, greater than about 2.5 mg / kg body weight, greater than about 5.0 mg / kg body weight, greater than about 7.5 mg / kg body weight, greater than about 10 mg / kg body weight, greater than about 12.5 mg / kg body weight, greater than about 15 mg / kg body weight, greater than about 17.5 mg / kg body weight, greater than about 20 mg / kg body weight, greater than about 22.5 mg / kg body weight, or greater than about 25 mg / kg body weight. In some embodiments, the therapeutically effective dose may be about 0.01 to 25 mg / kg body weight, about 0.01 to 20 mg / kg body weight, about 0.01 to 15 mg / kg body weight, about 0.01 to 10 mg / kg body weight, about 0.01 to 7.5 mg / kg body weight, about 0.01 to 5 mg / kg body weight, about 0.01 to 4 mg / kg body weight, about 0.01 to 3 mg / kg body weight, about 0.01 to 2 mg / kg body weight, about 0.01 to 1.5 mg / kg body weight, about 0.01 to 1.0 mg / kg body weight, about 0.01 to 0.5 mg / kg body weight, about 0.01 to 0.1 mg / kg body weight, about 1 to 20 mg / kg body weight, about 4 to 20 mg / kg body weight, about 5 to 15 mg / kg body weight, or about 5 to 10 mg / kg body weight.In some embodiments, the therapeutically effective dose is approximately 0.01 mg / kg, approximately 0.05 mg / kg, approximately 0.1 mg / kg, approximately 0.2 mg / kg, approximately 0.3 mg / kg, approximately 0.4 mg / kg, approximately 0.5 mg / kg, approximately 0.6 mg / kg, approximately 0.7 mg / kg, approximately 0.8 mg / kg, approximately 0.9 mg / kg, approximately 1.0 mg / kg, approximately 1.1 mg / kg, approximately 1.2 mg / kg, approximately 1.3 mg / kg, approximately 1.4 mg / kg, approximately 1.5 mg / kg, approximately 1.6 mg / kg, approximately 1.7 mg / kg, approximately 1.8 mg / kg, approximately 1.9 mg / kg The amounts are approximately 2.0 mg / kg, 2.5 mg / kg, 3.0 mg / kg, 4.0 mg / kg, 5.0 mg / kg, 6.0 mg / kg, 7.0 mg / kg, 8.0 mg / kg, 9.0 mg / kg, 10.0 mg / kg, 11.0 mg / kg, 12.0 mg / kg, 13.0 mg / kg, 14.0 mg / kg, 15.0 mg / kg, 16.0 mg / kg, 17.0 mg / kg, 18.0 mg / kg, 19.0 mg / kg, 20.0 mg / kg, body weight, or more. In some embodiments, the therapeutically effective dose is approximately 30 mg / kg body weight or less, approximately 20 mg / kg body weight or less, approximately 15 mg / kg body weight or less, approximately 10 mg / kg body weight or less, approximately 7.5 mg / kg body weight or less, approximately 5 mg / kg body weight or less, approximately 4 mg / kg body weight or less, approximately 3 mg / kg body weight or less, approximately 2 mg / kg body weight or less, or approximately 1 mg / kg body weight or less.

[0131] In some embodiments, the dosage for a particular individual is modified over time (e.g., increased or decreased) depending on the individual's needs.

[0132] In some embodiments, a loading dose of the therapeutic composition (e.g., a higher initial dose) is given at the start of the course of treatment, followed by the administration of a reduced maintenance dose of the therapeutic composition (e.g., a lower subsequent dose). While not bound by any theory, it is intended that the loading dose can clear an initial, and in some cases large, accumulation of undesirable material (e.g., fatty material and / or tumor cells, etc.) in tissues (e.g., in the liver), and that the maintenance dose can delay, reduce, or prevent the accumulation of fatty material after the initial clearing.

[0133] In some embodiments, it will be understood that the loading and maintenance doses, intervals, doses, and duration of treatment may be determined by any available method, such as those exemplified herein and those known in the art. In some embodiments, the loading dose is about 0.01–1 mg / kg body weight, about 0.01–5 mg / kg body weight, about 0.01–10 mg / kg body weight, about 0.1–10 mg / kg body weight, about 0.1–20 mg / kg body weight, about 0.1–25 mg / kg body weight, about 0.1–30 mg / kg body weight, about 0.1–5 mg / kg body weight, about 0.1–2 mg / kg body weight, about 0.1–1 mg / kg body weight, or about 0.1–0.5 mg / kg body weight. In some embodiments, the maintenance dose is approximately 0–10 mg / kg body weight, approximately 0–5 mg / kg body weight, approximately 0–2 mg / kg body weight, approximately 0–1 mg / kg body weight, approximately 0–0.5 mg / kg body weight, approximately 0–0.4 mg / kg body weight, approximately 0–0.3 mg / kg body weight, approximately 0–0.2 mg / kg body weight, and approximately 0–0.1 mg / kg body weight. In some embodiments, the loading dose is administered to the individual at regular intervals for a given period (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 months or more) and / or a given number of doses (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30 or more doses). In some embodiments, the maintenance dose ranges from approximately 0–2 mg / kg body weight, approximately 0–1.5 mg / kg body weight, approximately 0–1.0 mg / kg body weight, approximately 0–0.75 mg / kg body weight, approximately 0–0.5 mg / kg body weight, approximately 0–0.4 mg / kg body weight, approximately 0–0.3 mg / kg body weight, approximately 0–0.2 mg / kg body weight, and approximately 0–0.1 mg / kg body weight. In some embodiments, the maintenance dose is approximately 0.01, 0.02, 0.04, 0.06, 0.08, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.2, 1.4, 1.6, 1.8, or 2.0 mg / kg body weight. In some embodiments, the maintenance dose is administered for 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 months or longer. In some embodiments, the maintenance dose is administered for 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 years or longer. In some embodiments, the maintenance dose is administered indefinitely (e.g., for the remainder of life).

[0134] In some embodiments, a therapeutically effective dose of an immunomodulator (e.g., an immune checkpoint regulator) may be administered as a single dose or, depending on the nature and extent of the cancer, and may be administered continuously at intervals. As used herein, "interval" administration means that the therapeutically effective dose is administered periodically (to distinguish it from a single dose). In some embodiments, the interval may be determined by standard clinical techniques. In some embodiments, the immunomodulator (e.g., an immune checkpoint regulator) may be administered every other month, monthly, twice a month, every three weeks, every other week, weekly, twice a week, three times a week, or daily. In some embodiments, the administration interval for a single individual does not need to be fixed, but may be modified over time depending on the needs and the individual's recovery rate.

[0135] Where used herein, those skilled in the art will be familiar with certain terms used to describe drug regimens. For example, the term “bi-monthly” has the meaning understood by those skilled in the art and refers to administration once every two months (e.g., once every two months). The term “monthly” means administration once per month. The term “three times a week” means administration once every three weeks (e.g., once every three weeks). The term “bi-weekly” means administration once every two weeks (e.g., once every two weeks). The term “weekly” means administration once per week. And the term “daily” means administration once per day.

[0136] The present invention, in particular, is an additional component of a pharmaceutical composition comprising an immunomodulator (e.g., an immune checkpoint regulator), as described herein. In some embodiments, the composition is provided in a container (e.g., vial, bottle, bag for intravenous administration, syringe, etc.) having a label containing instructions for administration of the composition for the treatment of cancer. Combination therapy

[0137] In some embodiments, immunomodulators may be used in combination with other therapeutic agents for treating diseases such as cancer. In some embodiments, the immunomodulator, or the pharmaceutical composition comprising the immunotherapy described herein, may optionally contain one or more additional therapeutic agents, such as cancer therapeutic agents, e.g., chemotherapeutic agents or bioagents, and / or may be administered in combination with one or more additional therapeutic agents, such as cancer therapeutic agents, e.g., chemotherapeutic agents or bioagents. The additional agents may be, for example, therapeutic agents recognized by those skilled in the art as useful in treating the disease or condition being treated by the immunomodulator, or agents that restore symptoms associated with the disease or condition being treated. The additional agents may also be agents that impart useful attributes to the therapeutic composition (e.g., agents that affect the viscosity of the composition). For example, in some embodiments, the immunotherapy is administered to subjects who have received, are receiving, and / or will receive therapy with another therapeutic agent or modality (e.g., chemotherapeutic agents, surgery, radiation, or a combination thereof).

[0138] Some embodiments of the combination therapy modalities provided by this disclosure provide, for example, an immunomodulator and an additional(s) agent in a single pharmaceutical formulation. Some embodiments provide the administration of an immunomodulator and an additional therapeutic agent in separate pharmaceutical formulations.

[0139] Examples of chemotherapeutic agents that may be used in combination with the immunomodulatory agents described herein include platinum compounds (e.g., cisplatin, carboplatin, and oxaliplatin), alkylating agents (e.g., cyclophosphamide, ifosfamide, chlorambucil, nitrogen mustard, thiotepa, melphalan, busulfan, procarbazine, streptozocin, temozolomide, dacarbazine, and bendamustine), and antitumor antibiotics (e.g., daunorubicin, doxorubicin, idarubicin, epirubicin, mitoxantrone, bleomycin, myrrhizin). Tomycin C, plicamycin, and dactinomycin), taxanes (e.g., paclitaxel and docetaxel), antimetabolites (e.g., 5-fluorouracil, cytarabine, premetrexed, thioguanine, phloxuridine, capecitabine, and methotrexate), nucleoside analogs (e.g., fludarabine, clofarabine, cladribine, pentostatin, and nerarabine), topoisomerase inhibitors (e.g., topotecan and irinotecan), hypomethylating agents (e.g., azacitidine and decitabine), pro Theosome inhibitors (e.g., bortezomib), epipodophyllotoxins (e.g., etoposide and teniposide), DNA synthesis inhibitors (e.g., hydroxyurea), vinca alkaloids (e.g., bicristine, vindesine, vinorelbine, and vinblastine), tyrosine kinase inhibitors (e.g., imatinib, dasatinib, nilotinib, sorafenib, and sunitinib), nitrosoureas (e.g., carmustine, fotemustine, and lomustine), hexamethylmelamine, mitotane, angiogenesis inhibitors (e.g., thalidomide and lenalidomide), s Theroids (e.g., prednisone, dexamethasone, and prednisolone), hormones (e.g., tamoxifen, raloxifen, leuprolide, bicaluatmide, granisetron, and flutamide), aromatase inhibitors (e.g., letrozole and anastrozole), arsenic trioxide, tretinoin, non-selective cyclooxygenase inhibitors (e.g., nonsteroidal anti-inflammatory drugs, salicylates, aspirin, piroxicam, ibuprofen, indomethacin, naprosin, diclofenac, tolmetin, ketoprofen,This includes nabumetone, oxaprozin, selective cyclooxygenase-2 (COX-2) inhibitors, or any combination thereof.

