Methods for improving prediction of response in cancer patients treated with immunotherapy

Abstract

Provided herein are methods for determining a treatment regimen in a cancer patient, comprising determining tumor mutation burden (TMB) and loss of heterozygosity (LOH) in a sample from the patient, wherein a high TMB in combination with no LOH indicates a positive outcome when treated with a checkpoint inhibitor, and a high TMB with LOH indicates a poor outcome. TIFF2022513068000007.tif120163

Description

[Technical field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims the benefit of priority under 35 U.S.C. §119(e) to U.S. Application No. 62 / 767,979, filed November 15, 2018, which is incorporated by reference in its entirety.

[0002] FIELD OF THEINVENTION The present invention relates generally to cancer and immunotherapy, and more specifically to the analysis of loss of heterozygosity (LOH) in combination with tumor mutation burden (TMB) to select effective cancer therapies. [Background technology]

[0003] Background information Cancer is characterized by the proliferation of abnormal cells. The success of conventional treatments depends on the type of cancer and the stage at which it is detected. Many treatments involve expensive and painful surgery and chemotherapy, and many are unsuccessful or only slightly extend the patient's life. Promising treatment methods under development include tumor vaccines or T-cell therapy that target tumor antigens that enable the patient's immune system to distinguish between tumor cells and healthy cells and elicit an immune response in the patient. See Chen, et al., Oncology Meets Immunology: The Cancer-Immunity Cycle, Immunity 39, Jul. 25, 2013 (Non-Patent Document 1), the contents of which are incorporated herein in their entirety for all purposes.

[0004] Neoantigens are a type of immunogen associated with tumor-specific mutations unique to a patient's cancer. Neoantigens have been shown to be promising targets for antitumor immune techniques, including adoptive T cell transfer using tumor-infiltrating lymphocytes (TILs), cancer vaccines, and checkpoint inhibitors. See Hacohen, et al., Getting Personal with Neoantigen-Based Therapeutic Cancer Vaccines, Cancer Immunol Res, July 2013 1,11 (Non-Patent Document 2); Robbins, et al., Mining exomic sequencing data to identify mutated antigens recognized by adoptively transferred tumor-reactive T cells, Nature Medicine 19,747-752(2013) (Non-Patent Document 3), the contents of each of which are incorporated herein in their entirety for all purposes.

[0005] The receptor-ligand interaction of PD-1 is the major pathway hijacked by tumors to suppress immune regulation. The normal function of PD-1, which is expressed on the cell surface of activated T cells in healthy conditions, is to downregulate unwanted or excessive immune responses, including autoimmune responses. The ligands of 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 receptor-triggered T cell activation. PD-L1 is expressed at low levels in various non-hematopoietic tissues, most notably on 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 incorrect T cell function in peripheral tissues. Healthy organs express little, if any, PD-L1, whereas various cancers have been demonstrated to express abundant levels of this T cell inhibitor. High expression of PD-L1 (and to a lesser extent PD-L2) on tumor cells has been found to correlate with poor prognosis and survival in various types of cancer, including renal cell carcinoma (RCC), pancreatic carcinoma, hepatocellular carcinoma, ovarian carcinoma, and non-small cell lung cancer (NSCLC). Furthermore, PD-1 has been suggested to regulate tumor-specific T cell expansion in patients with malignant MEL. The observed correlation of PD-L1 expression with 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] Many tumor cells survive due to a suppressed immune response that prevents the destruction of tumor cells. This may be overcome during treatment with checkpoint inhibitors. Checkpoint inhibitors act by blocking the interaction of checkpoint receptors with their cognate ligands. Tumor mutation burden (TMB) serves as a surrogate marker of immune response, as it provides a readout for altered proteins that should be recognized by the immune system but are not due to a suppressed immune response by the tumor. TMB is measured through a sampling region of the cancer genome to estimate the number of mutations / Mb. A high TMB score may be associated with a better response to immunotherapy, as the tumor harbors more somatic mutations and has more opportunities to present immunogenic neoepitopes. However, not all high TMB tumors are affected by treatment, limiting the utility of TMB as a biomarker for responsiveness to checkpoint inhibitors.

[0007] The limited utility of TMB as a biomarker may be due to the fact that not all somatic mutations become neoantigens (Miller A et al. High somatic mutation and neoantigen burden are correlated with decreased progression-free survival in multiple myeloma. Blood Cancer J. 7, e612 (2017) doi:10.1038 / bcj.2017.94 (Non-Patent Document 4)). Potential neoantigens have been defined for each mutation and MHC haplotype combination, with an IC of less than 500 nM. 50 is WT and IC > 500 nM 50are variants. Moreover, the prediction of neoantigens for the same mutation is different for each MHC class I haplotype. As an example, an analysis of multiple myeloma in the COMPASS study (Miller A et al. High somatic mutation and neoantigen burden are correlated with decreased progression-free survival in multiple myeloma. Blood Cancer J. 7, e612 (2017) doi: 10.1038 / bcj.2017.94 (Non-Patent Document 4)) showed 63.9 missense mutations, 23.5 neoantigens, and 9.4 expressed neoantigens per patient.

[0008] Loss of heterozygosity (LOH) of MHC class I occurs in some tumors. The LOH frequency of the MHC region on chromosome 6p21 has been reported to be 70% in squamous cell head and neck cancer, 96% in breast carcinoma, 87% in colon carcinoma, 39% in pancreatic cancer, and 63% in melanoma (Garrido F and Algarra I. MHC antigens and tumor escape from immune surveillance. Adv Cancer Res. 2001; 83: 117-58 (Non-Patent Document 5)). The LOH frequency of the B2M region on chromosome 15q21 has been reported to be 35% in colon carcinoma, 16% in melanoma, 44% in bladder cancer, and 7% in kidney cancer (Maleno I. et al. Frequent loss of heterozygosity in the β2-microglobulin region of chromosome 15 in primary human tumors. Immunogenetics. 2011 Feb;63(2):65-71 (Non-Patent Document 6)). LOH at the MHC and B2M loci correlates with shorter survival in patients treated with checkpoint inhibitors (Chowell, D., et al. Patient HLA class I genotype influences cancer response to checkpoint blockade immunotherapy. Science 359:582-587, 2018 (Non-Patent Document 7); Sade-Feldman, M., et al., Resistance to checkpoint blockade therapy through inactivation of antigen presentation. Nature Communications 8:1136-1147, 2017 (Non-Patent Document 8)).Furthermore, HLA haplotypes influence the survival of patients treated with checkpoint inhibitors; for example, the hazard ratio for B44 and B62 HLA supertypes differs by 3.7-fold (Chowell, D., et al. Patient HLA class I genotype influences cancer response to checkpoint blockade immunotherapy. Science 359:582-587, 2018 (Non-Patent Document 7)).

[0009] Therefore, there is a need to predict the outcome of immunotherapy treatment based on the complexity of factors influencing the immune response in cancer, which can be useful in determining treatment regimens and selecting patients for treatment. [Prior art documents] [Non-patent literature]

[0010] [Non-Patent Document 1] Chen,et al.,Oncology Meets Immunology:The Cancer-Immunity Cycle,Immunity 39,Jul.25,2013 [Non-Patent Document 2] Hacohen,et al.,Getting Personal with Neoantigen-Based Therapeutic Cancer Vaccines,Cancer Immunol Res,July 2013 1,11 [Non-Patent Document 3] Robbins, et al., Mining exomic sequencing data to identify mutated antigens recognized by adoptively transferred tumor-reactive T cells, Nature Medicine 19,747-752(2013) [Non-Patent Document 4] Miller A et al.High somatic mutation and neoantigen burden are correlated with decreased progression-free survival in multiple myeloma.Blood Cancer J.7,e612(2017)doi:10.1038 / bcj.2017.94 [Non-Patent Document 5] Garrido F and Algarra I.MHC antigens and tumor escape from immune surveillance.Adv Cancer Res.2001;83:117-58 [Non-Patent Document 6] Maleno I.et al.Frequent loss of heterozygosity in the β2-microglobulin region of chromosome 15 in primary human tumors.Immunogenetics.2011 Feb;63(2):65-71 [Non-Patent Document 7] Chowell,D.,et al.Patient HLA class I genotype influences cancer response to checkpoint blockade immunotherapy.Science 359:582-587,2018 [Non-Patent Document 8] Sade-Feldman,M.,et al.,Resistance to checkpoint blockade therapy through inactivation of antigen presentation.Nature Communications 8:1136-1147,2017 Summary of the Invention

[0011] The methods provided herein are based on the seminal discovery that HLA loss of heterozygosity (LOH) status in combination with tumor mutation burden (TMB) score improves the prediction of response in cancer patients treated with checkpoint inhibitors. The inventors have previously shown that using a 507 gene tissue panel, LOH in MHC regions can be discovered and reliably detected without whole exome sequencing. Whereas previously it was believed that if a patient has high TMB, they are a responder to checkpoint therapy, the present invention shows that if a patient has TMB and also has LOH in MHC regions, they may not actually be a responder to checkpoint inhibitor therapy, and in some cases should not be administered checkpoint inhibitors. Based on the present invention, patient survival outcomes can be significantly improved.

[0012] In some embodiments, provided herein is a method for determining a treatment regimen in a cancer patient, comprising determining tumor mutation burden (TMB) and loss of heterozygosity (LOH) in a sample from the patient, where a combination of high TMB with no LOH indicates a positive outcome when treated with a checkpoint inhibitor, and high TMB with LOH indicates a poor outcome. In some embodiments, the cancer is a tumor. In some embodiments, the sample is from blood, saliva, plasma, serum, urine, or other biological fluid. In some embodiments, the sample is from a tumor. In some embodiments, LOH is determined within a region adjacent to or including an MHC class I gene. In some embodiments, LOH is determined within a region of the B2M gene. In some embodiments, the cancer is selected from breast cancer, pancreatic cancer, lung cancer, melanoma, hematopoietic cancer and leukemia, colon cancer, kidney cancer, head and neck cancer, brain cancer, bone cancer, ovarian cancer, cervical cancer, and prostate cancer. In some embodiments, the checkpoint inhibitor is pembrolizumab (KEYTRUDA), nivolumab (OPDIVO), atezolizumab (TECENTRIQ), or ipilimumab (YERVOY). To One or more exomes from which it is derived or that area In some embodiments, the tumor mutation comprises a neoantigen or neoepitope recognized by T cells.

[0013] In some embodiments, provided herein is a method for selecting a cancer patient for treatment with a checkpoint inhibitor, comprising selecting the patient for treatment with a checkpoint inhibitor when a sample obtained from the patient has high tumor mutation burden (TMB) without loss of heterozygosity (LOH). In some embodiments, the combination of high TMB with no LOH indicates a positive outcome when treated with a checkpoint inhibitor, and high TMB with LOH indicates a poor outcome. In some embodiments, the sample is a tumor sample. In some embodiments, the sample is from blood, saliva, plasma, serum, urine, or other biological fluid. In some embodiments, the LOH is within a region adjacent to or including an MHC class I gene. In some embodiments, the LOH is within a region of the B2M gene. In some embodiments, the cancer is selected from breast cancer, pancreatic cancer, lung cancer, melanoma, hematopoietic cancer and leukemia, colon cancer, kidney cancer, head and neck cancer, brain cancer, bone cancer, ovarian cancer, cervical cancer, and prostate cancer. In some embodiments, the checkpoint inhibitor is pembrolizumab (KEYTRUDA), nivolumab (OPDIVO), atezolizumab (TECENTRIQ), avelumab (BAVENCIO), durvalumab (IMFINZI), or ipilimumab (YERVOY). To One or more exomes from which it is derived or that area In some embodiments, the tumor mutation comprises a neoantigen or neoepitope recognized by T cells.

