Checkpoint blockade and microsatellite instability

Abstract

To provide methods for treating cancer patients.SOLUTION: Provided is a pharmaceutical composition for administering to a cancer patient to treat a cancer patient, which comprises an immune checkpoint inhibitory antibody which blocks immune checkpoint, such as cytotoxicity T-lymphocyte antigen-4 (CTLA-4) and programmed death-1 (PD-1), the cancer is selected from the group consisting of colon cancer, stomach cancer, endometrial cancer, bile duct cancer, pancreatic cancer, and prostate cancer, and the cancer patient having a microsatellite instable cancer (MSI).SELECTED DRAWING: None

Description

[Technical field]

[0001] This invention was made with Government support under CA43460 and CA62924 awarded by the National Institutes of Health. The Government has certain rights in this invention.

[0002] TECHNICAL FIELD OF THEINVENTION The present invention relates to the field of cancer, and in particular to cancer therapy. [Background technology]

[0003] 2. Background of the Invention Microsatellite instability (MSI) is the accumulation of sequence errors in microsatellites. It occurs in tumors with defective DNA mismatch repair. MSI is present in Lynch syndrome, an inherited cancer syndrome that predisposes patients to colon, endometrial, gastric, ovarian, small intestine, liver, hepatobiliary, upper urinary tract, brain, and prostate cancers. MSI is also present in 10-20% of sporadic colorectal, gastric, prostate, lung, ampullary, and endometrial cancers. 0.3%-13% of pancreatic cancers have also been reported to be MSI.

[0004] The importance of intact immunological surveillance in controlling the by-products of malignant transformation has been known for decades. Accumulating evidence indicates a correlation between tumor infiltrating lymphocytes (TILs) in cancer tissues and good prognosis in various malignancies. Specifically, the appearance of CD8+ T cells and the ratio of CD8+ effector T cells / FoxP3+ regulatory T cells appear to correlate with improved prognosis and long-term survival in solid malignancies such as ovarian, colorectal, and pancreatic cancer, hepatocellular carcinoma, malignant MEL and RCC. TILs can be expanded ex vivo and reinfused to induce durable objective tumor responses in cancers such as melanoma.

[0005] PD-1 receptor-ligand interaction is a major pathway hijacked by tumors to suppress immune control. Under healthy conditions, the normal function of PD-1, expressed on the cell surface of activated T cells, is to downregulate unwanted or excessive immune responses, including autoimmune responses. Ligands for PD-1 (PD-L1 and PD-L2) can be constitutively expressed or induced in various tumors. Binding of either PD-1 ligand to PD-1 inhibits T cell activation triggered through the T cell receptor. PD-L1 is expressed at low levels in various non-hematopoietic tissues, most notably in vascular endothelium, while PD-L2 protein is detectably expressed only on antigen-presenting cells found in lymphoid tissues or in chronic inflammatory environments. PD-L2 is thought to control immune T cell activation in lymphoid organs, while PD-L1 plays a role in suppressing unwanted T cell function in peripheral tissues. It has been demonstrated that healthy organs express little (if any) PD-L1, whereas various cancers express sufficient levels of this T cell inhibitor. High expression of PD-L1 (and to a lesser extent PD-L2) in tumor cells has been found to correlate with poor prognosis and survival in various cancer types, including renal cell carcinoma (RCC), pancreatic cancer, hepatocellular carcinoma, ovarian cancer, and non-small cell lung cancer (NSCLC). Furthermore, PD-1 has been suggested to regulate the proliferation of tumor-specific T cells in patients suffering from malignant MEL. The observed correlation between PD-L1 expression and clinical prognosis in multiple cancers suggests that the PD-1 / PD-L1 pathway plays a key role in tumor immune evasion and should be considered as an attractive target for therapeutic intervention.

[0006] Blockade of immune checkpoints such as cytotoxic T-lymphocyte antigen-4 (CTLA-4) and programmed death-1 (PD-1) shows promise in patients suffering from cancer. CTLA-4 and PD-1 are upregulated in activated T cells and provide inhibitory signals to T cells undergoing activation. Blocking antibodies directed against these receptors have been shown to break immune tolerance and promote antitumor immunity. MK-3475 is a humanized monoclonal IgG4 antibody against PD-1 and shows activity in multiple tumor types including melanoma and non-small cell lung cancer (NSCLC). Previously, activity of a different PD-1 blocking antibody, BMS-936558, a fully humanized monoclonal IgG4 antibody, also showed activity in melanoma, NSCLC, and complete remission in one patient suffering from colorectal cancer.

[0007] MK-3475 (previously known as SCH 900475) is a potent and highly selective humanized mAb of the IgG4 / kappa isotype designed to directly block the interaction between PD-1 and its ligands PD-L1 and PD-L2. MK-3475 contains an S228P stabilizing mutation and has no antibody-dependent cell-mediated cytotoxicity (ADCC) or complement-dependent cytotoxicity (CDC) activity. MK-3475 robustly enhances T lymphocyte immune responses in cultured blood cells from healthy human donors, cancer patients, and primates. In T cell activation assays with human donor blood cells, the EC50 was in the range of 0.1-0.3 nM. MK-3475 also modulates levels of interleukin-2 (IL-2), tumor necrosis factor alpha (TNFα), interferon gamma (IFNγ), and other cytokines. Antibodies enhance an existing immune response only in the presence of antigen and do not nonspecifically activate T cells.

[0008] The programmed death 1 (PD-1) pathway is a negative feedback system that, if unregulated, represents a Th1 cytotoxic immune response that can damage the host. 1~3It is upregulated in many tumors and their surrounding microenvironments. Blockade of this pathway with antibodies against PD-1 or its ligands has shown striking responses in some patients with many different cancer types, including melanoma, non-small cell lung cancer, renal cell carcinoma, bladder cancer, and Hodgkin lymphoma. 4~10 Expression of ligands for PD-1 (PD-L1 or PD-L2) on the surface of tumor or immune cells is an important but not definitive predictive biomarker of response to PD-1 blockade. 4、6~8、11 .

[0009] We were intrigued to note that in a report of the effect of PD-1 blockade in human tumors, only 1 of 33 colorectal cancer (CRC) patients responded to this treatment, in contrast to a significant proportion of patients with melanoma, renal cell carcinoma, and lung tumors. 10、12 What is different about this single patient? We found that MMR deficiency is only seen in a small proportion of advanced CRCs. 13、14 Somatic mutations found in tumors cannot be recognized by the patient's own immune system. 15 MMR-deficient cancers have 10- to 100-fold more somatic mutations than MMR-proficient CRCs. 16~18 Therefore, we hypothesized that this patient was MMR deficient. Furthermore, MMR-deficient cancers contain prominent lymphocytic infiltrates, consistent with an immune response. 19~22 A study by Topalian et al. 10 Two of the tumor types most responsive to PD-1 blockade in humans had increased somatic mutations as a result of exposure to cigarette smoking (lung cancer) or ultraviolet radiation (melanoma) 23、24 Our hypothesis that the tumor of the single CRC patient who responded to PD-1 blockade was MMR-deficient was confirmed. 25 Therefore, we hypothesized that MMR-deficient tumors would be more responsive to PD-1 blockade than MMR-competent tumors.

[0010] To test this hypothesis, we have initiated a phase 2 clinical trial to evaluate immune checkpoint blockade in patients whose tumors do or do not have MMR deficiency. 26~28 In this study, we recruited patients with hereditary nonpolyposis colorectal cancer (HNPCC, also known as Lynch syndrome), which arises from a congenital germline deletion in one of the four MMR genes, followed by a second, inactivated somatic alteration of the remaining wild-type allele. We also recruited patients with sporadic MMR-deficient tumors, where both alleles of an MMR gene are inactivated by somatic mutation or by epigenetic silencing. 29 In either case, the resulting neoplasm harbors hundreds or even thousands of mutations. 16、18 .

[0011] There is a continuing need in the art to improve cancer treatments so that patients' lives are not shortened and their quality of life is not diminished. Summary of the Invention

[0012] According to one embodiment of the present invention, there is provided a method of treating a cancer patient, the cancer patient having a high mutational burden, such as that found in microsatellite unstable cancers (MSI), and an immune checkpoint inhibitor antibody is administered to the cancer patient.

