Composition for treating cancer

Abstract

Provided is a composition for treating cancer in a subject, the composition containing: a nucleic acid which encodes a peptide that includes at least one non-self MHC Class I restricted epitope and at least one non-self MHC Class II restricted epitope; or cells which express the peptide. Also provided is a method comprising analyzing a gene for a cancer tissue obtained from a subject, and determining whether or not a non-self antigen peptide that comprises a non-self amino acid sequence having a longer length than a cut-off value is present in the cancer tissue.

Description

Compositions for treating cancer

[0001] This patent application claims priority to Japanese Patent Application No. 2024-070825, the entire contents of which are incorporated herein by reference. The present disclosure relates to a composition for treating cancer. The present disclosure also relates to a method for predicting the prognosis of a subject suffering from cancer or a method for predicting whether a subject's cancer will respond to an immune checkpoint inhibitor.

[0002] The immune system has the potential to fight cancer, but this ability is inhibited by the expression of immune checkpoint molecules on immune cells. Immune checkpoint blockade (ICB) using PD-1-blocking antibodies can unleash antitumor immunity, and cancer immunotherapy has shown promising clinical efficacy in patients with various types of cancer. However, durable responses are only achieved in 31-44% of patients with advanced melanoma, 22-25% of patients with renal cell carcinoma, and 19-20% of patients with non-small cell lung cancer. Therefore, there is a need to develop strategies to help overcome ICB non-response.

[0003] Cancer neoantigens are non-self proteins with individual specificities, generated by nonsynonymous mutations in the tumor cell genome. Cancer neoantigens are not expressed in normal tissues and have strong immunogenicity. One of the important factors that determines whether a mutation can be a tumor rejection antigen is the affinity of the mutant peptide with MHC class I (MHC-I) or MHC class II (MHC-II). Many studies have shown that the abundance of cancer neoantigens and cancer neoantigen-specific CD8 ＋ The accumulation of tumor-infiltrating lymphocytes (TILs) has been shown to be associated with ICB responsiveness.

[0004] Recently, it has been reported that MHC-II-restricted antigens expressed by tumor cells are required for tumor elimination. ＋ There is increasing evidence of the importance of T helper cells, and CD4 ＋ It has been shown that an increase in the proportion of tumor-specific CD4 T cells correlates with a positive clinical outcome after ICB. ＋ T cells are essentially tumor-specific CD8 ＋These cells regulate the tumor microenvironment (TME) through cytokine secretion or costimulatory signals, and support CD8 ＋ CD8 via "licensed" dendritic cells for T cell priming ＋ Facilitates T cell responses. CD8 to the TME ＋ T cell infiltration is CD4 ＋ It is promoted by T cells. ＋ CD8 with help from T cells ＋ T cells are CD8 ＋ They have stronger effector functions than T cells and express less immune checkpoint inhibitor molecules. However, it is unclear what kind of cancer neoantigens are effective against CD4 ＋ Enhances the helper function of T cells and CD8 ＋ It is unclear whether it promotes the tumoricidal activity of T cells.

[0005] CD8 in TME or chronic viral infection ＋ A hallmark of T cell responses is their exhaustion, a dysfunctional state that occurs as an adaptation to chronic antigen exposure. The exhaustion process requires the production of low numbers of CD8 T cells for long-term protective immunity. ＋ After the proliferation phase, T cells become memory CD8 ＋ Unlike a normal immune response, which generates T cells, in exhaustion, persistent CD8 ＋ T cells undergo a hierarchical loss of effector function, leading to a hyporesponsive state and eventual clonal deletion, with a decline in antitumor efficacy and cytotoxicity. ＋ TILs have stem cell-like characteristics, such as long-term persistence and spontaneous differentiation into terminally exhausted TILs. These proliferative effector memory T cells have been shown to respond to ICB by rapid proliferation, resulting in an expansion of effector cells and enhanced cytotoxicity. Stem cell-like precursor CD8 ＋ The optimal strategy to increase TIL infiltration and thereby enhance the efficacy of ICB is unknown.

[0006] Takahashi N, et al., First clinical trial of cancer vaccine therapy with artificially synthesized helper / killer-hybrid epitope long peptide of MAGE-A4 cancer antigen. Cancer Sci. 2012 Jan;103(1):150-3.CM Smith et al., Cognate CD4(+) T cell licensing of dendritic cells in CD8(+) T cell immunity. Nat Immunol 5, 1143-1148 (2004).Renard V, et al., HER-2 DNA and protein vaccines containing potent Th cell epitopes induce distinct protective and therapeutic antitumor responses in HER-2 transgenic mice. J Immunol. 2003 Aug 1;171(3):1588-95.

[0007] An object of the present disclosure is to provide a composition for treating cancer.An object of the present disclosure is to provide a method for predicting the prognosis of a subject suffering from cancer or a method for predicting whether an immune checkpoint inhibitor will be effective against the subject's cancer.

[0008] The present inventors have discovered that cancer in a subject can be treated by expressing in vivo a peptide comprising a non-self MHC class I-restricted epitope and a non-self MHC class II-restricted epitope.

[0009] Thus, in one aspect, a composition for treating cancer in a subject is provided, comprising a nucleic acid encoding a peptide comprising at least one non-self MHC class I-restricted epitope and at least one non-self MHC class II-restricted epitope.

[0010] In one aspect, a composition for treating cancer in a subject is provided, comprising cells expressing a peptide comprising at least one non-self MHC class I-restricted epitope and at least one non-self MHC class II-restricted epitope.

[0011] Furthermore, the present inventors have found that cancer patients with non-self antigen peptides containing long non-self amino acid sequences have a good prognosis and may respond well to immune checkpoint inhibitors.

[0012] Therefore, in one aspect, there is provided a method for predicting the prognosis of a subject suffering from cancer, comprising: (1) analyzing the genes of cancer tissue obtained from the subject and determining whether or not the cancer tissue contains a non-self antigen peptide containing a non-self amino acid sequence that is longer than a cutoff value; and (2) predicting that the subject will have a good prognosis if the non-self antigen peptide is present in the cancer tissue.

[0013] In one aspect, a method for predicting whether an immune checkpoint inhibitor will be effective against a subject's cancer is provided, comprising: (1) analyzing the genes of cancer tissue obtained from the subject to determine whether a non-self antigen peptide containing a non-self amino acid sequence longer than a cutoff value is present in the cancer tissue; and (2) predicting that the immune checkpoint inhibitor will be effective against the subject's cancer if the non-self antigen peptide is present in the cancer tissue.

[0014] The present disclosure is useful for treating cancer or predicting the prognosis of a subject suffering from cancer, or for predicting whether a subject's cancer will respond to an immune checkpoint inhibitor.

[0015] Figure 1 shows the tumor volumes of Bpmel-parent (left panel) and Bpmel-OVA (right panel) mice with and without anti-PD-L1 therapy (n=5 / group). The left panel is a schematic diagram of the cellular adjuvant model. Mice were injected with Bpmel-parent mice into the left flank. One week after inoculation, Bpmel-OVA, which served as a cellular adjuvant, was injected intradermally (i.d.), and anti-PD-L1 therapy was initiated on day 14. The right panel shows the tumor volumes of Bpmel-parent mice (n=5 / group). ***p<0.001. Figure 1 shows the tumor volumes of Bpmel-parent mice upon i.d. injection of Bpmel-OVA or MC38-OVA as a cellular adjuvant (n=5 / group). *p<0.05. Schematic diagram of OVA antigen. Tumor volumes of Bpmel-OVAI (left panel) and Bpmel-OVAII (right panel) with and without anti-PD-L1 therapy are shown (n=5 / group).

[0016] The left figure is a schematic diagram of the cellular adjuvant model. Bpmel-OVA, Bpmel-OVAI, or Bpmel-OVAII was injected i.d. as a cellular adjuvant. The right figure shows the tumor volume of Bpmel-parent mice (n=5 / group). **p<0.01. Adpgk ＭＵＴ Schematic diagram of OVAII (upper panel) and OVAI-Ea (lower panel). The left panel shows Bpmel-Adpgk as a cellular adjuvant. ＭＵＴ The figure shows the tumor volume of Bpmel-parent mice injected with Bpmel-OVAI-Ea and anti-PD-L1 (n=5 / group). The right panel shows the tumor volume of MC38 tumors injected with Bpmel-OVAI-Ea as a cellular adjuvant together with anti-PD-L1. *p<0.05. Schematic diagrams of Bpmel-SIY-OVAII / EGFP and Bpmel-SIY-EGFP / OVAII. The SIY and OVAII epitopes were expressed chimerically in Bpmel-SIY-OVAII / EGFP and separately in Bpmel-SIY-EGFP / OVAII. Seven days after injection of Bpmel-SIY-OVAII / EGFP or Bpmel-SIY-EGFP / OVAII, SIY-specific CD8 ＋ It shows that T cells were detected.

[0017] The left panel shows a schematic diagram of the cellular adjuvant model. MC38 was injected into C57BL / 6-Tg (CAG-EGFP) mice, and on day 9, Bpmel-SIY-OVAII / EGFP or Bpmel-SIY-EGFP / OVAII was injected as a cellular adjuvant into the opposite flank. The right panel shows the results of measuring MC38 tumor growth (n=5 / group). *p<0.05. Seven days after injection of Bpmel-OVA or OVA protein, OVAI-specific CD8+ cells were expressed in draining lymph node (DLN) cells using OVAI-MHC tetramers. ＋ T cells were detected. Tumor volumes of MC38 cells after i.d. injection of Bpmel-OVA cell adjuvant or OVA protein (200 μg / mouse) into the opposite flank (n=5 / group). **p<0.01. CD45 in tumors ＋ CD8 in cells ＋ The frequency of T cells is shown. **p<0.01. Adpgk ＭＵＴ Adpgk infiltrating MC38 assessed using / MHC pentamer ＭＵＴ specific CD8 ＋ The frequency of T cells is shown. *p<0.05.

[0018] 1 shows the experimental procedure for the MC38 model treated with Bpmel-SIY-OVAII cell adjuvant. Figure 1 shows tumor-infiltrating CD8+ cells on day 15 in MC38 tumor-bearing mice treated with or without Bpmel-SIY-OVAII cell adjuvant. ＋ TIM3 in T cells ＋ PD1 ＋ The percentage of CD8 cells infiltrating tumors on day 12 in MC38 tumor-bearing mice with and without Bpmel-SIY-OVAII cell adjuvant treatment is shown (n=3 / group). *p<0.05. ＋ Slamf6 in T cells ＋ PD1 － The percentage of CD8 cells from MC38 tumors with and without Bpmel-SIY-OVAII cell adjuvant treatment is shown (n=3 / group). **p<0.01. ＋Uniform manifold approximation and projection (UMAP) of TILs (SIY-OVAII TILs: n=19,946, control TILs: n=10,357) is shown. Eleven clusters were identified by Seurat. UMAP of all annotated cells obtained from the TIL phenotyping software ProjecTILs is shown.

[0019] Each CD8 based on the projection results obtained from ProjecTILs ＋ The percentage of TIL population is shown. ＋ This is a volcano plot showing differential gene expression (DEG) between the control group and the SIY-OVAII group for TIL (Tex+Tpex). ＋ Volcano plot showing DEGs between the control and SIY-OVAII groups for effector memory TILs. Experimental procedures for the MC38 model with CD4 depletion are shown. The left panel shows the MC38 tumor volume with and without Bpmel-OVAI-Ea cell adjuvant treatment. The right panel shows the CD4 ＋ MC38 tumor volumes with and without Bpmel-OVAI-Ea cellular adjuvant treatment after T cell depletion are shown, n=5 / group.

[0020] Figure 1 shows the UMAP of DLN cells (SO: n=18,440, control: n=10,952), excluding naive T cells, from MC38 tumor-bearing mice with and without Bpmel-SIY-OVAII cell adjuvant treatment. Scatter plot of interaction strength into and out of each cell population in the DLN. Bubble plot of the probability of transmission of all significant ligand-receptor pairs (Y-axis) from dendritic cells to other populations (X-axis) with and without SIY-OVAII adjuvant treatment. The top panel shows the DNA sequence of wild-type Notch2. The arrow indicates the site of deletion due to mutation. The bottom panel shows the DNA sequence of mutated Notch2 in MC38 cells based on whole-exome sequencing. EGFP or Notch2 ＭＵＴThe figures show the tumor volume in mice injected with Bpmel-parent cells overexpressing Bpmel (n=5 / group). ****p<0.0001.

[0021] The upper diagram shows the experimental procedure for the reinoculation experiment. The lower diagram shows the procedure for Notch2. ＭＵＴ Figure 1 shows the tumor volume of MC38 cells injected into mice that rejected or naive mice (n=5 / group). **p<0.01. Figure 2 shows the experimental procedure for the LLC model. Anti-PD-L1 mAb, Bpmel-Notch2 ＭＵＴ Cellular adjuvant (Bpmel-Notch2 ＭＵＴ ) or a combination thereof (Bpmel-Notch2 ＭＵＴ +PD-L1mAb) (n=5 / group). *p<0.05, **p<0.01. LLC tumor CD45 ＋ CD8 in the population ＋ or CD4 ＋ The percentage of T cells infiltrating the tumor is shown (n=4 / group, day 12). *p<0.05. ＋ FCM analysis of CD39 and PD1 expression on T cells (n=4 / group, day 12). *p<0.05, **p<0.01.

[0022] Tumor-infiltrating CD8 ＋ Figure 1 shows FCM analysis of SLAMF6 and PD1 expression in T cells (n=4 / group, day 12). *p<0.05, **p<0.01. Kaplan-Meier analysis of overall survival between patients with a maximum functional peptide length of more than 120 AA due to frameshift mutations (left panel), patients with a high and low tumor mutation burden (TMB) (center panel), and patients with a high and low number of frameshift mutations (FS) (right panel). The experimental procedure for immunization with pCAGGS-SIY-OVAII (complete T cell antigen) cDNA is shown. pCAGGS-SIY was used as a negative control. The tumor volume of MC38 tumors after electrotransfer of pCAGGS, pCAGGS-SIY, or pCAGGS-SIY-OVAII into the quadriceps muscle is shown. *p<0.05. Tumor-infiltrating CD8 ＋FCM analysis of 4-1BB, CD107a, CD127 and SLAMF6 expression in T cells (day 15). *p<0.05.