[0014] In some embodiments, provided herein is a method of treating a cancer patient, comprising: (i) selecting the patient for treatment with a checkpoint inhibitor when a sample obtained from the patient has high tumor mutation burden (TMB) without loss of heterozygosity (LOH); and (ii) administering an effective amount of a checkpoint inhibitor to the patient. In some embodiments, the combination of high TMB with no LOH indicates a positive outcome when treated with a checkpoint inhibitor, and high TMB with LOH indicates a poor outcome. In some embodiments, the sample is a tumor sample. In some embodiments, the sample is derived from blood, saliva, plasma, serum, urine, or other biological fluid. In some embodiments, the LOH is within a region adjacent to or including an MHC class I gene. In some embodiments, the LOH is within a region of the B2M gene. In some embodiments, the cancer is selected from breast cancer, pancreatic cancer, lung cancer, melanoma, hematopoietic cancer and leukemia, colon cancer, kidney cancer, head and neck cancer, brain cancer, bone cancer, ovarian cancer, cervical cancer, and prostate cancer. In some embodiments, the checkpoint inhibitor is pembrolizumab (KEYTRUDA), nivolumab (OPDIVO), atezolizumab (TECENTRIQ), avelumab (BAVENCIO), durvalumab (IMFINZI), avelumab (BAVENCIO), durvalumab (IMFINZI), or ipilimumab (YERVOY). In some embodiments, the determination of TMB and LOH comprises sequencing one or more exomes or regions thereof from the sample. In some embodiments, the tumor mutation comprises a neoantigen or neoepitope recognized by T cells. [The present invention 1001] 1. A method for determining a treatment regimen in a cancer patient, comprising determining tumor mutation burden (TMB) and loss of heterozygosity (LOH) in a sample from the patient, wherein a combination of high TMB with no LOH indicates a positive outcome when treated with a checkpoint inhibitor, and high TMB with LOH indicates a poor outcome. [The present invention 1002] The method of claim 1001, wherein the cancer is a tumor. [The present invention 1003] The method of any one of claims 1 to 10, wherein said sample is derived from blood, saliva, plasma, serum, urine, or other biological fluid. [The present invention 1004] The method of claim 10, wherein said sample is derived from a tumor. [The present invention 1005] 1001. The method of claim 1001, wherein said LOH is determined within a region adjacent to or including an MHC class I gene. [The present invention 1006] 1002. The method of claim 1001, wherein said LOH is determined within the region of the B2M gene. [The present invention 1007] The method of claim 1001, wherein said cancer is selected from breast cancer, pancreatic cancer, lung cancer, melanoma, hematopoietic cancer and leukemia, colon cancer, kidney cancer, head and neck cancer, brain cancer, bone cancer, ovarian cancer, cervical cancer, endometrial cancer, and prostate cancer. [The present invention 1008] The method of claim 1001, wherein the checkpoint inhibitor is pembrolizumab (KEYTRUDA), nivolumab (OPDIVO), atezolizumab (TECENTRIQ), or ipilimumab (YERVOY). [The present invention 1009] The method of claim 10, wherein said determining step comprises sequencing one or more exomes or regions thereof from said sample. [The present invention 1010] The method of claim 1001, wherein the tumor mutation comprises a neoantigen or neoepitope recognized by T cells. [The present invention 1011] 1. A method for selecting a cancer patient for treatment with a checkpoint inhibitor, the method comprising the step of selecting the patient for treatment with the checkpoint inhibitor if a sample obtained from the patient has high tumor mutation burden (TMB) in the absence of loss of heterozygosity (LOH). [The present invention 1012] The method of claim 1011, wherein a combination of high TMB without LOH indicates a positive outcome when treated with said checkpoint inhibitor, and high TMB with LOH indicates a poor outcome. [The present invention 1013] The method of claim 1011, wherein the sample is a tumor sample. [The present invention 1014] The method of any one of claims 10 to 11, wherein the sample is derived from blood, saliva, plasma, serum, urine, or other biological fluid. [The present invention 1015] The method of any one of claims 1 to 10, wherein said LOH comprises a region adjacent to or including an MHC class I gene. [The present invention 1016] The method of any one of claims 1 to 10, wherein the LOH comprises a region of the B2M gene. [The present invention 1017] The method of claim 1011, wherein said cancer is selected from breast cancer, pancreatic cancer, lung cancer, melanoma, hematopoietic cancer and leukemia, colon cancer, kidney cancer, head and neck cancer, brain cancer, bone cancer, ovarian cancer, cervical cancer, endometrial cancer, and prostate cancer. [The present invention 1018] The method of the present invention, wherein the checkpoint inhibitor is pembrolizumab (KEYTRUDA), nivolumab (OPDIVO), atezolizumab (TECENTRIQ), avelumab (BAVENCIO), durvalumab (IMFINZI), or ipilimumab (YERVOY). [The present invention 1019] The method of any one of claims 10 to 11, wherein determining TMB and LOH comprises sequencing one or more exomes or regions thereof from said sample. [The present invention 1020] The method of claim 1011, wherein the tumor mutation comprises a neoantigen or neoepitope recognized by T cells. [The present invention 1021] 1. A method of treating a cancer patient, comprising: (i) selecting the patient for treatment with a checkpoint inhibitor if a sample obtained from the patient has high tumor mutation burden (TMB) in the absence of loss of heterozygosity (LOH); (ii) administering to the patient an effective amount of the checkpoint inhibitor; A method comprising: [The present invention 1022] The method of the present invention 1021, wherein a combination of no LOH and high TMB indicates a positive outcome when treated with said checkpoint inhibitor, and high TMB with LOH indicates a poor outcome. [The present invention 1023] The method of claim 1021, wherein the sample is a tumor sample. [The present invention 1024] The method of claim 1021, wherein said sample is derived from blood, saliva, plasma, serum, urine, or other biological fluid. [The present invention 1025] The method of any one of claims 10 to 12, wherein the LOH comprises a region adjacent to or including an MHC class I gene. [The present invention 1026] The method of any one of claims 1 to 21, wherein the LOH comprises a region of the B2M gene. [The present invention 1027] The method of claim 1021, wherein the cancer is selected from breast cancer, pancreatic cancer, lung cancer, melanoma, hematopoietic cancer and leukemia, colon cancer, kidney cancer, head and neck cancer, brain cancer, bone cancer, ovarian cancer, cervical cancer, endometrial cancer, and prostate cancer. [The present invention 1028] The method of the present invention 1021, wherein the checkpoint inhibitor is pembrolizumab (KEYTRUDA), nivolumab (OPDIVO), atezolizumab (TECENTRIQ), avelumab (BAVENCIO), durvalumab (IMFINZI), avelumab (BAVENCIO), durvalumab (IMFINZI), or ipilimumab (YERVOY). [The present invention 1029] The method of claim 1021, wherein determining TMB and LOH comprises sequencing one or more exomes or regions thereof from said sample. [The present invention 1030] The method of claim 1021, wherein the tumor mutation comprises a neoantigen or neoepitope recognized by T cells. [Brief description of the drawings]

[0015] [Figure 1] 1 illustrates different scenarios of loss of heterozygosity for MHC class I. [Figure 2A] 1 shows an analysis of allele frequencies across chromosomal loci for detecting MHC heterozygosity. [Figure 2B] 1 shows an analysis of allele frequencies across chromosomal loci for detecting MHC heterozygosity. [Figure 3A] 4 shows the distribution of tumor purity of specimens used for validation of the method to detect MHC class I LOH. [Figure 3B] 1 shows an analysis of tumor purity in samples with mismatched MHC status between whole exome sequencing (WES) and PGDx elio™ tissue complete (Wolverine). [Figure 4] Figure 1 shows the in silico correlation of TMB and MHC status with clinical outcome in NSCLC patients. [Diagram 5]Single and double hits in maternal and paternal MHC alleles are shown. [Figure 6] The correlation between allele frequencies and heterozygosity is shown. [Figure 7] The MHC region on chromosome 6p21 is shown. [Figure 8] A pilot assessment of heterozygosity near the MHC genes in several samples, including those with and without potential LOH of the MHC, is shown. [Figure 9] 1 shows confirmation of LOH signals found with PGDx elio™ complete (Wolverine) by exome data. [Figure 10A] 1 shows that MHC LOH for PGRD00426 is tumor compartment specific. [Figure 10B] 1 shows that MHC LOH for PGRD00426 is tumor compartment specific. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] Detailed Description of the Invention For example, interpretation of the TMB score as a biomarker for immunotherapy, such as treatment with checkpoint inhibitors, can only be accurate if the patient has a functional immune system. + Without the ability to present to T cells, high mutational burden (TMB) is irrelevant to immunotherapy and does not accurately predict responsiveness to immunotherapy.

[0017] In some embodiments, provided herein is a method for determining a treatment regimen in a cancer patient, comprising determining tumor mutation burden (TMB) and loss of heterozygosity (LOH) in a sample from the patient, wherein a combination of high TMB without LOH indicates a positive outcome when treated with a checkpoint inhibitor, and high TMB with LOH indicates a poor outcome.

[0018] In some embodiments, provided herein is a method of selecting a cancer patient for treatment with a checkpoint inhibitor, the method comprising selecting the patient for treatment with a checkpoint inhibitor if TMB is high in the absence of LOH in a sample obtained from the patient.

[0019] In some embodiments, provided herein is a method of treating a cancer patient, the method comprising: (i) selecting the patient for treatment with a checkpoint inhibitor if TMB is high in the absence of LOH in a sample obtained from the patient; and (ii) administering an effective amount of a checkpoint inhibitor to the patient.

[0020] Loss of heterozygosity As used herein, the term "loss of heterozygosity" or "LOH" refers to the loss of one parent's contribution to a cell or individual. LOH can be the result of, for example, direct deletion, deletion due to unbalanced rearrangement, gene conversion, mitotic recombination, or loss of a chromosome (monosomy). Thus, LOH can refer to the loss of genetic material, which can include the loss of an entire gene and its surrounding chromosomal regions, but less than the entire gene can be lost. For example, LOH can refer to the loss of a functional gene as a result of complete or partial loss of the gene. As used herein, the term "LOH without copy number change" refers to LOH without a net change in copy number or gene in an individual or cell. LOH without copy number change can result, for example, from uniparental disomy (UPD) and gene conversion. In UPD, an individual or cell receives two copies of a chromosome, or a portion of a chromosome, from one parent, due to, for example, an error in meiosis I or meiosis II. The methods provided herein contemplate any mechanism for LOH.

[0021] Loss of heterozygosity (LOH) of neoantigens presenting HLA class I / β-2-microglulin (B2M) complexes is a mechanism of immune evasion in virus-infected or tumor cells. For example, loss of parental MHC class I alleles can occur due to nondisjunction during mitosis, loss of one arm, or interstitial deletion (Figure 1), limiting the number of potential neoantigens that can be presented on the cell surface.

[0022] The majority of occurrences of LOH in HLA class I and B2M genes can be identified using bioinformatics approaches for SNP analysis and copy number variation (CNV) of NGS data containing sequences from chromosome 6 (HLA class I) and chromosome 15 (B2M). Sequence information from the short arm of chromosome 6 (HLA class I) and the long arm of chromosome 15 is particularly important in deriving LOH in these genes / regions.

[0023] HLA allelic imbalance is characterized as somatic amplification / deletion that gives rise to tumor cells, which present an uneven number of copies of the two original HLA alleles found in the normal cells of the individual.HLA loss of heterozygosity (LOH) is an extreme case of allelic imbalance, which is defined by the complete disappearance or undetectable one of the two original HLA alleles in tumor cells.As used herein, HLA loss of heterozygosity (LOH) refers to both of the above-mentioned events (HLA LOH itself, and the more general concept of HLA allelic imbalance).

[0024] immunotherapy The methods provided herein include determining a treatment regimen for cancer patients, selecting cancer patients for treatment, and / or treating cancer patients.In some embodiments, the treatment regimen or treatment is immunotherapy.In some embodiments, the treatment regimen or treatment is checkpoint inhibitor therapy (described below).