[0140] Examples of biological agents that may be used in the compositions and methods described herein include monoclonal antibodies (e.g., rituximab, cetuximab, panetumumab, tocitumomab, trastuzumab, alemtuzumab, gemtuzumab ozogamisin, bevacizumab, catumakisomab, denosumab, obinutuzumab, oftamumab, ramucirumab, pertuzumab, ipilimumab, nivolumab, nimotuzumab, lambrolizumab, pisilizumab) This includes zumab, siltuximab, BMS-936559, RG7446 / MPDL3280A, MEDI4736, tremelimumab, or others known to those skilled in the art), enzymes (e.g., L-asparaginase), cytokines (e.g., interferons and interleukins), growth factors (e.g., colony-stimulating factors and erythropoietin), cancer vaccines, gene therapy vectors, or any combination thereof.

[0141] In some embodiments, the immunomodulator is administered to a subject requiring the immunomodulator in combination with another agent for the treatment of cancer, either in the same or a different pharmaceutical composition. In some embodiments, the additional agent is an anticancer agent. In some embodiments, the additional agent affects (e.g., inhibits) histone modifications such as histone acetylation or histone methylation. In certain embodiments, the additional anticancer agent is a chemotherapeutic agent (2CdA, 5-FU, 6-mercaptopurine, 6-TG, Abraxane®, Accutane®, Actinomycin D, Adriamycin®, Alimta®, all-trans retinoic acid, ametopterin, Ara-C, azacitadine, BCNU, Blenoxane®, Camptosar®, CeeNU®, clofarabine, clo Lar (trademark), Cytoxan (registered trademark), Daunorubicin hydrochloride, Daunoxosome (registered trademark), Dacogen (registered trademark), DIC, Doxil (registered trademark), Elence (registered trademark), Eloxatin (registered trademark), Emcyt (registered trademark), Etoposide phosphate, Fludara (registered trademark), FUDR (registered trademark), Gemzar (registered trademark), Gleevec, Hexamethylmelamine, Hycamtin (registered trademark), Hydrea (registered trademark), Idamycin (registered trademark) (Registered Trademark), Iffex (Registered Trademark), Ixabepyrone, Ixempra (Registered Trademark), L-asparaginase, Leukeran (Registered Trademark), Liposome Ara-C, L-PAM, Risodren, Matulane (Registered Trademark), Mitracin, Mitomycin C, Myrelan (Registered Trademark), Navelbine (Registered Trademark), Nutrexin (Registered Trademark), Nilotinib, Nipent (Registered Trademark), Nitrogen Mustard, Novantrone (Registered Trademark), Oncasper (Registered Trademark), Panretin (Registered Trademark), Paraplatin (Registered Trademark), Platinol (Registered Trademark), Prolifeprospan 20 with Carmustine Implant, Sandostatin (Registered Trademark), Targretin (Registered Trademark), Tasigna (Registered Trademark), Taxotere (Registered Trademark), Temodar (Registered Trademark), TESPA, Trisenox (Registered Trademark), Valstar (Registered Trademark), Verban (Registered Trademark), Vidaza (Registered Trademark), Vincristine Sulfate, VM26. Biologics (such as Xeloda (registered trademark) and Zanozar (registered trademark)), alpha-interferon, Bacillus Calmette-Guerin, Vexar (registered trademark), Campas (registered trademark), Ergamisol (registered trademark), Erlotinib, Herceptin (registered trademark), Interleukin-2, Iressa (registered trademark), Lenalidomide, Mylotarg (registered trademark), Ontac (registered trademark), Pegasys (registered trademark), Revlimid (registered trademark), Rituxan (registered trademark), Tarceva (trademark), Taromid (registered trademark), Velcade (registered trademark), and Zevalin (trademark)), small molecules (such as Tykerb (registered trademark)), corticosteroids (dexamethasone sodium phosphate, Deltazon (registered trademark), and Delta-Cortef (registered trademark) The treatment is selected from the group consisting of (such as) hormonal therapies (such as Arimidex®, Aromasin®, Casodex®, Sitadren®, Eligard®, Eurexin®, Evista®, Fastlodex®, Femara®, Halotestin®, Megas®, Nilandron®, Nolvadex®, Plenaxis®, and Zoladex®), and radiopharmaceuticals (such as Iodotope®, Metastron®, Phosphocol®, and Samarium SM-153).

[0142] Additional agents that may be used in combination with the immunotherapies described above are for illustrative purposes only and are not intended to be limiting. Combinations included in this disclosure include, without limitation, one or more immunomodulators provided herein or otherwise known to those skilled in the art, and one additional agent selected from the above list or otherwise provided herein. Immunomodulators may be used in combination with one or more additional agents, for example, 2, 3, 4, 5, or 6, or more additional agents.

[0143] In some embodiments, the therapeutic methods described herein are performed on subjects who have failed to receive other treatments for their medical condition or who have had little success with treatment by other means, for example, subjects with cancer that is refractory to standard care treatment. Additionally, the therapeutic methods described herein may be performed in combination with one or more additional treatments for their medical condition, for example, in addition to or in combination with standard care treatment. For example, the method may include administering a cancer regimen, such as non-myeloablative chemotherapy, hormone therapy, and / or radiation before, substantially concurrently with, or after the administration of the immunomodulator described herein, or a combination thereof. In certain embodiments, subjects receiving the immunomodulator described herein may also be treated with antibiotics and / or one or more pharmaceutical agents. [Examples]

[0144] Example 1. Survival after immunotherapy with whole-cancer analysis of tumor mutation loading thresholds and immune checkpoint regulators This example illustrates the association between tumor mutational burden, as measured by a targeted sequencing panel, and overall survival after treatment with immune checkpoint regulators (ICMs).

[0145] Previous studies relied primarily on whole exome sequencing, a typical but not widely performed part of routine clinical care, for tumor mutational burden data. Currently, the most widely used oncology platforms utilize next-generation sequencing of targeted gene panels. The association between higher tumor mutational burden and clinical utility from ICM is evident in patients with non-small cell lung cancer (NSCLC), melanoma, and bladder cancer treated with PD-1 / PD-L1. 5~7 Similarly, this was observed in melanoma patients treated with CTLA4 inhibitors. 3、4 Importantly, however, it remains unknown how broadly this predicts clinical utility across human cancers with different tumor mutation burdens.

[0146] At Memorial Sloan Kettering Cancer Center, more than 15,000 patients have undergone genomic profiling using an assay called "Integrated Actionable Mutation Profiling for Cancer Targets" (MSK-IMPACT), which identified somatic exon mutations in a predefined subset of 341, 410, or 468 in its latest version, cancer-related genes, using both tumor-derived and matched germline normal DNA. 8、17

[0147] Specifically, MSK-IMPACT was used to analyze a cohort of 1534 patients who had previously received at least one dose of ICM at Memorial Sloan Kettering Cancer Center (MSKCC) (Figure 1). Patients who had previously received atezolizumab, avelumab, durvalumab, ipilimumab, nivolumab, pembrolizumab, or tremelimumab as monotherapy or in combination were included in the study. In total, 130 patients received anti-CTLA-4 immunotherapy, 1166 received anti-PD-1 or PD-L1 immunotherapy, and 228 received both anti-CTLA-4 and anti-PD-1 or PD-L1 immunotherapy. The total number of somatic mutations was calculated for all patient samples within the cohort and normalized to the megabase sum in sequenced exons. Tumor mutational burden, measured by next-generation sequencing (NGS) panels including MSK-IMPACT, has been previously demonstrated by multiple researchers as a means of estimating the total tumor mutational burden of a tumor. 9、10、11 Overall survival (OS) was measured from the day of initial ICM treatment to death or the time of the last follow-up. The median follow-up was 11 months, and 984 patients (64%) were alive at the last follow-up.

[0148] The largest number of patients had tumors with histology for which ICM use was FDA approved. 351 patients had non-small cell lung cancer (NSCLC), 323 had melanoma, 155 had renal cell carcinoma (RCC), 127 had bladder cancer, and 78 had head and neck squamous cell carcinoma (Table 1). Patients with other cancer types such as breast cancer, glioma, and gastrointestinal cancer were also included in the study. Multivariate analysis of all patients using Cox proportional hazards regression showed that the normalized number of somatic exon nonsynonymous mutations found using MSK-IMPACT, or tumor mutational loading against a threshold, was significantly associated with overall survival after adjusting for cancer type, age, and drug class of ICM (continuous variable: HR=0.987, p=.001; binary cutoff: HR0.524, p=5.0×10⁻⁶). -5 Table 2 shows that in this case, the term "cutoff" is used to mean the tumor mutation burden threshold as used herein. As those skilled in the art will understand, the hazard ratio (HR) in survival analysis is the ratio of hazard rates corresponding to a condition explained by two levels of explanatory variables. For example, in drug research, if the treated population survives twice as long as the control population at a rate per unit time, the hazard ratio is 0.5, indicating a higher hazard than death due to no treatment. [Table 1-1] [Table 1-2] [Table 2-1] [Table 2-2]

[0149] In the whole-cancer analysis, a greater number of somatic mutations or a higher tumor mutational burden were proportionally associated with improved overall survival (Figure 2). As expected, the distribution of tumor mutational burden varied across diverse histologies. 12More importantly, the optimal tumor mutational burden threshold was identified as predicting the overall survival rate after therapy for ICM for each cancer subtype using maximum chi-square analysis (Figures 4A and 5A-B). 13 Significant associations or strong trends were observed in increased tumor mutation burden and improved overall survival from immunotherapy treatment across multiple histologies, consistent with the number of patients in each subgroup (Figures 6A-H and 7). Importantly, in patients who did not receive ICM therapy (n=9196), there was no association between higher tumor mutation burden and improved overall survival (Figures 3B and 4B).

[0150] A significant association between improved overall survival and higher tumor mutational burden was observed with CTLA-4 and PD-1 / PD-L1 inhibitor targeted therapies, while a similar, non-significant trend was observed with combination therapies. It is interesting that combination therapy appears to diminish the significance of tumor mutational burden to outcomes. This relationship suggests that suppressing multiple immune checkpoints may enable the immune system to more effectively target a broader set of potential neoantigens, increasing the likelihood of establishing a broader, more effective antitumor response.