[0023] Unless otherwise specified, terms used herein have the meanings commonly understood by those skilled in the art of organic chemistry, medicine, pharmacology, molecular biology, microbiology, etc. Definitions of some terms used herein are provided below, but these definitions take precedence over common understandings in this specification.

[0024] As used herein, when a numerical value is accompanied by the term "about," it is intended to encompass a range of ±10% of that value. For example, "about 20" is intended to include "18 to 22." A range of numerical values ​​includes all values ​​between and at the endpoints. "About" in reference to a range applies to both endpoints of the range. Thus, for example, "about 20 to 30" is intended to include "18 to 33."

[0025] I. Compositions for Treating Cancer In the Examples described below, it was demonstrated in mouse models that anti-tumor immunity against various cancers can be enhanced by expressing peptides containing non-self MHC class I-restricted epitopes (MHC-I epitopes) and non-self MHC class II-restricted epitopes (MHC-II epitopes) in the body of a subject, or by administering to a subject a cellular adjuvant expressing the peptides. In the present disclosure, the peptides are referred to as complete T cell antigens (CTAs). Therefore, cancer in a subject can be treated by administering to the subject a nucleic acid encoding the peptide or a cell expressing the peptide.

[0026] Without being limited by theory, administration of a cellular adjuvant expressing a CTA may stimulate the proliferation of pro-CD8 ＋ Promotes T cell infiltration into tumor sites and CD8 ＋ CTA significantly inhibited T cell exhaustion and improved the response to immune checkpoint inhibitors. Furthermore, CTA exerted a broad antitumor effect independent of cancer neoantigen epitopes. Intracellular expression of CTA promoted crosstalk between dendritic cells and T cells in draining lymph nodes, and the antitumor effect of CTA was enhanced by CD4 ＋ It was T cell dependent.

[0027] In the present disclosure, the subject may be of any species, and is typically a mammal (e.g., human, mouse, rat, hamster, rabbit, cat, dog, cow, sheep, monkey, etc.). In some embodiments, the subject is a rodent, particularly a mouse. In some embodiments, the subject is a primate, particularly a human.

[0028] CTAs can exert antitumor effects even if their MHC-I and MHC-II epitopes are different from cancer neoantigen epitopes. Therefore, in the present disclosure, cancer may be any cancer, and may be primary or metastatic cancer. Examples of cancer include leukemia (e.g., acute myeloid leukemia, chronic myeloid leukemia, acute lymphocytic leukemia, chronic lymphocytic leukemia), malignant lymphoma (Hodgkin's lymphoma (e.g., classical Hodgkin's lymphoma)), non-Hodgkin's lymphoma (e.g., adult T-cell leukemia, follicular lymphoma, diffuse large B-cell lymphoma, primary mediastinal large B-cell lymphoma)), multiple myeloma, myelodysplastic syndrome, head and neck cancer (e.g., head and neck squamous cell carcinoma), gastrointestinal cancer (e.g., esophageal cancer, esophageal adenocarcinoma, esophagogastric junction adenocarcinoma, gastric cancer, colon cancer, rectal cancer, colorectal cancer), liver cancer (e.g., hepatocellular carcinoma), gallbladder / bile duct cancer, biliary tract cancer, pancreatic cancer, thyroid cancer, lung cancer (e.g., non-small cell lung cancer, and small cell lung cancer), breast cancer, genitourinary cancer (e.g., ovarian cancer (e.g., serous ovarian cancer), cervical cancer, uterine cancer, endometrial cancer, vaginal cancer, vulvar cancer, renal cancer (e.g., renal cell carcinoma), urothelial cancer (e.g., bladder cancer, upper urinary tract cancer), prostate cancer, testicular tumor (e.g., germ cell tumor)), bone and soft tissue sarcoma (e.g., alveolar soft part sarcoma), skin cancer (e.g., uveal malignant melanoma, malignant melanoma, Merkel cell carcinoma, cutaneous squamous cell carcinoma, basal cell carcinoma), neuroendocrine tumor, glioma, brain tumor (e.g., glioblastoma), malignant mesothelioma (e.g., malignant pleural mesothelioma), or cancer of unknown primary origin.

[0029] CTAs can improve tumor response to immune checkpoint inhibitors. Thus, in some embodiments, the cancer is a cancer that responds to immune checkpoint inhibitors, such as malignant melanoma, lung cancer, non-small cell lung cancer, small cell lung cancer, renal cell carcinoma, classical Hodgkin's lymphoma, head and neck cancer, head and neck squamous cell carcinoma, cutaneous squamous cell carcinoma, transitional cell carcinoma, gastric cancer, malignant pleural mesothelioma, malignant mesothelioma, colorectal cancer with high microsatellite instability (MSI-High) or mismatch repair deficient (dMMR), esophageal cancer, esophagogastric junction adenocarcinoma, cancer of unknown primary site, urothelial carcinoma, urinary tract cancer, and high frequency These cancers are those for which the use of immune checkpoint inhibitors has been approved by pharmaceutical regulatory authorities, such as solid tumors with microsatellite instability (MSI-High) or mismatch repair deficiency (dMMR), breast cancer, bladder cancer, uterine cancer, cervical cancer, endometrial cancer, solid tumors with a high tumor mutation burden (TMB-High), primary mediastinal large B-cell lymphoma, liver cancer, hepatocellular carcinoma, biliary tract cancer, Merkel cell carcinoma, alveolar soft part sarcoma, basal cell carcinoma, colon cancer, rectal cancer, colorectal cancer, and neuroendocrine tumors.

[0030] CTA is CD8 ＋ It can significantly inhibit T cell exhaustion, so it can effectively inhibit CD8 T cells regardless of the type of cancer. ＋ Cancers with a high T cell infiltration are likely to respond. Thus, in one embodiment, the cancer is CD8 ＋ This is a cancer with a high level of T cell infiltration. ＋ The amount of T cell infiltration can be evaluated, for example, by measuring the amount of binding of complexes between cancer neoantigen peptides and MHC using cancer tissue collected from a subject as a sample.

[0031] CTAs express cancer neoantigen-specific CD8 in immunogenic cancers, regardless of cancer type. ＋ It can promote T cell infiltration. Thus, in some embodiments, the cancer is an immunogenic cancer. Generally, cancers that respond to immune checkpoint inhibitors are immunogenic cancers.

[0032] CTA expresses tumor neoantigen-specific CD8 receptors regardless of the type of cancer, even in cancers with poor immunogenicity that do not respond to immune checkpoint inhibitors. ＋This may promote T cell infiltration. Thus, in some embodiments, the cancer is a poorly immunogenic cancer. Generally, cancers that do not respond to immune checkpoint inhibitors are poorly immunogenic cancers.

[0033] In some embodiments, the cancer is lung cancer, genitourinary cancer, gastrointestinal cancer, or liver cancer.

[0034] In some embodiments, the cancer is malignant melanoma, colon adenocarcinoma, or lung cancer.

[0035] In this disclosure, "treating" or "treatment" means reducing or eliminating cancer cells in a cancer patient, slowing or stopping the progression, recurrence or metastasis of cancer, reducing, alleviating, ameliorating or eliminating symptoms of cancer, and / or increasing the overall survival or recurrence-free survival of a cancer patient.

[0036] MHC is the abbreviation for major histocompatibility complex, which is responsible for antigen presentation in the immune system of vertebrates. In humans, MHC is called human leukocyte antigen (HLA). MHC class I, which is expressed in almost all nucleated cells, and MHC class II, which is expressed in B cells, dendritic cells, and macrophages, are known.

[0037] In the present disclosure, "MHC class I restriction" refers to the property of being able to bind to MHC class I molecules and activate cytotoxic T cells. HLA, which corresponds to MHC class I molecules, has three loci: HLA-A, -B, and -C, each of which has known polymorphisms (alleles). An MHC class I-restricted epitope (MHC-I epitope) refers to an epitope that binds to any subtype of MHC class I. Typically, an MHC-I epitope consists of 7 to 12 amino acid residues, preferably 8 to 9 amino acid residues. It is known that there is a regularity (binding motif) in the amino acid sequence of peptides that can bind to each HLA subtype. Whether a certain amino acid sequence is an MHC-I epitope can be determined, for example, by algorithms for this purpose (such as the NetMHCpan algorithm provided by the Immune Epitope Database and Analysis Resource (http: / / www.immuneepitope.org), RANKPEP, nHLAPred, or the Kernel-based Inter-allele peptide binding prediction System (KISS)). Sequences within the top 1% of affinity rankings can be determined to be high-affinity binders of MHC class I.

[0038] Cytotoxic T cell activity can be experimentally confirmed by producing peptides by conventional peptide synthesis or genetic engineering techniques and then testing them. For example, cytotoxic T cell activity can be confirmed by measuring the number of cytotoxic T cells using the HLA tetramer method (Int. J. Cancer: 100, 565-570 (2002)) or the limiting dilution method (Nat. Med.: 4, 321-327 (1998)). Other methods include stimulating T cells with a peptide and measuring cytokines, or culturing cell lines expressing the peptide. ５１ After labeling with Cr isotope and co-culturing with T cells, ５１ There is a method for measuring Cr.

[0039] In the present disclosure, "MHC class II restriction" refers to the property of being able to bind to MHC class II molecules and activate helper T cells. HLA, which corresponds to MHC class II molecules, has HLA-DR, DQ, and DP loci, each of which is known to have polymorphisms. An MHC class II-restricted epitope (MHC-II epitope) refers to an epitope that binds to any subtype of MHC class II. Typically, an MHC-II epitope consists of 9 to 30 amino acid residues, preferably 10 to 25 amino acid residues, more preferably 12 to 24 amino acid residues, and even more preferably 15 to 22 amino acid residues. It is known that there is a regularity (binding motif) in the amino acid sequence of peptides that can bind to each HLA subtype. Whether a certain amino acid sequence is an MHC-II epitope can be determined, for example, by hmMHC, an HMM-based binding prediction method, or by algorithms therefor (RANKPEP, SYFPEITHI, ProPred, MHC2Pred, SVMHC, etc.). Sequences within the top 1% of affinity rankings can be determined to be high-affinity binders of MHC class II.

[0040] To experimentally confirm helper T cell activity, peptides can be produced by conventional peptide synthesis or genetic engineering techniques and then tested. For example, helper T cell activity can be confirmed by the method described in Cancer Immunol. Immunother. 51: 271 (2002). Other methods include the HLA tetramer method (NatBiotechnol: 39, 958-967 (2021)) or a method in which helper T cells are stimulated with a peptide and cytokines are measured.

[0041] In this disclosure, "non-self" means that a component is not a normal constituent of a subject and is recognized by the immune system as not being a self component. For example, foreign proteins, proteins of pathogens such as viruses, and cancer neoantigens expressed by cancer cells are non-self.

[0042] A CTA comprises at least one non-self MHC-I epitope and at least one non-self MHC-II epitope. In the present disclosure, a "non-self MHC-I epitope" refers to an epitope among MHC-I epitopes that consists of an amino acid sequence not contained in normal components of a subject, and a "non-self MHC-II epitope" refers to an epitope among MHC-II epitopes that consists of an amino acid sequence not contained in normal components of a subject.

[0043] Non-self MHC-I epitopes and non-self MHC-II epitopes may be derived from any non-self protein or peptide, for example, from a heterologous protein, a pathogen protein, or a cancer neoantigen. Examples of heterologous proteins include proteins derived from food, plants, and marine products, and artificially synthesized proteins. Examples of pathogen proteins include proteins derived from viruses and bacteria. In the present disclosure, "cancer neoantigen" refers to a non-self peptide generated by mutations in the tumor cell genome. Mutations include, but are not limited to, frameshift mutations, splicing mutations, somatic mutations, insertion / deletion mutations, coding mutations, and base substitutions. Examples of cancer neoantigens include common cancer neoantigens, Adpgk mutants, and Notch2 mutants.

[0044] A CTA may contain multiple non-self MHC-I epitopes and / or multiple non-self MHC-II epitopes. The position of each epitope in a CTA is not limited. A CTA may contain any amino acid sequence between each epitope, at the N-terminus, or at the C-terminus. The length of a CTA is not limited, and may be, for example, about 16, 20, 30, 50, or 60 amino acids or more. Because a CTA is cleaved intracellularly and the fragments bind to MHC, there is no upper limit to the length of a CTA, but it may be, for example, about 5,000, 3,000, 1,000, 500, 300, 200, or 100 amino acids or less.

[0045] The CTA may comprise at least one of an HLA-A epitope, an HLA-B epitope, and an HLA-C epitope as a non-self MHC class I epitope, and at least one of an HLA-DR epitope, an HLA-DQ epitope, and an HLA-DP epitope as a non-self MHC class II epitope. In one embodiment, the CTA comprises an HLA-A epitope, an HLA-B epitope, an HLA-C epitope, an HLA-DR epitope, an HLA-DQ epitope, and an HLA-DP epitope.

[0046] The CTA may contain an epitope of an HLA subtype that occurs frequently in the population to which the subject belongs. For example, HLA subtypes that occur frequently in the Japanese population include HLA-A2, HLA-A24, HLA-A26, HLA-A11, HLA-B13, HLA-B39, HLA-B61, HLA-B62, HLA-B71, HLA-B75, HLA-DR15 / 16(2), HLA-DR4, HLA-DR8, HLA-DR12, HLA-DR13, and HLA-DR14.

