Proteogenomic-based method for identifying tumor-specific antigens

Abstract

To provide a novel approach for the treatment of lung cancer.SOLUTION: T cells, particularly CD8 T cells, are essential players in tumor eradication, as the presence of tumor-infiltrating lymphocytes (TILs) in several cancers positively correlates with a good prognosis. To eliminate tumor cells, CD8 T cells recognize tumor antigens, which are MHC I-associated peptides present on the surface of tumor cells and either not expressed or expressed at very low levels on normal cells. Described herein is a proteogenomic approach using RNA sequencing data from cancer and matched normal mTEChi samples to identify non-tolerogenic tumor-specific antigens derived from (i) coding and non-coding regions of the genome, (ii) non-synonymous single-base mutations or short insertions / deletions, and more complex rearrangements, as well as (iii) endogenous retroelements, which function regardless of the sample's mutational load or complexity.SELECTED DRAWING: None

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application is a continuation of U.S. Provisional Patent Application No. 62 / 724,760, filed August 30, 2018. No. 6,299,499, filed on Oct. 1, 2004, which is hereby incorporated by reference in its entirety.

[0002] The present invention relates generally to cancer and, more specifically, to T cell-based cancer immunotherapy. This paper deals with the identification of tumor antigens. [Background technology]

[0003] CD8 T cells are present as tumor-infiltrating lymphocytes (TILs) in several cancers. , which positively correlates with favorable prognosis and response to immune checkpoint inhibitors, and He is known to be an essential player in the ultimate 1、2 To eliminate tumor cells To achieve this, CD8 T cells react to abnormal MHC I-associated peptides ( CD8 T cells recognize tumor antigens, which are MHC I-associated peptides (MAPs). ), the most important open question is how MA is recognized by CD8 TILs. It is a property of P 3 A high number of CD8 TILs has been shown to correlate with tumor mutation burden. The prevailing paradigm is that CD8 TILs express mutated tumor-specific antigens, commonly referred to as neoantigens. Supports recognition of target antigen (mTSA) 2、4、5 The high immunogenicity of mTSA is Minimizing the risk of immune resistance due to their selective expression in tumors 6 Moreover, Nevertheless, some TILs express aberrantly expressed TSA (aeTSA) in tumor-specific tumors. Normalized non-mutable MAP 7aeTSA has been shown to recognize endogenous retroelements. These proteins are involved in the transcription and translation of genomic sequences that are not expressed in normal cells, such as endogenous receptors (EREs). can result from a variety of cis- or trans-acting genetic and epigenetic changes 8- 10 .

[0004] Considerable effort has been made to discover viable TSAs that can be used in therapeutic cancer vaccines. The most common strategy is reverse immunology. y), i) exome sequencing is performed on tumor cells to identify mutations, and ii) MH Using a C binding prediction software tool, we identified which variant MAPs are good MHC binders. Identify what is possible 11、12 Reverse immunology can enrich TSA candidates, but Although available computational methods can predict MHC binding, other steps involved in the MAP process may be involved. Because the steps cannot be predicted 14、15 , at least 90% of these candidates are false. positive 5、13 To overcome this limitation, several studies have investigated the effectiveness of TSA-issued The pipeline includes mass spectrometry (MS) analysis. 16 , thereby some TS leading to the rigorous molecular determination of A. 17、18 However, the yield of these approaches is In melanoma, one of the most mutated tumor types, the treatment of individual tumors is highly underpowered. On average, two TSAs are verified by MS. 19 However, little is known about other cancer types. Only a few TSA approved 15 Note on TIL or immune checkpoint inhibitors TS does not induce tumor regression if the tumor does not express immunogenic antigens. The scarcity of A is a challenge 20 The exon mutation-based approach recognizes that they have two important It was speculated that the TSA had failed to identify the suspect because it had not taken into account certain factors. First, there is essentially no method currently available for high-throughput identification of aeTSA. However, these approaches focus only on mTSA and neglect aeTSA. This represents a significant drawback, as mTSA is a unique antigen, whereas aeTSA is a shared antigen by multiple tumors. This is because they can be used to treat cancer and may be a desirable target for vaccine development. 7、9 . 2 Therefore, focusing on the exome as the sole source of TSA is very limiting. The exome (i.e., all protein-coding genes) makes up only 2% of the human genome. represents the total number of genes in the genome, whereas up to 75% of the genome can be transcribed and potentially translated 22 .

[0005] Therefore, novel methods for identifying tumor antigens that can be used in T cell-based cancer immunotherapy are being developed. An approach is needed.

[0006] Acute lymphoblastic leukemia (ALL) is a type of lymphoid leukemia that occurs in the bone marrow, blood, and extramedullary sites. ALL is a malignant transformation and proliferation of precursor cells. 80% of ALL occurs in children; It represents a devastating disease when it occurs in humans. In the United States, the incidence of ALL is approximately 100,000 per 100,000 people. Dose-intensification strategies have led to significant improvements in outcomes for pediatric patients. However, the prognosis for elderly patients remains very poor. Despite this, only 30-40% of adult patients with ALL achieve long-term remission.

[0007] Therefore, new approaches for the treatment of ALL are needed.

[0008] Lung cancer, a highly aggressive, rapidly metastasizing, and widespread cancer, is a leading cause of death in the United States (U.S.) It is the most lethal cancer in both men and women in the world. Approximately 90% of lung cancer cases are However, radon gas, Other factors, such as sbestos, air pollution exposure, and chronic infections, may contribute to lung cancer development. In addition, multiple genetic and acquired mechanisms of susceptibility to lung cancer have been proposed. Lung cancer is classified into two broad histological classes, small cell lung cancer and small cell lung cancer, which grow and spread differently. Lung cancer is divided into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). Treatment options for lung cancer include: These include surgery, radiation therapy, chemotherapy, and targeted therapy. Despite improvements in diagnosis and treatment, the prognosis for patients with lung cancer remains unsatisfactory. Response to current standard therapies is poor in all but the most localized cancers. It is something.