[0025] Immunotherapy includes treatment with activating immunotherapy and treatment with suppressing immunotherapy. Activating immunotherapy induces or activates an immune response, while suppressing immunotherapy reduces or suppresses an immune response. Immunotherapy may include treatment with immune regulators, such as interleukins, cytokines, chemokines, and immunomodulatory imid drugs (IMiDs). Any interleukin, cytokine, chemokine, or immunomodulatory imid drug (IMiD) can be used for immunotherapy. Exemplary interleukins for immunotherapy include IL-1, IL-2, IL-3, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12, IL-15, IL-18, IL-21, and IL-23. Exemplary cytokines for immunotherapy include interferons, TNF-α, TGF-β, G-CSF, and GM-CSF. Exemplary chemokines for immunotherapy include CCL3, CCL26, and CXCL7.Exemplary IMiDs include thalidomide and its analogs lenalidomide, pomalidomide, and apremilast.Other immunomodulators include, for example, cytosine phosphate guanosine, oligodeoxynucleotides, and glucans.

[0026] Cancer immunotherapy generally involves the stimulation of the immune system to destroy cancer cells and tumors. Exemplary cancer immunotherapy includes CAR T cell therapy, which introduces a chimeric antigen receptor (CAR) into a patient's T cells to generate CAR-T cells. The CAR-T cells are then introduced into the patient's bloodstream to treat cancer by adoptive cell transfer (ACT). CARs generally include an antigen recognition domain that can target antigens expressed on the cell surface of cancer cells, and one or more signaling domains. Thus, CAR-T cells can target and destroy cancer cells that express the target antigen. Exemplary CAR-T cell therapies include tisagenlecleucel (KYMRIAH) and axicabtageneciloreucel (YESCARTA).

[0027] Further cancer immunotherapy includes TCR therapy, which is another type of ACT. Similar to CAR-T cell therapy, T cells are taken from the patient, redesigned, and introduced into the patient. Further ACT includes tumor infiltrating lymphocyte (TIL) therapy. Patient-derived TILs are isolated from the patient's tumor tissue, expanded in vitro, and then introduced into the patient.

[0028] Yet another type of cancer immunotherapy is treatment with monoclonal antibodies. Monoclonal antibodies for use in immunotherapy can be naked (i.e., unconjugated) or conjugated (i.e., have chemotherapy drugs or radioactive particles attached to them). In addition to monoclonal antibodies, other molecules, such as interleukins and cytokines, can be conjugated to target cancer cells. As an example, denileukin diftitox (ONTAK) contains IL-2 linked to diphtheria toxin. Furthermore, monoclonal antibodies for cancer immunotherapy can be bispecific, i.e., designed to recognize and bind to two different proteins. Thus, bispecific monoclonal antibodies can recognize more than one antigen on the surface of, for example, cancer cells. As another example, bispecific antibodies can recognize proteins or antigens on cancer cells and proteins or antigens on immune cells, thereby promoting the immune cells to attack the cancer cells.

[0029] Exemplary monoclonal antibodies for treating cancer include alemtuzumab (CAMPATH), trastuzumab (HERCEPTIN), ibritumomab tiuxetan (ZEVALIN), brentuximab vedotin (ADCETRIS), ado-trastuzumab emtansine (KADCYLA), blinatumomab (BLINCYTO), bevacizumab (AVASTIN), and cetuximab (ERBITUX).

[0030] Further cancer immunotherapies include cancer vaccines that induce an immune response against cancer cells. Yet another cancer immunotherapy is "checkpoint inhibitor therapy," which is described further below.

[0031] Checkpoint inhibitor therapy "Checkpoint inhibitor therapy" is a form of cancer treatment that uses or targets immune checkpoints that affect the function of the immune system. Immune checkpoints can be stimulatory or inhibitory. Tumors can use these checkpoints to protect themselves from immune system attacks. Checkpoint therapy can block inhibitory checkpoints and restore immune system function. Checkpoint proteins include programmed cell death 1 protein (also known as PDCD1, PD-1, CD279) and its ligand, PD-1 ligand 1 (PD-L1, CD274), cytotoxic T lymphocyte-associated protein 4 (CTLA-4), A2AR (adenosine A2A receptor), B7-H3 (or CD276), B7-H4 (or VTCN1), BTLA (B- and T-lymphocyte attenuator, or CD272), IDO (indoleamine 2,3-dioxygenase), KIR (killer cell immunoglobulin-like receptor), LAG3 (lymphocyte activation gene-3), TIM-3 (T-cell immunoglobulin-like domain and mucin domain 3), and VISTA (V-domain Ig suppressor of T-cell activation).

[0032] Programmed cell death 1 protein, also known as PD-1 and CD279 (cluster of differentiation 279), is a cell surface receptor that plays a key role in downregulating the immune system and promoting self-tolerance by suppressing the inflammatory activity of T cells. Without being limited by theory, PD-1 is an immune checkpoint that protects against autoimmunity through a dual mechanism of promoting apoptosis (programmed cell death) in antigen-specific T cells in lymph nodes while simultaneously reducing apoptosis in regulatory T cells (anti-inflammatory and suppressive T cells). PD-1 has two ligands, PD-L1 and PD-L2, which are members of the B7 family. PD-L1 protein is upregulated on macrophages and dendritic cells (DCs) in response to LPS and GM-CSF treatment, and on T and B cells upon TCR and B cell receptor signaling, whereas in resting mice, for example, PD-L1 mRNA can be detected in the heart, lungs, thymus, spleen, and kidney. PD-L1 is expressed on nearly all murine tumor cell lines, including PA1 myeloma, P815 mastocytoma, and B16 melanoma, upon treatment with IFN-γ. PD-L2 expression is more restricted, being expressed primarily on DCs and some tumor lines.

[0033] PD-L1 is expressed in several cancers. Monoclonal antibodies targeting PD-1 can enhance the immune system for cancer treatment. Many tumor cells express PD-L1, an immunosuppressive PD-1 ligand, and inhibition of the interaction between PD-1 and PD-L1 can enhance T cell responses in vitro and mediate preclinical antitumor activity.

[0034] CTLA4 or CTLA-4 (cytotoxic T-lymphocyte-associated protein 4), also known as CD152 (cluster of differentiation 152), is a protein receptor that functions as an immune checkpoint and downregulates immune responses. CTLA4 is constitutively expressed in regulatory T cells, but is commonly upregulated in typical T cells after activation, especially in cancer. CTLA4 is a member of the immunoglobulin superfamily that is expressed by activated T cells and transmits inhibitory signals to T cells. CTLA4 functions similarly to the T cell costimulatory protein CD28, both molecules binding to CD80 and CD86 (also called B7-1 and B7-2, respectively) on antigen-presenting cells. Without being limited by theory, CTLA-4 binds to CD80 and CD86 with higher affinity and avidity than CD28, and thus can outcompete CD28 for its ligand. CTLA4 transmits inhibitory signals to T cells, while CD28 transmits stimulatory signals. CTLA4 is also found on regulatory T cells, where it contributes to their inhibitory function. T cell activation via the T cell receptor and CD28 leads to increased expression of CTLA-4.

[0035] Some checkpoint inhibitors can be used to treat cancer. PD-1 inhibitors include, for example, pembrolizumab (KEYTRUDA) and nivolumab (OPDIVO). PD-L1 inhibitors include, for example, atezolizumab (TECENTRIQ), avelumab (BAVENCIO) and durvalumab (IMFINZI). CTLA-4 inhibitors include, for example, ipilimumab (YERVOY). Other checkpoint inhibitors include, for example, B7-H3 antibody (MGA271), anti-KIR antibody (lirilumab) and anti-LAG3 antibody (BMS-986016). Any checkpoint inhibitor can be used in the methods described herein. Furthermore, the methods described herein can be used to determine or predict responsiveness to any checkpoint inhibitor. In some embodiments, the checkpoint inhibitor of the methods described herein is pembrolizumab (KEYTRUDA), nivolumab (OPDIVO), atezolizumab (TECENTRIQ), avelumab (BAVENCIO), durvalumab (IMFINZI), or ipilimumab (YERVOY).

[0036] Tumor mutation burden The methods described herein include, for example, determining tumor mutation burden (TMB) in patient samples and / or using TMB to select cancer patients for treatment. TMB can serve as a surrogate marker of immune response, as it provides a readout for altered proteins that should be recognized by the immune system but are not due to suppression of the immune response by the tumor. TMB can be measured through a sampling region of the cancer genome to estimate the number of mutations / Mb. A higher TMB score can be associated with a better response to immunotherapy, as the tumor harbors more somatic mutations and has more opportunities to present immunogenic neoepitopes.

[0037] Samples may be tested for high genetic mutation burden 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 genetic mutation burden means that there are more somatic mutations in tumors compared to normal tissues of an individual. The average number of somatic mutations in tumors that are not microsatellite unstable (MSI) is about 70 somatic mutations. Different types of somatic mutations may contribute to TMB, including, for example, missense mutations, nonsense mutations, insertions and deletions.

[0038] Determination of LOH The methods described herein include, for example, determining loss of heterozygosity (LOH) in patient samples and / or using LOH to select cancer patients for treatment. In some embodiments, LOH is determined in combination with TMB to determine treatment regimens in cancer patients, as provided by the methods described herein. In some embodiments, the methods provided herein use LOH in combination with TMB to select cancer patients for treatment. As described in the examples below, the methods described herein use PGDx elio™ tissue complete testing and provide for the use of existing data from NGS sequencing to 1) identify somatic alterations of genes in antigen-presenting complexes, 2) use these data to infer whether normal or abnormal antigen-presenting complexes are present, and 3) use these data to refine TMB-based predictions of responsiveness to immunotherapy.

[0039] In the methods provided herein, any gene or genes can be analyzed for LOH. In some embodiments, LOH is determined within the region adjacent to or including MHC genes. Both MHC class I and MHC class II genes can be analyzed for LOH. In some embodiments, LOH is determined within the region adjacent to or including MHC class I genes. In some embodiments, LOH is determined within the region adjacent to or including MHC class II genes. In some embodiments, LOH is determined within the region adjacent to or including MHC class I and MHC class II genes. In some embodiments, LOH is determined within the region of the B2M gene. In some embodiments, LOH is determined within the region of the B2M gene and within the region adjacent to or including MHC genes. In some embodiments, LOH is determined within the region of the B2M gene and within the region adjacent to or including MHC genes. In some embodiments, LOH is determined within the region of the B2M gene and within the region adjacent to or including an MHC class II gene.

[0040] The method is useful with any available gene panel that provides the desired genes of interest, including the current version of the PGDx elio™ tissue complete test. (http: / / www.personalgenome.com / ). Certain software updates are useful for analyzing single nucleotide polymorphisms (SNPs) and copy number variations (CNVs) and calling regions of LOH in target genes. Additionally, hybrid capture regions (ROIs) of interest that include MHC class I genes may be added to the PGDx elio™ tissue complete panel.

[0041] This method can predict responsiveness to immunotherapy more accurately than TMB testing alone. Currently, all high TMB patients are considered to be "likely" to be responders. If testing for somatic mutations in genes in the antigen-presenting complex is added to the current TMB testing, patients can be identified as "likely" to be responders if they have both (1) high TMB and (2) normal antigen presentation. This may change the diagnosis of patients in the upper right quadrant of Table 1 from good outcome to poor outcome.

[0042] (Table 1) TMB / LOH status and treatment outcome TIFF0007623281000001.tif23150

[0043] Loss of antigen presentation is a mechanism of immune evasion, and the present methods show that LOH in these genes can be identified, for example, using the PGDx elio™ tissue complete test or other PCR or NGS techniques.