[0013] According to another embodiment of the present invention, a method of treating a cancer patient is provided. A sample from a cancer patient is tested for one or more microsatellite markers selected from the group consisting of BAT-25, BAT-26, MON0-27, NR-21, NR-24, Penta C, and Penta D to determine that the cancer has microsatellite instability. The cancer is selected from the group consisting of colon cancer, gastric cancer, endometrial cancer, bile duct cancer, pancreatic cancer, and prostate cancer. An anti-PD-1 antibody is administered to the cancer patient.

[0014] According to another embodiment of the present invention, a method is provided for classifying human tumors. A sample from a human is tested to evaluate the stability of one or more microsatellite markers. Microsatellite instability is determined in the sample. The tumor is identified as a good candidate for treatment with an immune checkpoint inhibitor antibody.

[0015] According to yet another embodiment of the present invention, a method is provided for classifying a human tumor. A sample from the human is tested to assess the stability of one or more microsatellite markers. The microsatellite stability in the sample is determined. The tumor is identified as a poor candidate for treatment with an immune checkpoint inhibitor antibody.

[0016] These and other embodiments, which will become apparent to those of skill in the art upon reading this specification, provide the art with methods for treating microsatellite unstable cancers. [The present invention 1001] A method for treating a cancer patient, comprising administering an immune checkpoint inhibitor antibody to a cancer patient having microsatellite unstable cancer (MSI). [The present invention 1002] The method of claim 1001, wherein said cancer is selected from the group consisting of colon cancer, gastric cancer, endometrial cancer, bile duct cancer, pancreatic cancer, and prostate cancer. [The present invention 1003] The method of any one of claims 1 to 10, wherein said antibody is an anti-PD-1 antibody. [The present invention 1004] The method of any one of claims 1 to 10, wherein said antibody is an anti-IDO antibody. [The present invention 1005] The method of claim 10, wherein said antibody is an anti-CTLA-4 antibody. [The present invention 1006] The method of any one of claims 1 to 10, wherein the antibody is an anti-PD-L1 antibody. [The present invention 1007] 1001. The method of claim 10, wherein said antibody is an anti-LAG-3 antibody. [The present invention 1008] 1001. The method of claim 1001, wherein prior to said administering step, a sample from said MSI cancer patient is tested to assess the stability of one or more microsatellite markers. [The present invention 1009] The method of any one of claims 1 to 10, wherein said antibody is a humanized monoclonal antibody. [The present invention 1010] The method of any one of claims 1 to 10, wherein said antibody is MK-3475. [The present invention 1011] The method of claim 10, wherein said antibody is an IgG4 antibody. [The present invention 1012] The method of any one of claims 10 to 15, wherein a plurality of microsatellite markers are tested. [The present invention 1013] 1008. The method of claim 1008, wherein said one or more microsatellite markers are selected from the group consisting of BAT-25, BAT-26, MON0-27, NR-21, NR-24, Penta C, and Penta D. [The present invention 1014] The method of claim 1012, wherein the plurality of microsatellite markers comprises BAT-25, BAT-26, MON0-27, NR-21, NR-24, Penta C, and Penta D. [The present invention 1015] testing a sample from a cancer patient to determine instability of one or more microsatellite markers selected from the group consisting of BAT-25, BAT-26, MON0-27, NR-21, NR-24, Penta C, and Penta D; administering an anti-PD-1 antibody to the cancer patient; A method for treating a cancer patient, comprising: The method, wherein the cancer is selected from the group consisting of colon cancer, gastric cancer, endometrial cancer, bile duct cancer, pancreatic cancer, and prostate cancer. [The present invention 1016] 1. A method for classifying human tumors, comprising: testing a sample from said human to assess the stability of one or more microsatellite markers; determining microsatellite instability in said sample; and identifying the tumor as a good candidate for treatment with an immune checkpoint inhibitor antibody. [The present invention 1017] The method of any one of claims 10 to 16, further comprising administering to said human an immune checkpoint inhibitor antibody. [The present invention 1018] 1016. The method of claim 1016, wherein said one or more microsatellite markers are selected from the group consisting of BAT-25, BAT-26, MON0-27, NR-21, NR-24, Penta C, and Penta D. [The present invention 1019] 1016. The method of claim 1016, wherein said one or more microsatellite markers are selected from the group consisting of BAT-25, BAT-26, MON0-27, NR-21, NR-24, Penta C, and Penta D. [The present invention 1020] 1. A method for classifying human tumors, comprising: testing a sample from said human to assess the stability of one or more microsatellite markers; determining microsatellite stability in said sample; and identifying the tumor as a poor candidate for treatment with an immune checkpoint inhibitor antibody. [The present invention 1021] The method of claim 1020, wherein the human is being treated with an immune checkpoint inhibitor antibody, further comprising the step of stopping treatment with the immune checkpoint inhibitor antibody. [The present invention 1022] 1020. The method of claim 1020, wherein said one or more microsatellite markers are selected from the group consisting of BAT-25, BAT-26, MON0-27, NR-21, NR-24, Penta C, and Penta D. [The present invention 1023] 1020. The method of claim 1020, wherein said one or more microsatellite markers are selected from the group consisting of BAT-25, BAT-26, MON0-27, NR-21, NR-24, Penta C, and Penta D. [The present invention 1024] 1. A method of treating a cancer patient, comprising administering to the cancer patient having a mutational burden of at least 100 somatic mutations per tumor an immune checkpoint inhibitor antibody. [The present invention 1025] The method of claim 1024, wherein the antibody is an anti-PD-1 antibody. [The present invention 1026] The method of claim 1024, wherein said antibody is an anti-IDO antibody. [The present invention 1027] The method of claim 1024, wherein said antibody is an anti-CTLA-4 antibody. [The present invention 1028] The method of any one of claims 1 to 24, wherein the antibody is an anti-PD-L1 antibody. [The present invention 1029] The method of claim 1024, wherein said antibody is an anti-LAG-3 antibody. [The present invention 1030] The method of claim 1024, further comprising the step of determining a high mutational burden in said tumor prior to said administering step. [Brief description of the drawings]