[0047] A CTA may contain multiple epitopes restricted to multiple different HLA subtypes, for example, a CTA may contain epitopes of multiple HLA subtypes that are frequently represented in the subject's population.

[0048] In some embodiments, the CTA includes an MHC-I epitope and / or an MHC-II epitope not expressed by the subject to be treated. "Expressed by the subject" includes epitopes expressed as normal components in the subject and epitopes expressed due to an abnormality such as a disease or infection. For example, cancer neoantigens expressed by the subject's cancer are included in the components expressed by the subject. In other words, "MHC-I epitopes not expressed by the subject" and "MHC-II epitopes not expressed by the subject" do not include epitopes of cancer neoantigens expressed by the subject's cancer.

[0049] In some embodiments, the MHC-I epitope and / or MHC-II epitope contained in the CTA may or may not be expressed by the subject being treated. Thus, the composition may be administered even if the cancer neoantigens expressed by the subject's cancer are unknown. For example, the composition may be administered to a subject without determining prior to administration whether the subject expresses at least one non-self MHC class I-restricted epitope and / or at least one non-self MHC class II-restricted epitope contained in the peptide.

[0050] The nucleic acid encoding the CTA may be DNA or RNA and may contain one or more artificial nucleotides. Artificial nucleotides may be selected to have a structure different from that of natural nucleotides and to enhance nuclease resistance, etc. For example, the artificial nucleotides described in Deleavey, GF, & Damha, MJ (2012). Designing chemically modified oligonucleotides for targeted gene silencing. Chemistry & biology, 19(8), 937-954, which is incorporated herein by reference, may be used. All of the artificial nucleotides in the nucleic acid may be of the same type, or two or more different types of artificial nucleotides may be used.

[0051] The nucleic acid encoding the CTA may be operably linked to a promoter. In the present disclosure, "operably linked" means that a regulatory sequence element, such as a promoter, and the nucleic acid encoding the CTA are linked in a manner that allows expression of the CTA. They may be directly linked, or any nucleotide sequence may be present between them. The promoter may be a constitutive promoter, an inducible promoter, or a tissue- or cell-specific promoter. Constitutive promoters include the CMV (cytomegalovirus) promoter, the PGK (phosphoglycerate kinase) promoter, the EF1α (elongation factor 1-alpha) promoter, the CAG promoter, the SV40 promoter, and the MSCV promoter.

[0052] In some embodiments, the nucleic acid encoding the CTA is RNA. The RNA may include a 5' cap structure, a 5' untranslated region (UTR), a CTA coding sequence, a 3' UTR, and a polyA sequence. Such RNA may be produced, for example, by in vitro transcription using plasmid DNA as a template.

[0053] The nucleic acid encoding the CTA may be contained in a vector. The vector can deliver a nucleic acid of a desired sequence into cells and can be a viral vector or a non-viral vector. Viral vectors include retrovirus, lentivirus, adenovirus, adeno-associated virus (AAV), herpes simplex virus (HSV), vaccinia virus, Sendai virus, or measles virus vectors. Non-viral vectors include plasmid vectors, liposome vectors, and artificial chromosomes (e.g., YAC, BAC, PAC). Each vector can be prepared according to conventional methods.

[0054] The vector may contain one or more regulatory sequences that regulate the expression of the CTA. Regulatory sequences include expression control elements such as promoters, enhancers, polyadenylation signals, and post-transcriptional regulatory elements (PREs). The vector may also contain an origin of replication (ori) for replication. It may also contain a marker for selecting cells containing the vector. Examples of selection markers include genes that confer resistance to drugs such as neomycin, kanamycin, puromycin, hygromycin, zeocin, and ampicillin.

[0055] In some embodiments, the vector is an AAV vector. There are many serotypes of AAV, including AAV1, AAV2, AAV3, AAV4, AAV5, AAV6, AAV7, AAV8, AAV9, AAV10, AAV11, AAV12, AAV-rhlO, AAV-DJ, and AAVAnc80. In some embodiments, the vector is an AAV9 vector. AAV vectors may be in their natural form or in their recombinant form, with modified capsid proteins or the like.

[0056] AAV vectors can be prepared, for example, by introducing an AAV vector plasmid containing a CTA-encoding sequence (or a CTA-encoding sequence located downstream of a promoter) and inverted terminal repeats (ITRs) at both ends into packaging cells together with an AAV helper plasmid containing the Rep and Cap genes required for AAV replication and particle formation, and an adenovirus helper plasmid containing adenovirus helper genes required for AAV propagation. Examples of packaging cells include 293T cells, 293 cells, HeLa cells, COS1 cells, and COS7 cells. Viral particles released from packaging cells can be recovered from the packaging cell culture supernatant by purification methods such as centrifugation, filtration, and column purification.

[0057] Alternatively, cells expressing a nucleic acid encoding a CTA may be administered to a subject. The type of cell is not limited as long as it can express a CTA, and may also be a tumor cell. Preferred cells are fibroblasts or blood cells. The cells may be autologous cells, allogeneic cells, allogeneic cells, or xenogeneic cells, with autologous cells being preferred. Examples of allogeneic cells include Jurkat and Daudi. Construction of vectors for introducing nucleic acids, transformation, etc. can be performed by known methods (Molecular Cloning: A Laboratory Manual 2nd edition (1989), Cold Spring Harbor Laboratory Press).

[0058] The method of administration of the composition is not particularly limited, and can be via common administration routes such as oral administration, parenteral administration, injection, and infusion, and the composition can be in a dosage form suitable for each administration route. In some embodiments, the composition is administered intravenously. In some embodiments, the composition is administered locally to cancer tissue. In some embodiments, the composition is administered by intradermal or subcutaneous injection near regional lymph nodes or near tumors.

[0059] Oral dosage forms include granules, fine granules, powders, tablets, powders, capsules, microcapsules, chewable tablets, liquids, suspensions, emulsions, etc. Injectable dosage forms include common pharmaceutical dosage forms such as intravenous injections, infusions, and formulations that extend the release of active substances. Intravenous or infusion dosage forms include aqueous and non-aqueous injection solutions (which may contain antioxidants, buffers, bacteriostats, isotonic agents, etc.) and aqueous and non-aqueous injection suspensions (which may contain suspending agents, thickeners, etc.). Injectable dosage forms may be provided in sealed ampoules or vials, or as lyophilized products that require only the addition of a sterile liquid (e.g., water for injection) immediately before use. Injectable solutions or suspensions may be prepared from powders, granules, or tablets.

[0060] These dosage forms are prepared by conventional formulation methods. Furthermore, various pharmaceutically acceptable pharmaceutical substances can be blended as needed for the formulation. The pharmaceutical substances can be appropriately selected depending on the dosage form of the preparation, and examples thereof include buffering agents, surfactants, stabilizers, preservatives, excipients, diluents, additives, disintegrants, binders, coating agents, lubricants, glidants, flavoring agents, sweeteners, solubilizers, etc.

[0061] When administering a nucleic acid encoding a CTA or a vector containing the same, the nucleic acid or vector may be encapsulated in a lipid or polymer particle for intracellular delivery. The nucleic acid encoding a CTA or a vector containing the same may be introduced into the subject's cells by electroporation (see Yato et al., Identification of neutralizing epitopes in the preS2 domain of the hepatitis B virus. Virus Res. 2023 Jan 2;323:199014). For example, it may be introduced into cells of muscle, tumor tissue, or draining lymph nodes.

[0062] The dosage and frequency of administration of the composition can be appropriately determined by those skilled in the art depending on the species, health condition, age, body weight, route of administration, dosage form, etc. of the animal to be administered, so that an effective amount of nucleic acid encoding CTA or cells expressing CTA is administered to the subject. The effective amount in a given situation can be easily determined by routine experimentation and is within the skill and judgment of an ordinary clinician. For example, an effective amount of nucleic acid encoding CTA can be about 0.1 to 1000 μg / kg body weight, about 1 to 500 μg / kg body weight, about 10 to 50 μg / kg body weight, about 10 to 500 μg / kg body weight, about 0.1 to 20 μg / kg body weight, about 0.2 to 10 μg / kg body weight, or about 0.2 to about 2 μg / kg body weight, or about 0.005 to 1 mg, about 0.01 to 0.5 mg, or about 0.01 to about 0.1 mg per administration. For example, an effective amount of cells expressing CTA can be about 10 μg / kg body weight. ５ ~10 １０ pieces, about 10 ６ ~10 ９ pieces or about 10 ７ ~10 ８The composition may be administered in a single dose, multiple doses, or continuously. When administered multiple times, the composition may be administered, for example, once to several times a day, for example, once, twice, or three times a day, every day or every few days, for example, every 1, 2, 3, or 7 days. The administration period is not limited, and a drug-free period may be included. In one embodiment, the composition is administered in a single dose.

[0063] The present composition can be used alone or in combination with one or more additional active ingredients, particularly active ingredients for the treatment of cancer. "Combined use" of ingredients refers not only to the use of a dosage form containing all ingredients or the use of a combination of dosage forms containing each ingredient separately, but also to the simultaneous, sequential, or delayed administration of each ingredient, as long as they are used for the treatment of cancer. Two or more additional active ingredients can also be used in combination. Active ingredients suitable for combination use include, for example, known anticancer agents and agents for suppressing the side effects of anticancer agents.

[0064] Known anticancer agents include, for example, immune checkpoint inhibitors, alkylating agents, antimetabolites, anticancer antibiotics, plant alkaloids, antihormones, platinum compounds, cytokine preparations, molecularly targeted drugs, tumor immunotherapeutic agents, and cancer vaccines. In some embodiments, the active ingredient used in combination with the present composition is an immune checkpoint inhibitor. In particular, the present composition may be used in combination with an immune checkpoint inhibitor in the treatment of cancers with low immunogenicity. Treatment with an immune checkpoint inhibitor may be performed as described in Section II below.

[0065] Other cancer therapies can also be administered in combination with the administration of the composition. Suitable therapies include, for example, chemotherapy, radiation therapy, immunotherapy, hematopoietic stem cell transplantation, endoscopic resection, surgery, etc. In some embodiments, the composition is not administered in combination with immunotherapy using cancer neoantigens expressed by the subject's cancer.

[0066] In some aspects, methods for treating cancer in a subject are provided, comprising administering to a subject in need thereof an effective amount of a nucleic acid encoding a peptide comprising at least one non-self MHC class I-restricted epitope and at least one non-self MHC class II-restricted epitope. In some aspects, nucleic acids are provided that encode peptides comprising at least one non-self MHC class I-restricted epitope and at least one non-self MHC class II-restricted epitope for treating cancer in a subject. In some aspects, use of nucleic acids encoding peptides comprising at least one non-self MHC class I-restricted epitope and at least one non-self MHC class II-restricted epitope for treating cancer in a subject is provided. In some aspects, use of nucleic acids encoding peptides comprising at least one non-self MHC class I-restricted epitope and at least one non-self MHC class II-restricted epitope in the manufacture of a composition for treating cancer in a subject is provided.

[0067] In some aspects, a method of treating cancer in a subject is provided, comprising administering to a subject in need thereof an effective amount of cells expressing a peptide comprising at least one non-self MHC class I-restricted epitope and at least one non-self MHC class II-restricted epitope. In some aspects, cells expressing a peptide comprising at least one non-self MHC class I-restricted epitope and at least one non-self MHC class II-restricted epitope are provided for treating cancer in a subject. In some aspects, the use of cells expressing a peptide comprising at least one non-self MHC class I-restricted epitope and at least one non-self MHC class II-restricted epitope for treating cancer in a subject is provided. In some aspects, the use of cells expressing a peptide comprising at least one non-self MHC class I-restricted epitope and at least one non-self MHC class II-restricted epitope in the manufacture of a composition for treating cancer in a subject is provided.

[0068] In certain aspects, nucleic acids encoding peptides comprising at least one non-self MHC class I-restricted epitope and at least one non-self MHC class II-restricted epitope, or cells expressing such peptides, may be used to enhance the immunity of a subject.

[0069] For example, the following embodiments are provided: [1] A composition for treating cancer in a subject, comprising a nucleic acid encoding a peptide comprising at least one non-self MHC class I-restricted epitope and at least one non-self MHC class II-restricted epitope. [2] The composition according to item 1, wherein the nucleic acid is RNA. [3] The composition according to item 1 or 2, wherein the nucleic acid is contained in a vector. [4] The composition according to item 3, wherein the vector is a retroviral vector, lentiviral vector, adenoviral vector, adeno-associated viral vector, herpes simplex viral vector, vaccinia viral vector, Sendai viral vector, or measles viral vector. [5] The composition according to item 3 or 4, wherein the vector is an adeno-associated viral vector. [6] The composition according to any one of items 1 to 5, wherein the nucleic acid is introduced into the subject's cells by electroporation. [7] The composition according to item 6, wherein the subject's cells are muscle, tumor tissue, or draining lymph node cells. [8] The composition according to item 6 or 7, wherein the subject's cells are muscle cells. [9] A composition for treating cancer in a subject, comprising cells expressing a peptide comprising at least one non-self MHC class I-restricted epitope and at least one non-self MHC class II-restricted epitope.

[10] The composition according to claim 9, wherein the cells are autologous cells.

[11] The composition according to claim 9 or 10, wherein the cells are fibroblasts or blood cells.

[12] The composition according to any of claims 1 to 11, wherein the composition is administered to a subject whose cancer neoantigens are unknown.

[13] The composition according to any of claims 1 to 12, wherein the composition is administered to a subject without determining before administration whether the subject expresses at least one non-self MHC class I-restricted epitope contained in the peptide.

[14] The composition according to any of claims 1 to 13, wherein the composition is administered to a subject without determining before administration whether the subject expresses at least one non-self MHC class II-restricted epitope contained in the peptide.

[15] The composition according to any one of 1 to 14, wherein at least one non-self MHC class I-restricted epitope is an MHC class I-restricted epitope not expressed by the subject.