[0044] In some embodiments of the methods provided herein, a high TMB score in the absence of LOH indicates a good outcome, i.e., the patient is more likely to respond to immunotherapy. In some embodiments, a low TMB score in the absence of LOH indicates a bad outcome, i.e., the patient is less likely to respond to immunotherapy. In some embodiments, a low TMB score in the presence of LOH indicates a bad outcome, i.e., the patient is less likely to respond to immunotherapy. In some embodiments, a high TMB score in the presence of LOH indicates a bad outcome, i.e., the patient is less likely to respond to immunotherapy. In some embodiments, the immunotherapy is a checkpoint inhibitor therapy.

[0045] As used herein, the term "less likely to respond" or "less likely to be a responder" refers to the responsiveness of a patient to a treatment compared to a patient predicted to have a good or positive outcome or response to the treatment. In some embodiments, "less likely to be a responder" refers to a patient that is 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%, or any number or range therebetween that is less likely to respond to the treatment than a patient predicted to have a good or positive outcome or response to the treatment. As used herein, "positive response to treatment" or "good response to treatment" may be used interchangeably with respect to "treatment", as defined below. As used herein, the term "more likely to respond" or "more likely to be a responder" refers to the responsiveness of a patient to a treatment compared to a patient predicted to have a bad or negative outcome or response to the treatment. In some embodiments, "likely to be a responder" means a patient who is 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%, or any number or range therebetween, more likely to respond to the treatment than a patient predicted to have a poor or negative outcome or response to the treatment. As used herein, the terms "poor outcome", "negative outcome", or "negative response" when referring to the treatment of a patient, with respect to "treatment" as defined below, mean that the patient does not respond to the treatment, i.e., the treatment is not effective.

[0046] In some embodiments, the immunotherapy comprises administration of a checkpoint inhibitor. Any checkpoint inhibitor can be used in the methods provided herein. In some embodiments, the checkpoint inhibitor is pembrolizumab (KEYTRUDA), nivolumab (OPDIVO), atezolizumab (TECENTRIQ), avelumab (BAVENCIO), durvalumab (IMFINZI), avelumab (BAVENCIO), durvalumab (IMFINZI), or ipilimumab (YERVOY).

[0047] sample In some embodiments, the methods provided herein include determining tumor mutation burden (TMB) and loss of heterozygosity (LOH) in samples from cancer patients. In some embodiments, the cancer is a tumor. Samples from both solid and liquid tumors may be used in the methods described herein. As used herein, the term "tumor" refers to a mass or lump of tissue formed by the accumulation of abnormal cells. A tumor may be benign (i.e., not cancer), malignant (i.e., cancer), or premalignant (i.e., precancerous). The terms "tumor" and "neoplasm" may be used interchangeably. Generally, a cancer that is a tumor is malignant.

[0048] As used herein, the term "solid tumor" refers to a mass of abnormal tissue that does not usually contain cysts or liquid areas. Exemplary solid tumors include, for example, sarcomas and carcinomas. As used herein, the term "liquid tumor" refers to a tumor or cancer that exists in bodily fluids, such as blood and bone marrow. Exemplary liquid tumors include, for example, hematopoietic tumors, such as leukemias and lymphomas, even though lymphomas have the ability to grow as solid tumors, for example, by growing in lymph nodes. The term "liquid tumor" may be used interchangeably with the term "blood cancer", unless the context clearly indicates otherwise.

[0049] Samples from any cancer can be analyzed by the method provided herein.In some embodiments, the cancer is selected from breast cancer, pancreatic cancer, lung cancer, melanoma, hematopoietic cancer and leukemia, colon cancer, kidney cancer, head and neck cancer, brain cancer, bone cancer, ovarian cancer, cervical cancer, endometrial cancer, and prostate cancer.Therefore, the patient of the method provided herein may suffer from any cancer.In some embodiments, the cancer is a tumor.In some embodiments, the patient suffers from breast cancer, pancreatic cancer, lung cancer, melanoma, hematopoietic cancer, leukemia, colon cancer, kidney cancer, head and neck cancer, brain cancer, bone cancer, ovarian cancer, cervical cancer, endometrial cancer, or prostate cancer.

[0050] Any sample or type of sample can be used in the methods provided herein. In some embodiments, the sample is blood, saliva, plasma, serum, urine, or other biological fluid. Further exemplary biological fluids include serous fluid, lymphatic fluid, cerebrospinal fluid, mucosal secretions, vaginal fluid, peritoneal fluid, pleural fluid, pericardial fluid, peritoneal fluid, ascites. In some embodiments, the sample is a tissue sample. In some embodiments, the sample is a tissue sample from a cancer. In some embodiments, the sample is a cell sample. In some embodiments, the sample is a cell sample from a cancer. In some embodiments, the sample is a cancer sample. The cancer sample may be a sample from a solid tumor or a liquid tumor.

[0051] MHC / B2M genes As described above, any gene or genes can be analyzed for LOH in the methods provided herein. In some embodiments, LOH is determined in the region adjacent to or including MHC genes. Both MHC class I and MHC class II genes can be analyzed for LOH. In some embodiments, LOH is determined in the region adjacent to or including MHC class I genes. In some embodiments, LOH is determined in the region adjacent to or including MHC class II genes. In some embodiments, LOH is determined in the region adjacent to or including MHC class I and MHC class II genes. In some embodiments, LOH is determined in the region of B2M genes. In some embodiments, LOH is determined in the region of B2M genes and in the region adjacent to or including MHC genes. In some embodiments, LOH is determined in the region of B2M genes and in the region adjacent to or including MHC genes. In some embodiments, LOH is determined within the region of the B2M gene and within the region adjacent to or including an MHC class II gene.

[0052] Major histocompatibility complex (MHC) class I and MHC class II complexes are the primary MHC molecules. MHC class I molecules are found on the surface of all nucleated cells and on platelets. MHC class I molecules function to present peptide fragments of intracellular proteins to cytotoxic T cells. Presentation of peptide fragments triggers an immune response against non-self antigens or neo-antigens. MHC class I molecules present peptides generated primarily from the degradation of cytoplasmic proteins (cytoplasmic or endogenous presentation pathway), but class I MHC can also present peptides generated from exogenous proteins in a process called cross-presentation.

[0053] MHC class I molecules are heterodimers containing two non-covalently linked polypeptide chains, α and β2-microglobulin (b2m). The α chain is polymorphic and is encoded by the HLA gene in humans. The b2m subunit is not polymorphic and is encoded by the β-2 microglobulin (B2M gene).

[0054] As used herein, the term "MHC class I genes" refers to genes that code for the α subunits of MHC class I molecules. Genes that code for the α subunits of MHC class I molecules are part of the human leukocyte antigen (HLA) gene complex, which resides in a gene stretch of approximately 3 Mbp on chromosome 6p21 (Figure 7). The HLA gene complex also includes genes that code for class II MHC molecules. MHC class II molecules are typically found on professional antigen-presenting cells, such as, for example, dendritic cells, mononuclear phagocytes, some endothelial cells, thymic epithelial cells, and B cells. Exemplary genes that code for the α subunits of MHC class I molecules include the highly polymorphic HLA-A, HLA-B, and HLA-C genes. Further exemplary genes that code for the α subunits include HLA-E, HLA-F, and HLA-G, as well as the pseudogenes HLA-K and HLA-L. Exemplary genes encoding class II MHC molecules include the HLA-DM, HLA-DO, HLA-DP, HLA-DQ, and HLA-DR genes.

[0055] As used herein, the term "B2M gene" refers to the gene encoding the β2-microglobulin (b2M) chain. The human B2M gene is located at position 21.1 on the long arm of chromosome 15.

[0056] In some embodiments, the methods provided herein include determining LOH within a region adjacent to or including an MHC class I gene. In some embodiments, the methods provided herein include LOH within a region adjacent to or including an MHC class I gene.

[0057] In some embodiments, the methods provided herein include determining LOH within a region of the B2M gene. In some embodiments, the methods provided herein include LOH within a region of the B2M gene.

[0058] In some embodiments, the methods provided herein include determining LOH within a region adjacent to or including an MHC class I gene and within a region of the B2M gene. In some embodiments, the LOH is within a region adjacent to or including an MHC class I gene and within a region of the B2M gene.

[0059] As used herein, the term "region near a gene" refers to a region that is within 10 bp, 20 bp, 30 bp, 40 bp, 50 bp, 60 bp, 70 bp, 80 bp, 90 bp, 100 bp, 200 bp, 300 bp, 400 bp, 500 bp, 600 bp, 700 bp, 800 bp, 900 bp, 1,000 bp, 1,100 bp, 1,200 bp, 1,300 bp, 1,400 bp, or 2,500 bp of a gene, a gene in a gene cluster, or the gene cluster itself. Within 00bp, Within 1,500bp, Within 1,600bp, Within 1,700bp, Within 1,800bp, Within 1,900bp, Within 2,000bp, Within 2,100bp, Within 2,200bp, Within 2,300bp, Within 2,400bp, Within 2,500bp, Within 2,600bp, Within 2,700bp, Within 2,800bp, Within 2,900bp, Within 3,000bp, Within 3,100bp, Within 3,200bp, Within 3,300bp, Within 3,400bp, Within 3,500bp, Within 3,600bp, Within 3,700bp, Within 3,800bp, Within 3,900bp, Within 4,000bp, Within 4,100bp, Within 4,200bp, Within 4,300bp, Within 4,400bp, Within 4,500bp, Within 4,600bp, Within 4,700bp, Within 4,800bp, Within 4,900bp, Within 5,000bp, Within 5,500bp, Within 6,000bp, Within 6,500bp, Within 7,000bp, Within 7,500bp, Within 8,000bp, Within 8,500bp, Within 9,000bp, Within 9,500bp, Within 10,000bp, Within 11,000bp, Within 12,000bp, Within 13,000 bp, 14,000bp, 15,000, 16,000bp, 17,000bp, 18,000bp, 19,000bp, 20,000bp, 25,000bp, 30,000bp, 35,000bp, 40,000bp, 45,000bp, 50,000bp, 55,000bp, 60,000bp, 65,000bp, 70,000bp, 75,000bp, 80,000bp, 85,000bp, 90,000bp, 95,000bp, 100,000bp, and any number or range therebetween.

[0060] As used herein, the term "region of a gene" refers to any location within a region of DNA or functional unit of heredity that controls genetic characteristics, including protein- and RNA-coding genes and pseudogenes. A region of a gene may include any location within a complete functional unit, including, for example, coding sequences, non-coding sequences such as introns and non-translated sequences, non-coding regulatory sequences such as promoters, enhancers, and insulators. A "region of a gene" may include any number of base pairs (bp).

[0061] Neoantigens In some embodiments, the tumor mutation in the methods provided herein comprises a neoantigen or neoepitope recognized by T cells. In some embodiments, the neoantigen or neoepitope is a tumor antigen or tumor epitope. Exemplary tumor antigens include mutated oncogene products, products or mutated tumor suppressors, mutated gene products other than oncogenes or tumor suppressors, tumor antigens produced by oncogenic viruses, modified cell surface glycolipids and glycoproteins, carcinoembryonic antigens, and the like.

[0062] Neoantigens or neoepitopes may be any newly formed antigens or epitopes that have not been previously recognized by the immune system. Thus, neoantigens or neoepitopes may be recognized by the immune system as non-self and trigger an immune response. Neoantigens and neoepitopes may arise, for example, from oncoproteins that have changed as a result of mutations, as described in detail above, or from viral proteins. In some embodiments, viral proteins may give rise to neoantigens or neoepitopes, including, for example, viral proteins from Hepatitis B virus (HBV), Hepatitis C virus (HCV), Epstein-Barr virus (EBV), human papillomavirus (HPV), human T-lymphotropic virus (HTLV), Kaposi's sarcoma-associated herpesvirus (KSHV), Merkel cell polyomavirus, or any other oncovirus.