[0151] In increased tumor mutational burden, glioma was an outlier in this study (Figure 4A), or a high tumor mutational burden threshold was associated with a tendency toward less favorable overall survival. This contrasts with reports of dramatic responses to immune checkpoint regulators in glioblastoma patients associated with biallelic mismatch repair deficiencies in children. 14 This discrepancy may reflect the fact that mismatch repair is very rare in GBM and tumor mutational burden in these patients, which may reflect previous exposure to the alkylating agent temozolomide, which has been shown to promote the expansion of subclonal mutations that were suggested to be less immunogenic. 15 As expected from a large-scale all-cancer analysis, the included patients were heterogeneous; some had received extensive prior treatment, while others had been treated with various combination therapies.

[0152] These findings are confirmed by additional analyses of a larger cohort in the MSK-IMPACT study. The cohort includes 1662 patients whose tumors were profiled by next-generation sequencing and who received at least one dose of ICI therapy, representing a sufficient number of patients with diverse cancer types for analysis (Figure 13). Patients who received atezolizumab, avelumab, durvalumab, ipilimumab, nivolumab, pembrolizumab, or tremelimumab as monotherapy or in combination were included in the study. The vast majority of patients (1446, 94% of tumors excluding gliomas) had stage IV or metastatic disease. A small number of patients had locally recurrent disease (n=10) or locally progressive unresectable melanoma (stage III, n=89 (Table 3)). In total, 146 received anti-CTLA4, 1447 received anti-PD1 or PD-L1, and 189 received both. A large number of patients had cancers for which ICI was FDA approved, including 350 NSCLC, 321 melanoma, 151 renal cell carcinoma (RCC), 214 bladder cancer, and 138 head and neck squamous cell carcinoma (Table 4). To calculate mutational burden (TMB), the total number of somatic nonsynonymous mutations was normalized to the total number of sequenced megabases. OS was measured from the date of first ICI treatment to death or time of last follow-up. The median follow-up was 19 months (range 0–80), and 830 patients [50%] were alive and censored at last follow-up. [Table 3-1] [Table 3-2] [Table 4-1]

[0153] TMB subgroups were defined by percentiles within each histology. This approach was used because the median and range of mutational burdens have been shown to vary across tumor types. 13Therefore, a universal cutoff for “high TMB” would be enriched for tumor types with higher mutational burdens. Across the cohort, stratifying tumors by histological TMB deciles revealed that a greater number of mutations were associated with improved OS. This significant association, stratified by histology, was observed across various cutpoints chosen to define the high TMB group (top 10–50%, Figures 14A, 15, 16). A clear trend toward a decreasing hazard ratio (HR) for mortality with increasing TMB was observed across cancer types, indicating increased utility from ICI at higher TMB (Figures 14B, 16). 13

[0154] To confirm that these results were present across multiple cancer types, two additional analyses were performed. First, a multivariate analysis across the entire cohort using Cox proportional hazards regression showed that, after adjusting for cancer type, age, ICI drug class, and year of ICI initiation, tumor mutational burden was a continuous variable (HR=0.985, p=3.4×10⁻⁶). -7 ) as both OS and binary cutoff (top 20% of each histology, HR 0.61 p=1.3×10) -7 This was shown to be significantly associated with (Table 5). Furthermore, this association remained significant even after excluding melanoma and NSCLC patients from the cohort (Table 4), indicating that this effect was not caused by these histological factors alone. [Table 5-1]

[0155] We also performed stratified analyses within each cancer type by selecting high mutational burden quintiles (top 20%) in each histology, such as the high TMB group. Using this approach, we observed a similar association between higher TMB (top 20% within each histology) and longer OS across multiple cancer types (Figures 17, 18). Although the effect for some individual cancers did not reach statistical significance, possibly due to smaller sample sizes, a quantitative trend of better OS (HR<1) was observed in almost all cancer types, with glioma being the most obvious exception. In summary, these data suggest that an association between TMB and improved survival after ICI is likely to exist across a large proportion of cancer histologies.

[0156] In line with the histologically varied distribution of TMB, the TMB cutoff associated with the top 20% of each cancer type changed significantly (Figures 17, 19). Importantly, this suggests that there is likely no universal number defining high TMB, which predicts clinical utility for ICI across all cancer types, and that the optimal cutoff point appears to vary across different cancers.

[0157] Similar numerical trends were observed for longer OS with TMB measured as a continuous variable across many histologies, consistent with the number of patients in the subgroup (Figure 20). Consistent with the differences in OS, similar associations between TMB and the rate of clinical utility to ICI or progression-free survival were observed in patients with cancer types for which response data were available—NSCLC, melanoma, gastroesophageal, head and neck, and renal cell carcinoma (Figures 21-22). 72~74

[0158] To investigate whether the survival differences observed among patients with higher TMB tumors could be solely attributable to the general prognostic utility of high mutational burden, outcomes were measured independently of ICI in 5371 patients with metastatic cancer whose tumors were sequenced with MSK-IMPACT and who did not undergo ICI. In these patients, there was no association between higher TMB and improved OS (HR 1.12, p=0.11). The lack of prognostic utility was also observed within each histology (Figures 17, 23).

[0159] Notably, the TMB cutpoint for the top 20% of colorectal cancer patients was high (52.2 / MB), potentially coinciding with many MSI high colorectal tumors treated with ICI. For example, if clinicians triage patients with higher TMB in both ICI and non-ICI settings more highly, we repeated the survival analysis and instead calculated the top 20% of TMB among all patients (both ICI and non-ICI treated). The TMB cutpoint for other cancer types did not change with this calculation, and the association with survival in each cancer type remained very similar in both ICI and non-ICI treated cohorts (Figures 24, 25).

[0160] Unlike other cancer types, there was no association between higher TMB and improved survival in patients with glioma. In fact, the trend was towards less favorable survival. There was a case report of a dramatic response to ICI in patients with glioblastoma associated with childhood biallelic mismatch repair deficiency. 14 Mismatch repair is very rare in GBM, and higher TMB in many glioma patients may reflect prior exposure to the alkylating agent temozolomide, which can promote the expansion of less immunogenic subclonal mutations. 15 Alternatively, antitumor immune responses in the CNS can be different and TMB-independent.

[0161] As might be expected in a large-scale multi-cancer analysis of sequenced tumors as part of clinical care, the included patients were heterogeneous, with some having received significant prior treatment while others had been treated with various combination therapies. The timing of MSK-IMPACT testing for ICI initiation also varied. Nevertheless, the finding of a significant association with OS in this heterogeneous cohort highlights the robustness of TMB as a predictive biomarker, suggesting its clinical significance.

[0162] While the variable threshold of TMB across histology may be attributable to different tumor microenvirons, a number of other factors similarly appear to individually predict the response to ICI, including clonality, immune infiltration, immune cell elimination, HLA genotype and modification, checkpoint molecule expression levels, and others. 15、75~78 Our data as a whole suggest that TMB is associated with increased OS in a dose-dependent manner. The overall oncological nature of this biomarker likely reflects the underlying mechanism by which ICI functions. Our data are also consistent with the hypothesis that higher mutational burden is associated with a greater number of tumor neoantigens presented on MHC molecules, which promotes immune recognition as exogenous and the development of a high tumor response. 79、80

[0163] This finding aligns with the observation that patients with hypermutated tumors resulting from mismatch repair have a high response rate to pembrolizumab, a finding that led to the FDA's tissue / site-unknown approval of this drug for tumors with high microsatellite instability or mismatch repair deficiency. 65Mutational burden can predict survival across diverse types of human cancer and is relevant in patients treated with either anti-CTLA4 or anti-PD1 therapy. Secondly, previous studies on the association between mutational burden and survival after ICI have examined small cohorts, and therefore the effect of TMB on clinical utility could not be quantified in an accurate manner. This study presents genomic data from the largest cohort of patients treated with ICI to date and shows a continuous association between higher TMB and superior OS. Capturing just 3% of coding exomes using a targeted panel such as MSK IMPACT appears to provide a sufficient estimate of total tumor mutational burden to provide predictive values ​​for patients being considered for ICI treatment. Finally, the number of mutations defining high TMB appears to vary across cancer types, and there does not seem to be a universal number that defines the potential utility from ICI across all histologies. Example 2: Selection criteria for the patient population in Example 1

[0164] This embodiment describes criteria selected for analysis when predicting overall survival based on tumor mutation burden thresholds in patients.

[0165] Following institutional review board approval from Memorial Sloan Kettering Cancer Center, institutional pharmacy records were used to identify patients who received at least one dose of an immune checkpoint modulator (e.g., tezolizumab, avelumab, durvalumab, ipilimumab, nivolumab, pembrolizumab, or tremelimumab) and subsequently cross-referenced with patients who completed MSK-IMPACT testing in the context of routine clinical care. Importantly, concurrent germline DNA sequencing from peripheral blood was performed on all samples to identify somatic tumor mutations. Patients participating in ongoing clinical trials for which publication of outcome data was prohibited were excluded. Other preceding or concurrent non-ICM treatments were not recorded or explained for analysis. The timing of histopathology in which MSK-IMPACT was performed for ICM administration is also heterogeneous in a small portion of patients with post-ICM testing.

[0166] For the analysis of patients who did not receive ICM, all patients for whom MSK-IMPACT data was available across all histological categories were included. Overall survival analysis was performed from the initiation of the first chemotherapy.

[0167] This study addresses several fundamentally important issues in immuno-oncology. First, it was previously unclear how broadly tumor mutational burden thresholds predict clinical utility from immune checkpoint regulators across human cancers. Our study suggests that tumor mutational burden thresholds can predict survival across many diverse types of human cancer in patients treated with either CTLA-4 inhibitors or PD-1 inhibitors. Second, previous studies on the association between tumor mutational burden and survival after ICM therapy have examined smaller cohorts, and therefore the effect of tumor mutational burden on clinical utility could not be quantified in an accurate manner. This study presents genomic data from the largest cohort of patients treated for ICM to date (over 1500 patients) and also expands upon and validates previous data from smaller studies. Finally, the MSK-IMPACT targeted panel captures approximately 3% of coding exomes, and our data show that this profiling strategy provides a sufficient representation of the total tumor mutational burden to have predictive value in patients treated for ICM. In summary, these data suggest that tumor mutational burden and tumor mutational burden threshold are predictive biomarkers for ICM response across multiple human cancer types and may have potential value in conjunction with PD-L1 immunohistochemistry. 16 The overall oncological properties of this biomarker appear to reflect the underlying mechanisms by which ICM functions. Therefore, our data are also consistent with the theory that a higher tumor mutational burden is associated with a greater number of tumor neoantigens presented on MHC molecules, which promotes immune recognition as exogenous and the development of a high tumor response. Example 3: Calculation of tumor mutation loading threshold for Example 1

[0168] This embodiment describes how tumor mutation burden is calculated from collected patient data.