[16] The composition according to any one of 1 to 15 above, wherein at least one non-self MHC class II-restricted epitope is an MHC class II-restricted epitope not expressed by the subject.

[17] The composition according to any one of 1 to 16 above, wherein at least one non-self MHC class I-restricted epitope comprises an HLA-A epitope, an HLA-B epitope, or an HLA-C epitope.

[18] The composition according to any one of 1 to 17 above, wherein at least one non-self MHC class II-restricted epitope comprises an HLA-DR epitope, an HLA-DQ epitope, or an HLA-DP epitope.

[19] The composition according to any one of 1 to 18 above, wherein at least one non-self MHC class I-restricted epitope comprises an HLA-A epitope, an HLA-B epitope, and an HLA-C epitope.

[20] The composition according to any one of 1 to 19 above, wherein at least one non-self MHC class II-restricted epitope comprises an HLA-DR epitope, an HLA-DQ epitope, and an HLA-DP epitope.

[21] The composition according to any one of 1 to 20 above, wherein at least one non-self MHC class I-restricted epitope and / or at least one non-self MHC class II-restricted epitope comprises an epitope of an HLA subtype that is frequently expressed in a population to which the subject belongs.

[22] The composition according to any one of 1 to 21 above, wherein at least one non-self MHC class I-restricted epitope comprises multiple epitopes restricted by multiple different HLA subtypes, and / or wherein at least one non-self MHC class II-restricted epitope comprises multiple epitopes restricted by multiple different HLA subtypes.

[23] The composition according to any one of 1 to 22 above, wherein the composition is used in combination with an immune checkpoint inhibitor.

[24] The composition according to 23, wherein the immune checkpoint inhibitor is an anti-PD-1 antibody or an anti-PD-L1 antibody.

[25] The composition according to 23 or 24, wherein the immune checkpoint inhibitor is nivolumab, pembrolizumab, atezolizumab, avelumab, or durvalumab.

[26] The composition according to any of 23 to 25, wherein the immune checkpoint inhibitor is nivolumab.

[27] The composition according to any one of 1 to 26, wherein the cancer is leukemia, malignant lymphoma, multiple myeloma, myelodysplastic syndrome, head and neck cancer, gastrointestinal cancer, liver cancer, gallbladder / bile duct cancer, biliary tract cancer, pancreatic cancer, thyroid cancer, lung cancer, breast cancer, urogenital cancer, bone and soft tissue sarcoma, skin cancer, neuroendocrine tumor, glioma, brain tumor, malignant mesothelioma, or cancer of unknown primary origin.

[28] The cancer is malignant melanoma, lung cancer, non-small cell lung cancer, small cell lung cancer, renal cell carcinoma, classical Hodgkin's lymphoma, head and neck cancer, head and neck squamous cell carcinoma, cutaneous squamous cell carcinoma, transitional cell carcinoma, gastric cancer, malignant pleural mesothelioma, mesothelioma, colorectal cancer with high microsatellite instability (MSI-High) or mismatch repair function deficiency (dMMR), esophageal cancer, esophagogastric junction adenocarcinoma, cancer of unknown primary site, urothelial carcinoma, urinary tract cancer, and high microsatellite instability

[29] The composition according to any one of [1] to

[26] , wherein the cancer is a stable (MSI-High) or mismatch repair deficient (dMMR) solid cancer, breast cancer, bladder cancer, uterine body cancer, cervical cancer, endometrial cancer, a solid cancer with a high tumor mutation burden (TMB-High), primary mediastinal large B-cell lymphoma, liver cancer, hepatocellular carcinoma, biliary tract cancer, Merkel cell carcinoma, alveolar soft part sarcoma, basal cell carcinoma, colon cancer, rectal cancer, colorectal cancer, or neuroendocrine tumor.

[30] The composition according to any one of [1] to

[29] , wherein the cancer is malignant melanoma, colorectal adenocarcinoma, or lung cancer.

[31] The composition according to any one of [1] to

[29] , wherein the cancer is a cancer with high CD8 infiltration.

[32] The composition according to any one of [1] to

[29] , wherein the cancer is a cancer with low immunogenicity.

[33] The composition according to any one of 1 to 29, wherein the cancer is a cancer with low immunogenicity and is used in combination with an immune checkpoint inhibitor.

[0070] II. Methods for predicting the prognosis of a subject suffering from cancer and methods for predicting whether an immune checkpoint inhibitor will be effective against a subject's cancer In Section II, unless otherwise specified, the definitions of terms are as described in Section I. In the Examples described below, it was shown that cancer patients with non-self antigenic peptides containing long non-self amino acid sequences have a good prognosis. Without being limited by theory, it is believed that a long non-self amino acid sequence is more likely to contain non-self MHC-I epitopes and non-self MHC-II epitopes, and that the non-self antigenic peptide functions as a natural CTA, thereby resulting in a good prognosis. Furthermore, such CTA peptides are thought to be highly immunogenic, and when the immune system is activated by an immune checkpoint inhibitor, the tumor is likely to be eliminated by the immune system. Therefore, it is believed that cancer patients with non-self antigenic peptides containing long non-self amino acid sequences are more likely to respond to immune checkpoint inhibitors.

[0071] Thus, the present disclosure provides a method for predicting the prognosis of a subject suffering from cancer (Method 1) and a method for predicting whether a subject's cancer will respond to an immune checkpoint inhibitor (Method 2). These methods include step (1) analyzing the genes of cancer tissue obtained from the subject to determine whether a non-self antigen peptide containing a non-self amino acid sequence longer than a cutoff value is present in the cancer tissue.

[0072] In methods 1 and 2, the cancer can be any cancer, whether primary or metastatic. Examples of cancers are described in Section I. In some embodiments, the cancer is colon cancer.

[0073] The cancer tissue may be, for example, a biopsied cancer tissue or a resected cancer tissue. If necessary, the cancer tissue may be subjected to processes such as homogenization, centrifugation, concentration, dilution, freeze-drying, etc. The cancer tissue may be stored at a low temperature during or after its preparation prior to use, for example, by freezing.

[0074] In the present disclosure, a "non-self antigenic peptide" is a peptide that is not a normal component of a subject, is recognized by the immune system as a non-self component, and functions as an antigen. Typically, cancer neoantigens, i.e., non-self peptides generated by mutations in the tumor cell genome, are included in non-self antigenic peptides. Mutations include, but are not limited to, frameshift mutations, splicing mutations, somatic mutations, insertion / deletion mutations, coding mutations, and base substitutions.

[0075] A non-self antigen peptide may contain an amino acid sequence contained in a normal component of a subject and an amino acid sequence not contained in the normal component of a subject. In the present disclosure, "non-self amino acid sequence" refers to an amino acid sequence in a non-self antigen peptide that is not contained in the normal component of a subject. For example, in the case of a frameshift mutation, the sequence from the mutation site to the naturally generated stop codon is a non-self amino acid sequence. For example, in the case of a splicing mutation, the amino acid sequence derived from an intron is a non-self amino acid sequence.

[0076] The length of a non-self amino acid sequence can be determined by analyzing the genes of cancer tissue. For example, next-generation sequencing such as whole genome sequencing (WGS), whole exome sequencing (WES), or RNA-sequencing is performed to identify non-self antigenic peptides. The non-self amino acid sequence in the non-self antigenic peptide is determined, and its amino acid length is determined. If a non-self antigenic peptide contains multiple non-self amino acid sequences, the sum of their amino acid lengths is taken as the amino acid length of the non-self amino acid sequence in that non-self antigenic peptide. The determined amino acid length is compared to a cutoff value to determine whether a non-self antigenic peptide containing a non-self amino acid sequence longer than the cutoff value is present. If multiple non-self antigenic peptides are present in cancer tissue, if the amino acid length of the non-self amino acid sequence of at least one non-self antigenic peptide is longer than the cutoff value, it is determined that a non-self antigenic peptide containing a non-self amino acid sequence longer than the cutoff value is present.

[0077] In step (1) of Method 1, the cutoff value is a value that can statistically significantly separate a group of subjects with a good prognosis from a group of subjects with a poor prognosis. The cutoff value can be set by known methods using various statistical analysis techniques. For example, the cutoff value can be set by statistically analyzing the lengths of non-self amino acid sequences in a group of cancer patients with a good prognosis and in a group of cancer patients with a poor prognosis. Statistical significance can be analyzed by known testing methods such as the chi-square test, generalized Wilcoxon test, Wilcoxon signed-rank test, Mann-Whitney test, log-rank test, and Cox proportional hazards. Statistical analysis software such as Prism can be used to set the cutoff value. In one embodiment, the cutoff value in Method 1 is a length of about 50 to 120 amino acids, for example, about 50, 60, 70, 80, 90, 100, 110, or 120 amino acids.

[0078] The cutoff value can be set based on sensitivity and / or specificity. Preferably, the cutoff value exhibits both high sensitivity and high specificity. Here, sensitivity refers to the true positive rate. Specificity refers to the true negative rate. For example, the length of a non-self amino acid sequence that exhibits a high positive rate in a group of subjects with a good prognosis and a high negative rate in a group of subjects with a poor prognosis can be set as the cutoff value.

[0079] For example, a cutoff value can be set using receiver operating characteristic (ROC) analysis, which is commonly used as a method for examining the usefulness of diagnostic tests. In ROC analysis, an ROC curve is created by plotting the sensitivity at each cutoff value on the vertical axis and the false positive rate (1 - specificity) on the horizontal axis. The ROC curve is a diagonal straight line for tests without diagnostic ability, but as the diagnostic ability improves, it becomes a curve that arches upward to the left. The cutoff value that gives the point on the ROC curve with the smallest distance from the upper left corner can be said to have excellent sensitivity and specificity. The cutoff value can also be set based on the Youden index. For example, sensitivity and specificity are determined from the length of the non-self amino acid sequence in subjects with a good prognosis and subjects with a poor prognosis, and an ROC curve is created based on these values ​​using commercially available analysis software. The values ​​at which sensitivity and specificity are as close to 100% as possible are then determined, and these values ​​can be used as the cutoff value.

[0080] Furthermore, for example, the diagnostic efficiency (i.e., the ratio of the total number of cases in which subjects with a good prognosis were correctly diagnosed as having a "good prognosis" and the total number of cases in which subjects with a poor prognosis were correctly diagnosed as having a "poor prognosis" to the total number of cases) can be calculated, and the length of the non-self amino acid sequence that gives the highest diagnostic efficiency can be used as the cutoff value.

[0081] Cutoff values ​​can also be set for subgroups of patients based on characteristics, such as gender, age, race, cancer type, stage, mutation type, and previous treatment.

[0082] When the length of the non-self amino acid sequence is equivalent to the cutoff value, a non-self antigen peptide containing a non-self amino acid sequence longer than the cutoff value is determined to be present or absent, which can be arbitrarily set depending on the purpose of the determination, etc. Thus, in one embodiment, a non-self antigen peptide is determined to be present when the length of the non-self amino acid sequence is equal to or greater than the cutoff value, and is determined to be absent when the length of the non-self amino acid sequence is less than the cutoff value. In another embodiment, a non-self antigen peptide is determined to be present when the length of the non-self amino acid sequence is longer than the cutoff value, and is determined to be absent when the length of the non-self amino acid sequence is equal to or less than the cutoff value.

[0083] In step (2) of method 1, if a non-self antigen peptide containing a non-self amino acid sequence longer than the cutoff value is present in the cancer tissue, the subject's prognosis is predicted to be good. In the present disclosure, "good prognosis" means that the subject's overall survival or progression-free survival is long. Treatments the subject has received in the past and treatments the subject will receive in the future are not limited. For example, the overall survival or progression-free survival of a subject with a good prognosis is longer than the median survival of a population with the same type of cancer and receiving the same type of treatment. Alternatively, a group of subjects with a good prognosis is a group with a long survival time when a population with the same type of cancer and receiving the same type of treatment is divided by the survival time cutoff value and compared between the two groups.

[0084] In step (1) of Method 2, the cutoff value is a value that can statistically significantly separate a group of subjects who respond to an immune checkpoint inhibitor from a group of subjects who do not. The cutoff value is set using a method similar to Method 1, and it can be determined whether or not a non-self antigen peptide containing a non-self amino acid sequence longer than the cutoff value is present in the cancer tissue.

[0085] If a subject suffering from cancer has a good prognosis, the tumor is likely to be immunogenic, and therefore likely to respond to an immune checkpoint inhibitor. Thus, the cutoff value in step (1) of method 1, i.e., a value that can statistically significantly separate subjects with a good prognosis from subjects with a poor prognosis, may be used as the cutoff value in step (1) of method 2. In some embodiments, the cutoff value in method 2 is any length of about 50 to 120 amino acids, for example, a length of about 50, about 60, about 70, about 80, about 90, about 100, about 110, or about 120 amino acids.

[0086] In step (2) of method 2, if a non-self antigen peptide containing a non-self amino acid sequence longer than the cutoff value is present in the cancer tissue, it is predicted that the subject's cancer will respond to an immune checkpoint inhibitor. In the present disclosure, "the subject's cancer will respond to an immune checkpoint inhibitor" means that the subject's cancer can be improved by the immune checkpoint inhibitor. Improvement of cancer can be, for example, reducing or eliminating cancer cells, delaying or stopping the progression, recurrence, or metastasis of cancer, alleviating, ameliorating, or eliminating cancer symptoms, or extending overall survival or progression-free survival, for example, extending overall survival or progression-free survival compared to the median survival or progression-free survival of a placebo group or an untreated group.

[0087] Methods 1 and 2 may include obtaining cancer tissue from a subject. Methods 1 and 2 may include analyzing the genes of the cancer tissue obtained from the subject to identify a non-self antigen peptide. Methods 1 and 2 may include determining the length of a non-self amino acid sequence in the non-self antigen peptide. Methods 1 and 2 may be performed to assist diagnosis. The prediction results from Methods 1 and 2 may be provided as information for diagnosis.