[0063] Exome sequencing In some embodiments, the methods provided herein include To One or more exomes from which it is derived or that area The present invention includes determining tumor mutation burden (TMB) and loss of heterozygosity (LOH) in samples from cancer patients by sequencing. As used herein, the term "exome" refers to the portion of the genome that is composed of exons. An exome may include all DNA regions that are transcribed into mature RNA in any type of cell. The human exome contains about 180,000 exons, which constitute about 1% of the human genome, or about 30 million base pairs of DNA.

[0064] As used herein, the term "exome sequencing" refers to sequencing all protein-coding exons of genes in genome. Exome sequencing may include target enrichment methods, such as array-based capture and in-solution capture of nucleic acids. Any sequencing method can be used, including Sanger sequencing using labeled terminators or primers, and gel separation in slab or capillary systems, and next-generation sequencing (NGS). Exemplary next-generation sequencing methods include Roche 454 sequencer, Life Technologies SOLiD system, Life Technologies Ion Torrent, and Illumina systems, such as Illumina Genome Analyzer II, Illumina MiSeq, Illumina Hi Seq, and Illumina NovaSeq instruments.

[0065] Methods for determining a treatment regimen In some embodiments, provided herein is a method for determining a treatment regimen in a cancer patient, comprising determining tumor mutation burden (TMB) and loss of heterozygosity (LOH) in a sample from the patient, wherein a combination of no LOH and high TMB indicates a positive outcome when treated with a checkpoint inhibitor, and high TMB with LOH indicates a poor outcome. In some embodiments, a combination of no LOH and low TMB indicates a poor outcome when treated with a checkpoint inhibitor. In some embodiments, a combination of LOH and low TMB indicates a poor outcome when treated with a checkpoint inhibitor.

[0066] In some embodiments, the cancer is a tumor.The patient for whom the treatment regimen is determined may have any type of cancer, including but not limited to breast cancer, pancreatic cancer, lung cancer, melanoma, hematopoietic cancer, leukemia, colon cancer, kidney cancer, head and neck cancer, brain cancer, bone cancer, ovarian cancer, cervical cancer and prostate cancer, as described herein.Similarly, the patient for whom the treatment regimen is determined may have any type of cancer, including solid tumor or liquid tumor, as described in detail above, as described herein.

[0067] In some embodiments, the sample used in the methods provided herein is a sample derived from a solid or liquid tumor. In some embodiments, the sample is a cancer sample. A tumor or cancer sample may contain both cancer or tumor cells and normal (i.e., non-malignant tumor) cells. Samples derived from any cancer or tumor can be used or analyzed in the methods provided herein, including samples derived from breast cancer, pancreatic cancer, lung cancer, melanoma, hematopoietic cancer, and leukemia, colon cancer, kidney cancer, head and neck cancer, brain cancer, bone cancer, ovarian cancer, cervical cancer, and prostate cancer, as well as samples derived from solid or liquid tumors.

[0068] Any type of sample can be used in the methods provided herein. In some embodiments, the sample is derived from blood, saliva, plasma, serum, urine, or other biological fluid. Further exemplary biological fluids include serous fluid, lymphatic fluid, cerebrospinal fluid, mucosal secretions, vaginal fluid, peritoneal fluid, pleural fluid, pericardial fluid, peritoneal fluid, ascites. In some embodiments, the sample is a tissue sample. In some embodiments, the sample is a tissue sample from a cancer. In some embodiments, the sample is a cell sample. In some embodiments, the sample is a cell sample from a cancer. In some embodiments, the sample is a cancer sample.

[0069] In some embodiments, the methods provided herein include determining loss of heterozygosity (LOH). LOH can be determined for any gene encoding a protein of an antigen-presenting complex. In some embodiments, LOH is determined for genes of the MHC class I gene complex. In some embodiments, LOH is determined for genes of the MHC class II gene complex. In some embodiments, LOH is determined in the region adjacent to or including the MHC class I gene. In some embodiments, LOH is determined in the region of the B2M gene. In some embodiments, LOH is determined in the region adjacent to or including the MHC class I gene and in the region of the B2M gene. LOH may be in any combination of genes, including a combination of MHC class I, MHC class II, and B2M genes.

[0070] In some embodiments, the combination of no LOH and high TMB indicates a positive outcome when treated with a checkpoint inhibitor, and high TMB with LOH indicates a poor outcome. The methods provided herein contemplate the use, selection, or treatment with any immunotherapy. In some embodiments, the immunotherapy is treatment with a checkpoint inhibitor. In some embodiments, the checkpoint inhibitor is pembrolizumab (KEYTRUDA), nivolumab (OPDIVO), atezolizumab (TECENTRIQ), avelumab (BAVENCIO), durvalumab (IMFINZI), or ipilimumab (YERVOY).

[0071] In some embodiments, determining tumor mutation burden (TMB) and loss of heterozygosity (LOH) in a sample from a patient comprises: To One or more exomes from which it is derived or that areaExome sequencing includes sequencing. As described in detail above, exome sequencing may include target enrichment methods such as array-based capture and in-solution capture of nucleic acid. Any sequencing method can be used, including Sanger sequencing using labeled terminators or primers, and gel separation in slab or capillary systems, and next-generation sequencing (NGS). Exemplary next-generation sequencing methods include Roche 454 sequencer, Life Technologies SOLiD system, Life Technologies Ion Torrent, and Illumina systems, such as Illumina Genome Analyzer II, Illumina MiSeq, Illumina Hi Seq, and Illumina NovaSeq instruments.

[0072] Tumor mutations generally contribute to TMB. In some embodiments, the tumor mutations include neoantigens or neopepitopes that are recognized by T cells. In some embodiments, the neoantigens or neoepitopes are tumor antigens or tumor epitopes. Exemplary tumor antigens include products of mutated oncogenes, products or mutated tumor suppressors, products of mutated genes other than oncogenes or tumor suppressors, tumor antigens produced by oncogenic viruses, modified cell surface glycolipids and glycoproteins, carcinoembryonic antigens, and the like.

[0073] Neoantigens or neoepitopes may be any newly formed antigens or epitopes that have not been previously recognized by the immune system. Thus, neoantigens or neoepitopes may be recognized by the immune system as non-self and trigger an immune response. Neoantigens and neoepitopes may arise, for example, from oncoproteins that have changed as a result of mutations, as described in detail above, or from viral proteins. In some embodiments, viral proteins may give rise to neoantigens or neoepitopes, including, for example, viral proteins from Hepatitis B virus (HBV), Hepatitis C virus (HCV), Epstein-Barr virus (EBV), human papillomavirus (HPV), human T-lymphotropic virus (HTLV), Kaposi's sarcoma-associated herpesvirus (KSHV), Merkel cell polyomavirus, or any other oncovirus.

[0074] Patient Selection Method In some embodiments, provided herein is a method for selecting a cancer patient for treatment with a checkpoint inhibitor, comprising selecting the patient for treatment with a checkpoint inhibitor if a sample obtained from the patient has high TMB in the absence of LOH. In some embodiments, the combination of no LOH and high TMB indicates a positive outcome when treated with a checkpoint inhibitor, and high TMB with LOH indicates a poor outcome. In some embodiments, the combination of no LOH and low TMB indicates a poor outcome when treated with a checkpoint inhibitor. In some embodiments, the combination of LOH and low TMB indicates a poor outcome when treated with a checkpoint inhibitor.

[0075] In some embodiments, cancer is tumor.The patient selected for treatment according to the method provided herein may have any type of cancer, including but not limited to breast cancer, pancreatic cancer, lung cancer, melanoma, hematopoietic cancer, leukemia, colon cancer, kidney cancer, head and neck cancer, brain cancer, bone cancer, ovarian cancer, cervical cancer and prostate cancer.Similarly, the patient selected for treatment according to the method provided herein may have any type of tumor, including solid tumor or liquid tumor as described in detail above.

[0076] In some embodiments, the sample used in the methods provided herein is a sample derived from a solid or liquid tumor. In some embodiments, the sample is a cancer sample. A tumor or cancer sample may contain both cancer or tumor cells and normal (i.e., non-malignant tumor) cells. Samples derived from any cancer or tumor can be used or analyzed in the methods provided herein, including samples derived from breast cancer, pancreatic cancer, lung cancer, melanoma, hematopoietic cancer, and leukemia, colon cancer, kidney cancer, head and neck cancer, brain cancer, bone cancer, ovarian cancer, cervical cancer, and prostate cancer, as well as samples derived from solid or liquid tumors.

[0077] Any type of sample can be used in the methods provided herein. In some embodiments, the sample is derived from blood, saliva, plasma, serum, urine, or other biological fluid. Further exemplary biological fluids include serous fluid, lymphatic fluid, cerebrospinal fluid, mucosal secretions, vaginal fluid, peritoneal fluid, pleural fluid, pericardial fluid, peritoneal fluid, ascites. In some embodiments, the sample is a tissue sample. In some embodiments, the sample is a tissue sample from a cancer. In some embodiments, the sample is a cell sample. In some embodiments, the sample is a cell sample from a cancer. In some embodiments, the sample is a cancer sample.

[0078] In some embodiments, the methods provided herein include loss of heterozygosity (LOH). The LOH may be in any gene encoding a protein of the antigen-presenting complex. In some embodiments, the LOH is in a gene of the MHC class I complex. In some embodiments, the LOH is in a gene of the MHC class II complex. In some embodiments, the LOH is in a region adjacent to or including the MHC class I gene. In some embodiments, the LOH is in a region of the B2M gene. In some embodiments, the LOH is in a region adjacent to or including the MHC class I gene and in the region of the B2M gene. The LOH may be in any combination of genes, including a combination of the MHC class I, MHC class II, and B2M genes.

[0079] In some embodiments, the combination of no LOH and high TMB indicates a positive outcome when treated with a checkpoint inhibitor, and high TMB with LOH indicates a poor outcome. The methods provided herein contemplate the use, selection, or treatment with any immunotherapy. In some embodiments, the immunotherapy is treatment with a checkpoint inhibitor. In some embodiments, the checkpoint inhibitor is pembrolizumab (KEYTRUDA), nivolumab (OPDIVO), atezolizumab (TECENTRIQ), avelumab (BAVENCIO), durvalumab (IMFINZI), or ipilimumab (YERVOY).

[0080] In some embodiments, determining tumor mutation burden (TMB) and loss of heterozygosity (LOH) in a sample from a patient comprises: To One or more exomes from which it is derived or that areaExome sequencing includes sequencing exomes. As described in detail above, exome sequencing may include target enrichment methods such as array-based capture and in-solution capture of nucleic acid. Any sequencing method can be used, including Sanger sequencing using labeled terminators or primers, and gel separation in slab or capillary systems, and next-generation sequencing (NGS). Exemplary next-generation sequencing methods include Roche 454 sequencer, Life Technologies SOLiD system, Life Technologies Ion Torrent, and Illumina systems, such as Illumina Genome Analyzer II, Illumina MiSeq, Illumina Hi Seq, and Illumina NovaSeq instruments. Any sample described herein can be analyzed for TMB and LOH to select patients for treatment.

[0081] Tumor mutations generally contribute to TMB. In some embodiments, the tumor mutations include neoantigens or neopepitopes that are recognized by T cells. In some embodiments, the neoantigens or neoepitopes are tumor antigens or tumor epitopes. Exemplary tumor antigens include products of mutated oncogenes, products or mutated tumor suppressors, products of mutated genes other than oncogenes or tumor suppressors, tumor antigens produced by oncogenic viruses, modified cell surface glycolipids and glycoproteins, carcinoembryonic antigens, and the like.