[0017] [Figure 1]Clinical response to pembrolizumab. (Figure 1A) Biochemical response. Serum protein biomarker levels were measured at each cycle, and these values ​​represent the percent change from baseline. Patients were included if their baseline tumor marker values ​​were greater than the upper limit of normal. CA-125 was used for patients with endometrial cancer, CA19-9 was used for some cholangiocarcinomas and some ampullary carcinomas, and CEA was used for all other patients. The green, red, and black lines represent MMR-deficient CRC, MMR-competent CRC, and MMR-deficient non-CRC, respectively. (Figure 1B) Radiologic response. Tumor response was measured at regular intervals, and values ​​indicate the change in best fraction of the sum of longest diameters (SLD) from the baseline measurement for each measurable tumor. [Diagram 2] Clinical benefit to pembrolizumab according to MMR status. Kaplan-Meier curves are shown for (Figure 2A) progression-free survival in the colorectal cancer cohort, (Figure 2B) overall survival in the colorectal cancer cohort, (Figure 2C) progression-free survival in patients with MMR-deficient cancers other than colorectal (median PFS = 5.4 months, 95% confidence interval, 3% to not estimable), and (Figure 2D) overall survival in patients with MMR-deficient cancers other than colorectal. In both cohorts with MMR-deficient tumors (CRC and non-CRC), median overall survival was not reached. Patients in the cohort with MMR-competent cancers had a median PFS of 2.2 months (95% confidence interval 1.4 to 2.8%) and a median OS of 5.0 months (95% confidence interval 3.0 to not estimable). [Diagram 3] (Figure S2.) Spider plot of radiological response. Tumor response was measured at regular intervals and values ​​indicate the percent change in sum of longest diameters (SLD) from baseline measurement for each measurable tumor. Patients were included only if baseline and study treatment scans were available. Green and red represent patients with MMR-deficient and MMR-competent CRC, respectively. Blue represents patients with MMR-deficient cancers other than CRC. [Figure 4](Figure S3) MMR-competent and MMR-deficient CRC have comparable time to treatment and duration of metastatic disease prior to study enrollment. In this pembrolizumab study, Kaplan-Meier estimates of (Figure 4A) time on therapy immediately prior to study enrollment (HR 0.81, 95% CI 0.38-1.752, p=0.60) and (Figure 4B) duration of metastatic disease prior to enrollment (HR 1.13, 95% CI 0.49-2.62, p=0.78) were comparable between the MMR-deficient and MMR-competent CRC cohorts. A short period on upfront therapy is expected for the treatment-refractory CRC population. [Diagram 5] (Figure S4.) Waterfall plot of biochemical responses. Serum protein biomarker levels were measured at each cycle, and these values ​​represent the best percent change from baseline. Patients were included if their baseline tumor marker value was greater than the upper limit of normal. CA-125 was used for patients with endometrial cancer, CA19-9 was used for some cholangiocarcinomas and some ampullary cancers, and CEA was used for all other patients. Green and red represent patients with MMR-deficient and MMR-competent CRC, respectively. Blue represents patients with MMR-deficient cancers other than CRC. [Figure 6] (Figure S5.) Somatic mutations in MMR-deficient and MMR-competent tumors. Total somatic mutations per tumor identified by exome sequencing of tumor and matched normal DNA (Figure 6A) and correlation with objective response (Figure 6B) (nonparametric Wilcoxon test, p = 0.007, and Jonckheere-Terpstra trend test, p = 0.02). [Figure 7](Figure S6) Immunohistochemistry of CD8 and PD-L1 expression. Invasive zone (dashed yellow line) from MMR-deficient CRC (subject #16, top) and MMR-competent CRC (subject #3, bottom). Dashed yellow line separates tumor (T) from normal (N) tissue. There is prominent expression of PD-L1 (blue arrow) and CD8 (brown dot) in the patient with MMR-deficient tumor (top panel), whereas there is only faint expression of either marker in the MMR-competent tumor (bottom panel). Representative images of tumor-infiltrating lymphocytes (TILs) in another MMR-deficient CRC (subject #19, top) and MMR-competent CRC (subject #3, bottom) immunolabeled with antibody against CD8 (brown dot). Note the infiltration of CD8 cells in the MMR-deficient tumor. Original magnification of invasive zone 10x and TILs 20x. [Figure 8] (Figure S7.) CD8 and PD-L1 expression in the microenvironment of MMR-deficient and MMR-competent tumors. T cell density units are cells / mm2 (tumor). Deepest invasion refers to immune cells (TILs and macrophages) at the junction between tumor and normal tissue. P values ​​were obtained using unpaired t-test. [Figure 9] (Figure S8.) CD8 expression and clinical benefit to pembrolizumab. Correlation between intratumoral CD8+ T cell density (cells / mm2) and objective response (Jonckheere-Terpstra test, p=0.02). [Figure 10] (Table S1.) Comparison of immune-related and RECIST response criteria (Source: Wolchok et al. Clin Can Res 2009;15:7412-20.) [Figure 11] (Table S2.) Immune-related responses to treatment [Figure 12] (Table S4.) Correlation of total cell mutations and mutation-associated neoantigens (MANA) with clinical outcomes [Figure 13] (Table S5.) Correlation of immune markers and clinical outcomes DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0018] Detailed Description of the Invention The inventors have found that immune checkpoint inhibitors work best in tumors with high mutational burden. Furthermore, tumors with mismatch repair deficiencies are particularly susceptible to certain forms of immunotherapy, as this phenotype results in a high frequency of continuous accumulation of mutations. The inventors have developed a treatment for cancer patients who exhibit a microsatellite instability phenotype or other high mutational burden. The treatment includes an inhibitory antibody for an immune checkpoint. Such checkpoints include PD-1, IDO, CTLA-4, PD-L1, and LAG-3. Other immune checkpoints can also be used. The antibody can be administered by any convenient means, including, but not limited to, intravenous injection, oral administration, subcutaneous administration, sublingual administration, intraocular administration, intranasal administration, etc.

[0019] Microsatellite unstable (MSI) tumors are defective in DNA mismatch repair, which leads to high spontaneous mutation rates and the potential for the expression of neoantigens. In addition, like melanoma, there is often significant lymphocytic infiltration in MSI-positive colon cancers. Any tumor with MSI or otherwise high mutation load can be treated by the present invention. They can be tested for MSI attributes by any method known in the art, including but not limited to those described in Example 1 below. Any of one or more MSI markers can be tested to determine MSI phenotype. Samples can be tested for high mutation load by identifying tumors with at least 100, at least 200, at least 300, at least 400, at least 500, at least 600, at least 700, at least 800, at least 900, at least 1000, at least 1100, at least 1200, at least 1300, at least 1400, at least 1500, or at least 1600 mutations per tumor genome. High mutational burden refers to a large number of somatic mutations in a tumor compared to the normal tissue of an individual. The average number of somatic mutations in a non-MSI tumor is about 70 somatic mutations.

[0020] Any type of tumor that shows MSI phenotype or high mutation load can be tested and / or treated by the present invention.These include, but are not limited to, colon, stomach, endometrium, bile duct, pancreatic cancer, and prostate cancer.Glioma, breast, lung, skin, esophagus, liver, kidney, ovary, sarcoma, uterus, cervix, bladder, testis, oral cavity, tongue, and ampullary, bile duct, brain tumors, including small and large intestine, can also be tested and / or treated.

[0021] MSI testing can be accomplished by any means known in the art. One or more of the following markers can be tested: five nearly monomorphic mononucleotide repeat markers (BAT-25, BAT-26, MON0-27, NR-21, and NR-24) and two highly diverse pentanucleotide repeat markers (Penta C and Penta D). In one commercial system that can be used, fluorescently labeled primers (marker panel) are used to co-amplify all seven of the above named markers. Fragments are detected after amplification for genotype / phenotype assignment.

[0022] Samples that can be tested for MSI include tumor tissues and bodily fluids in which certain nucleic acids are excreted from tumors. Tests for tumor DNA in such tissues and fluids are well known.

[0023] The types of antibodies that can be used include any that have been developed against immune checkpoint inhibitors. They can be monoclonal or polyclonal. They can be single chain fragments or other fragments of complete antibodies, including those made by enzymatic cleavage or recombinant DNA technology. They can be of any isotype, including but not limited to IgG, IgM, IgE. The antibodies can be of any species origin, including human, goat, rabbit, mouse, bovine, chimpanzee. The antibodies can be humanized or chimeric. The antibodies can be conjugated or engineered to be bound to another moiety, whether a therapeutic or tracer molecule. The therapeutic molecule can be, for example, a toxin.

[0024] Data from a small phase 2 trial of pembrolizumab to treat MMR-deficient and -nondeficient tumors support the hypothesis that MMR-deficient tumors respond better to PD-1 blockade than MMR-competent tumors. MMR deficiency occurs in many cancers, including colorectal, uterine, gastric, biliary, pancreatic, ovarian, prostate, and small intestinal cancers. 18、34~42 Patients with these types of MMR-deficient tumors would also benefit from anti-PD-1 therapy, as their tumors may contain other DNA repair defects, such as those with mutations in POLD, POLE, or MYH. 18、43、44 .

[0025] The hypothesis that MMR-deficient tumors stimulate the immune system is not a new idea. 45 , supported by the dense immune infiltrate and Th1-associated cytokine-rich environment observed in MMR-deficient tumors. 19~22、46 Recent studies have refined these classical observations by showing that MMR-deficient tumor microenvironments robustly express several immune checkpoint ligands, including PD-1, PD-L1, CTLA-4, LAG-3, and IDO, indicating that their active immune microenvironment is counterbalanced by immune inhibitory signals that resist tumor clearance. 47The most plausible explanation for both the old and new ideas was that the immune infiltrate associated with MMR-deficient carcinomas was directed against a neoantigen. Anti-CTLA-4 in melanoma 41 and anti-PD-1 in lung cancer 48 The correlation of higher mutational burden and higher response rates to MANA provides further support for the idea that MANA recognition is a critical component of the endogenous antitumor immune response.