[0169] The total number of identified somatic mutations or tumor mutation burdens was normalized to the exon coverage of each MSK-IMPACT panel in the base state. Overall survival analyses were performed for ICM-therapy patients from the date of the first infusion of any ICM. For patients who received multiple courses of ICM, the first treatment was used for analysis. Patients were terminated on the date of the last appointment attended. For non-ICM patients, the date of the first dose of any chemotherapy was used for overall survival analyses.

[0170] Survival analysis was performed using Kaplan-Meier regression, and log-rank p-values ​​were reported. Multivariate analysis was performed using Cox proportional hazards regression. These data analysis methods are known to those skilled in the art. Because the distribution of tumor mutational burden varied significantly depending on histology, the optimal tumor mutational burden cutoff or tumor mutational burden threshold used herein was determined by maximum chi-square analysis, known to those skilled in the art. Statistical analysis was performed in R using the survival package. Example 4: HLA class I genotype affects survival as an immune checkpoint regulator. Materials and methods Description of the study design and patient set

[0171] For the analysis presented in this study, we used two distinct sets of cancer patients treated with immune checkpoint inhibitors. For Cohort 1, we obtained exome sequencing and clinical data from 371 patients treated with anti-CTLA-4 or anti-PD-1 therapy. Two patients did not have overall survival data and were not included in the analysis. Of the 369 patients with complete clinical data, 269 had advanced melanoma and 100 had advanced non-small cell lung cancer (NSCLC). Melanoma data came from four previously reported studies (3, 4, 7, 36). NSCLC data came primarily from patients with metastatic disease treated with anti-PD-1 monotherapy. Patients were from a prospective trial we previously reported (5) and from New York-Presbyterian / Columbia University Medical Center. Exome sequencing data was unavailable for 67 patients with NSCLC. All patients were treated under a prospective protocol approved by institutional review. For Cohort 2, we obtained independent next-generation sequencing data using clinical data from 1,166 patients representing different cancer types on a targeted gene panel (MSK-IMPACT) and an intra-institutional IRB-approved research protocol (NCT01775072). These patients were treated at Memorial Sloan Kettering Cancer Center with anti-CTLA-4, PD-1 / PD-L1 inhibitors, or a combination of both (32). Clinical characteristics of the patient cohort are provided in Annex 1. For germline variant analysis, the original sequencing files and associated clinical data were anonymized by a third party without the researchers' access to the identification of the original patients, in accordance with the protocol design. Additional details regarding these tumors can be found in the original publications (3–5, 7, 11, 36). The results published here are based in part on data generated by the TCGA pilot project established by the National Cancer Institute and the National Human Genome Research Institute.Information about TCGA and the researchers and institutions that comprise the TCGA research network can be found at cancergenome.nih.gov / . TCGA exome data for patients with melanoma was obtained from the Cancer Genome Atlas (TCGA) (N=378). Overall survival and clinical response data

[0172] The clinical endpoint used in these analyses was overall survival, defined as the length of time from the start of treatment to an event (survival or censoring). All clinical data were obtained from the original studies (3–5, 7, 11, 36). Clinical data from TCGA patients with melanoma were accessed through the TCGA Data Portal. HLA Class I Genotyping Data

[0173] We performed high-resolution HLA class I genotyping directly from germline normal DNA exome sequencing data or using a clinically validated HLA typing assay (LabCorp). Patient exome data or targeted gene panels were obtained, and HLA class I alleles with default parameter settings were identified using the well-validated tool Polysolver (38). The high accuracy of Polysolver compared to serological or PCR-based methods has been previously demonstrated (37, 38). For quality assurance, a subset of these patients (N=22) were molecularly HLA-classified at a CLIA-certified center (New York Blood Center) and then classified using Polysolver. The overall agreement between Polysolver and molecular typing was 96%. Agreement is defined as [(6 - number of allele mismatches between Polysolver and molecular typing) / 6] × 100. Furthermore, HLA class I isozygosity detected by Polysolver was confirmed by two additional computational tools, OptiType and HLA-SOAP. (39, 40). HLA class I molecular typing was performed in LabCorp for 67 patients with NSCLC for whom exome sequencing data was unavailable. For quality assurance of captured HLA class I by MSK-IMPACT (CLIA certified hybridization capture-based assay) (8, 11, 41), we compared HLA class I typing by Polysolver among 37 samples that we sequenced using MSK-IMPACT and whole exome. The MSK-IMPACT panel successfully captured HLA-A, -B, and -C.To confirm that HLA class I genes have sufficient coverage in MSK-IMPACT BAM files, we applied the bedtools multicov tool ( / / bedtools.readthedocs.io / en / latest / content / tools / multicov.html), which reports the counting of alignments from multiple position-sorted and indexed BAM files overlapping with the target interval in BED format. Only high-quality readings were counted, and only samples with sufficient coverage were used. The overall agreement in class I typing between MSK-IMPACT samples and their matched WES samples was 96%. statistical analysis

[0174] We performed survival analyses using Kaplan-Meier estimators. Log-rank tests were used to determine the statistical significance of survival distributions between patients with and without a particular genotype. We calculated hazard ratios using univariate or multivariate Cox regression. To stratify patients into two groups, high and low tumor mutational burden, we used cutoffs calculated by the R function maxstat.test( / / cran.r-project.org / web / packages / maxstat / vignettes / maxstat.pdf). In Figures 8F, 8G, 9G, and 9H, we used cutoff ranges across the quartiles of the distribution of somatic mutation counts for the specific cohort analyzed. Cutoffs were used to stratify patients into two groups, high or low tumor mutational burden, and to generate box plots showing the distribution of hazard ratios resulting from survival analyses using multiple cutoffs. In Figure 8F, we used the range [80,542]. For Figure 8G, we used [5,65]. For Figure 9G, we used the range [108,569]. For Figure 9H, we used [5,25]. We performed a comparison of the number of somatic variations between HLA class I isozygotes and heterozygotes using the Wilcoxon rank-sum test. All statistical analyses were performed using the R Statistical Computing environment version 3.3.1 (www.r-project.org). Mutation analysis pipeline

[0175] For Cohort 1, whole exome sequencing for all datasets had been previously completed (3–5, 36). We performed the analysis as described by DePristo et al. (42, 43). As previously stated (42), paired-end reads in FASTQ format were aligned to the reference human genome GRCh37 using the Burrows-Wheeler aligner (BWA, v0.7.10) (44). Local alignment was performed using the Genome Analysis Toolkit (GATK 3.2.2) (45). Duplicate reads were removed using Picard version 1.119. To identify somatic single-nucleotide variants (SNVs), we used a pipeline integrating mutation calls from four different mutation callers: MuTect 1.1.4, Strelka 1.0.3, 1.0.4 SomaticSniper, and Varscan 2.3.7 (46–49). Insertions and deletions were determined using Strelka 1.0.3 with default settings (42, 43). SNVs with corresponding normal coverage for allele read counts less than 4 or read counts less than 7 were selected. For Cohort 2, relative mutational burden was determined using MSK-IMPACT matched to the targeted panel as a proven method for determining relative mutational burden (8, 11, 41, 50). Loss of heterozygosity in HLA class I analysis

[0176] To determine allele-specific copy numbers, copy number variation analysis was performed using FACETS 0.5.6(51). Fragments within the chromosome 6p locus were identified as containing HLA-A, HLA-B, and HLA-C loci. Loss of zygosity (LOH) was defined as an estimated minor allele copy number of 0 for any of the HLA loci using an expectation maximization model. HLA Class I structural analysis and molecular dynamics simulation

[0177] Using the VMD mutator plugin, neoantigen structures within the pHLA complex presented in PDB 1M6O were mutated to match the desired B44 motifs (F3I, P4G, A6V, F9Y). All images were rendered using the VMD 1.9.2 software package (52).

[0178] Molecular dynamics (MD) simulations of isolated HLA class I alleles and HLA-peptide complexes were initiated from the configurations derived from the crystal structures at the highest available resolutions: HLA-B*15:01 (PDB ID: 1XR9), HLA-B*07:02 (PDB ID: 5EO0), and HLA-B*53:01 (PDB ID: 1A1M). To generate the isolated HLA configurations, atoms corresponding to the bound peptides were removed. After adding hydrogen atoms and disulfide bond patches, each system was solvated with TIP3P water molecules, and Na + and Cl - The ion concentration was varied to a physiological level (150 mM). Following a similar protocol used in our previous studies (53-55), the resulting protein-water system was minimized using the steepest descent method over 25,000 steps, and then equilibrated with and without harmonic protein restraint in separate 5 ns simulations. The configurations taken from the end of the equilibrium operation were used for seed production simulations, extended to a length of 500 ns for HLA-B*15:01 and 300 ns for HLA-B*07:02 and HLA-B*53:01. In all equilibration and production operations, temperature and pressure were constrained to 310 K and 1 atm using a Langevin thermostat and a Parinello-Rahman barostat. All MD simulations were performed using the NAMD 2.11 simulation package (56). Residue separation and residue position root mean squared fluctuation (RMSF) were calculated using the standard utilities included in the GROMACS 5.1 software suite (57). Simulation snapshots were generated using VMD (52). result

[0179] We conducted survival and gene association analyses to address two hypotheses: (i) that heterozygosity in HLA class I genes confers a selective advantage in survival with immune checkpoint inhibitor administration in cancer patients, and (ii) that individual HLA class I germline alleles differ in their effects on survival after ICM therapy.

[0180] To examine these hypotheses, we reviewed two sets of cancer patients treated with ICM therapy (hereinafter referred to as Cohort 1 and Cohort 2). Cohort 1 consisted of 369 patients treated with anti-CTLA-4 or anti-PD-1 drugs for which exome sequencing data and clinical data were available. Of these 369 patients, 269 had advanced melanoma as previously reported by Snyder et al. (3), Van Allen et al. (4), Hugo et al. (7), and Riaz et al. (36), and 100 had advanced non-small cell lung cancer (NSCLC) (5) (Appendix 1). Patients with NSCLC were treated primarily with anti-PD-1 monotherapy. Cohort 2 consisted of 1,166 patients representing different cancer types, including melanoma and NSCLC (Appendix 1), whose tumors underwent targeted next-generation sequencing (MSK-IMPACT) (11). These patients were treated at Memorial Sloan Kettering Cancer Center with drugs targeting CTLA-4, PD-1 / PD-L1, or a combination of both (11). For all patients in both cohorts, we performed high-resolution HLA class I genotyping from conventional DNA using DNA sequencing data or a clinically proven HLA typing assay (LabCorp). HLA typing was performed from sequencing data using a widely proven Polysolver (33, 34). For quality assurance, a subset of these patients (N=22) were HLA-classified using a CLIA-certified assay (New York Blood Center) and then classified using a Polysolver (38). As expected and previously demonstrated, the overall agreement between the Polysolver and the HLA typing assay was very high (96%).