[0082] Neoantigens or neoepitopes may be any newly formed antigens or epitopes that have not been previously recognized by the immune system. Thus, neoantigens or neoepitopes may be recognized by the immune system as non-self and trigger an immune response. Neoantigens and neoepitopes may arise, for example, from oncoproteins that have changed as a result of mutations, as described in detail above, or from viral proteins. In some embodiments, viral proteins may give rise to neoantigens or neoepitopes, including, for example, viral proteins from Hepatitis B virus (HBV), Hepatitis C virus (HCV), Epstein-Barr virus (EBV), human papillomavirus (HPV), human T-lymphotropic virus (HTLV), Kaposi's sarcoma-associated herpesvirus (KSHV), Merkel cell polyomavirus, or any other oncovirus.

[0083] Treatment method In some embodiments, provided herein is a method of treating a cancer patient, comprising: (i) selecting the patient for treatment with a checkpoint inhibitor if a sample obtained from the patient has high TMB in the absence of LOH; and (ii) administering an effective amount of a checkpoint inhibitor to the patient. In some embodiments, the combination of no LOH and high TMB indicates a positive outcome when treated with a checkpoint inhibitor, and high TMB with LOH indicates a poor outcome. In some embodiments, the combination of no LOH and low TMB indicates a poor outcome when treated with a checkpoint inhibitor. In some embodiments, the combination of LOH and low TMB indicates a poor outcome when treated with a checkpoint inhibitor.

[0084] In some embodiments, cancer is tumor.The patient treated according to the method provided herein may have any type of cancer, including but not limited to breast cancer, pancreatic cancer, lung cancer, melanoma, hematopoietic cancer, leukemia, colon cancer, kidney cancer, head and neck cancer, brain cancer, bone cancer, ovarian cancer, cervical cancer and prostate cancer.Similarly, the patient treated according to the method provided herein may have any type of cancer, including solid tumor or liquid tumor as described in detail above.

[0085] In some embodiments, the sample used in the methods provided herein is a sample derived from a solid or liquid tumor. In some embodiments, the sample is a cancer sample. A tumor or cancer sample may contain both cancer or tumor cells and normal (i.e., non-malignant tumor) cells. Samples derived from any cancer or tumor can be used or analyzed in the methods provided herein, including samples derived from breast cancer, pancreatic cancer, lung cancer, melanoma, hematopoietic cancer, and leukemia, colon cancer, kidney cancer, head and neck cancer, brain cancer, bone cancer, ovarian cancer, cervical cancer, and prostate cancer, as well as samples derived from solid or liquid tumors.

[0086] Any type of sample can be used in the methods provided herein. In some embodiments, the sample is derived from blood, saliva, plasma, serum, urine, or other biological fluid. Further exemplary biological fluids include serous fluid, lymphatic fluid, cerebrospinal fluid, mucosal secretions, vaginal fluid, peritoneal fluid, pleural fluid, pericardial fluid, peritoneal fluid, ascites. In some embodiments, the sample is a tissue sample. In some embodiments, the sample is a tissue sample from a cancer. In some embodiments, the sample is a cell sample. In some embodiments, the sample is a cell sample from a cancer. In some embodiments, the sample is a cancer sample.

[0087] In some embodiments, the methods provided herein include loss of heterozygosity (LOH). LOH for any gene encoding a protein of an antigen-presenting complex can be determined. In some embodiments, the LOH is in a gene of the MHC class I complex. In some embodiments, the LOH is in a gene of the MHC class II complex. In some embodiments, the LOH is in a region adjacent to or including the MHC class I gene. In some embodiments, the LOH is in a region of the B2M gene. In some embodiments, the LOH is in a region adjacent to or including the MHC class I gene and in a region of the B2M gene.

[0088] In some embodiments, the combination of no LOH and high TMB indicates a positive outcome when treated with a checkpoint inhibitor, and high TMB with LOH indicates a poor outcome. The methods provided herein contemplate the use, selection, or treatment with any immunotherapy. In some embodiments, the immunotherapy is treatment with a checkpoint inhibitor. In some embodiments, the checkpoint inhibitor is pembrolizumab (KEYTRUDA), nivolumab (OPDIVO), atezolizumab (TECENTRIQ), avelumab (BAVENCIO), durvalumab (IMFINZI), or ipilimumab (YERVOY). Thus, patients can be selected for treatment with any checkpoint inhibitor described herein, and an effective amount of any checkpoint inhibitor can be administered to the patient. In some embodiments, the checkpoint inhibitor is pembrolizumab (KEYTRUDA), nivolumab (OPDIVO), atezolizumab (TECENTRIQ), avelumab (BAVENCIO), durvalumab (IMFINZI), avelumab (BAVENCIO), durvalumab (IMFINZI), or ipilimumab (YERVOY).

[0089] In some embodiments, determining tumor mutation burden (TMB) and loss of heterozygosity (LOH) in a sample from a patient comprises: To One or more exomes from which it is derived or that area Exome sequencing includes sequencing. As described in detail above, exome sequencing may include target enrichment methods such as array-based capture and in-solution capture of nucleic acid. Any sequencing method can be used, including Sanger sequencing using labeled terminators or primers, and gel separation in slab or capillary systems, and next-generation sequencing (NGS). Exemplary next-generation sequencing methods include Roche 454 sequencer, Life Technologies SOLiD system, Life Technologies Ion Torrent, and Illumina systems, such as Illumina Genome Analyzer II, Illumina MiSeq, Illumina Hi Seq, and Illumina NovaSeq instruments.

[0090] Tumor mutations generally contribute to TMB. In some embodiments, the tumor mutations include neoantigens or neopepitopes that are recognized by T cells. In some embodiments, the neoantigens or neoepitopes are tumor antigens or tumor epitopes. Exemplary tumor antigens include products of mutated oncogenes, products or mutated tumor suppressors, products of mutated genes other than oncogenes or tumor suppressors, tumor antigens produced by oncogenic viruses, modified cell surface glycolipids and glycoproteins, carcinoembryonic antigens, and the like.

[0091] Neoantigens or neoepitopes may be any newly formed antigens or epitopes that have not been previously recognized by the immune system. Thus, neoantigens or neoepitopes may be recognized by the immune system as non-self and trigger an immune response. Neoantigens and neoepitopes may arise, for example, from oncoproteins that have changed as a result of mutations, as described in detail above, or from viral proteins. In some embodiments, viral proteins may give rise to neoantigens or neoepitopes, including, for example, viral proteins from Hepatitis B virus (HBV), Hepatitis C virus (HCV), Epstein-Barr virus (EBV), human papillomavirus (HPV), human T-lymphotropic virus (HTLV), Kaposi's sarcoma-associated herpesvirus (KSHV), Merkel cell polyomavirus, or any other oncovirus.

[0092] As used herein, the terms "treat", "treatment", "therapy", "therapeutic" and the like refer to obtaining a desired pharmacological and / or physiological effect, including, but not limited to, relieving, delaying or slowing the progression of an effect or symptom, preventing the onset, suppressing the onset of a disease or disorder, ameliorating, obtaining a beneficial or desirable result with respect to a disease, disorder, or medical condition, e.g., therapeutic benefit and / or prophylactic benefit. "Treatment", as used herein, encompasses any treatment of disease in a mammal, particularly a human, and includes (a) preventing the disease from occurring in a subject who may be pre-diagnosed as susceptible to the disease or at risk of suffering from the disease, but who may not yet be diagnosed as suffering from the disease, (b) suppressing the disease, i.e., arresting its onset, and (c) alleviating the disease, i.e., reversing the disease. Therapeutic benefit includes eradication or amelioration of the underlying disorder being treated. Therapeutic benefits are also achieved with the eradication or amelioration of one or more of the physiological symptoms associated with the underlying disorder, such that improvement is observed in the subject, even though the subject may still be affected by the underlying disorder. In some cases, for preventative benefits, a treatment or composition for treatment is administered to a subject at risk of developing a particular disease, or to a subject who reports one or more of the physiological symptoms of a disease, even if the disease has not been diagnosed. The methods of the present disclosure can be used on any mammal or other animal. In some cases, treatment can result in a reduction or cessation of symptoms. A preventative effect can include delaying or eliminating the appearance of a disease or condition, delaying or eliminating the onset of symptoms of a disease or condition, delaying, stopping, or reversing the progression of a disease or condition, or any combination thereof.

[0093] As used herein, the term "effective amount" or "therapeutically effective amount" refers to an amount of a checkpoint inhibitor or other composition described herein sufficient to affect the intended use as defined herein (including, but not limited to, disease treatment). The therapeutically effective amount may vary depending on the intended therapeutic use (in vivo), or the patient and disease state to be treated, such as the patient's weight and age, the severity of the disease state, the mode of administration, etc., which can be easily determined by one of ordinary skill in the art. The term also applies to a dose that induces a specific response in target cells. The specific dose will vary depending on the particular checkpoint inhibitor or other composition selected, the dosing regimen to be followed, whether it is administered in combination with other compounds, the timing of administration, the tissue to which it is administered, and the physical delivery system in which it is delivered.

[0094] The therapeutic method provided herein may include treating any cancer.Exemplary cancers include breast cancer, pancreatic cancer, lung cancer, melanoma, hematopoietic cancer and leukemia, colon cancer, kidney cancer, head and neck cancer, brain cancer, bone cancer, ovarian cancer, cervical cancer and prostate cancer, as described above in detail.In addition, any sample described herein can be analyzed for TMB and LOH to select patients for treatment.

[0095] Computing Devices As one of ordinary skill in the art will recognize as necessary or best suited, performance of the methods provided herein may involve one or more computing devices, systems, or computers including one or more of a processor (e.g., a central processing unit (CPU), a graphics processing unit (GPU), etc.), computer-readable storage devices (e.g., main memory, static memory, etc.), or combinations thereof in communication with each other via a bus.

[0096] The processor may include any suitable processor known in the art, such as the processor sold under the trademark XEON E7 by Intel (Santa Clara, Calif.) or the processor sold under the trademark OPTERON 6200 by AMD (Sunnyvale, Calif.).

[0097] The memory preferably includes at least one tangible, non-transitory medium capable of storing one or more sets of executable instructions (e.g., software embodying any methodology or functionality found herein, or computer programs referred to above) to cause the system to perform the functions described herein, data (e.g., source images of pharmaceutical data, personal data, or pharmaceutical databases), or both. Although the computer-readable storage device may be a single medium in an exemplary embodiment, the term "computer-readable storage device" should be interpreted to include a single medium or multiple media (e.g., a centralized or distributed database, and / or associated caches and servers) that store instructions or data. Thus, the term "computer-readable storage device" is interpreted to include, but is not limited to, solid-state memory (e.g., a subscriber identity module (SIM) card, a secure digital card (SD card), a micro SD card, or a solid-state drive (SSD)), optical and magnetic media, and any other tangible storage medium.

[0098] Any suitable service may be used for storage, such as Amazon Web Services, memory of a computing system, cloud storage, a server, or other computer readable storage.

[0099] The input / output devices of the methods provided herein may include one or more of a display unit (e.g., a liquid crystal display (LCD) or cathode ray tube (CRT) monitor), an alphanumeric input device (e.g., a keyboard), a cursor control device (e.g., a mouse or trackpad), a disk drive unit, a printer, a signal generating device (e.g., a speaker), a touch screen, a button, an accelerometer, a microphone, a cellular radio frequency antenna, a network interface device, which may be, for example, a network interface card (NIC), a Wi-Fi card, or a cellular modem, or any combination thereof.

[0100] Those skilled in the art will recognize that any suitable development environment or programming language may be used to implement the methods described herein. For example, the methods herein may be implemented using Perl, Python, C++, C#, Java, JavaScript, Visual Basic, Ruby on Rails, Groovy and Grails, or any other suitable tools. For mobile devices, it may be preferable to use native xCode or Android Java.

[0101] As used herein, the singular forms "a," "an," and "the" include plural references unless the context clearly dictates otherwise. Thus, for example, reference to "the method" includes one or more methods, and / or steps of the type described herein that will become apparent to those skilled in the art upon reading this disclosure, and so forth.