[0088] If method 2 predicts that the subject's cancer will be effective against an immune checkpoint inhibitor, the patient is recommended to receive treatment with an immune checkpoint inhibitor. Thus, method 2 may comprise administering an immune checkpoint inhibitor to the subject if the subject's cancer is predicted to be effective against an immune checkpoint inhibitor. Also, in one aspect, there is provided a method for treating cancer, comprising administering an effective amount of an immune checkpoint inhibitor to a subject predicted to be effective against an immune checkpoint inhibitor by the prediction method of the present disclosure.

[0089] In the context of the present disclosure, "immune checkpoint inhibitor" refers to a substance that inhibits the function of an immune checkpoint molecule and / or its ligand. "Immune checkpoint molecules" are molecules that suppress immune responses against self and / or excessive immune responses, and include, but are not limited to, CTLA-4, PD-1, TIGIT, Tim3, etc. Ligands for immune checkpoint molecules include, but are not limited to, PD-L1, PD-L2, etc. Examples of immune checkpoint inhibitors include anti-CTLA-4 antibodies (e.g., ipilimumab, tremelimumab, AGEN-1884), anti-PD-1 antibodies (e.g., nivolumab, REGN-2810, pembrolizumab, PDR-001, BGB-A317, AMP-514 (MEDI0680), BCD-100, IBI-308, JS-001, PF-06801591, TSR-042, cemiplimab), anti-TIGIT antibodies (e.g., tiragolumab), anti-Tim3 antibodies (e.g., covolimab), and anti-PD-L1 antibodies (e.g., atezolizumab). (RG7446, MPDL3280A), avelumab (PF-06834635, MSB0010718C), durvalumab (MEDI4736), BMS-936559, CA-170, LY-3300054), anti-PD-L2 antibodies (e.g., rHIgM12B7), PD-L1 fusion proteins, PD-L2 fusion proteins (e.g., AMP-224), etc., as well as antibodies having the heavy and light chain complementarity-determining regions (CDRs) of these antibodies, and antibodies comprising the heavy chain variable region (VH) and light chain variable region (VL) of these antibodies. In some embodiments, the immune checkpoint inhibitor is a PD-1 inhibitor or a PD-L1 inhibitor. In some embodiments, the immune checkpoint inhibitor is an anti-PD-1 antibody or an anti-PD-L1 antibody. In some embodiments, the immune checkpoint inhibitor is nivolumab, pembrolizumab, atezolizumab, avelumab, or durvalumab. In some embodiments, the immune checkpoint inhibitor is nivolumab.

[0090] In the present disclosure, the term "antibody" includes molecules that contain a portion of an antibody as a component and retain antigen-binding ability, such as Fab, Fab', F(ab')２ , Fv, or single chain Fv (scFv), Fab3, diabody, triabody, tetrabody, minibody, Bis-scFv, (scFv) ２ -Fc, intact IgG, etc. The antibody may be a human antibody or a humanized antibody. A humanized antibody refers to an antibody in which the amino acid sequences of the CDRs of the VH and VL of a non-human animal antibody are transplanted into appropriate positions of the VH and VL of a human antibody.

[0091] The method of administration of the immune checkpoint inhibitor is not particularly limited, and can be via common administration routes such as oral administration, parenteral administration, injection, and infusion, and can be administered in a dosage form suitable for each administration route. In some embodiments, the immune checkpoint inhibitor is administered intravenously. In some embodiments, the immune checkpoint inhibitor is administered locally to cancer tissue.

[0092] Oral dosage forms include granules, fine granules, powders, tablets, powders, capsules, microcapsules, chewable tablets, liquids, suspensions, emulsions, etc. Injectable dosage forms include common pharmaceutical dosage forms such as intravenous injections, infusions, and formulations that extend the release of active substances. Intravenous or infusion dosage forms include aqueous and non-aqueous injection solutions (which may contain antioxidants, buffers, bacteriostats, isotonic agents, etc.) and aqueous and non-aqueous injection suspensions (which may contain suspending agents, thickeners, etc.). Injectable dosage forms may be provided in sealed ampoules or vials, or as lyophilized products that require only the addition of a sterile liquid (e.g., water for injection) immediately before use. Injectable solutions or suspensions may be prepared from powders, granules, or tablets.

[0093] These dosage forms are prepared by conventional formulation methods. Furthermore, various pharmaceutically acceptable pharmaceutical substances can be blended as needed for the formulation. The pharmaceutical substances can be appropriately selected depending on the dosage form of the preparation, and examples thereof include buffering agents, surfactants, stabilizers, preservatives, excipients, diluents, additives, disintegrants, binders, coating agents, lubricants, glidants, flavoring agents, sweeteners, solubilizers, etc.

[0094] The dosage and frequency of administration of immune checkpoint inhibitors can be appropriately determined by those skilled in the art based on the animal species, health condition, age, body weight, administration route, administration form, etc., of the recipient, so that an effective amount is administered to the subject. The effective amount in a given situation can be easily determined through routine experimentation and is within the skill and judgment of an ordinary clinician. For example, when an anti-PD-1 antibody is used, the dosage may be about 0.1 to 20 mg / kg body weight. For example, the dosage of nivolumab is about 0.3 to 10 mg / kg body weight, preferably about 2 mg / kg body weight or about 3 mg / kg body weight, or about 240 mg / body weight or about 480 mg / body weight. For example, the dosage of pembrolizumab is about 0.2 to 10 mg / kg body weight, preferably about 200 mg / body weight. For example, the anti-PD-1 antibody may be administered every two weeks, three weeks, or four weeks.

[0095] The immune checkpoint inhibitor may be used in combination with one or more additional active ingredients, particularly active ingredients for treating cancer. Suitable active ingredients for combination use include, for example, known anticancer agents and agents for suppressing the side effects of anticancer agents.

[0096] Known anticancer agents include, for example, alkylating agents, antimetabolites, anticancer antibiotics, plant alkaloid drugs, antihormones, platinum compounds, cytokine preparations, molecular targeted drugs, tumor immunotherapy drugs, and cancer vaccines.

[0097] Other cancer treatments can also be administered in combination with the administration of immune checkpoint inhibitors. Suitable treatments include, for example, chemotherapy, radiation therapy, immunotherapy, hematopoietic stem cell transplantation, endoscopic resection, surgery, etc.

[0098] In one aspect, a method of treating a subject suffering from cancer is provided, the method comprising predicting whether or not an immune checkpoint inhibitor will be effective against the cancer of the subject by Method 2; and administering an effective amount of an immune checkpoint inhibitor to the subject based on the prediction. In one aspect, a composition comprising an immune checkpoint inhibitor is provided for treating cancer in a subject predicted to be effective against an immune checkpoint inhibitor by Method 2. In one aspect, an immune checkpoint inhibitor is provided for use in treating cancer in a subject predicted to be effective against an immune checkpoint inhibitor by Method 2. In one aspect, a use of an immune checkpoint inhibitor is provided in treating cancer in a subject predicted to be effective against an immune checkpoint inhibitor by Method 2. In one aspect, a use of an immune checkpoint inhibitor for the manufacture of a composition for treating cancer in a subject predicted to be effective against an immune checkpoint inhibitor by Method 2 is provided.

[0099] For example, the following embodiments are provided: [1] A method for predicting the prognosis of a subject suffering from cancer, comprising: (1) analyzing the genes of cancer tissue obtained from the subject and determining whether or not a non-self antigenic peptide containing a non-self amino acid sequence longer than a cutoff value is present in the cancer tissue; and (2) predicting that the subject's prognosis will be good if the non-self antigenic peptide is present in the cancer tissue. [2] A method for predicting whether or not an immune checkpoint inhibitor will be effective against a subject's cancer, comprising: (1) analyzing the genes of cancer tissue obtained from the subject and determining whether or not a non-self antigenic peptide containing a non-self amino acid sequence longer than a cutoff value is present in the cancer tissue; and (2) predicting that the immune checkpoint inhibitor will be effective against the subject's cancer if the non-self antigenic peptide is present in the cancer tissue. [3] The method described in 2 above, comprising administering an immune checkpoint inhibitor to the subject if it is predicted that the immune checkpoint inhibitor will be effective against the subject's cancer. [4] The method described in 2 or 3 above, wherein the immune checkpoint inhibitor is an anti-PD-1 antibody or an anti-PD-L1 antibody. [5] The method according to any one of 2 to 4 above, wherein the immune checkpoint inhibitor is nivolumab, pembrolizumab, atezolizumab, avelumab, or durvalumab. [6] The method according to any one of 2 to 5 above, wherein the immune checkpoint inhibitor is nivolumab. [7] The method according to any one of 1 to 6 above, wherein the cutoff value is a length of about 50 to 120 amino acids. [8] The method according to any one of 1 to 7 above, wherein the cutoff value is a length of about 50, about 60, about 70, about 80, about 90, about 100, about 110, or about 120 amino acids. [9] The method according to any one of 1 to 8 above, wherein the cutoff value is a length of about 120 amino acids.

[10] The method according to any one of 1 to 9 above, comprising obtaining cancer tissue from a subject.

[11] The method according to any one of 1 to 10 above, comprising analyzing the genes of cancer tissue obtained from a subject and identifying non-self antigen peptides.

[12] The method according to any one of 1 to 11, comprising determining the length of a non-self amino acid sequence in a non-self antigen peptide.

[13] The method according to any one of 1 to 12 above, wherein the cancer is leukemia, malignant lymphoma, multiple myeloma, myelodysplastic syndrome, head and neck cancer, gastrointestinal cancer, liver cancer, gallbladder / bile duct cancer, biliary tract cancer, pancreatic cancer, thyroid cancer, lung cancer, breast cancer, urogenital cancer, bone and soft tissue sarcoma, skin cancer, neuroendocrine tumor, glioma, brain tumor, malignant mesothelioma, or cancer of unknown primary origin.

[14] The cancer is malignant melanoma, lung cancer, non-small cell lung cancer, small cell lung cancer, renal cell carcinoma, classical Hodgkin's lymphoma, head and neck cancer, head and neck squamous cell carcinoma, cutaneous squamous cell carcinoma, transitional cell carcinoma, gastric cancer, malignant pleural mesothelioma, mesothelioma, colorectal cancer with high microsatellite instability (MSI-High) or mismatch repair function deficiency (dMMR), esophageal cancer, esophagogastric junction adenocarcinoma, cancer of unknown primary site, urothelial carcinoma, urinary cancer, high microsatellite instability

[14] The method according to any one of 1 to 12, wherein the cancer is a solid cancer with MSI-High or mismatch repair deficient (dMMR), breast cancer, bladder cancer, uterine body cancer, cervical cancer, endometrial cancer, a solid cancer with a high tumor mutation burden (TMB-High), primary mediastinal large B-cell lymphoma, liver cancer, hepatocellular carcinoma, biliary tract cancer, Merkel cell carcinoma, alveolar soft part sarcoma, basal cell carcinoma, colon cancer, rectal cancer, colorectal cancer, or neuroendocrine tumor.

[15] The method according to any one of 1 to 12, wherein the cancer is colorectal cancer.

[16] The method according to any one of 1 to 15, wherein the cancer is a cancer with high CD8 infiltration.

[17] The method according to any one of 1 to 15, wherein the cancer is an immunogenic cancer.

[18] The method according to any one of 1 to 15, wherein the cancer is a poorly immunogenic cancer.

[0100] All documents cited in this specification are incorporated herein by reference. The above descriptions are all non-limiting, and the present invention is defined in the appended claims, and various modifications are possible within the scope of the technical idea. The present invention will be described in more detail below with reference to examples, but the present invention is not limited to these examples.

[0101] Materials and Methods Mice and Cells Mice were maintained under specific pathogen-free conditions at the Kyoto University Graduate School of Medicine Animal Experiment Facility. All animal experiments were performed in accordance with guidelines approved by the respective institutional review boards. C57BL / 6NWT or C57-Tg (CAG-EGFP) mice were purchased from Charles River Japan or Shimizu Experimental Materials. The mouse colon adenocarcinoma (MC38) cell line was a gift from J.P. Allison, Memorial Sloan-Kettering Cancer (New York, NY). LLC was obtained from the American Type Culture Collection. Bpmel-parent cells were obtained from Braf Ｖ６００Ｅ / PTEN －／－ The melanoma model was established. ｔｍ１Ｍｍｃｍ Patent ｍ１Ｈｗｕ The dorsal skin of Tg(Tyr-cre / ERT2)13Bos / BosJ mice (purchased from the Jackson Laboratory, Dankort, D. et al. Braf cooperates with Pten loss to induce metastatic melanoma. Nat. Genet. 41, 544-552 (2009)) was cleaned, shaved, and treated with 4-OH tamoxifen to induce tumor tissue. Spontaneous melanoma cells were isolated and cultured at Keio University to establish the mouse melanoma cell line BPmel-1 with the BRAF mutation / PTEN loss genotype. Bpmel-OVAI-Ea, MC38-OVAI-Ea, Bpmel-SIY-OVAII, Bpmel-OVAI, and Bpmel-Adpgk were used. ＭＵＴAntigen-expressing cells containing Bpmel-OVAII or Bpmel-OVAII were generated by transducing tumor cell lines with pLJM1-based lentivirus. Cells were maintained in RPMI 1640 (Gibco; 11875-093) or DMEM (Gibco; 11995-065) supplemented with 10% heat-inactivated fetal bovine serum (FBS) and penicillin-streptomycin (Nacalai Tesque, Kyoto, Japan, 26253-84) and were free of mycobacterial infection. Cell cultures were maintained in a humidified incubator at 37°C and 5% CO. ２ was maintained.