[0181] MHC class I molecules are highly polymorphic, with most polymorphisms located in the peptide-binding region. Each variant binds a select repertoire of peptide ligands. Therefore, individuals who are isozygous at at least one HLA class I locus are expected to present a smaller and less diverse repertoire of tumor-derived peptides recognized by cytotoxic T lymphocytes (CTLs) compared with individuals who are heterozygous at each class I locus (32). Accordingly, we hypothesized that greater diversity (heterozygosity) in the repertoire of antigen-presenting HLA class I molecules would be associated with better survival after ICM treatment. Conversely, less diversity (homozygosity) in these class I genes would be associated with worse survival. We tested this hypothesis by examining HLA zygosity for each of the HLA class I genes (HLA-A, -B, and -C) individually in cohorts 1 and 2. For this analysis, we employed the Cox proportional hazards regression model to examine the probability of overall survival. The results showed a statistically significant association between HLA class I isozygosity and reduced survival in 369 patients from Cohort 1 treated with ICM therapy (Figure 8A). The association was clear when at least one HLA class I locus was isozygous (Cohort 1, P=0.036, HR=1.40, 95% CI 1.02–1.9, Figure 8A). We validated this finding in an independent cohort of 1,166 patients treated with ICM therapy (Cohort 2, P=0.028, HR=1.31, 95% CI 1.03–1.70, Figure 8B). The number of somatic mutations in tumors did not differ statistically between isozygous and heterozygous patients in either Cohort 1 (Wilcoxon rank-sum test P=0.09, Figure 11A) or Cohort 2 (Wilcoxon rank-sum test P=0.7, Figure 11B).In Cohort 1 (P=0.02, HR=1.50, 95% CI 1.07–2.10) (Table 4) and Cohort 2 (P=0.028, HR=1.31, 95% CI 1.03–1.67) (Table 5), including mutational burden, tumor stage, age, and drug class, the association between isozygosity and reduced survival remained significant in multivariate Cox regression modeling. [Table 4-2] [Table 4-3] [Table 5-2]

[0182] The generation of HLA class I-restricted T cell responses has been shown to be important for the clinical response in cancer patients treated with immunotherapy (3, 5, 34, 35). These results suggest that HLA homozygosity may impair patient survival after ICM therapy by limiting the number of HLA class I-restricted tumor-derived epitopes that can be presented to T cells, thereby reducing the opportunity for antigens necessary for antitumor immunity to be presented. Interestingly, these data are consistent with the association of rapid progression to AIDS in HIV-infected patients with HLA class I homozygosity (22, 25) and the association of HLA class II with persistent hepatitis B virus infection (58).

[0183] Next, we examined all 1,535 patients from cohorts 1 and 2 together to determine whether the isozygosity effect could be due to a single class I locus or a combination of different loci. This analysis revealed that isozygosity at one HLA class I locus (A, B, or C) was associated with a significant reduction in overall survival (P=0.003, HR=1.38, 95%CI 1.11–1.70, Figure 8C). Interestingly, the effect of isozygosity on survival at specific HLA class I loci appeared to be primarily associated with HLA-B (P=0.052, HR=1.66, 95%CI 0.93–2.94, Figure 8C) and HLA-C (P=0.004, HR=1.60, 95%CI 1.16–2.21, Figure 8C). It is worth noting that the number of available patients likely limited the interpretability of analyses involving seating combinations (e.g., HLA-A and -B).

[0184] While not bound by any particular theory, there are two possible explanations for the significant association between HLA-B isozygosity and reduced survival. First, HLA-B is expressed at higher levels on the cell surface than HLA-A and HLA-C, and the HLA-B allele binds to a wider variety of peptides (59, 60). The amino acids that bind to the B pocket of the HLA-A allele are broadly hydrophobic residues. In contrast, the B pocket of the HLA-B allele can accommodate a wider variety of residues (proline, positively and negatively charged residues, as well as histidine and glutamine) (60). The primary source of HLA-B diversity arises from intralocusal recombination events within exon 3 that primarily affect the F, C, and D pockets (60), and the HLA-B locus is dominant in determining clinical outcomes in infectious diseases such as HIV and malaria (21-28). Similarly, heterozygosity at the HLA-C locus allows for greater peptide ligand diversity. +While also capable of presenting peptides to T cells, antigen-presenting cells (APCs) express higher levels of HLA-C on their cell surface than other cell types (61). Because HLA-C molecules bind to inhibitory killer cell immunoglobulin receptors (KIRs) that are upregulated for the acquisition of effector function (62), atypical HLA-C loci can more effectively limit CTL lysis by cross-presenting APCs. This, therefore, can facilitate the continuous priming of naive CTLs during treatment with ICM therapy (63).

[0185] Previous reports have shown that the total number of somatic coding mutations in the cancer genome correlates with the response to ICM therapy (6, 3-5, 65). An explanation for this observation is that the number of neopeptides presented by the tumor increases with the number of somatic mutations, while CD8 + The key factor is T cell recognition of neoepitopes after ICM therapy (64). Therefore, we evaluated the effect of zygosity at HLA class I loci in combination with mutational burden. This analysis revealed that HLA class I isozygosity and low mutational burden were strongly associated with reduced survival compared to patients who were atypically zygosity at each class I locus and whose tumors had high mutational burden. This effect was observed in both cohort 1 (P=0.003, HR=2.03, 95%CI 1.27–3.30, Figure 8D) and cohort 2 (P<0.0001, HR=2.98, 95%CI 1.84–4.82, Figure 8E). In particular, the combined effect of HLA class I atypical zygosity and mutational burden on survival was greater than that of mutational burden alone in both cohort 1 and cohort 2 (Figure 8, F and G).

[0186] Previous studies have reported the presence of loss of atypia (LOH) of HLA class I genes in cancer (66). Therefore, we investigated whether LOH of HLA class I in tumors could have a similar effect on survival outcomes after ICM therapy as germline HLA class I homozygosity. We analyzed all tumor exomes from Cohort 1 and identified 32 patients who were atypia at all HLA class I loci but had at least one HLA class I locus in their tumors (Appendix 1). We found that patients with LOH of HLA class I were associated with reduced survival compared to patients who were atypia at each HLA class I locus but did not have LOH (P=0.05, HR=1.60, 95% CI 1.03–2.43, Figure 8H). Consistent with the above results, the effect of LOH on survival of HLA class I was enhanced in patients whose tumors contained low mutational burden compared to patients whose tumors were atypically zygosity at all HLA class I loci, did not have LOH, and whose tumors had high mutational burden (P=0.0006, HR=3.68, 95% CI 1.64~8.23, Figure 8I). In summary, these results indicate that patient-specific diversity of antigen-presenting HLA class I molecules and mutational burden in tumors together influences the number of immunogenic neoantigens presented on the cell surface, and conversely, influences the response to ICM therapy. Furthermore, the demonstration of a significant survival advantage over HLA class I atypical zygosity in patients treated with ICM therapy at both the germline and somatic cell levels highlights its importance in dynamic antitumor immune responses and their evasion.

[0187] To investigate the clinical relevance of individual HLA class I alleles after anti-PD-1 or anti-CTLA-4 therapy, we examined the effect of HLA class I supertypes on overall survival after ICM treatment. Individual HLA class I alleles are classified into 12 separate supertypes (or superfamilies) (67, 68). HLA alleles within the same supertype are expected to present similar peptides, and this classification is supported by strong evidence for the shared presentation of peptide bond motifs by different HLA class I molecules (25, 67, 68). Importantly, these supertypes together deal with most HLA-A and HLA-B alleles found in different populations (67, 68).

[0188] Given the diversity of HLA alleles, we had enough patients for two sets of patients for a meaningful analysis. Therefore, to evaluate the effect of HLA supertypes on survival, we focused on melanoma patients. Based on the biological definition of supertypes, we classified the 27 HLA-A alleles present in patients with melanoma into six A supertypes and the 50 HLA-B alleles into six B supertypes (Appendix 1 and Figure 9A). We determined whether each HLA superfamily was associated with survival after ICM treatment. Surprisingly, this analysis identified two supertypes, both B supertypes, that were associated with survival outcomes in patients with advanced melanoma treated with anti-CTLA-4. Patients with the B44 superfamily allele had significantly better overall survival (P=0.01, HR=0.61, 95%CI 0.42–0.89) (Table 3), while patients with the B62 allele had significantly reduced survival (P=0.0007, HR=2.29, 95%CI 1.40–3.7) (Table 3). In these patients, the B44 supertype was present in 45% of cases, and the B62 supertype in 15% (Figure 9A). We did not identify any supertypes that were significantly associated with overall survival in patients with NSCLC, likely due to our limited sample size. [Table 3-3] [Table 3-4]

[0189] Next, we examined whether these supertype associations were influenced by the presence of specific component HLA class I alleles. The association of B44 was influenced by HLA-B*18:01, HLA-B*44:02, HLA-B*44:03, HLA-B*44:05, and HLA-B*50:01 (P=0.001, HR=0.49, 95%CI 0.32~0.76, Figure 9C) (Table 3). The association of B62 was significantly induced by HLA-B*15:01 (P=0.002, HR=2.21, 95%CI 1.33~3.7, Figure 10A) (Table 3). After conservative Bonferroni correction for multiple comparisons, both associations between these B44 and B62 supertype alleles were statistically significant (P=0.01 and P=0.02, respectively).