[0102] As used herein, "about" when referring to a measurable value, such as an amount, duration in time, and the like, is meant to encompass a variation of ±20%, or ±10%, or ±5%, or even ±1% from the specified value, where such variations are appropriate for or for practicing the disclosed methods. The term "about" may be used interchangeably with the term "approximately," unless clearly contradicted by context.

[0103] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0104] As used herein, the term "protein" refers to any polymeric chain of amino acids. The terms "peptide" and "polypeptide" are used interchangeably with the term "protein" and also refer to a polymeric chain of amino acids. The term "protein" encompasses natural or artificial proteins, protein fragments, and polypeptide analogs of protein sequences. Proteins may be monomeric or polymeric. The term "protein" encompasses fragments and mutants thereof (including variant fragments), unless otherwise contradicted by context.

[0105] As used herein, the term "nucleic acid" refers to any deoxyribonucleic acid (DNA) molecule, ribonucleic acid (RNA) molecule, or nucleic acid analog. The DNA or RNA molecule may be double-stranded or single-stranded and may have any size. Exemplary nucleic acids include, but are not limited to, chromosomal DNA, plasmid DNA, cDNA, cell-free DNA (cfDNA), mRNA, tRNA, rRNA, siRNA, microRNA (miRNA or miR), hnRNA. Exemplary nucleic acid analogs include peptide nucleic acid, morpholino and locked nucleic acid, glycol nucleic acid, and threose nucleic acid.

[0106] As used herein, the term "patient" refers to any individual or subject on which the method disclosed herein is carried out. The term "patient" can be used interchangeably with the term "individual" or "subject". As will be understood by those skilled in the art, a patient can be an animal, but a patient can also be a human. Thus, other animals are included in the definition of a patient, including farm animals, including rodents (including mice, rats, hamsters and guinea pigs), cats, dogs, rabbits, cows, horses, goats, sheep, pigs, etc., as well as mammals, such as primates (including monkeys, chimpanzees, orangutans and gorillas).

[0107] As used herein, the terms "sample" and "biological sample" refer to any sample suitable for the method provided herein. The sample used in the method can be obtained from a tissue sample or body fluid from a subject, or from tissue obtained by biopsy procedure (e.g., needle biopsy) or surgical procedure. In certain embodiments, the biological sample of the method is, for example, a sample of body fluid, such as cerebrospinal fluid (CSF), blood, serum, plasma, urine, saliva, tears, and ascites. The sample of body fluid can be collected by any suitable method known to those skilled in the art.

[0108] The following patent applications provide background teachings of the present invention and are incorporated herein by reference in their entireties: PCT / US2017 / 052908, PCT / US2015 / 062208, PCT / US2017 / 038942, PCT / US2017 / 056557, PCT / US2018 / 013637, PCT / US2016 / 042288, US20180064793A1, US20180251553A1, US20170016075A1, EP3288581A1, and EP3347039A1. EXAMPLES

[0109] Materials and Methods of the Examples In a heterogeneous sample consisting of a mixture of tumor and normal cells, heterozygous sites in regions affected by loss of heterozygosity (LOH) in the tumor fraction are generally reported, for example, as having an allele frequency (AF) of more than 50%, rather than the expected AF of 50%. Without being limited by theory, HLA is extremely difficult to sequence via hybrid capture due to high variability in the general population. The method provided herein circumvents this difficulty by utilizing deviations from 50% AF values ​​for heterozygous sites in the vicinity of HLA class I for detection of LOH.

[0110] Without being limited by theory, the actual AF of the heterozygous site in the region with LOH varies according to the tumor purity of the sample as represented by the percentage of tumor cells. For example, samples with high tumor purity have AF with a relative deviation higher than 50%, while samples with low tumor purity generally show a relative low deviation. Allele frequency may also be affected by allele-specific copy number changes. The method provided herein applies correction and normalization based on the tumor purity estimate of the sample and potential copy number changes to improve the detection accuracy of LOH on HLA class I.

[0111] The reference set for evaluating the accuracy of the developed algorithm (e.g., Example 1 below) was defined by sequencing and analyzing exome data from 226 formalin-fixed paraffin-embedded (FFPE) specimens of non-small cell lung cancer (NSCLC) and corresponding matched normal samples. The algorithm was trained using the PGDx elio™ tissue complete assay (PGDxETC), which targets more than 500 genes and encompasses 1.3 Mb, and measures TMB and latent antigen presentation (LOH of MHC) in the same assay. 20 of the 226 samples were used for training. The remaining 206 samples were used to validate the results.

[0112] Example 1 This example describes the training of algorithms for the analysis of TMB and LOH.

[0113] As described above (Materials and Methods), we developed an algorithm for determining MHC class I LOH (MHC LOH) using the PGDx elio™ tissue complete assay, a tissue-based genomic profiling assay that targets over 500 genes. A reference set for assessing the accuracy of this algorithm was defined by sequencing and analyzing exome datasets from 226 formalin-fixed, paraffin-embedded (FFPE) specimens of non-small cell lung cancer (NSCLC) and corresponding matched normal samples (Figures 2A and 2B).

[0114] The algorithm was first trained using PGDx elio tissue complete on a subset of 20 of the 226 samples and then validated using data associated with the remaining 206 samples.

[0115] The data show that LOH of chromosomes 6 (MHC), 10, 12 (LOH of the long arm only), 15 (B2M), 18, 19, and 21 was detected by analysis of allele frequencies of polymorphic sites reported by exome sequencing of tumor and normal samples from the same individuals.

[0116] Example 2 This example describes the correlation of LOH-MHC detection between WES and PGDx elio™ tissue complete.

[0117] The concordance between predicted MHC LOH reported by PGDx elio™ tissue complete and observed MHC LOH based on exome sequencing of the same samples is shown in Table 2 below.

[0118] Table 2: Correlation of LOH MHC detection between WES and PGDx elio™ tissue complete (206 samples) TIFF0007623281000002.tif74148

[0119] PGDx elio™ tissue complete had an overall 88% concordance with the reference set of exome-based sequence analysis of 206 NSCLC samples when determining MHC LOH (Table 2). When considering only samples with tumor purity >35% (n=86), the overall concordance increased to 94%. PPA: positive concordance, NPA: negative concordance, OPA: overall concordance, CI: confidence interval.

[0120] The results of the analysis of 78 NSCLC samples and the distribution of tumor purity of the 78 samples are shown in Table 3 and Figures 3A-B, respectively.

[0121] Table 3. Correlation of LOH MHC detection between WES and PGDx elio™ tissue complete (78 samples) TIFF0007623281000003.tif69149

[0122] PGDx elio™ tissue complete had an overall 88% concordance with the reference set of exome-based sequence analysis of 78 NSCLC samples when determining MHC LOH (Table 3). When considering only samples with tumor purity >35% (n=31), the overall concordance increased to 97%. PPA: positive concordance, NPA: negative concordance, OPA: overall concordance, CI: confidence interval.

[0123] The distribution of tumor purity across 78 samples assessed for MHC status between whole exome sequencing and PGDx elio™ tissue complete is shown in Figure 3A. Figure 3B shows the distribution of tumor purity among cases assigned an incorrect MHC status. False positives (3 cases) and false negatives (6 cases) of MHC LOH (Table 3) were associated with low tumor purity. More specifically, discordance was observed in specimens with tumor purity below 35%.

[0124] These data show a correlation of LOH-MHC detection between WES and PGDx elio™ complete.

[0125] Example 3 This example describes the in silico correlation of TMB and MHC status to clinical outcome in NSCLC patients.

[0126] The hypothesis that TMB should be considered together with the ability of tumors to present these putative neo-antigens as a predictor of responsiveness to checkpoint inhibitor therapy was next evaluated. PGDx elio™ tissue complete results were simulated in silico from a published NSCLC cohort with available WES data and patient outcome results to checkpoint inhibitor treatment (Rizvi NA, et al. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science. 2015 Apr 3;348(6230):124-8). Patients were stratified into TMB low (≤120 mutations per exome, first from the left, dark grey) and TMB high (>120 mutations per exome), as well as into either normal MHC (third from the left, black) or LOH of MHC (second from the left, light grey) (Figure 4). Patients with TMB high and normal MHC (third from left, black) had better responses than patients with TMB high but LOH MHC (second from left, light grey) and patients with TMB low (first from left, dark grey). Patients with TMB high but LOH of MHC showed similar survival patterns to TMB low cases, the latter of which were considered less likely to be responders to checkpoint inhibitor treatment.

[0127] The results shown in Figure 4 confirmed the hypothesis that it is possible to measure TMB and assess potential antigen presentation in the same NGS assay. Without being limited to theory, loss of antigen presentation caused by mutations and loss of heterozygosity (LOH) in MHC class I genes has been shown to be a common means of evading CD8+ T cell destruction, so monitoring MHC status may enhance the utility of TMB to predict responsiveness.

[0128] For the above mentioned panel of 34 NSCLC samples analyzed by whole exome sequencing and for which checkpoint inhibitor therapy (pembrolizumab) outcomes are publicly available (Rizvi NA, et al. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science. 2015 Apr 3;348(6230):124-8), the PGDx elio™ tissue complete panel was simulated by removing exome-derived regions not present in the PGDx elio™ tissue complete panel. The methods of the present invention show that progression-free survival (PFS) is shorter in high TMB patients with LOH of MHC class I genes compared to high TMB patients with normal MHC class I genes (see, e.g., Figures 2-4 and Tables 2-3). Therefore, the addition of NGS analysis of two genes of the antigen-presenting complex (MHC class I and B2M) to the current TMB testing using the PGDx elio™ tissue complete panel provides a better prediction of outcome for cancer patients being considered for treatment with checkpoint inhibitors, including but not limited to pembrolizumab and nivolimumab.

[0129] In summary, patients with TMB-low (≤120 mutations per exome) or TMB-high but predicted MHC LOH had a worse outcome than patients with high TMB and intact MHC, with a higher hazard ratio (7.9, CI95% 1.3–49). A study of 190 cancer patients showed that MHC class I LOH can be detected with 88% accuracy in FFPE tissue samples with ≥20% tumor content. These results support the use of a combined assessment of TMB and antigen presentation potential to predict patient outcome. Thus, patients with high gene mutation burden may have a different response to immunotherapy depending on their MHC status (Table 4).

[0130] Table 4. Prediction of likelihood of responder to immune checkpoint inhibitor therapy by MHC status TIFF0007623281000004.tif23148

[0131] Without being limited by theory, the inventors found that, although unexpected, there appears to be a very strong biological effect to see the difference in survival rate in such a small sample set (n=34). It would be possible to see such results using whole exome sequencing. However, using the PGDx elio™ tissue complete test with only a limited set of genes, for example, only 71 ROIs in 6p21 around HLA class I genes, it was unclear and unpredictable whether the genes were close enough or whether the 507 gene panel would need to be redesigned to include MHC class I genes themselves. In one embodiment, MHC class I genes could be added to the 507 genes (or any other gene panel) in the PGDx elio™ tissue complete test, or a novel machine learning approach could potentially be applied to LOH detection.

[0132] Taken together, this data demonstrates the ability of PGDx elio™ tissue complete to measure TMB and evaluate genes involved in antigen presentation in a single next generation sequencing product in development. This data further shows that TMB and MHC status were correlated in silico with clinical outcomes in NSCLC patients. Without being limited by theory, these data support the consideration of TMB along with the ability of tumors to present putative neo-antigens as measured by LOH of MHC, for example, to determine treatment regimens and select patients for treatment with immunotherapy, such as checkpoint inhibitor therapy.

[0133] Example 4 This example describes the analysis of somatic alterations of TMB and antigen-presenting complexes in cancer.