[0102] Mouse treatment model: MC38 cells (2 × 10 ６ cells) or Bpmel-parent cells (3 × 10 ６ Mice were injected intradermally (i.d.) into the left flank of the mouse (day 0). Tumor growth was monitored by measuring tumor size with a caliper, and volume was calculated using the formula for a typical ellipsoid (π(length x width x height) / 6). The cellular adjuvant model included antigen-expressing tumor cells (1 x 10) that would be naturally rejected. ６ Mice were injected i.d. into the contralateral flank 6 or 9 days after tumor cell inoculation. For electrotransfer of a cDNA vaccine encoding a complete T cell antigen (CTA), mice were intramuscularly administered the plasmid followed by in vivo electroporation (see Yato et al., Identification of neutralizing epitopes in the preS2 domain of the hepatitis B virus. Virus Res. 2023 Jan 2;323:199014). Briefly, hyaluronidase (50 U) was injected into the quadriceps muscle. 15 minutes later, mice were anesthetized with isoflurane and injected with 50 μg of pCAGGS, pCAGGS-SIY, or pCAGGS-SIY-OVAII into the quadriceps muscle. An electrode needle was inserted into the muscle, and an electric pulse was delivered using an electric pulse generator (Nepa Gene, NEPA21). Each injection site received three pouring pulses (50 V, 30 ms) followed by three transfer pulses (20 V, 50 ms).

[0103] Preparation of Cells for Analysis For draining lymph node (DLN) analysis, axillary, brachial, and inguinal lymph nodes were collected from the tumor-bearing (left) side of the mice. For tumor-infiltrating lymphocyte (TIL) analysis, tumor tissue was collected, cut into 1-2 mm pieces with scissors, and digested with type IV collagenase (Worthington Biochemical Corporation, Lakewood, NJ, Catalog # LS004188) using a gentle MACS Dissociator (Miltenyi Biotec).

[0104] Flow cytometry analysis and tetramer preparation. The following monoclonal antibodies were used for antigen detection: CD3 (145-2C11) and CD8 (53-6.7) from Invitrogen; CD44 (IM7), CD62L (MEL-14), CD127 (A7R34), KLRG1 (2F1), CX3CR1 (QA16A03), CD27 (LG.3A10), CD39 (Duha59), PD1 (29F.1A12), TIM3 (B8.2C12), and Slamf6 (330-AJ) from BioLegend; CD8 (KT15) from MBL Life Science; and CD45RB (16A) and CD4 (RM4-4) from BD Pharmingen. H-2Kb-Negative (SIY) tetramer-SIYRYYGL-PE (TS-M008-1) and H-2Kb-OVA tetramer-SIINFEKL-PE (TS-5001-1C) were obtained from MBL Life Science (USA), and H-2Kb-Adpgk ＭＵＴ Pentamers were obtained from Proimmune (Oxford, UK). Neoantigen tetramers were constructed using the ScapMUT or ARAFMUT peptide (10 μM) according to the manufacturer's instructions (QuickSwitch™ Quant H-2Kb tetramer kit; TB-7400-K1, MBL, USA). Flow cytometry experiments were performed using an LSRFortessa X-20 (BD Biosciences) and analyzed using FlowJo software (FlowJo).

[0105] Epitope Prediction. To identify point mutations and predict MHC-I epitopes in Bpmel-parent melanoma cells, all missense mutations in Bpmel-parent melanoma cells were analyzed for their ability to form MHC class I epitopes that bind to H-2Db or H-2Kb based on the NetMHCpan algorithm provided by the Immune Epitope Database and Analysis Resource (http: / / www.immuneepitope.org). The affinity and results were finally calculated as affinity values ​​(1 / IC ５０ ×100; IC ５０ In NotchMUT-related experiments, prediction of H2-I-Ab-restricted epitopes was based on hmMHC, an HMM-based binding prediction method, and the top 1% of affinities were considered as strong binding.

[0106] Immune subset depletion and checkpoint inhibition. CD4 depletion was achieved by i.p. administration of 200 μg of a depleting antibody (InVivoMAb anti-mouse CD4, clone GK1.5, BioXcell) 4 days before treatment. ＋ For checkpoint blockade, mice were injected i.p. every 6 days with 40 μg of α-mouse PD-L1 mAb (clone 1-111A.4).

[0107] Allele-specific PCR: Total RNA was isolated from MC38 cells using Nucleospin RNA (Macherey-Nagel) and used for cDNA synthesis with RevatraAce reverse transcriptase (Toyobo). The Notch2 segment was amplified by PCR to include the Nhel and EcoRI restriction sites (sense, 5'-CGGCTAGCATGTCCACCTCTCACCCCTG-3' (SEQ ID NO: 1), antisense, 5'-CCGGAATTCCGCTCCAGCCGTTCA-3' (SEQ ID NO: 2)). The gene segment was cloned, inserted into the pLJM1 vector, transformed into competent E. coli, and grown overnight on selective plates. Notch2 in each E. coli colony was examined using two primers designed to detect the wild-type allele (sense, 5'-CTCACCCCTGCTTTGTGT-3' (SEQ ID NO: 3), antisense, 5'-GGCATCTGTAGGAACCAGGA-3' (SEQ ID NO: 4)) and another primer designed to detect the frameshift mutant allele (sense, 5'-CTCACCCCTGCTTTTGTC-3' (SEQ ID NO: 5), antisense, 5'-GGCATCTGTAGGAACCAGGA-3' (SEQ ID NO: 6)). The Notch2 frameshift mutation was confirmed by DNA sequencing.

[0108] Selective binding and isolation of His-tagged proteins. MC38-ZsGreen-HisTag or MC38-Notch2 were isolated by adding 0.5 ml of xTractor Buffer (Takara, Z5623N) per 25 mg of cell mass. ＭＵＴ The His-Tag was dissolved in 1 μl of 1 unit / μl DNase I solution and added. After centrifugation, insoluble material was removed, and the His-tagged protein was purified using His60 Ni Magnetic Beads (Takara, 635692) according to the manufacturer's instructions. The protein-bound beads were washed twice with His60 Ni equilibration buffer, and the His-tagged protein was obtained by adding elution buffer. The resulting protein was used in subsequent experiments.

[0109] Single-cell RNA-seq analysis of CD45 from pooled MC38 tumors (5 mice per condition). ＋ CD8 ＋ TILs were isolated and sorted 7 days after Bpmel-SIY-OVAII cell adjuvant therapy. Naive T cells (CD3 ＋ CD44 － The remaining DLN cells were used for single-cell sequencing, with the exception of the 10x Genomics cells. These cells were sequenced using 10x Genomics. Sequencing was performed on a NextSeq 2000 system. The resulting FASTQ files were processed in Cell Ranger Count using default settings for 5' RNA gene expression analysis (Cell Ranger v4.0.0, 10x Genomics).

[0110] Unsupervised clustering was performed using the FindNeighbors method implemented in Seurat with default parameters and FindClusters at a resolution of 0.3 (Hao et al., Integrated analysis of multimodal single-cell data. Cell 184, 3573-3587.e3529 (2021)). For supervised analysis and comparison with previous annotations, scRNA-seq data were projected onto a reference atlas of TILs using the ProjecTILs package (Andreatta et al., Interpretation of T cell states from single-cell transcriptomics data using reference atlases. Nat Commun 12, 2965 (2021)). CD8 T cell states were analyzed using the Monocle3 package. ＋We analyzed the lineage trajectories of TILs (Cao et al., The single-cell transcriptional landscape of mammalian organogenesis. Nature 566, 496-502 (2019)), and used the CellChat package (version 1.1.3) to infer, analyze, and visualize cell-cell communication (Jin et al., Inference and analysis of cell-cell communication using CellChat. Nat Commun 12, 1088 (2021)). Data were deposited in the Gene Expression Omnibus (GEO) repository (https: / / www.ncbi.nlm.nih.gov / geo / ) under accession number GSE245743. Single-cell RNA-seq analysis was performed using RStudio in R version 4.3.0.

[0111] TCGA Cancer Patient Database Analysis: The colorectal adenocarcinoma dataset (TCGA-COAD) was downloaded from the Cancer Genome Atlas (TCGA) data portal (http: / / tcga-data.nci.nih.gov). The "data matrix" tool provided by the TCGA data portal was used to extract somatic mutations and RNA-seq data normalized by fragments per kilobase per million (FPKM). To explore the mutational landscape of colorectal cancer, somatic mutation data were processed and analyzed using R software (version 4.3.0) with the "maftools" package (Mayakonda et al., Maftools: efficient and comprehensive analysis of somatic variants in cancer. Genome Res. 2018 Nov;28(11):1747-1756). TMB was defined as the total number of somatic mutations (including somatic mutations, indels, coding mutations, and base substitutions) per million bases. For frameshift mutations, the CDS following the mutation site was translated into amino acids, and the sequence between the mutation site and the naturally occurring stop codon was defined as the "functional peptide."

[0112] Patients with colorectal cancer were divided into low and high TMB groups using the median TMB value. Patients were divided into low and high FS groups based on the number of frameshift mutations, and into long and short FP groups based on whether they could generate functional peptides longer than 120 amino acids. To analyze the correlation between TMB, the number of frameshift mutations, and the length of functional peptides and clinicopathological factors in colorectal cancer patients, the above data were overlaid with corresponding clinical information. Clinical variables were compared between the two groups using the Wilcoxon rank-sum test.

[0113] Antigen-specific assays Bpmel-parent or Bpmel-Notch2 ＭＵＴ were injected intradermally (i.d.) into the right flank of mice and allowed to grow for 2 weeks. Draining lymph node (DLN) single cells were harvested after 2 weeks and 5 × 10５ DLN single cells / well were cultured in RPMI 1640 supplemented with fetal bovine serum and incubated with the indicated peptides (5 μg / ml) for 6 hours or full-length antigens (10 μg / ml) for 16 hours at 37°C, 5% CO ２ After stimulation, CD4+ cells were stimulated in a humidified incubator using a mouse IFN-γ secretion assay according to the manufacturer's instructions (Miltenyi Biotec, 130-090-516). ＋ or CD8 ＋ IFN-γ release from T cells was measured and peptide synthesis was performed by Genscript.

[0114] ELISpot assay Six-week-old female C57BL / 6N mice were transfected with Bpmel-parent or Bpmel-Notch2 mice. ＭＵＴ The mice were immunized by injection of 5 × 10 freshly isolated DLN cells. ELISpot assays were performed using Mouse IFN-γ ELISpot (immunoSpot) according to the manufacturer's instructions. ５ ) together with the peptide overnight at 37°C, 5% CO ２ The cells were incubated in a white ELISpot polyvinylidene fluoride (PVDF) plate coated with an anti-IFN-γ antibody (clone AN18). When testing MHC I-restricted peptides, H-2Kb OVA peptide SIINFEKL (SEQ ID NO: 7) (MBL) was used as a negative control, and when testing MHC II-restricted peptides, I-Ab MOG35-55 (MBL, TS-M704-P) (MEVGWYRSPFSRVVHLYRNGK, SEQ ID NO: 8) was used as a negative control. IFN-γ secretion was then detected using a capture antibody (clone R4-6A2) and 5-bromo-4-chloro-3-indolyl phosphate / nitroblue tetrazolium-plus substrate. After allowing the plate to dry, the number of spots was counted using a dissecting microscope. Spot images were obtained using an ImmunoSpot S6 Ultimate analyzer (Cellular Technology Limited).

[0115] Statistical analysis: Data were analyzed using Prism 7 (GraphPad), and results are presented as mean ± SEM. Comparisons between two groups were analyzed using an unpaired two-tailed Student's t-test. Comparisons between more than two groups were analyzed using one-way analysis of variance (ANOVA) followed by Tukey's multiple comparison test. Survival rates were assessed using the Kaplan-Meier method.

[0116] Results Study 1: Complete T cell antigen suppresses tumor growth regardless of antigen specificity Braf Ｖ６００Ｅ / PTEN －／－ Using a melanoma model, we established a new melanoma cell line, designated Bpmel-parent (manuscript in progress). This melanoma cell line did not respond to anti-PD-L1 therapy, but OVA antigen-overexpressing Bpmel (Bpmel-OVA) was rejected in mice with or without anti-PD-L1 therapy (Figure 1).

[0117] We found that when Bpmel-OVA was injected into the right flank of mice, Bpmel-parent mice in the left flank began to respond to anti-PD-L1 therapy (Figure 2). We initially speculated that this phenomenon occurred because disrupted Bpmel-OVA released Bpmel-derived neoantigens, allowing the immune system to better recognize Bpmel-parent mice. To test this hypothesis, we generated MC38-OVA cells as a negative control and reproduced this "cellular adjuvant" model. Unexpectedly, MC38-OVA alone effectively reversed the unresponsiveness of Bpmel-parent mice to anti-PD-L1 mAb treatment (Figure 3). This finding suggested that the expressed OVA antigens, rather than the background Bpmel neoantigens, may be responsible for the antitumor effects of the cellular adjuvant.

[0118] In C57BL / 6 mice, there are two important antigenic epitopes in the OVA antigen. One of them is CD8 ＋ It has affinity for MHC class I (MHC I) that can stimulate T cells (OVA). ２５７－２６４ OVAI), and the other is CD4 ＋ It has affinity for MHC class II (MHC II) that can stimulate T cells (OVA). ３２３－３３９OVAI and OVAII) (Figure 4). To determine which epitope is responsible for the antitumor effect, OVAI and OVAII were separately expressed in Bpmel-parent cells. Both Bpmel-OVAI and Bpmel-OVAII were highly immunogenic and were rejected regardless of the presence or absence of anti-PD-L1 therapy (Figure 5). When Bpmel-OVA (containing both OVAI and II), Bpmel-OVAI, or Bpmel-OVAII were used as cellular adjuvants, only Bpmel-OVA enhanced anti-PD-L1 activity against the left-hand Bpmel-parent cells (Figure 6). These data indicate that cellular adjuvant-mediated antitumor activity requires both MHC I- and MHC II-restricted OVA epitopes.