[0190] In individual sets of patients, in Cohort 2, melanoma patients with the B44 supertype allele and treated with anti-PD-1 or anti-CTLA-4 had significantly better overall survival (P=0.05, HR=0.32, 95% CI 0.09–1.1, Figure 9, B and D). When mutational burden, tumor stage, age, and drug class (anti-CTLA-4 or anti-PD-1) were included in both Cohort 1 (Table 6) and Cohort 2 (Table 7), the association of B44 with extended survival remained significant in multivariate analysis. The effect of B44 on extended survival was enhanced when somatic mutational burden in the tumor was also considered. Patients with melanoma carrying B44, whose tumors contained high mutational burden, had significantly longer survival in Cohort 1 (P<0.0001, HR=0.23, 95% CI 0.13–0.41, Figure 9E) and Cohort 2 (P=0.023, HR=0.13, 95% CI 0.02–1.07, Figure 9F) compared to patients with tumors not carrying B44 and containing low mutational burden. The combined effect of B44 and mutational burden was greater in both Cohort 1 and Cohort 2 than simply considering mutational burden alone (Figure 9, G and H). We noted that the outcomes for melanoma patients in Cohort 2 tended to be better than in Cohort 1 because, in general, patients who received ICM therapy and became part of our protocol for MSK-IMPACT survived longer. However, despite this trend, we observed a significant effect from the B44 superfamily allele. In particular, the B44 supertype was not associated with overall survival in patients with melanoma from the Cancer Genome Atlas (TCGA), suggesting that the presence of B44 is a predictor of response to both ICMs but not a prognostic indicator (Figure 9I). [Table 6] [Table 7-1] [Table 7-2]

[0191] Members of the B44 supertype share a loading residue at the anchor position P2(Glu) near the N-terminus and a polar residue at the C-terminus, as well as a preference for peptides (69) (Figure 9J). Several previously identified immunogenic antigens expressed by melanoma include the testicular antigen MAGEA3 epitope, which has been shown to be restricted to HLA-B*44:03 and HLA-B*18:01 (both members of B44), and the immunogenic clonal neoantigen (FAM3C:TESPFEQHI) identified in melanoma patients who induced a long-term response to CTLA-4 inhibitors from Cohort 1 (Table 8) (Figure 9J and Table 8), (3, 15). In addition, the association of B44 with spontaneous immune responses in tumor-expressing NY-ESO-1 has recently been reported (70). In summary, these data suggest that B44 can facilitate the presentation of tumor-derived antigens recognized by CD8+ T cells, and conversely, contribute to improved survival outcomes after ICM therapy. [Table 8] The WT score and neoantigen score refer to the binding sensitivities of wild-type peptide and its mutant peptide, respectively, as predicted by NetMHC version 4.0 (73).

[0192] In contrast, the association of B62 with poor survival caused by the HLA-B*15:01 allele was intriguing (Figure 10A) (Table 3). In exploratory analysis, we sought to determine whether any molecular features in the HLA-B*15:01 allele were associated with their effect on survival after immunotherapy. From all HLA-B alleles available for three-dimensional structural analysis (N=119, Appendix 2), we identified three alleles possessing structural crosslinks in the peptide bond groove at positions 62, 66, and 163: HLA-B*15:01 (PDB ID: 1XR9), HLA-B*07:02 (PDB ID: 5EO0), and HLA-B*53:01 (PDB ID: 1A1M) at their highest resolution. Crosslinking at HLA-B*15:01 appears to sequester binding peptide residues P2 and P3 (Figure 10, B and C).

[0193] Since significant peptide presentation has been reported for this allele, poor survival associated with the HLA-B*15:01 allele cannot simply reflect a failure to this peptide (71). Therefore, we hypothesized that this particular structural feature can regulate the effective T cell recognition of neoepitopes presented on the HLA-B*15:01 molecule. To evaluate the validity of this hypothesis, we performed molecular dynamics (MD) simulations for the following three HLA class I molecules following a similar protocol used in previous studies (53-55).

[0194] For HLA-B*07:02 and HLA-B*53:01, molecular dynamics simulations showed that the binding peptides effectively disrupted the crosslinks and expanded the respective HLA binding gaps (Figure 12, A-D). Conversely, in the HLA-B*15:01 molecule, the crosslinks were largely maintained with the present peptides, and the crosslinking residues were made much less mobile (Figure 10, D and E). Figure 10D shows MD simulation snapshots of both the isolated HLA B*15:01 molecule and its complex with the 9-merUBCH6 peptide, each over a 500 ns dynamics course. In both cases, the crosslinking residues (Arg62, Ile66, and Leu163) separated somewhat as their crystal coordinates relaxed and the crosslinking residue positions fluctuated as trajectory progressed. However, the general crosslink configuration observed in the crystal structure was conserved in our simulated conformational ensemble (Figure 10, D and E). As shown in Figure 10E, the occupancy of the peptide bond groove in HLA-B*15:01 had the effect of suppressing the kinetics of the crosslinking residues. The mean crosslink separation remained nearly constant (approximately 6 Å) in both systems of HLA-B*15:01 (Figure 10E), but the fluctuation in this distance was less dramatic in the peptide bond complex. The residue position root mean square fluctuation (RMSF) indicates that each crosslinking residue was more rigid in the presence of the peptide (Figure 10E). In short, these unique structural and kinetic elements of the HLA-B*15:01 molecule impair the overall strength of the interaction between the HLA-B*15:01 neoepitope and the T cell receptor for effective antigen recognition. However, further experimental work will be necessary to verify this hypothesis.

[0195] Therefore, the results presented here indicate that HLA class I genes influence survival outcomes in ICM therapy. Our data show that patient-specific HLA class I genotypes and somatic modifications, in combination or alternatively, influence clinical outcomes after ICM therapy in tumors. Both may be considered in the design of future clinical trials and / or recommended therapeutic doping regimens. The observation that the B44 superfamily is associated with extended overall survival may offer an opportunity for the development of therapeutic vaccines that potentially target immunodominant HLA-B44 restriction neoantigens expressed by melanoma. Additionally, our findings suggest that HLA class I homozygosity and LOH of HLA class I represent genetic barriers that may enhance the efficacy of immunotherapy. Example 5: Exemplary dosing regimens for approved PD-1 immune checkpoint modulators This embodiment describes a specific drug regimen approved by the U.S. Food and Drug Administration for the indicated immune checkpoint modifier agent: Atezolizumab (TECENTRIQ®).

[0196] ----------------Indications and Use----------------

[0197] TECENTRIQ is a programmed death ligand 1 (PD-L1) inhibitor antibody, which is indicated for the treatment of patients with locally advanced or metastatic urothelial carcinoma, and said patients

[0198] If you are experiencing disease exacerbation during or after platinum-containing chemotherapy,

[0199] This antibody is associated with disease exacerbation within 12 months of neoadjuvant or adjuvant therapy with platinum-containing chemotherapy.

[0200] This indication will be approved under accelerated approval based on tumor response rate and duration of response. Continued approval for this indication may be subject to verification and explanation of clinical utility in confirmatory trials.

[0201] ----------------Medication and Administration----------------

[0202] Administer 1200 mg intravenously over 60 minutes every three weeks.

[0203] Dilute before intravenous infusion.

[0204] ----------------Medication Form and Intensity--------------

[0205] Infusion: 1200 mg / 20 mL (60 mg / mL) solution in a single-dose vial.

[0206] ----------------Contraindications----------------

[0207] none.

[0208] --------------Warnings and Precautions for Use---------------

[0209] Immune-associated interstitial pneumonia: Treatment should be withheld for moderate interstitial pneumonia, and permanently discontinued for severe or critical interstitial pneumonia. (5.1)

[0210] Immune-associated hepatitis: Monitor changes in liver function. Moderate elevations of transaminase or total bilirubin should be avoided, while severe or critical elevations of transaminase or total bilirubin should be permanently discontinued.

[0211] Immune-associated colitis: Avoid treatment for moderate or severe colitis, and discontinue treatment permanently for severe colitis.

[0212] Immune-related endocrine diseases:

[0213] Pituitary inflammation: Avoid treatment for moderate or severe pituitary inflammation, and discontinue treatment permanently for severe pituitary inflammation.

[0214] Thyroid disorder: Monitor changes in thyroid function. Withhold for symptomatic thyroid disease.

[0215] Adrenal insufficiency: Withhold for symptomatic adrenal insufficiency.

[0216] Type 1 diabetes: Withhold for hyperglycemia of grade 3 or higher.

[0217] Immune-related myasthenia syndrome / myasthenia gravis, Guillain-Barré or encephalomyelitis: Discontinue permanently for any grade.

[0218] Ocular inflammatory toxicity: Withhold for moderate ocular inflammatory toxicity and discontinue permanently for severe ocular inflammatory toxicity.

[0219] Immune-related pancreatitis: Withhold for moderate or severe pancreatitis and discontinue permanently for severe pancreatitis or recurrent pancreatitis of any grade.

[0220] Infection: Withhold for severe or critical infection.

[0221] Infusion reaction: Interrupt or slow the infusion rate for mild or moderate infusion reaction and discontinue for severe or critical infusion reaction.

[0222] Embryo-fetal toxicity: TECENTRIQ can cause fetal harm. Advise women of reproductive potential about the potential risks to the fetus and the use of effective contraception. Avelumab (BAVENCIO®)

[0223] ----------------Indications and Usage----------------

[0224] BAVENCIO is a programmed death ligand 1 (PD-L1) inhibitory antibody indicated for the treatment of adults and pediatric patients 12 years of age and older with metastatic Merkel cell carcinoma (MCC).

[0225] This indication has been approved under accelerated approval. Continued approval for this indication may be subject to verification and explanation of clinical efficacy in confirmatory trials.

[0226] ----------------Medication and Administration----------------

[0227] Administer 10 mg / kg intravenously over 60 minutes every two weeks.

[0228] The first four infusions, and subsequently, if necessary, are pre-administered with acetaminophen and antihistamines.

[0229] ---------------Medication Form and Intensity---------------

[0230] Infusion: 200 mg / 10 mL (20 mg / mL) solution in a single-dose vial.

[0231] ------------------Contraindications-------------------

[0232] None. (4)

[0233] --------------Warnings and Precautions for Use---------------

[0234] Immune-mediated interstitial pneumonia: Avoid treatment for moderate interstitial pneumonia, and permanently discontinue treatment for severe, critical, or recurrent interstitial pneumonia.

[0235] Immune-mediated hepatitis: Monitor changes in liver function. Avoid treatment for moderate hepatitis, and discontinue treatment permanently for severe or critical hepatitis.

[0236] Immune-mediated colitis: Avoid treatment for moderate or severe colitis, and discontinue permanently for severe or recurrent colitis.

[0237] Immune-mediated endocrine disorders: Avoid in severe or critical endocrine disorders.

[0238] Immune-mediated nephritis and renal dysfunction: Avoid in moderate or severe nephritis and renal dysfunction, and permanently discontinue in critical nephritis and renal dysfunction.

[0239] Infusion-related reactions: Interrupt or slow the infusion rate for mild or moderate infusion-related reactions. Stop the infusion and permanently discontinue Bavencio for severe or critical infusion-related reactions.