[0134] Samples from cancers including, but not limited to, breast cancer, pancreatic cancer, lung cancer, melanoma, hematopoietic cancer, leukemia, colon cancer, kidney cancer, head and neck cancer, brain cancer, bone cancer, ovarian cancer, cervical cancer, endometrial cancer, and prostate cancer are analyzed using the algorithm and PGDx elio™ tissue complete assay described above in Examples 1-3. Both fresh and lyophilized or preserved tissue samples can be analyzed, including formalin-fixed paraffin-embedded (FFPE) tissues or tissues preserved by any other method known in the art.

[0135] The combination of TMB and LOH measurements at MHC class I and / or B2M locus is used to determine responsiveness to immunotherapy, such as checkpoint inhibitor therapy. For example, cancer samples that show high TMB and no LOH or no abnormality at MHC class I and / or B2M locus show positive responsiveness to immunotherapy, such as checkpoint inhibitor therapy. Thus, the patient from whom the sample is taken is likely to be a responder and can be selected to receive immunotherapy, including checkpoint inhibitor therapy. Patients whose samples show low TMB and no LOH (i.e., no abnormality at MHC class I and / or B2M locus) and patients whose samples show LOH or abnormality at MHC class I and / or B2M locus in either low TMB or high TMB situations are unlikely to be responders to immunotherapy, such as checkpoint inhibitor therapy. Thus, these patients may not be selected for immunotherapy, such as checkpoint inhibitor therapy, but may be selected for other treatment regimens.

[0136] In summary, the methods provided herein can be used to predict a patient's response to a therapeutic regimen, to select a therapeutic regimen for the treatment of cancer, and to select patients for treatment with immunotherapy.

[0137] Example 5 This example demonstrates testing for loss of heterozygosity (LOH) using PGDx elio™ complete (Wolverine).

[0138] Without being limited by theory, LOH of MHC class I and β2M genes is associated with resistance to immunotherapy by preventing neoantigen presentation by tumor cells. Whether the PGDx elio™ complete (Wolverine) panel could reliably detect LOH of MHC class I genes on chromosome 6p21 was tested, as described further below. Furthermore, whether analysis of LOH status of MHC class I genes in combination with tumor mutation burden (TMB) improves outcome prediction for cancer patients treated with checkpoint inhibitors such as, for example, pembrolizumab (KEYTRUDA), nivolumab (OPDIVO), atezolizumab (TECENTRIQ), avelumab (BAVENCIO), durvalumab (IMFINZI), or ipilimumab (YERVOY) was evaluated (e.g., Examples 3 and 4 above).

[0139] The effects of single and double mutations in maternal and paternal MHC genes are shown in Figure 5. Mutations in both maternal and paternal MHC alleles cause loss of MHC presentation. The correlation between heterozygosity and allele frequency for LOH testing is shown in Figure 6. Heterozygosity can be used to confirm loss of chromosomal regions. Heterozygosity is directly proportional to allele frequency and has a variability of 0.0-0.5 per locus. Without being limited by theory, LOH can be inferred by the presence of consecutive homozygosity that cannot occur by chance in diploid cells. For example, long stretches of homozygosity are more likely to result from somatic loss of chromosomal regions than from the distributed chance of homozygosity at adjacent single nucleotide polymorphisms (SNPs).

[0140] The MHC region on chromosome 6p21 is shown in Figure 7. The region of chromosome 6 between 28, 510, 120-33, 480, 577 spans all or nearly all of the HLA genes, such as the exemplary genes shown in Table 5.

[0141] (Table 5) The regions 28, 510, 120-33, 480, and 577 on chromosome 6 span all / most HLA genes. TIFF0007623281000005.tif93128

[0142] In the initial analysis, the length of the region investigated spanned 4,970,457 Mb (approximately 5 Mb). A total of 102 samples were evaluated. For the exome analysis, the number of non-overlapping exons in this region was 1750. The total length of exons in this region was approximately 727 kb (approximately 14%). The number of heterozygous sites investigated in the exome data was 1217. For the analysis using the PGDx elio™ complete (Wolverine) panel, the number of regions of interest (ROIs) in the region was 71. The total length of ROIs in this region was approximately 19 kb (approximately 0.4%). The number of heterozygous sites investigated in these ROIs was 52. Samples selected at the two ends of the spectrum to evaluate the detection of LOH using the PGDx elio™ complete (Wolverine) panel are shown in Figure 8.

[0143] Figures 9A and 9B show confirmation of the LOH signal obtained using PGDx elio™ complete (Wolverine) by exome data of the same samples. Samples identified by PGDx elio™ complete (Wolverine) as heterozygote (0448) and homozygote (0426) are shown. The plot shown in Figure 9A shows the whole exome sequencing (WES) data confirming sample 0048 as a heterozygote. The plot shown in Figure 9B shows the whole exome sequencing (WES) data confirming sample 0426 as a homozygote. Thus, the WES data confirmed the LOH call made using PGDx elio™ complete (Wolverine).

[0144] Figures 10A and 10B show that the LOH of MHC in sample PGRD00426 was specific to the tumor fraction as confirmed by WES. Using PGDx elio™ complete (Wolverine), the LOH calls in the tumor sample confirmed by WES (Figure 10A) were not found in the matched normal sample from the same patient (Figure 10B). These results confirmed that the LOH was tumor specific.

[0145] Taken together, these data show that PGDx elio™ complete (Wolverine) can report LOH at chromosome 6p in the MHC class I gene cluster and report loss of the entire chromosome 6. Analysis using the 52 SNPs described above in the MHC gene cluster showed good agreement with the exome data. Without being limited by theory, the addition of LOH detection to PGDx elio™ complete (Wolverine) provides the best prediction of class I immunotherapy response, as described in detail above (e.g., Examples 3-4), clearly distinguishing the method for TMB testing provided herein from other methods.

[0146] Without being limited by theory, the detection of LOH MHC using PGDx elio™ complete (Wolverine) can be improved, for example, by using a more refined algorithm. As an example, the number of SNPs evaluated can be expanded by expanding the region analyzed. Without being limited by theory, such expansion is possible because most LOH cases are due to loss or complete loss of one arm of chromosome 6. In addition, copy number changes (CNV) and tumor purity estimates may be included. In addition to this, a better cutoff for calling LOH using PGDx elio™ complete (Wolverine) can be defined based on LOH of tumor exome data as a standard (e.g., for samples used in TMB test).

[0147] Although the invention has been described with reference to the above examples, it will be understood that modifications and variations are encompassed within the spirit and scope of the invention. Accordingly, the invention is limited only by the scope of the following claims.

Claims

1. 1. A method for determining a treatment regimen for a cancer patient, comprising: determining a tumor mutational burden (TMB) score for the patient based on nucleic acid in a sample from the patient, wherein the TMB score is determined based on the number of mutations per megabase (Mb); determining loss of heterozygosity (LOH) status in a region within 10 bp to 200 bp of a major histocompatibility complex (MHC) class I gene; and determining a treatment regimen for the patient, (i) the treatment regimen comprising indicating a positive outcome if the patient is treated with a checkpoint inhibitor when the patient has a high TMB score and no LOH, and (ii) the treatment regimen comprises indicating a negative outcome if the patient is treated with a checkpoint inhibitor when the patient has a high TMB score with LOH, where a high TMB score occurs when there are more than 120 mutations per exome; The method comprising:

2. The method of claim 1 , wherein the cancer is a tumor.

3. 10. The method of claim 1, wherein the sample is derived from blood, saliva, plasma, serum, urine, or other biological fluid.

4. The method of claim 1 , wherein the sample is from a tumor.

5. 2. The method of claim 1, wherein the LOH status is determined using data used to determine a TMB score.

6. MHC class I genes are HLA-F, HLA-V, HLA-P, HLA-G, HLA-H, HLA-T, HLA-K, HLA-U, HLA-A, HLA-W, HLA-J, HLA-L, HLA -N, HLA-E, HLA-C, HLA-B, HLA-S, HLA-DRA, HLA-DRB9, HLA-DRB5, HLA-DRB6, HLA-DRB1, HLA-DQA1, HLA-DQB1 2. The method of claim 1, comprising one or more human leukocyte antigen (HLA) genes selected from the group consisting of HLA-DQB1-AS1, HLA-DQB3, HLA-DQA2, HLA-DQB2, HLA-DOB, HLA-Z, HLA-DMB, HLA-DMA, HLA-DOA, HLA-DPA1, HLA-DPB1, HLA-DPA2, HLA-DPB2, and HLA-DPA3.

7. 2. The method of claim 1, wherein the cancer is selected from breast cancer, pancreatic cancer, lung cancer, melanoma, hematopoietic cancer and leukemia, colon cancer, kidney cancer, head and neck cancer, brain cancer, bone cancer, ovarian cancer, cervical cancer, endometrial cancer, and prostate cancer.

8. 2. The method of claim 1, wherein the checkpoint inhibitor is pembrolizumab (KEYTRUDA), nivolumab (OPDIVO), atezolizumab (TECENTRIQ), or ipilimumab (YERVOY).

9. 2. The method of claim 1, wherein determining the TMB score comprises sequencing one or more exomes or regions of the one or more exomes from the sample.

10. 2. The method of claim 1, wherein the tumor mutation comprises a neoantigen or neoepitope recognized by T cells.

11. 1. A method of selecting a cancer patient for treatment with a checkpoint inhibitor comprising selecting the patient for treatment with the checkpoint inhibitor if a sample obtained from the patient has a high tumor mutation burden (TMB) score in the absence of loss of heterozygosity (LOH), wherein the TMB score is determined based on the number of mutations per megabase (Mb), and the TMB score is high when there are more than 120 mutations per exome, and the LOH status is determined in a region within 10 bp to 200 bp of a major histocompatibility complex (MHC) class I gene.

12. 12. The method of claim 11, wherein the combination of no LOH and a high TMB score indicates a positive outcome when treated with the checkpoint inhibitor, and a high TMB score with LOH indicates a negative outcome.

13. The method of claim 11 , wherein the sample is a tumor sample.

14. 12. The method of claim 11, wherein the sample is derived from blood, saliva, plasma, serum, urine, or other biological fluid.

15. 12. The method of claim 11, wherein the LOH status is determined using data used to determine a TMB score.

16. MHC class I genes are HLA-F, HLA-V, HLA-P, HLA-G, HLA-H, HLA-T, HLA-K, HLA-U, HLA-A, HLA-W, HLA-J, HLA-L, HLA- N, HLA-E, HLA-C, HLA-B, HLA-S, HLA-DRA, HLA-DRB9, HLA-DRB5, HLA-DRB6, HLA-DRB1, HLA-DQA1, HLA-DQB1, 12. The method of claim 11, comprising one or more human leukocyte antigen (HLA) genes selected from the group consisting of HLA-DQB1-AS1, HLA-DQB3, HLA-DQA2, HLA-DQB2, HLA-DOB, HLA-Z, HLA-DMB, HLA-DMA, HLA-DOA, HLA-DPA1, HLA-DPB1, HLA-DPA2, HLA-DPB2, and HLA-DPA3.

17. 12. The method of claim 11, wherein the cancer is selected from breast cancer, pancreatic cancer, lung cancer, melanoma, hematopoietic cancer and leukemia, colon cancer, kidney cancer, head and neck cancer, brain cancer, bone cancer, ovarian cancer, cervical cancer, endometrial cancer, and prostate cancer.

18. 12. The method of claim 11, wherein the checkpoint inhibitor is pembrolizumab (KEYTRUDA), nivolumab (OPDIVO), atezolizumab (TECENTRIQ), avelumab (BAVENCIO), durvalumab (IMFINZI), or ipilimumab (YERVOY).

19. 12. The method of claim 11, wherein determining the TMB score and LOH status comprises sequencing one or more exomes or regions of the one or more exomes from the sample.

20. The method of claim 11 , wherein the tumor mutation comprises a neoantigen or neoepitope recognized by T cells.

21. A composition for treating a cancer patient selected according to the method of any one of claims 11 to 20, comprising an effective amount of said checkpoint inhibitor.

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