[0119] To rule out antigen specificity in tumor models, new artificial chimeric antigens were constructed. ＭＵＴ -OVAII binds to H2-D via Adpgk as an MHC-I restricted epitope. ＭＵＴ OVAI-Ea is a fusion protein consisting of OVAI and the MHC-II-restricted epitope Ea. ５２－６８ This was a chimeric antibody formed by combining the IE alpha chain transgene and the IE alpha chain (Iwamoto et al., Prevention of murine lupus by an IE alpha chain transgene: Protective role of IE alpha chain-derived peptides with a high affinity to I-Ab molecules. Eur J Immunol. 1996 Feb;26(2):307-14) (Figure 7). ＭＵＴOVAII and OVAI-Ea were expressed in Bpmel cells and used as cellular adjuvants in Bpmel-parent tumor-bearing mice and MC38 tumor-bearing mice, respectively. As shown in Figure 8, Adpgk used with anti-PD-L1 ＭＵＴ -OVAII and OVAI-Ea significantly suppressed the growth of contralateral Bpmel-parent and MC38 tumors, respectively.

[0120] To determine whether the MHC I-restricted epitopes and the MHC II-restricted epitopes must be chimeric on a single peptide chain, two cell lines were constructed. In Bpmel-SIY-OVAII / EGFP, the MHC I-restricted epitopes SIY and OVAII are chimeric on the same peptide chain, while Bpmel-SIY-EGFP / OVAII expresses SIY and OVAII separately (Figure 9). To exclude the immunogenicity of the selectable marker EGFP, tumor cells were inoculated into C57BL / 6-Tg(CAG-EGFP) mice. Nine days after MC38 implantation, mice were treated with Bpmel-SIY-OVAII / EGFP or Bpmel-SIY-EGFP / OVAII cellular adjuvant in the opposite flank. SIY-specific CD8 in peripheral blood mononuclear cells (PBMCs) of both groups of mice. ＋ T cells were detected (Figure 10), suggesting that both cellular adjuvants activated antigen-specific immune responses. However, only Bpmel-SIY-OVAII / EGFP inhibited the proliferation of contralateral MC38 cells, and Bpmel-SIY-EGFP / OVAII did not exhibit a significant antitumor effect (Figure 11). These results suggest that if any MHC I- and MHC II-restricted non-self epitopes are chimeric on a single peptide chain, expression of this type of antigen may result in a broad-spectrum antitumor effect independent of antigen specificity. An antigen with this structure is referred to as a "complete T cell antigen (CTA)."

[0121]

[0122] Test 2: Intracellular expression of intact T cell antigens is determined by neoantigen-specific CD8 ＋We investigated whether immunization with CTA proteins, which promote T cell infiltration, would have a comparable antitumor effect. To answer this question, MC38 tumor-bearing mice were immunized with OVA proteins and compared with Bpmel-OVA cellular adjuvant. Both immunizations significantly increased OVA-specific CD8 ＋ Both treatments promoted the generation of T cells (Figure 12). This suggests that both methods can activate antigen-specific immune responses. However, only Bpmel-OVA cell adjuvant treatment significantly inhibited the growth of MC38 tumors, whereas immunization with OVA protein did not (Figure 13). Further studies revealed that both treatments significantly inhibited the expression of CD62L in the DLN adjacent to the MC38 tumor. － CD44 ＋ Effector CD8 ＋ Although the Bpmel-OVA cell adjuvant could promote the generation of CD8 T cells (Figure 14), only the Bpmel-OVA cell adjuvant significantly increased the CD8 T cell production compared to immunization with OVA protein. ＋ TIL and MC38 neoantigen (Adpgk ＭＵＴ ) specific CD8 ＋ It was shown that CTA can promote T cell infiltration (Figure 15). These results indicate that intracellular expression of CTA is required to induce antitumor effects.

[0123] Because MC38 is an immunogenic tumor, neoantigen-specific CD8 ＋ T cell infiltration may be enhanced by cellular adjuvants. The cellular adjuvant in CTA can induce neoantigen-specific CD8 T cell proliferation even in poorly immunogenic tumors that do not respond to PD-1 blockade therapy. ＋ We investigated whether Bpmel-parent neoantigens promote T cell infiltration. To this end, we attempted to identify neoantigens in Bpmel-parent mice. Whole exome sequencing (WES) of Bpmel revealed 14,035 mutations at the exome level. Subsequent RNA sequencing showed that 4,924 of these mutations could be expressed at the RNA level. We focused on 328 missense mutations that directly alter the protein sequence. The epitopes generated by these missense mutations were further screened based on expression level, predicted affinity to MHC I, and changes in affinity before and after mutation. Finally, we identified DLN CD8＋ Forty-four peptide candidates were identified and synthesized to stimulate T cells. Four peptides, namely, AZIN1 ＭＵＴ , ARAF ＭＵＴ , AIFM1 ＭＵＴ and Scap ＭＵＴ is CD8 ＋ These four candidates were further confirmed by ELISpot assay, and three of the candidates (i.e., ARAF) stimulated the release of IFN-γ from T cells. ＭＵＴ , AIFM1 ＭＵＴ and Scap ＭＵＴ ) is CD8 ＋ Promoted IFN-γ release from T cells. CD8 ＋ Scape TIL ＭＵＴ and ARAF ＭＵＴ MHC tetramer (AIFM ＭＵＴ When stained with ARAF (which failed to assemble MHC tetramers), 0.5% to 1.5% of ARAF was detected in each of the five mice tested. ＭＵＴ specific CD8 ＋ These results suggest that ARAF T cells could be detected. ＭＵＴ (CGYTFHQHC (SEQ ID NO: 13)) was shown to be the best neoantigen for Bpmel. Then, mice bearing Bpmel tumors were treated with MC38-OVAI-Ea cell adjuvant. ARAF infiltrating the tumors ＭＵＴ specific CD8 ＋ T cells were significantly increased by treatment with MC38-OVAI-Ea cell adjuvant. These results suggest that intracellular expression of intact T cell antigens is related to neoantigen-specific CD8 ＋ It has been shown to promote T cell infiltration.

[0124] Test 3: Complete T cell antigen is CD8 ＋ Suppresses TIL exhaustion and activates effector memory CD8 ＋ In an analysis of MC38 tumor-bearing mice treated with Bpmel-SIY-OVAII cell adjuvant (Figure 16), CX3CR1 expression was significantly elevated in the DLN. ＋ and CD62L － CD44 ＋ Effector CD8 ＋A sustained increase in the proportion of T cells (Yan et al., CX3CR1 identifies PD-1 therapy-responsive CD8+ T cells that withstand chemotherapy during cancer chemoimmunotherapy. JCI Insight. 2018 Apr 19;3(8):e97828) and CD8 ＋ A significant increase in TIL infiltration was observed. ＋ The effect of increasing TILs lasted for one week. ＋ PD1 ＋ or TIM3 ＋ PD1 ＋ Terminally exhausted CD8 cells are marked ＋ T cells were significantly suppressed by cellular adjuvant therapy (Figure 17). ＋ Slamf6 showing TIL population ＋ PD1 － These results suggest that intact T cell antigens are expressed by CD8 at the tumor site. ＋ This is thought to indicate that it suppresses TIL exhaustion and promotes the accumulation of precursor / effector cells.

[0125] CD8 after CTA adjuvant therapy ＋ To further understand the precise phenotypic changes of TILs, single-cell RNA sequencing was used to analyze total CD8 T cells from MC38 tumors with and without Bpmel-SIY-OVAII (SO) treatment. ＋ TILs (hereafter abbreviated as SO TILs and control TILs, respectively) were analyzed. After quality control and duplicate removal, transcriptomes from 10,357 control TILs and 19,946 SO TILs were used for further analysis. Unsupervised clustering analysis revealed 11 clusters with no significant batch effect across the two conditions (Figure 19). CD8 TILs obtained from ProjecTILs ＋ According to the TIL annotation reference, the majority of TILs are terminally exhausted (Tex) CD8 ＋TILs constitute clusters 0 and 1; progenitor exhausted T cells (Tpx) CD8 ＋ TILs comprise clusters 5 and 6; predominantly effector memory CD8 ＋ TILs constituted clusters 2, 3, 4, and 7 (Figure 20). Based on this annotation, exhausted CD8 T cells were more abundant in the SO group than in the control group. ＋ The frequency of T cells (Tex or Tpx) is low, while the frequency of effector memory CD8 ＋ We found that T cells increased (Figure 21). Similar results were observed when comparing the frequencies of each cluster between the control group and the SO group.

[0126] Exhausted CD8 ＋ To understand the differences in T cell quality, we examined gene expression differences (GED) between the control and SO groups. Total CD8 T cells from SO TILs were significantly higher than those from control TILs. ＋ The exhausted population (Tex + Tpx) expressed high levels of Mki67, Top2a, Cdk6, and Bcl2 (Figure 22), indicating a higher residual proliferative capacity and resistance to apoptosis. Gating on the terminally exhausted population (Tex), cluster 0 decreased, whereas cluster 1 increased, in SO TILs compared with control TILs. Because cluster 0 expressed advanced exhaustion markers such as Lag3, Tigit, and Id2, while cluster 1 primarily expressed naive or proliferation markers such as Il7r, Bcl2, and Cdk6, the difference in quality between the control and SO groups may be due to a population shift from cluster 0 to cluster 1 following SO therapy.

[0127] On the other hand, CD8 ＋Focusing on the effector memory population, the SO group expressed higher levels of Il7r and Mki67 genes compared to control TILs (Figure 23), indicating their proliferative potential and rejuvenated phenotype. The effector memory population in the SO group also expressed higher levels of Gzmf and Gzmc, which promote cytolytic function (Figure 23). When gating on the effector memory population to examine changes in components, clusters 2 and 3 were strongly expressed in SO TILs but very rare in control TILs. Classical CD8 ＋ In contrast to the effector memory population (cluster 4), clusters 2 and 3 newly emerged by SO therapy expressed high levels of proliferation markers (Mki67 and Cdk6), anti-apoptotic genes (Bcl2), and backup granzymes (Gzmf and Gzmc), and low levels of exhaustion markers (Ccl5 and Id2). These data indicate that clusters 2 and 3 are characterized by less exhaustion and higher proliferative capacity compared to cluster 4. Taken together, CTA therapy may reduce exhausted populations and change their phenotype to a "younger" effector memory population with proliferative capacity. Notably, the FACS analysis in Figure 18 showed that Slamf6 was increased by SO therapy. ＋ The population primarily represents the effector memory population.

[0128] Trajectory analysis using Monocle3 further revealed two transition pathways: from clusters 3 and 4 to cluster 0, and from cluster 2 to cluster 1. This analysis raised the novel possibility that SO therapy boosts the invasion of cluster 2, which has a high proliferative potential and a young phenotype. When cluster 2 enters the terminal exhaustion stage, it may differentiate into cluster 1 and replace the original cluster 0, which is prone to apoptosis.

[0129] Test 4: CD4 ＋ T cells are essential for intact T cell antigen-induced antitumor effects. Because MHC II-restricted epitopes were found to be required for intact T cell antigen-mediated antitumor effects, CD4 ＋We hypothesized that T cells play an important role. To test this hypothesis, we injected anti-CD4 antibodies into MC38 tumor-bearing mice to induce CD4 T cell proliferation. ＋ T cells were depleted and Bpmel-OVAI-Ea cell adjuvant therapy was performed (Figure 24). After injection of anti-CD4 antibody, CD4 ＋ As expected, the Bpmel-OVAI-Ea cell adjuvant therapy completely depleted CD4 T cells. ＋ In the T cell-depleted group, antitumor activity (Figure 25), effector CD8 in the DLN ＋ Increased T cells or CD8 ＋ As usual, Bpmel-OVAI-Ea cell adjuvant therapy did not affect the accumulation of TIL infiltration. ＭＵＴ specific CD8 ＋ significantly promoted TIL infiltration, but this effect was not observed in CD4 ＋ These results suggest that the antitumor effect induced by intact T cell antigens is mediated by CD4 ＋ This shows that T cells are essential.

[0130] Study 5: Cellular adjuvants containing complete T cell antigens boost dendritic cell-T cell crosstalk CD4 ＋ T cells license antigen-presenting cells and CD8 ＋ It has been reported that cellular adjuvants enhance T cell activity, thereby altering the crosstalk between various immune cells and subsequently increasing CD8 ＋We hypothesized that this alters the activation state of T cells. To further understand the crosstalk between immune cells, we performed single-cell RNA-seq analysis to examine total DLN cells from MC38 tumor-bearing mice that received or did not receive Bpmel-SIY-OVAII cellular adjuvant therapy (SO). Based on gene expression, cells were classified into 12 clusters (Figure 26). Comparing the outgoing and incoming signals from each cell population in the control and SO groups using CellChat revealed that dendritic cells (DCs) were most altered compared with other cell populations (Figure 27). To identify alternative signaling pathways mediated by cellular adjuvant therapy, we compared the overall information flow for each signaling pathway. The immune checkpoint signal TIGIT and the developmental signal FLT3 were detected only in the control and SO groups, respectively. CD86, ICOS, and CD40 signals were relatively stronger in the SO group than in the control group. The overall signaling was most significantly altered by cellular adjuvant therapy in DCs compared to other cell populations, including costimulatory signals such as CD6 and ALCAM, which have been reported to be supportive in the restimulation of effector T cells. Analysis of signals sent from DCs to other cell populations revealed that CD4 from MHC I and MHC II expressed on DCs was significantly altered. ＋ T helper 1 (Th1) and CD8 ＋ It was shown that signals to T cell populations were enhanced after cellular adjuvant therapy (Figure 28). These results suggest that cellular adjuvant therapy expressing complete T cell antigens promotes crosstalk between antigen-presenting cells and T cells, and enhances CD8 ＋ This supported the hypothesis that it alters the activation state of T cells.