[0026] Based on the results of the current and previous studies, we suggest that the greatly (>20-fold) increased number of mutation-associated neoantigens resulting from MMR deficiency (Figure 12 (Table S4), also available online in the New England Journal of Medicine and incorporated herein by reference) is the basis for the enhanced anti-PD-1 responsiveness of some of these genetically defined cancers. Through our estimation of the number of mutation-associated neoantigens in tumors based solely on in silico predictions of binding affinity, this suggestion is consistent with the observation that MMR-competent tumors were much less infiltrated by lymphocytes than MMR-deficient tumors (Figure 7 (S6), Figure 8 (S7), and Figure 13 (Table S5), also available online in the New England Journal of Medicine and incorporated herein by reference). Recent studies 49、50 show that only a small proportion of predicted neoepitopes are actually presented on the MHC-bearing cell surface and are targets of endogenous T cell responses. Although the number of predicted mutation-associated neoantigens is proportional to the number of actual mutation-associated neoantigens, it seems more likely that tumors with an increase in actual mutation-associated neoantigens prime the immune system to react against the tumor. Alternative mechanisms underlying the difference in anti-PD-1 responsiveness between MMR-deficient and MMR-competent tumors should also be considered. For example, different signaling pathways activated in MMR-deficient and MMR-competent tumors may result in differences in the secretion of soluble factors that may result in differential activation of the PD-1 pathway within the tumor microenvironment. 26~28Genetic differences may alter the expression of tumor-associated self-antigens, as well as affect epigenetic differences that may alter tumor antigenicity. Experimental analysis of antigen-specific immune responses and changes in the immune microenvironment should help define the relative contributions of these factors to the striking responsiveness of MMR-deficient tumors to PD-1 antibodies.

[0027] Several noteworthy observations were made during the course of this study. First, changes in serum protein biomarkers such as CEA were consistent with clinical benefit after a single dose of the therapeutic agent. Reductions in CEA levels preceded objective radiological evidence by several months, and perhaps other biomarkers such as circulating tumor DNA (ctDNA) may also be useful as surrogate markers of early response. 51、52 Second, our results suggest that tumor genomic assessment may help inform immunotherapy decisions. They support the view that the number and type of surrogates may prove useful in determining the potential utility of immune checkpoint inhibitors, even in MMR-competent cancers. 41、48、53 Most importantly, our results demonstrate a novel approach to the treatment of specific tumor types based solely on genetic status, i.e., regardless of the underlying tumor type.

[0028] The above disclosure generally describes the present invention. All references disclosed herein are expressly incorporated by reference. A more complete understanding can be obtained by referring to the following specific examples, which are provided herein for illustrative purposes only and are not intended to limit the scope of the present invention. EXAMPLES

[0029] Example 1 MSI Testing MSI testing will be performed in an already standardized, CLIA-certified laboratory without the need for assay development. Archived tumor samples or newly obtained biopsies will be used to determine MSI. MSI status will be performed locally by CLIA-certified immunohistochemistry (IHC) or PCR-based testing for eligibility. Evaluable patients will be confirmed using the MSI Analysis System from Promega at Johns Hopkins. This test will determine MSI status through insertion or deletion of repeat units in five near-monomorphic mononucleotide repeat markers (BAT-25, BAT-26, MON0-27, NR-21, and NR-24). At least two MSI loci are required to be evaluable in cohorts A and C. Patients may be assigned to new cohorts and / or replaced based on the results of the Promega test.

[0030] Example 2 method patient Patients with treatment-refractory advanced metastatic cancer for this phase 2 study were recruited from three participating centers (Table 1). Three cohorts were evaluated: Cohort A consisted of patients with MMR-deficient colorectal adenocarcinoma, Cohort B consisted of patients with MMR-competent colorectal adenocarcinoma, and Cohort C consisted of patients with MMR-deficient cancers other than colorectal.

[0031] Research monitoring The protocol, which can be found at NEJM.org, was approved by the Institutional Review Boards at each site, and the study was conducted in accordance with the Declaration of Helsinki and the International Conference on Harmonization Guidelines for Good Clinical Practice. All patients provided written informed consent before study enrollment. The principal investigator (DL) and study sponsor (LAD) were involved in study oversight. Merck provided the study drug and reviewed the protocol and the final draft of this manuscript. The clinical study was primarily funded through philanthropic support.

[0032] research design This phase 2 study was conducted using a Green-Dahlberg two-stage design and consisted of three parallel cohorts as described above. The study drug, pembrolizumab (Merck), was administered intravenously at 10 mg / kg every 14 days. Pembrolizumab is a humanized monoclonal anti-PD-1 antibody of the IgG4 / kappa isotype that blocks the interaction between PD-1 and its ligands PD-L1 and PD-L2.

[0033] Safety assessments were performed before each treatment. Total tumor burden assessments were performed via serum biomarker measurements at the beginning of each cycle. Radiological assessments were performed at 12 weeks and every 8 weeks thereafter. Further details regarding the clinical protocol are provided in Example 3.

[0034] Analysis of mismatch repair status Tumors with genetic abnormalities in the MMR pathway are known to harbor thousands of somatic mutations, particularly in regions of repetitive DNA known as microsatellites. The accumulation of mutations in these regions of the genome is termed microsatellite instability (MSI). 26~28 MMR status was assessed in tumors using the MSI Analysis System from Promega through evaluation of selected microsatellite sequences that are prone to harboring errors when MMR is compromised.26~28 For further details, see additional appendices.

[0035] Genomic and bioinformatics analysis Primary tumor samples and matched normal peripheral blood specimens were obtained from subjects with MMR deficiency and a subset of subjects with MMR competent carcinomas, and sufficient tumor tissue was analyzed for exon sequencing. 30 and HLA haplotyping were available. To assess the potential for mutant peptide binding, somatic exon data together with individual patient MHC class I HLA haplotypes were applied to an epitope prediction algorithm. 31、32 This algorithm provided an estimate of the total number of mutation-associated neoantigens in each tumor. Further details are provided in an additional appendix (available online at the New England Journal of Medicine and incorporated herein by reference).

[0036] statistical analysis The primary endpoints in cohorts A and B were immune-related objective response rate (irORR) at 20 weeks, as assessed using immune-related response criteria (irRC), and immune-related progression-free survival (irPFS) rate. 33 The primary endpoint was irPFS rate at 20 weeks in cohort C. Immune-related criteria (i.e., the criteria used to evaluate immune-based therapies) are based on radiological response and, unlike RECIST criteria, capture the extent of disease after disease progression; these criteria are defined in Figure 10 (Table S1) and compared with RECIST v1.1. Response and PFS rates at 20 weeks were evaluated and reported in this study using RECIST v1.1 and irRC (Figure 10 (Table S1)). PFS and overall survival were summarized by the Kaplan-Meier method. Details of the hypotheses, decision rules for rejecting the null hypothesis and early stopping rules for efficacy and futility, and statistical methods are provided in additional appendices.

[0037] Example 3 How to refill patient To be eligible to participate in this study, patients must be at least 18 years of age and have histologically confirmed evidence of previously treated advanced cancer. All patients underwent testing for MMR status prior to enrollment. All patients had at least one measurable lesion as defined by Response Evaluation Criteria in Solid Tumors (RECIST), version 1.1, Eastern Cooperative Oncology Group (ECOG) performance score of 0 or 1, and adequate hematological, liver, and renal function. Eligible patients with CRC must have received at least two prior cancer therapies, and patients with other cancer types must have received at least one prior cancer therapy. Patients with untreated brain metastases, HIV, hepatitis B, hepatitis C, clinically significant ascites / effusion, or a history of autoimmune disease were excluded.

[0038] Research monitoring An initial draft of the manuscript was prepared by some of the authors and all authors contributing to the final manuscript. All authors decided to submit the manuscript for publication. The investigators and study sponsor guarantee the accuracy and completeness of the reported data and compliance with the protocol.