[0240] Embryo-fetal toxicity: Bavencio can cause fetal harm. Advise on potential risks to the fetus and use of effective contraception. Durvalumab (IMFINZI (trademark))

[0241] ----------------Indications and Usage----------------

[0242] IMFINZI is a programmed death ligand 1 (PD-L1) inhibitory antibody, which is applicable for the treatment of patients who

[0243] have locally advanced or metastatic urothelial carcinoma,

[0244] have disease progression during or after platinum-containing chemotherapy,

[0245] or have disease progression within 12 months of neoadjuvant or adjuvant treatment with platinum-containing chemotherapy.

[0246] This indication is approved under accelerated approval based on tumor response rate and duration of response. Continued approval for this indication may be conditioned on verification of clinical utility and description in confirmatory trials.

[0247] ----------------Dosage and Administration----------------

[0248] Administer 10 mg / kg intravenously over 60 minutes every two weeks.

[0249] The first four infusions, and subsequently, if necessary, are pre-administered with acetaminophen and antihistamines.

[0250] ---------------Medication Form and Intensity---------------

[0251] Administer 10 mg / kg intravenously over 60 minutes every two weeks, diluting the solution before intravenous administration.

[0252] ------------------Contraindications-------------------

[0253] none.

[0254] --------------Warnings and Precautions for Use---------------

[0255] Immune-mediated interstitial pneumonia: Treatment should be withheld for moderate interstitial pneumonia, and permanently discontinued for severe or critical interstitial pneumonia.

[0256] Immune-mediated hepatitis: Monitor changes in liver function.

[0257] Moderate elevations of transaminase or total bilirubin should be avoided, while severe or critical elevations of transaminase or total bilirubin should be permanently discontinued.

[0258] Immune-mediated colitis: Avoid treatment for moderate colitis, and discontinue treatment permanently for severe or critical colitis.

[0259] Immune-mediated endocrine disorders: Adrenal insufficiency, hypophysitis, or type 1 diabetes: Avoid use in moderate, severe, or critical cases.

[0260] Immune-mediated nephritis: Monitor changes in renal function. Avoid treatment for moderate nephritis, and discontinue permanently for severe or critical nephritis.

[0261] Infection: Avoid severe or serious infections.

[0262] Infusion-related reactions: For mild or moderate infusion-related reactions, discontinue the infusion or slow the infusion rate; for severe or critical infusion-related reactions, discontinue the infusion permanently.

[0263] Embryo-fetal toxicity: May cause harm to the fetus. Advise women of reproductive capacity about the potential risks to the fetus and the use of effective contraception. Nivolumab (OPDIVO® registered trademark)

[0264] ----------------Indications and Use----------------

[0265] OPDIVO is a human programmed death receptor-1 (PD-1) inhibitor antibody indicated for use after ipilimumab and BRAF inhibitors in patients with unresectable or metastatic melanoma who are positive for BRAF V600 mutations.

[0266] This indication will be approved under accelerated approval based on tumor response rate and duration of response. Continued approval for this indication may be subject to verification and explanation of clinical efficacy in confirmatory trials. (1, 14)

[0267] ----------------Medication and Administration----------------

[0268] Administer 3 mg / kg intravenously over 60 minutes every two weeks.

[0269] ---------------Medication Form and Intensity---------------

[0270] Injection: 40 mg / 4 mL and 100 mg / 10 mL solutions in single-use vials.

[0271] ------------------Contraindications-------------------

[0272] none.

[0273] --------------Warnings and Precautions for Use---------------

[0274] Immune-related adverse reactions: Corticosteroids are administered based on the severity of the reaction.

[0275] Immune-mediated interstitial pneumonia: Treatment should be withheld for moderate interstitial pneumonia, and permanently discontinued for severe or critical interstitial pneumonia.

[0276] Immune-associated colitis: Avoid treatment for moderate or severe colitis, and discontinue treatment permanently for severe colitis.

[0277] Immune-mediated hepatitis: Monitor changes in liver function. Moderate elevations of transaminase or total bilirubin should be avoided, while severe or critical elevations of transaminase or total bilirubin should be permanently discontinued.

[0278] Immune-mediated nephritis and renal dysfunction: Monitor changes in renal function. Moderate elevation of plasma creatinine should be avoided, while severe or critical elevation of plasma creatinine should be permanently discontinued.

[0279] Immune-mediated hypothyroidism and hyperthyroidism: Monitor changes in thyroid function. Initiate thyroid hormone replacement therapy as needed.

[0280] Embryofetal toxicity: May cause harm to the fetus. Advice will be given regarding potential risks to the fetus and the use of effective contraception. Pembrolizumab (KEYTRUDA®)

[0281] ----------------Indications and Use----------------

[0282] KEYTRUDA is a human programmed death receptor-1 (PD-1) inhibitor antibody indicated for use after ipilimumab and BRAF inhibitors in patients with unresectable or metastatic melanoma who are positive for BRAF V600 mutations.

[0283] This indication will be approved under accelerated approval based on tumor response rate and persistence of response. Survival or improvement of disease-related symptoms has not yet been established. Continued approval for this indication may be subject to verification and explanation of clinical efficacy in confirmatory trials.

[0284] ----------------Medication and Administration----------------

[0285] Administer 2 mg / kg intravenously over 30 minutes every three weeks.

[0286] Reconstitute and dilute before intravenous infusion.

[0287] ---------------Medication Form and Intensity---------------

[0288] For injection: 50 mg, lyophilized powder in a single-use vial for reconstitution.

[0289] ------------------Contraindications-------------------

[0290] none.

[0291] --------------Warnings and Precautions for Use---------------

[0292] Immune-related adverse reactions: Corticosteroids are administered based on the severity of the reaction.

[0293] Immune-mediated interstitial pneumonia: Treatment should be withheld for moderate interstitial pneumonia, and permanently discontinued for severe or critical interstitial pneumonia.

[0294] Immune-associated colitis: Avoid treatment for moderate or severe colitis, and discontinue treatment permanently for severe colitis.

[0295] Immune-mediated hepatitis: Monitor changes in liver function. Treatment may be suspended or discontinued based on the severity of elevated liver enzymes.

[0296] Immune-mediated hypophysitis: For moderate hypophysitis, discontinue the medication; for severe hypophysitis, discontinue or stop the medication; and for severe hypophysitis, discontinue it permanently.

[0297] Immune-mediated nephritis: Monitor changes in renal function. Avoid treatment for moderate nephritis, and discontinue permanently for severe or critical nephritis.

[0298] Immune-mediated hyperthyroidism and hypothyroidism: Monitor changes in thyroid function. Treatment should be withheld in cases of severe hyperthyroidism, and permanently discontinued in cases of severe hyperthyroidism.

[0299] Embryofetal toxicity: KEYTRUDA may cause harm to the fetus. Advise fertile women about the potential risks to the fetus. Example 6: Exemplary dosing regimen for an approved CTLA-4 immune checkpoint modulator This embodiment describes a specific drug regimen approved by the U.S. Food and Drug Administration for the indicated immune checkpoint modulator drug. Ipilimumab (YERVOY® trademark)

[0300] ----------------Indications and Use----------------

[0301] YERVOY is a human cytotoxic T lymphocyte antigen 4 (CTLA-4) inhibitor antibody adapted for the following:

[0302] Treatment of unresectable or metastatic melanoma.

[0303] Adjuvant therapy for patients with cutaneous melanoma involving pathological involvement of regional lymph nodes larger than 1 mm, who have undergone infected excision, including total lymphadenectomy.

[0304] ----------------Medication and Administration----------------

[0305] Unresectable or metastatic melanoma: 3 mg / kg is administered intravenously over 90 minutes every three weeks in a total of four doses.

[0306] Adjuvant-treated melanoma: 10 mg / kg is administered intravenously over 90 minutes every 3 weeks in four doses, followed by 10 mg / kg every 12 weeks for up to 3 years or until recorded disease relapse or unacceptable toxicity.

[0307] In the event of a serious adverse reaction, the treatment will be permanently discontinued.

[0308] ---------------Medication Form and Intensity---------------

[0309] Injection: 50mg / 10mL (5mg / mL)

[0310] Injection: 200mg / 40mL (5mg / mL)

[0311] ------------------Contraindications-------------------

[0312] none.

[0313] --------------Warnings and Precautions for Use---------------

[0314] Immune-mediated adverse reactions: Severe reactions should be permanently discontinued. For moderate immune-mediated adverse reactions, treatment should be withheld until the patient returns to baseline, improves to mild severity, or makes a full recovery, receiving 7.5 mg of prednisone or less per day. For severe, chronic, or relapsing immune-mediated reactions, high-dose systemic corticosteroids should be administered.

[0315] Immune-mediated hepatitis: Evaluate liver function tests before each dose of YERVOY.

[0316] Immune-mediated endocrine disorders: Monitor clinical chemicals, ACTH levels, and thyroid function tests before each dose. Evaluate signs and symptoms of endocrine disorders at each visit. Administer hormone replacement therapy as needed.

[0317] Embryo-fetal toxicity: May cause harm to the fetus. Advice is provided regarding potential risks to the fetus and the use of effective contraception. Tremelimumab

[0318] ----------------Indications and Use----------------

[0319] Tremelimumab is a human cytotoxic T lymphocyte antigen 4 (CTLA-4) inhibitory antibody, and is still described below.

[0320] Clinical trials are underway for the treatment of head and neck cancer, HR+ / HER2 breast cancer, malignant mesothelioma, melanoma, metastatic renal cell carcinoma, unresectable malignant melanoma, urothelial carcinoma, and NSCLC.