[0131] Test 6: Notch ＭＵＴis a natural complete T cell antigen derived from MC38. The complete T cell antigens used in the above cellular adjuvant therapy were all artificially constructed and expressed. Therefore, we next investigated whether immunogenic tumor cells naturally produce complete T cell antigens using MC38 as an example. Most neoantigen studies have focused on missense mutations and common mutations. However, we focused on frameshift mutations, which theoretically can generate long single-chain peptides containing both MHC I-restricted and MHC II-restricted epitopes. Examining the results of whole exome sequencing (WES) of MC38 revealed 25 frameshift mutations, one of which was a guanine deletion at position 331 of Notch2 (Notch2 ＭＵＴ ), which resulted in a 216 amino acid (AA) long neoepitope (Figure 29). This immunogenic peptide could theoretically generate 11 and 14 strong binding sites for MHC I (H2-Db and -Kb) and MHC II (I-Ab), respectively (Tables 2 and 3), and thus is expected to meet the requirements of a CTA.

[0132]

[0133]

[0134] Allele-specific PCR was performed on E. coli clones containing the MC38 Notch2 segment. In some E. coli clones, the Notch2 segment was amplified only with primers for this mutation, but not with primers for the wild type. Sequencing of the amplified product confirmed a frameshift mutation, as revealed by WES. Notch2 ＭＵＴ To determine the immunogenicity of the resulting Notch2 ＭＵＴ was expressed in Bpmel-parent cells. EGFP represents Notch2. ＭＵＴ As a control, Bpmel-EGFP was constructed because it is similar in length to Bpmel-Notch2 and is also a foreign antigen. Similar to Bpmel-parent tumors, Bpmel-EGFP tumors continued to grow in mice, but Bpmel-Notch2 ＭＵＴThe tumor was highly immunogenic and was spontaneously rejected within approximately two weeks (Figure 30). ＭＵＴ Growth of MC38 tumors re-inoculated 3 weeks after rejection was significantly reduced by Bpmel-Notch2. ＭＵＴ These data support the conclusion that Notch2 expressed by MC38 is significantly inhibited in mice that have never been inoculated with MC38 (Figure 31). ＭＵＴ Next, we show that Notch2 is recognized by adaptive immunity. ＭＵＴ We investigated whether the derived MHC-I-restricted epitopes and MHC-II-restricted epitopes were immunogenic. ＭＵＴ were inoculated and DLN cells were isolated on day 13. ＭＵＴ zsGreen-HisTag or Notch2 isolated from MC38 cells overexpressing HisTag ＭＵＴ DLN cells were stimulated with the -HisTag protein and CD4 ＋ and CD8 ＋ IFN-γ release from T cells was assessed by IFN-γ capture assay. ＋ and CD4 ＋ The proportion of T cells is Notch2 ＭＵＴ The Notch2 expression level increased 8- and 4-fold after stimulation with zsGreen-HisTag, but not after stimulation with zsGreen-HisTag, indicating that Notch2 expression levels were significantly higher than those of the control group. ＭＵＴ This shows that both MHC I and II epitopes of CD4 are immunogenic. ＋ T cell IFN-γ production is CD8 ＋ Notch2 was thought to be weaker than T cells. ＭＵＴ The affinity of the epitope for MHC III-Ab was predicted, and CD4 ＋ The 15 most potent affinity candidate peptides were synthesized for T cell stimulation (Table 4). NotMHCII4 and 14 stimulated CD4 T cells in the DLN by ELISPOT assay. ＋ Furthermore, IFN-γ capture assays demonstrated that NotMHCII4 stimulated CD4 T cells to release IFN-γ. ＋These data suggest that MC38 cells naturally possess CTA, which may contribute to their sensitivity to PD-1 blockade.

[0135]

[0136] In contrast, WES revealed eight frameshift mutations in the Bpmel-parent, and only Usp49 was predicted to be a complete T cell antigen (two MHC-I binding sites and one MHC-II binding site). However, these two predicted MHC-I binding sites were actually both CD8 ＋ These data suggest that Bpmel-parent mice do not naturally produce complete T cell antigens, which may be one of the reasons why Bpmel-parent mice do not respond to anti-PD-L1. Taken together, these results suggest that immunogenic MC38 does not naturally produce complete T cell antigens, such as Notch. ＭＵＴ Indicates that it contains.

[0137] Study 7: Cellular adjuvants containing natural whole T cell antigens enhance progenitor-like CD8 ＋ Cellular adjuvants containing artificial CTAs can reverse unresponsive tumors by inducing exhausted CD8 T cells. ＋ Natural CTA also suppressed CD8 T cells and induced exhausted precursor T cells (Test 3). ＋ We aimed to determine whether Bpmel-Notch2 exerts similar effects on T cell phenotype and whether such phenotypic changes alter responsiveness to PD-1 blockade therapy. To address these questions, we performed combination therapy in LLC mice that are unresponsive to anti-PD-L1 treatment (Figure 32). ＭＵＴ Injection of the cellular adjuvant or anti-PD-L1 antibody alone resulted in a slight reduction in LLC tumor volume, whereas injection of Bpmel-Notch2 ＭＵＴ The cellular adjuvant and anti-PD-L1 antibody (combined treatment) significantly suppressed LLC tumor volume (Figure 33). ＋ Enhanced TIL infiltration but CD4 ＋It did not affect TIL infiltration (Figure 34). Notably, anti-PD-L1 therapy alone did not affect CD8 ＋ Promotes TIL exhaustion and self-renewal-competent slam6 ＋ CD8 ＋ Although the combination therapy reduced TIL infiltration, it also suppressed exhaustion and increased the number of self-renewing CD8 ＋ These data suggest that cellular adjuvants containing natural whole T cell antigens promote the infiltration of CD8 TILs. ＋ This indicates that the effect of anti-PD-L1 therapy was reversed, accompanied by a change in the phenotype of TILs. In the same LLC tumor model, we found that the MC38 adjuvant was also sufficient to enhance the efficacy of PD-1 blockade therapy. This is likely due to the fact that MC38 cells naturally express Notch2. ＭＵＴ Considering that cancer tissues are heterogeneous collections of cancer clones, the presence of clones expressing natural CTAs may at least partially regulate the responsiveness of all cancer tissues to immunotherapy.

[0138] Study 8: Longer frameshift mutations increase the frequency of intact T cell antigens and predict a favorable prognosis for cancer patients. Next, we speculated that the CTAs produced by a patient's tumor may also affect disease progression. To answer this question, we obtained WES data from a public database of 456 colorectal cancer patients who had received any treatment and analyzed the immunogenic peptides produced by each type of mutation. Because frameshift mutations usually result in a premature stop codon, preventing further elongation of the immunogenic peptide, 90% of the immunogenic peptides produced by frameshift mutations were less than 60 amino acids (AA) in length (Table 4).

[0139]

[0140] The immunogenic neopeptide generated by the frameshift mutation, extending from the mutation site to the naturally occurring stop codon, was designated the "functional peptide." Because the length of the functional peptide directly correlates with the likelihood of generating a complete T cell antigen, the maximum length of the functional peptide generated by each patient was used as a prognostic marker to predict patient survival. As shown in Figure 37, patients whose tumors generated functional peptides (FP) longer than 120 AA had a significantly better prognosis than patients whose tumors generated functional peptides shorter than 120 AA. Furthermore, the maximum length of the functional peptide served as a better prognostic marker than tumor mutation burden (TMB) or the number of frameshift mutations (FS) (Figure 37). These data suggest that the ability of tumors to generate natural CTAs via frameshift mutations may be associated with a favorable prognosis.

[0141] Experiment 9: Electrotransfer of a complete T cell antigen vector in muscle enhances antitumor immunity. In clinical applications, it would be difficult to inoculate patients with a live (tumor) adjuvant expressing CTA. Therefore, we investigated whether expression of CTA in muscle cells by electrotransfer of a DNA vector could enhance antitumor immunity. One week after inoculation with MC38, pCAGGS-SIY-OVAII was electrotransferred into muscle (Figure 38). On day 14, SIY-specific CD8 T cells were detected in PBMCs. ＋ T cells were detected, indicating successful gene transfer and immunization. Electrotransfer of pCAGGS-SIY-OVAII alone suppressed the growth of MC38 tumors, while electrotransfer of pCAGGS-SIY had no antitumor effect (Figure 39). In an extreme case, one mouse almost rejected the tumor after electrotransfer of pCAGGS-SIY-OVAII, but this case was not observed in the other two groups. As expected, only electrotransfer of pCAGGS-SIY-OVAII suppressed the CD8 T cells in the DLN. ＋ and CD4 ＋ CD27 on T cells ＋ CX3CR1 ＋ At the tumor site, electrotransfer of pCAGGS-SIY-OVAII promoted the generation of 4-1BB colonies, whereas pCAGGS-SIY did not. ＋ CD107a＋ CD8 ＋ T cells (activated T cells) and Slamf6 ＋ CD127 ＋ CD8 ＋ It also promoted the infiltration of TIL (self-renewal T cells) (Figure 40). These results indicate that electrotransfer of CTA promotes antitumor effects.

[0142] According to the present disclosure, it is possible to treat cancer in a subject, predict the prognosis of a subject suffering from cancer, and predict whether an immune checkpoint inhibitor will be effective against cancer in a subject, which is useful in the medical field.

Claims

1. A composition for treating cancer in a subject, comprising a nucleic acid encoding a peptide comprising at least one non-self MHC class I-restricted epitope and at least one non-self MHC class II-restricted epitope.

2. The composition of claim 1, which is administered to a subject whose cancer expresses unknown cancer neoantigens.

3. The composition of claim 1 or 2, which is administered to a subject without determining prior to administration whether the subject expresses at least one non-self MHC class I-restricted epitope and at least one non-self MHC class II-restricted epitope contained in the peptide.

4. The composition of any one of claims 1 to 3, wherein at least one non-self MHC class I-restricted epitope is an MHC class I-restricted epitope not expressed by the subject, and at least one non-self MHC class II-restricted epitope is an MHC class II-restricted epitope not expressed by the subject.

5. The composition of any one of claims 1 to 4, wherein the at least one non-self MHC class I restricted epitope comprises an HLA-A epitope, an HLA-B epitope, or an HLA-C epitope.

6. The composition of any one of claims 1 to 5, wherein the at least one non-self MHC class II restricted epitope comprises an HLA-DR epitope, an HLA-DQ epitope, or an HLA-DP epitope.

7. The composition of any one of claims 1 to 6, wherein at least one non-self MHC class I-restricted epitope and / or at least one non-self MHC class II-restricted epitope comprises an epitope of an HLA subtype that is frequently represented in a population to which the subject belongs.

8. The composition of any one of claims 1 to 7, wherein at least one non-self MHC class I-restricted epitope comprises multiple epitopes restricted by multiple different HLA subtypes, and / or at least one non-self MHC class II-restricted epitope comprises multiple epitopes restricted by multiple different HLA subtypes.

9. The composition of any one of claims 1 to 8, used in combination with an immune checkpoint inhibitor.

10. The composition described in any one of claims 1 to 9, wherein the cancer is leukemia, malignant lymphoma, multiple myeloma, myelodysplastic syndrome, head and neck cancer, gastrointestinal cancer, liver cancer, gallbladder / bile duct cancer, biliary tract cancer, pancreatic cancer, thyroid cancer, lung cancer, breast cancer, urogenital cancer, bone and soft tissue sarcoma, skin cancer, neuroendocrine tumor, glioma, brain tumor, malignant mesothelioma, or cancer of unknown primary origin.

11. The composition of any one of claims 1 to 10, wherein the nucleic acid is contained in a vector.

12. The composition of claim 11, wherein the vector is a retroviral vector, lentiviral vector, adenoviral vector, adeno-associated viral vector, herpes simplex viral vector, vaccinia viral vector, Sendai viral vector, or measles viral vector.

13. A composition for treating cancer in a subject, comprising cells expressing a peptide comprising at least one non-self MHC class I-restricted epitope and at least one non-self MHC class II-restricted epitope.

14. The composition of claim 13, wherein the cells are autologous cells.

15. The composition of claim 13 or 14, wherein the cells are fibroblasts or blood cells.

16. A method for predicting the prognosis of a subject suffering from cancer, comprising: (1) analyzing the genes of cancer tissue obtained from the subject and determining whether or not the cancer tissue contains a non-self antigen peptide containing a non-self amino acid sequence that is longer than a cutoff value; and (2) predicting that the subject will have a good prognosis if the non-self antigen peptide is present in the cancer tissue.

17. A method for predicting whether an immune checkpoint inhibitor will be effective against a subject's cancer, comprising: (1) analyzing the genes of cancer tissue obtained from the subject and determining whether the cancer tissue contains a non-self antigen peptide containing a non-self amino acid sequence that is longer than a cutoff value; and (2) predicting that the immune checkpoint inhibitor will be effective against the subject's cancer if the non-self antigen peptide is present in the cancer tissue.

18. The method of claim 17, wherein the cutoff value is anywhere from about 50 to 120 amino acids in length.

19. The method according to claim 17 or 18, wherein the cancer is leukemia, malignant lymphoma, multiple myeloma, myelodysplastic syndrome, head and neck cancer, gastrointestinal cancer, liver cancer, gallbladder / bile duct cancer, biliary tract cancer, pancreatic cancer, thyroid cancer, lung cancer, breast cancer, urogenital cancer, bone and soft tissue sarcoma, skin cancer, neuroendocrine tumor, glioma, brain tumor, malignant mesothelioma or cancer of unknown primary origin.

20. The method according to any one of claims 17 to 19, wherein the cancer is colon cancer.

21. The method of any one of claims 17 to 20, comprising administering an immune checkpoint inhibitor to the subject when it is predicted that the subject's cancer will be effective against the immune checkpoint inhibitor.

22. The method of claim 21, wherein the immune checkpoint inhibitor is an anti-PD-1 antibody or an anti-PD-L1 antibody.

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