[0039] HLA typing HLA-A, HLA-B, and HLA-C sequence-based typing can be divided into three different steps, as follows: A generic, A*02 specific, B generic, B group specific, C generic and C*07 specific PCR and sequencing mix were done at the JHU core facility. Celera's Allele SEQR HLA-B sequence-based typing kit was used for the B generic SBT. The HLA-A typing scheme consists of two PCR reactions, A generic and A*02 specific. The A generic amplicon encompasses partial exon 1 to partial exon 5. The A*02 amplicon encompasses partial exon 1 to partial exon 5. The HLA-B typing scheme consists of two PCR reactions, B generic and B group specific. The B generic PCR is a multiplex reaction containing two PCR amplicons encompassing exon 2-exon 3 and exon 4-exon 7. The B group specific amplicon encompasses partial exon 1 to partial exon 5. The HLA-C typing scheme consists of two PCR reactions, C generic and C*07 specific. The C generic and C*07 specific amplicons encompass exons 1-7.

[0040] Specificity for HLA-A and B PCR was achieved using AmpliTaq Gold DNA polymerase. GeneAmp High Fidelity enzyme is used for HLA-C and C*07 PCR mix. This enzyme is a mix of two polymerases: AmpliTaq DNA polymerase (a non-proofreading polymerase) and a proofreading polymerase. This enzyme mix is ​​necessary to generate sufficient and robust amplification of the larger full-length HLA-C amplicon.

[0041] Purification of PCR products was performed using exonuclease I and shrimp alkaline phosphatase. A-generic and B-generic amplicons were sequenced bidirectionally to exons 2, 3, and 4. C-generic amplicons were sequenced bidirectionally to exons 2, 3, and unidirectionally to exons 1, 4, 5, 6, and 7. A*02-specific, B-group-specific, and C*07-specific amplicons were sequenced unidirectionally to exons 2, 3. All sequencing reactions were performed with Big Dye Terminator V1.1 from Applied Biosystems and sequenced on an ABI Prism 3500XL Genetic Analyzer. Data files were processed using Conexio Genomic's "Assign SBT" allele assignment software.

[0042] Mismatch repair status test 1、2 Six pieces of tumor and normal (non-involved lymph nodes or margin resections) were sectioned (5 microns each), deparaffinized (xylene), and one stained with hematoxylin and eosin (H+E). Tumor areas containing at least 20% tumor cells, as represented by a qualified anatomic pathologist, were macrodissected using the Pinpoint DNA Isolation System (Zymo Research, Irvine, CA), digested with proteinase K for 8 hours, and DNA was isolated using the QIAamp DNA Mini kit (Qiagen, Valencia, CA). MSI was assessed using the MSI Analysis System (Promega, Madison, WI), consisting of five pseudomonomorphic mononucleotide repeats (BAT-25, BAT-26, NR-21, NR-24, and MONO-27) to detect MSI and two-pentanucleotide repeat loci (PentaC and PentaD) to confirm identity between normal and tumor samples as per the manufacturer's instructions. After amplification of 50–100 ng of DNA, fluorescent PCR products were size-ordered in an Applied Biosystems 3130xl capillary electrophoresis instrument (Invitrogen, Calsbad, CA). Pentanucleotide loci were confirmed for identity in all cases. Controls included water as a negative control and a mixture of 80% germline DNA and 20% MSI cancer DNA as a positive control. Criterion sizes were determined for each microsatellite locus, and tumors were designated as MSI if two or more mononucleotide loci differed in length compared to germline DNA.

[0043] Sequencing analysis sample Samples provided as FFPE blocked or frozen tissue were pathologically reviewed to determine tumor cytoplasm. Tumors were macro-dissected to remove contaminating normal tissue, resulting in samples containing >20% tumor cells. Matched normal samples were provided as blood, saliva, or normal tissue obtained from surgery.

[0044] Sample preparation and next generation sequencing 3 Sample preparation, library construction, exome capture, next-generation sequencing, and bioinformatics analysis of tumor and normal samples were performed at Personal Genome Diagnostics, Inc. (Baltimore, Maryland). Briefly, DNA was extracted from frozen or formalin-fixed paraffin-embedded (FFPE) tissues along with matched blood or saliva samples using the Qiagen DNA FFPE Tissue Kit or Qiagen DNA Blood Mini Kit (Qiagen, CA). Genomic DNA from tumor and normal samples was sheared and used for Illumina TruSeq library construction (Illumina, San Diego, CA) according to the manufacturer's instructions or as previously described in 4. Briefly, 50 nanograms (ng) to 3 micrograms (μg) of genomic DNA in 100 microliters (μl) of TE was sheared to sizes of 150 to 450 bp with a Covaris sonicator (Covaris, Woburn, MA). To remove fragments shorter than 150 bp, DNA was purified twice with Agencourt AMPure XP beads (Beckman Coulter, IN) at a PCR product to beads ratio of 1.0 to 0.9 and washed with 70% ethanol according to the manufacturer's instructions. The purified, fragmented DNA was mixed with 36 μl H2O, 10 μl End Repair reaction buffer, and 5 μl End Repair enzyme mix (catalog number #E6050, NEB, Ipswich, MA). 100 μl of the end-repair mixture was incubated at 20°C for 30 minutes and purified with Agencourt AMPure XP beads (Beckman Coulter, IN) at a PCR product to beads ratio of 1.0 to 1.25 and washed with 70% ethanol according to the manufacturer's instructions. 42 μl of A-tailed end-repaired DNA was mixed with 5 μl of 10× dA Tailing reaction buffer and 3 μl of Klenow (exo-) (catalog no. #E6053, NEB, Ipswich, Mass.).The 50 μl mixture was incubated at 37° C. for 30 minutes and purified with Agencourt AMPure XP beads (Beckman Coulter, IN) at a 1.0 to 1.0 ratio of PCR product to beads and washed with 70% ethanol according to the manufacturer's instructions. For adapter ligation, 25 μl of A-tailed DNA was mixed with 6.7 μl H2O, 3.3 μl PE-adapters (Illumina), 10 μl 5X ligation buffer, and 5 μl Quick T4 DNA ligase (catalog no. #E6056, NEB, Ipswich, MA). The ligation mixture was incubated at 20° C. for 15 minutes and purified twice with Agencourt AMPure XP beads (Beckman Coulter, IN) at a 1.0 to 0.95 and 1.0 ratio of PCR product to beads and washed with 70% ethanol according to the manufacturer's instructions. To obtain the amplified library, twelve PCRs of 25 μl each were prepared, each containing 15.5 μl H2O, 5 μl 5× Phusion HF buffer, 0.5 μl dNTP mix containing 10 mM of each dNTP, 1.25 μl DMSO, 0.25 μl Illumina PE primer #1, 0.25 μl Illumina PE primer #2, 0.25 μl Hotstart Phusion polymerase, and 2 μl DNA. The PCR program used was 98° C. for 2 min, 12 cycles of 98° C. for 15 s, 65° C. for 30 s, 72° C. for 30 s, and 72° C. for 5 min. DNA was purified using Agencourt AMPure XP beads (Beckman Coulter, IN) at a ratio of 1.0:1.0 PCR product to beads and washed with 70% ethanol according to the manufacturer's instructions. Exomes or target regions were captured in solution using the Agilent SureSelect v.4 kit (Agilent, Santa Clara, CA) according to the manufacturer's instructions. The captured library was then purified with a Qiagen MinElute column purification kit and eluted in 17 μl of EB at 70° C. to obtain 15 μl of captured DNA library.(5) The captured DNA library was amplified in the following manner: eight 30 uL PCR reactions were prepared, each containing 19 μl H2O, 6 μl 5× Phusion HF buffer, 0.6 μl 10 mM dNTPs, 1.5 μl DMSO, 0.30 μl Illumina PE primer #1, 0.30 μl Illumina PE primer #2, 0.30 μl Hotstart Phusion polymerase, and 2 μl of the captured exome library. The PCR program used was 98°C for 30 s; 14 (exome) or 16 (target) cycles of 98°C for 10 s, 65°C for 30 s, and 72°C for 30 s; and 72°C for 5 min. To purify the PCR products, a NucleoSpin Extract II purification kit (Macherey-Nagel, PA) was used according to the manufacturer's instructions. Paired-end sequencing, obtaining 100 bases from each end of the fragment for the exome library and 150 bases from each end of the fragment for the targeted library, was performed using Illumina HiSeq 2000 / 2500 and Illumina MiSeq instruments (Illumina, San Diego, CA).