[0321] ----------------Medication and Administration----------------

[0322] In combination with one or more other drugs, tremelimumab is administered intravenously over one hour on day 29 of a monthly dosing cycle, repeating three of the treatment regimens. The dose ranges from 6 mg / kg to 15 mg / kg. Alternatively, administered in combination with one or more other drugs or alone, tremelimumab is administered intravenously at a concentration of 15 mg / kg every 90 days for four cycles, or intravenously every three weeks for 12 weeks for four cycles with an additional dose at week 16. Appendix 1, Cohort 1 [Table B-1] [Table B-2] [Table B-3] [Table B-4] [Table B-5] [Table B-6] [Table B-7] [Table B-8] [Table B-9] [Table B-10] [Table B-11] [Table B-12] [Table B-13] Table B-14 Table B-15 Table B-16 Table B-17 Table B-18 Table B-19 Table B-20 Table B-21 Table B-22 Table B-23 Table B-24 Table B-25 Table B-26 Table B-27 Table B-28 Table B-29 Table B-30 Table B-31 Table B-32 Table B-33 Table B-34 Table B-35 Table B-36 Table B-37 Table B-38 Table B-39 Table B-40 Table B-41 Table B-42 Table B-43 Table B-44 Table B-45 Table B-46 Table B-47 [Table B-48] [Table B-49] [Table B-50] [Table B-51] [Table B-52] Appendix 1, Cohort 2 [Table C-1] [Table C-2] [Table C-3] [Table C-4] [Table C-5] [Table C-6] [Table C-7] [Table C-8] [Table C-9] [Table C-10] [Table C-11] Table C-12 Table C-13 Table C-14 Table C-15 Table C-16 Table C-17 Table C-18 Table C-19 Table C-20 Table C-21 Table C-22 Table C-23 Table C-24 Table C-25 Table C-26 Table C-27 Table C-28 Table C-29 Table C-30 Table C-31 Table C-32 Table C-33 Table C-34 Table C-35 Table C-36 Table C-37 Table C-38 Table C-39 Table C-40 Table C-41 Table C-42 Table C-43 Table C-44 Table C-45 Table C-46 Table C-47 Table C-48 Table C-49 Table C-50 Table C-51 Table C-52 Table C-53 Table C-54 Table C-55 Table C-56 Table C-57 Table C-58 Table C-59 Table C-60 Table C-61 Table C-62 Table C-63 Table C-64 Table C-65 Table C-66 Table C-67 Table C-68 Table C-69 Table C-70 Table C-71 Table C-72 Table C-73 Table C-74 Table C-75 Table C-76 Table C-77 Table C-78 Table C-79

Table C-80

Table C-90

Table C-95

Table D-12

[0323] While the present invention has been described in relation to embodiments for carrying out the invention, it should be understood that the foregoing description is illustrative and does not limit the scope of the invention as defined by the appended claims. Other embodiments, advantages, and modifications are within the scope of the following claims. In certain embodiments, for example, the following items are provided: (Item 1) A method comprising the step of administering immunotherapy to subjects who have previously received immunotherapy and exhibit a tumor mutational burden exceeding a threshold correlated with a statistically significant probability of responding to immunotherapy. (Item 2) The method described in item 1, wherein the cancer is a solid tumor. (Item 3) The method according to item 1, wherein the cancer is selected from the group consisting of bladder cancer, breast cancer, esophageal and gastric cancer, glioma, head and neck cancer, melanoma, non-small cell lung cancer, renal cell carcinoma, and combinations thereof. (Item 4) The method according to item 1, wherein the immunotherapy is the administration of an immune checkpoint modulator, or includes the administration of an immune checkpoint modulator. (Item 5) The method according to item 1, wherein the immunotherapy is the administration of an antibody drug, or includes the administration of an antibody drug. (Item 6) The method according to item 1, wherein the immunotherapy is the administration of a monoclonal antibody or includes the administration of a monoclonal antibody. (Item 7) The method according to item 1, wherein the immunotherapy is the administration of one or more PD-1 or PD-L1 inhibitor therapies, or includes the administration of one or more PD-1 or PD-L1 inhibitor therapies. (Item 8) The method according to item 1, wherein the immunotherapy is the administration of one or more CTLA-4 inhibitor therapies, or comprises the administration of one or more CTLA-4 inhibitor therapies. (Item 9) The method according to item 1, wherein the immunotherapy is a combination of one or more PD-1 inhibitors and CTLA-4 inhibitors. (Item 10) The method according to item 1, wherein the immunotherapy is selected from the group consisting of atezolizumab, avelumab, durvalumab, ipilimumab, nivolumab, pembrolizumab, or tremelimumab, and combinations thereof. (Item 11) The method according to item 1, wherein the displayed tumor mutation burden is determined by the use of a targeted sequence panel, or determined by the use of a targeted sequence panel. (Item 12) The method according to item 1, further comprising the step of measuring the tumor mutation load in the subject, wherein the measuring step is performed at a time selected from the group consisting of before administration, during administration, after administration, and combinations thereof. (Item 13) The method according to item 1, wherein the tumor mutation burden is measured by next-generation sequencing. (Item 14) The method according to item 1, wherein the tumor mutation burden is measured by mutation profiling of actionable cancer targets (MSK-IMPACT). (Item 15) The method according to item 1, wherein the subject has a cancer included in the following, and the tumor mutational burden threshold after immune checkpoint modifier therapy is as shown below. [Table E] (Item 16) The method according to item 1, wherein the subject has a cancer included in the following, and the tumor mutational burden threshold after immune checkpoint modifier therapy is as shown below. [Table F] (Item 17) The method according to item 1, wherein the immunotherapy is a therapy that has been shown to have a statistically significant probability of improving overall survival when administered to a population exhibiting the tumor mutation burden exceeding the threshold, or a therapy that has been shown to have a statistically significant probability of improving overall survival. (Item 18) The method according to item 1, wherein the statistically significant probability of response is established by demonstrating a statistically significant improvement in overall survival. (Item 19) A method comprising the step of administering immunotherapy to a subject exhibiting HLA class I supertype B44. (Item 20) A method comprising the step of administering immunotherapy to a subject exhibiting HLA class I supertype B62. (Item 21) A method comprising the step of administering immunotherapy to a subject exhibiting HLA class I atypia. (Item 22) The method according to item 21, wherein the subject exhibits atypical juxtaposition in one or more HLA class I seating positions. (Item 23) The method described in item 22, wherein the subject exhibits the greatest atypical fusion in an HLA class I seated position. (Item 24) The method according to item 21, wherein the HLA class I heterozygosity is determined by sequencing. (Item 25) The method according to item 21, wherein the HLA class I heterozygosity is determined by an HLA typing assay. (Item 26) The method according to any one of items 19 to 21, wherein the immunotherapy is the administration of an immune checkpoint modulator, or includes the administration of an immune checkpoint modulator. (Item 27) The method according to any one of items 19 to 21, wherein the immunotherapy is the administration of an antibody drug, or includes the administration of an antibody drug. (Item 28) The method according to any one of items 19 to 21, wherein the immunotherapy is the administration of a monoclonal antibody, or includes the administration of a monoclonal antibody. (Item 29) The method according to any one of items 19 to 21, wherein the immunotherapy is the administration of one or more PD-1 or PD-L1 inhibitor therapies, or includes the administration of one or more PD-1 or PD-L1 inhibitor therapies. (Item 30) The method according to any one of items 19 to 21, wherein the immunotherapy is the administration of one or more CTLA-4 inhibitor therapies, or comprises the administration of one or more CTLA-4 inhibitor therapies. (Item 31) The method according to any one of items 19 to 21, wherein the immunotherapy is a combination of one or more PD-1 inhibitors and CTLA-4 inhibitors. (Item 32) The method according to any one of items 19 to 21, wherein the immunotherapy is selected from the group consisting of atezolizumab, avelumab, durvalumab, ipilimumab, nivolumab, pembrolizumab, or tremelimumab, and combinations thereof. (Item 33) A method comprising the step of administering immunotherapy to subjects who have previously received immunotherapy, exhibit a tumor mutation burden exceeding a threshold correlated with a statistically significant probability of responding to immunotherapy, and exhibit HLA class I atypia. (Item 34) The method according to item 33, wherein the subject exhibits atypical juxtaposition in one or more HLA class I seating positions. (Item 35) The method described in item 34, wherein the subject exhibits the greatest atypical junction in an HLA class I seated position. (Item 36) The method according to item 33, wherein the HLA class I heterozygosity is determined by sequencing. (Item 37) The method according to item 33, wherein the HLA class I heterozygosity is determined by an HLA typing assay. (Item 38) The method described in item 33, wherein the cancer is a solid tumor. (Item 39) The method according to item 33, wherein the cancer is selected from the group consisting of bladder cancer, breast cancer, esophageal and gastric cancer, glioma, head and neck cancer, melanoma, non-small cell lung cancer, renal cell carcinoma, and combinations thereof. (Item 40) The method according to item 33, wherein the immunotherapy is the administration of an immune checkpoint modulator, or includes the administration of an immune checkpoint modulator. (Item 41) The method according to item 33, wherein the immunotherapy is the administration of an antibody drug or includes the administration of an antibody drug. (Item 42) The method according to item 33, wherein the immunotherapy is the administration of a monoclonal antibody or includes the administration of a monoclonal antibody. (Item 43) The method according to item 33, wherein the immunotherapy is the administration of one or more PD-1 or PD-L1 inhibitor therapies, or includes the administration of one or more PD-1 or PD-L1 inhibitor therapies. (Item 44) The method according to item 33, wherein the immunotherapy is an administration of one or more CTLA-4 inhibitor therapies, or comprises an administration of one or more CTLA-4 inhibitor therapies. (Item 45) The method according to item 33, wherein the immunotherapy is a combination of one or more PD-1 inhibitors and CTLA-4 inhibitors. (Item 46) The method according to item 33, wherein the immunotherapy is selected from the group consisting of atezolizumab, avelumab, durvalumab, ipilimumab, nivolumab, pembrolizumab, or tremelimumab, and combinations thereof. (Item 47) The method according to item 33, wherein the displayed tumor mutation burden is determined by the use of a targeted sequence panel, or determined by the use of a targeted sequence panel. (Item 48) The method according to item 33, further comprising the step of measuring the tumor mutation burden in the subject, wherein the measuring step is performed at a time selected from the group consisting of before administration, during administration, after administration, and combinations thereof. (Item 49) The method according to item 33, wherein the tumor mutation burden is measured by next-generation sequencing. (Item 50) The method according to item 33, wherein the tumor mutation burden is measured by mutation profiling of actionable cancer targets (MSK-IMPACT). (Item 51) The method according to item 33, wherein the subject has a cancer included in the following, and the tumor mutational burden threshold after immune checkpoint modifier therapy is as shown below. [Table G] (Item 52) The method according to item 33, wherein the subject has a cancer included in the following, and the tumor mutational burden threshold after immune checkpoint modifier therapy is as shown below. [Table H] (Item 53) The method according to item 33, wherein the immunotherapy is a therapy that has been shown to have a statistically significant probability of improving overall survival when administered to a population exhibiting the tumor mutation burden exceeding the threshold, or a therapy that has been shown to have a statistically significant probability of improving overall survival. (Item 54) The method described in item 33, wherein the statistically significant probability of response is established by demonstrating a statistically significant improvement in overall survival.

Claims

[Claim 1] The invention as shown in the drawings.

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