[0045] Primary processing of next-generation sequencing data and identification of putative somatic mutations3 Somatic mutations were identified using VariantDx custom software (Personal Genome Diagnostics, Baltimore, Maryland) to identify mutations in matched tumor and normal samples. Prior to mutation calling, primary processing of sequence data for both tumor and normal samples was performed using Illumina CASAVA software (v1.8), including masking of adapter sequences. Sequence reads were aligned to the human reference genome (version hg18) using ELAND, and further realignment of selected regions was performed using the Needleman-Wunsch method5. Candidate cellular mutations consisting of point mutations, insertions, and deletions were then identified across the whole exome or region of interest using VariantDx. VariantDx tests sequence alignment of tumor samples against matched normal samples, but applies filters to exclude alignment and sequencing artifacts. Briefly, alignment filters were applied to exclude poor quality reads, unpaired reads, and poorly mapped reads in tumors. A base quality filter was applied to restrict the inclusion of bases with a reported phred quality score of >30 for tumors and >20 for normals. Mutations in tumors were identified as candidate somatic mutations only if (i) a distinct pair of reads contained the tumor mutation, (ii) the number of distinct paired reads containing a particular mutation in the tumor was at least 10% of the read pairs, (iii) the mismatched base was not present in >1% of reads in the matched normal sample and was not present in a custom database of common germline variants from dbSNP, and (iv) the position was covered by both tumor and normal >150-fold. Mutations resulting from genomic alignments at the wrong position, including paralogous sequences, were identified and excluded by probing the reference genome.

[0046] Candidate somatic mutations were further filtered based on gene annotation to identify those occurring in protein-coding regions. Functional outcomes were predicted using snpEff and a custom database of CCDS, RefSeq, and Ensembl annotations using the latest transcript version in hg18 from UCSC (https: / / genome.ucsc.edu / ). The predictions directed preferred transcripts with canonical start and stop codons, and CCDS or Refseq transcripts across Ensembl, when available. Finally, mutations were filtered to exclude introns and silent changes, while the remaining mutations produced missense mutations, nonsense mutations, frameshifts, or splice site mutations. A manual visual inspection step was used to further eliminate artifactual changes.

[0047] Mutant peptide MHC binding prediction Somatic frameshift, insertion, deletion, and missense mutations predicted to result in amino acid changes were analyzed for MHC class I binding potential based on the individual patient's HLA haplotype. Our initial analysis focused on HLA-A and HLA-B. Amino acid mutations were linked to their corresponding CCDS accession numbers, and when this was not available, protein sequences were extracted using Refseq or ensemble transcripts. Amino acid fragments surrounding each mutation were identified to identify 8-mer, 9-mer, and 10-mer epitopes. These 15-, 17-, and 19-mutant amino acid fragments were analyzed by the epitope prediction program NetMHC 3.4.6. Epitopes with predicted affinities below 50 nm were considered to be strong potential binders, and epitopes with predicted affinities below 500 nm were considered to be weak potential binders, as suggested by NetMHC group 6.

[0048] To further refine the total neoantigen load, we repeated the same process with the complementary wild-type peptide for each mutant peptide. We then filtered for mutant peptides that were strong potential binders when the complementary wild-type peptide was predicted to be a weak potential binder. These mutant peptides are referred to as mutation-associated neoantigens (MANA). In cases where patients had a single MHC haplotype that was not supported by NetMHC 3.4 (e.g., cases 1, 17, and 21), the individual haplotype was not included in our analysis.

[0049] statistical methods test 7 Design This study was conducted using a parallel two-stage design to simultaneously evaluate the efficacy of MK-3475 and MSI as treatment selection markers for anti-PD-1 therapy. It consisted of a parallel two-stage phase 2 study in three cohorts of patients as described below. The study drug, MK-3475, was administered intravenously at 10 mg / kg every 14 days.

[0050] In each of cohorts A and B, the coprimary endpoint was progression-free survival (irPFS) at 20 weeks, and objective response (irOR) was assessed using immune-related criteria. A step-down gatekeeping procedure was used to preserve all type I errors. Using a two-stage Green-Dahlberg design, interim and final analyses evaluated irPFS in 15 and 25 patients, respectively. In stage 1, 1 or more of 15 progression-free at 20 weeks were required to proceed to stage 2, and 4 or more of 25 progression-free at 20 weeks were required to proceed to the trial for irOR, with 4 or more of 25 responders (irCR or irPR) indicating promising efficacy in that cohort. Each cohort could be terminated for efficacy as soon as 4 or more progressions were confirmed and 4 or more responses at 20 weeks, or for futility as soon as 0 of 15 in stage 1 were progression-free at 20 weeks or 22 or more subjects had disease progression at 20 weeks. This design achieves 90% power to detect an irPFS rate of 25% at 20 weeks and 80% power to detect an irOR rate (irORR) of 21%, with an overall type I error of 0.05 under the null hypotheses of 5% irPFS rate and 5% irORR at 20 weeks.

[0051] For cohort C, the primary endpoint was irPFS at 20 weeks. A two-stage Green-Dahlberg two-stage design was used with 14 and 21 patients after interim and final analyses, where in stage 1, 1 or more of 14 progression-free at 20 weeks was required to proceed to stage 2, and finally, 4 or more of 21 progression-free at 20 weeks demonstrated sufficient efficacy in cohort C. The cohort could be terminated as soon as 4 or more progression-free at 20 weeks were confirmed. This design has 81% power to detect an irPFS rate of 25% at 20 weeks and has a type I error of 5% under the null hypothesis of an irPFS rate of 5% at 20 weeks.

[0052] statistical analysis Response and progression were assessed using RECIST v1.1 and immune-related response criteria (irRC) adopted from Wolchok et al., which uses the sum of the products of two-dimensional tumor measurements and incorporates new lesions into this sum. Progression-free survival (PFS) and irPFS rates at 20 weeks were estimated as the proportion of patients who were disease progression-free and alive 20 weeks after initiation of pembrolizumab. Patients who had disease progression before 20 weeks or were enrolled for more than 20 weeks at the time study data were collated were included in this analysis to estimate the 20-week PFS (irPFS) rate. Patients who dropped out early due to toxicity or disease progression and therefore did not have a tumor assessment at 20 weeks were considered to have progressive disease. ORR (irORR) was the proportion of patients who achieved a best overall response of CR or PR (irCR or irPR). Patients who were on the study long enough to have a tumor response assessment were included in the analysis to estimate the response rate. Among responders (CR or PR), duration of response was the time from first RECIST response to disease progression, censored at last evaluable tumor assessment in responders who did not progress.

[0053] PFS and irPFS were defined as the time from the date of initial treatment to the date of disease progression or death from any cause, whichever occurred first. PFS and irPFS were censored at the date of the last evaluable tumor assessment documenting the absence of progressive disease for patients who were alive and progression-free. Overall survival (OS) was defined as the time from the date of initial treatment to the date of death from any cause. For patients who were still alive at the time of analysis, OS was censored at the last date the patient was known to be alive. Survival times were summarized by the Kaplan-Meier method. As a post hoc analysis, the log-rank test was used to compare cohorts A and B, and hazard ratios were estimated based on the Cox model.

[0054] The relationship between the decline in CEA rate after one cycle and PFS or OS was evaluated using landmark analyses based on Cox regression models. For correlation studies, the non-parametric Wilcoxon test was used to compare the mutation burden between MMR-deficient and MMR-competent patients. The effect of baseline mutation burden and immune markers on response and survival was tested using logistic and Cox regression, respectively.

[0055] Immunohistochemistry and image analysis The fraction of malignant cells, showing the membranous pattern of B7-H1 expression and the proportion at the invasive apex, was quantified by three pathologists (RAA, FB, and JMT) as previously reported9,10. Image analysis was used to determine the number of cells stained with diaminobenzidine (DAB) for CD8. For each case, H&E-stained slides were used to identify the following regions: i) tumor, ii) invasive apex (the border between malignant and non-malignant tissue), and iii) normal tissue. CD8-stained slides were scanned at 20x equivalent magnification (0.49 micrometers per pixel) on an Aperio ScanScope AT. Regions corresponding to tumor, invasive apex, and normal tissue (above, from H&E) were annotated on separate layers using Aperio ImageScope v12.1.0.5029.

[0056] CD8 positive lymphocyte density was calculated in each of the above regions using a custom algorithm implemented in PIP11. Results were converted to Deepzoom images using the VIPS library12 and visualized using the OpenSeadragon viewer (http: / / openseadragon.github.io).

[0057] References for Example 3 only TIFF2025065337000001.tif63161TIFF2025065337000002.tif234160

[0058] Example 4 patient Forty-one consecutive patients were enrolled and treated from September 2013 to January 2015 (Table 1). Recruitment included patients known to have tumors with mismatch repair or with tumors of unknown status and being tested in pursuit of an investigational option. One patient in the MMR-deficient CRC cohort was enrolled under an IRB eligibility waiver allowing for a grade 3 bilirubin level. A total of 32 CRC patients were enrolled in cohorts A and B. All CRC patients had received ≥2 prior chemotherapy regimens (median = 4), except for one MMR-competent patient who had received 1 chemotherapy and 1 (non-PD1-based) immunotherapy regimen.

[0059] Nine subjects diagnosed with MMR-deficient solid tumors other than CRC were enrolled in Cohort C. Patients in Cohort C received ≥1 prior chemotherapy regimen (median = 2).

[0060] Example 5 Evaluation of primary endpoint In cohort A, irORR and irPFS at 20 weeks (Figure S1(Table S2)) were 40% (4 of 10 patients; 95% CI, 12-74%) and 78% (7 of 9 patients; 95% CI, 40-97%), and in cohort C, 71% (5 of 7 patients; 95% CI, 29-96%) and 67% (4 of 6 patients; 95% CI, 22-96%). In cohort B, consisting of MMR-competent CRC, irORR and irPFS at 20 weeks were 0% (95% CI, 0-20%) and 11% (2 of 18 patients; 95% CI, 1-35%). Both MMR-deficient cohorts A and C reached their predefined early stopping rules in efficacy when 4 subjects were disease progression-free at 20 weeks and 4 objective responses were observed based on immune-related response criteria (Figure 11 (Table S2), available online at the New England Journal of Medicine and incorporated herein by reference, Supplementary Methods above).

[0061] The median follow-up for patients was 32 weeks (range, 5–51 weeks) for patients with MMR-deficient CRC (cohort A), 12 weeks (range, 2–56 weeks) for patients with MMR-competent CRC (cohort B), and 12 weeks (range, 4–42 weeks) for patients with MMR-deficient non-CRC tumors (cohort C). All patients evaluable for irPFS at 20 weeks were followed up for at least 20 weeks.

[0062] Example 6 Radiological evaluation Of the 10 evaluable MMR-deficient CRC patients in cohort A, 4 (40%; 95% confidence interval, 12-74%) achieved an objective response by RECIST criteria (Table 2, Figure 1, and Figure 3(S2)). Patients were considered non-evaluable if a 12-week scan was not performed. Disease control rate, defined as the proportion of patients who achieved an objective response and had stable disease, was 90% in cohort A (9 of 10 patients; 95% confidence interval, 55-100%).

[0063] Of the seven evaluable patients with MMR-deficient cancer types other than CRC enrolled in cohort C, five (71%; 95% confidence interval, 29–96%) achieved an objective response using RECIST criteria ( Table 2 , Fig. 3 (S2) and Fig. 1 ), with a disease control rate of 71% (five of seven patients; 95% confidence interval, 29–96%).

[0064] Patients in Cohort C responded faster than patients in Cohort A (median time to response by RECIST 12 vs. 28 weeks, p=0.03). Furthermore, all six MMR-deficient tumors (100%) that were not associated with Lynch syndrome achieved an objective response, whereas only three of eleven tumors (27%) that were associated with Lynch syndrome responded (Table S3, p=0.009, also available online in the New England Journal of Medicine and incorporated herein by reference). Other baseline characterizations showed no statistically significant association with objective response.

[0065] Among the 18 patients with MMR-competent CRC in cohort B, no objective responses using RECIST criteria were observed ( Table 2 , Fig. 3 (S2) and Fig. 1 ), with a disease control rate of 11% (2 of 18 patients; 95% confidence interval, 1–35%).

[0066] All patients who achieved a response by RECIST criteria (FIG. 11 (Table 2)) also achieved a response by immune-related response criteria (FIG. 11 (Table S2)).

[0067] Example 7 survival In cohort A, patients with MMR-deficient CRC did not reach median progression-free survival (PFS) and median overall survival (OS) (Figure 2). In contrast, patients with MMR-competent cancer in cohort B achieved a PFS of only 2.2 months (95% CI, 1.4 to 2.8) and a median OS of 5.0 months (95% CI, 3.0 to not estimable). In cohort C (MMR-deficient non-CRC), median PFS was 5.4 months (95% CI, 3 to not estimable) and median OS was not reached.

[0068] Post hoc ( Figure 2 ) comparison of cohorts with MMR-deficient and MMR-competent CRC showed a hazard ratio (HR) for disease progression (HR = 0.10, 95% CI, 0.03-0.37, p < 0.001) and overall survival (HR = 0.22, 95% CI, 0.05-1.00, p = 0.05) for candidate patients with MMR-deficient CRC.

[0069] To assess whether the difference in survival could be due to differences in prognosis, we measured the duration of time that patients had been diagnosed with metastatic disease, and the clinical outcomes of patients on their previous regimens prior to enrollment. We found no significant differences between patients with MMR-deficient versus MMR-competent CRC in terms of duration of metastatic disease (p=0.77, log-rank test) or median PFS (p=0.60, log-rank test) on patients' previous regimens (Figure 4(S3)). We also performed further multivariate analyses of PFS and OS to test for differences in outcomes between MMR-deficient CRC and MMR-competent tumors, adjusting for time since initial diagnosis. The magnitude of the hazard ratios for PFS (HR 0.04, 95% CI 0.01 to 0.21, P < 0.001) and OS (HR 0.18, 95% CI 0.03 to 1.01, P = 0.05), representing a differential effect of pembrolizumab between MMR-deficient and MMR-competent tumors, remained after adjusting for this potential difference.

[0070] Example 8 Safety assessment Adverse events occurring in >5% of patients are listed in Table 3. Selected adverse events included rash / pruritus (24%), thyroiditis / hypothyroidism / hypophysitis (10%), and subclinical pancreatitis (15%). Although fewer in number, thyroid function abnormalities were restricted to the MMR-deficient cohort (Table 3).

[0071] Example 9 Tumor markers In the two CRC cohorts, baseline CEA levels were evaluable and above the upper limit of normal (3 mg / dl) in 29 of the 32 patients prior to enrollment. Major CEA declines occurred in 7 of the 10 patients with MMR-deficient CRC and in none of the 19 patients with MMR-competent CRC in whom CEA was evaluable (Figure 1 and Figure 5(S4)). In non-CRC MMR-deficient patients, tumor marker levels (CEA, CA19-9 or CA-125) were elevated above the upper limit of normal in four patients. A decline in CA19-9 or CA-125 of more than 70% occurred in three of these four patients. Tumor marker kinetics for all three cohorts are shown in Figure 1. Decreasing levels of CEA after a single dose of pembrolizumab (days 14-28) predicted both progression-free (p=0.01) and overall survival outcomes (p=0.02). CEA responses occurred well before radiological confirmation of disease control (range, 10-35 weeks). In contrast, patients who progressed showed rapid biomarker elevation within 30 days of treatment. Hence, changes in CEA levels significantly preceded and correlated with final radiological changes.

[0072] Example 10 Genomic analysis Whole-exome sequencing revealed an average of 1,782 somatic mutations per tumor in MMR-deficient patients (n=9) compared with 73 mutations per tumor in MMR-competent patients (n=6) (nonparametric Wilcoxon test, p=0.007) (Figures 6A-6B (S5); see also Table S3, available online at the New England Journal of Medicine, incorporated herein by reference). The majority of these mutations (63%) are predicted to alter amino acids.

[0073] These mutations were then evaluated for their immunogenic potential in the context of each patient's individual MHC haplotype. Thereby, an average of 578 and 21 potential mutation-associated neoantigens were identified from tumors of MMR-deficient and MMR-competent patients, respectively (Table S3, available online in the New England Journal of Medicine and incorporated herein by reference). Among all somatic mutations, the proportion of potential mutation-associated neoantigens was similar in both cohorts (averaging 32% and 29% in MMR-deficient and MMR-competent patients, respectively). An increase in somatic mutations and mutation-associated neoantigens was associated with a trend in favor of improved progression-free survival and objective responses (Figure 13 (S5) and Figure 12 (Table S4), also available online in the New England Journal of Medicine and incorporated herein by reference).

[0074] Example 11 immunohistochemistry Expression of CD8 and PD-L1 was assessed by immunohistochemistry within the tumors and at the invasive depths of the tumors in 30 cases where tumor tissue was available (Figure 7 (S6), also available online at the New England Journal of Medicine and incorporated herein by reference). Tumors from patients in cohorts A and C contained a higher density of CD8-positive lymphocytes than tumors from patients in cohort B (Figure 8 (S7); p=0.10), and CD8 labeling tended to be associated with favorable objective responses and stable disease (Figure 9 (S8) and Figure 13 (Table S5), also available online at the New England Journal of Medicine and incorporated herein by reference). This CD8-positive lymphocyte infiltration was particularly prominent at the invasive depths of the tumors (Figure 8 (S7), p=0.04). Significant membrane PD-L1 expression occurred only in MMR-deficient patients and was prominent in tumor-infiltrating lymphocytes (TILs) and tumor-associated macrophages located at the deepest invasive part of the tumor (Fig. 8 (S7), p=0.04). CD8 and PD-L1 expression were not statistically associated with PFS or OS (Fig. 13 (Table S5)).

[0075] Table 1. Demographic and baseline characteristics of patients TIFF2025065337000003.tif186170MMR, mismatch repair; CRC, colorectal cancer 1 MMR-deficient versus MMR-competent CRC 2 ECOG, Eastern Cooperative Oncology Group

[0076] (Table 2) Objective RECIST responses TIFF2025065337000004.tif53170 1 Originally PR at 12 weeks, converted to CR at 20 weeks 2 1 PR in 12 weeks 3 Patients were considered unevaluable if they did not have a 12-week scan due to clinical progression. 4 Disease control rate was defined as the proportion of patients who had a complete response, partial response, or stable disease for ≥12 weeks. 5 No documented responses for MMR-competent CRC patients

[0077] Table 3: Drug-related adverse events TIFF2025065337000005.tif175158 1 Adverse events occurring in >5% of patients 2 All cases of pancreatitis were asymptomatic. 3 One pneumonia event occurred (2%)

[0078] References The disclosure of each reference mentioned is expressly incorporated herein. TIFF2025065337000006.tif204146TIFF2025065337000007.tif224147TIFF2025065337000008.tif244147TIFF2025065337 000009.tif244147TIFF2025065337000010.tif244147TIFF2025065337000011.tif234147TIFF2025065337000012.tif94145

Claims

1. 1. A pharmaceutical composition for administration to a cancer patient to treat the cancer patient, the cancer patient having a microsatellite unstable cancer (MSI), comprising an immune checkpoint inhibitor antibody.

2. 2. The pharmaceutical composition of claim 1, wherein the cancer is selected from the group consisting of colon cancer, gastric cancer, endometrial cancer, bile duct cancer, pancreatic cancer, and prostate cancer.

3. The pharmaceutical composition of claim 1, wherein the antibody is an anti-PD-1 antibody.

4. The pharmaceutical composition of claim 1 , wherein the antibody is an anti-IDO antibody.

5. The pharmaceutical composition of claim 1, wherein the antibody is an anti-CTLA-4 antibody.

6. The pharmaceutical composition of claim 1, wherein the antibody is an anti-PD-L1 antibody.

7. The pharmaceutical composition of claim 1, wherein the antibody is an anti-LAG-3 antibody.

8. The pharmaceutical composition of claim 1, wherein prior to said administration, a sample from said MSI cancer patient has been tested to assess the stability of one or more microsatellite markers.

9. The pharmaceutical composition of claim 1 , wherein the antibody is a humanized monoclonal antibody.

10. The pharmaceutical composition of claim 1, wherein the antibody is MK-3475.

11. The pharmaceutical composition of claim 1 , wherein the antibody is an IgG4 antibody.

12. The pharmaceutical composition of claim 8, wherein the microsatellite marker is a plurality of microsatellite markers.

13. 9. The pharmaceutical composition of claim 8, wherein the one or more microsatellite markers are selected from the group consisting of BAT-25, BAT-26, MON0-27, NR-21, NR-24, Penta C, and Penta D.

14. 13. The pharmaceutical composition of claim 12, wherein the plurality of microsatellite markers comprises BAT-25, BAT-26, MON0-27, NR-21, NR-24, Penta C, and Penta D.

15. 1. A pharmaceutical composition for administration to a cancer patient to treat the cancer patient comprising an anti-PD-1 antibody, wherein a sample from the cancer patient has been tested to determine instability of one or more microsatellite markers selected from the group consisting of BAT-25, BAT-26, MON0-27, NR-21, NR-24, Penta C, and Penta D, and wherein the cancer is selected from the group consisting of colon cancer, gastric cancer, endometrial cancer, bile duct cancer, pancreatic cancer, and prostate cancer.

16. 1. A method for classifying human tumors, comprising: testing a sample from said human to assess the stability of one or more microsatellite markers; determining microsatellite instability in said sample; and identifying the tumor as a good candidate for treatment with an immune checkpoint inhibitor antibody.

17. 17. The method of claim 16, which aids in the decision to prescribe an immune checkpoint inhibitor antibody to the human.

18. 17. The method of claim 16, wherein the one or more microsatellite markers are selected from the group consisting of BAT-25, BAT-26, MON0-27, NR-21, NR-24, Penta C, and Penta D.

19. 1. A method for classifying human tumors, comprising: testing a sample from said human to assess the stability of one or more microsatellite markers; determining microsatellite stability in said sample; and identifying the tumor as a poor candidate for treatment with an immune checkpoint inhibitor antibody.

20. 20. The method of claim 19, wherein the method aids in the decision to stop treatment with an immune checkpoint inhibitor antibody if the human is being treated with an immune checkpoint inhibitor antibody.

21. 20. The method of claim 19, wherein the one or more microsatellite markers are selected from the group consisting of BAT-25, BAT-26, MON0-27, NR-21, NR-24, Penta C, and Penta D.

22. 1. A pharmaceutical composition for administration to a cancer patient to treat the cancer patient, the pharmaceutical composition comprising an immune checkpoint inhibitor antibody, wherein the cancer patient has a mutational burden of at least 100 somatic mutations per tumor.

23. The pharmaceutical composition of claim 22, wherein the antibody is an anti-PD-1 antibody.

24. 23. The pharmaceutical composition of claim 22, wherein the antibody is an anti-IDO antibody.

25. The pharmaceutical composition of claim 22, wherein the antibody is an anti-CTLA-4 antibody.

26. The pharmaceutical composition of claim 22, wherein the antibody is an anti-PD-L1 antibody.

27. The pharmaceutical composition of claim 22, wherein the antibody is an anti-LAG-3 antibody.

28. 23. The pharmaceutical composition of claim 22, wherein a high mutational burden in the tumor has been determined prior to said administration.

Images