[0009] Therefore, new approaches for the treatment of lung cancer are needed.

[0010] This description refers to a number of documents, the contents of which are incorporated herein by reference in their entireties. will be incorporated into Summary of the Invention

[0011] The present disclosure provides the following items 1 to 75. 1. A method for identifying candidate tumor antigens in a tumor cell sample, comprising: (a) Tumor-specific proteome databases are compiled using (i) at least three tumor RNA sequences. (ii) extracting a set of subsequences (k-mers) containing 3 base pairs; The set of tumor subsequences was constructed using at least 33 base pairs extracted from RNA sequences from normal cells. (iii) comparing the corresponding control subsequences to a set of corresponding control subsequences containing the corresponding control subsequences; Tumor subsequences that are not present in the control subsequences are extracted, thereby providing tumor-specific subsequences. (iv) computer-translating the tumor-specific subsequences and obtaining a tumor-specific proteome database by (b) A personalized tumor proteome database is constructed by comparing (i) tumor RNA sequences with reference genome sequences. (ii) identify single-nucleotide mutations in tumor RNA sequences compared to (i) The identified single base mutations are inserted into the reference genome sequence, thereby creating a personalized tumor genome sequence. and (iii) generating expressed protein-coding transcripts from the personalized tumor genome sequence. The resulting data are then translated by computer to create a personalized tumor proteome database. Obtaining and generating by (c) Sequences of major histocompatibility complex (MHC)-associated peptides (MAPs) from tumors were analyzed using the a) Tumor-specific proteome database and (b) personalized tumor proteome database Identifying MAPs by comparing sequences from the database; (d) identifying candidate tumor antigens among the MAPs identified in (c), The original candidate is a gene whose sequence and / or coding sequence is over-represented in tumor cells compared to normal cells. The method is an expressed or over-presented peptide. 2. The above method comprises: (1) extracting major histocompatibility complex (MHC)-related peptides from a tumor cell sample; and / or (2) isolating and sequencing MAPs in tumor cell samples. and performing whole transcriptome sequencing to obtain tumor RNA sequences. , the method described in item 1. 3. Isolation of the MAP involves (i) releasing the MAP from the cell sample by treatment with a weak acid. and (ii) subjecting the released MAP to chromatography. The method described in item 2. 4. The method comprises separating the released peptides through a size exclusion column prior to the chromatography. 4. The method of claim 3, further comprising filtering the sample through a filter. 5. The method according to any one of items 1 to 4, wherein the subsequence comprises 33 to 54 base pairs. . 6. Assemble overlapping tumor-specific subsequences into longer tumor subsequences (contigs) 6. The method according to any one of items 1 to 5, further comprising: 7. The method according to item 6, wherein the size exclusion column has a cutoff of about 3000 Da. method. 8. Sequencing of the MAPs involves subjecting the isolated MAPs to mass spectrometry (MS) sequencing analysis. 8. The method according to any one of items 1 to 7, comprising: 9. The method comprises generating a personalized normal proteome database using corresponding normal cells. 9. The method according to any one of items 1 to 8, further comprising generating 10. The identification in (d) is performed by identifying the MAP as a normal individualized proteome. 10. The method of claim 9, further comprising excluding the gene if detected in the database. 11. The method comprises: determining whether 24 or 3 RNA sequences from the tumor RNA sequence and RNA sequences from normal cells are identical; A 9-nucleotide k-mer database was generated to compare the tumor k-mer database and positive Obtaining the normal k-mer database and the tumor k-mer database and normal k-mer database The er database was analyzed using 24 or 39 nucleotide k-meta sequences derived from MAP coding sequences. r, and comparing the tumor k-mers to the normal k-mer database. Overexpression or overexpression of k-mers derived from MAP coding sequences in the cancer k-mer database Any of items 1 to 10, where over- or under-expression indicates that the corresponding MAP is a candidate tumor antigen. The method according to any one of claims 1 to 5. 12. The k-mers derived from the MAP coding sequence are compared with the normal k-mer database. In comparison, at least 10-fold overexpression or overexpression in the tumor k-mer database Item 12. The method of item 11, wherein the method is presented in a multi-step manner. 13. The k-mers derived from the MAP coding sequence are compared with the normal k-mer database. 13. The method according to item 11 or 12, wherein 14. The method comprises: (a) isolating and sequencing MAPs in a tumor cell sample; (b) performing whole transcriptome sequencing on the tumor cell sample, thereby determining whether the tumor Obtaining an RNA sequence; (c) generating a tumor-specific proteome database from (i) the tumor RNA sequences; (ii) extracting a set of subsequences containing at least 33 nucleotides from the tumor sample of (i); A set of knock-in sequences was prepared by extracting RNA sequences from normal cells containing at least 33 nucleotides. (iii) comparing the corresponding set of control subsequences containing the corresponding Tumors that are absent or down-expressed at least 4-fold in the control subsequence (iv) extracting tumor subsequences, thereby obtaining tumor-specific subsequences; The target subsequences are then translated by computer to generate tumor-specific proteome data. Obtaining a base and generating by (d) A personalized tumor proteome database is generated by comparing (i) tumor RNA sequences with reference genome sequences. (ii) identifying single nucleotide mutations in the tumor RNA sequence compared to (i) The single nucleotide mutations identified in the above are inserted into the reference genome sequence, thereby generating a personalized tumor genome sequence. and (iii) generating an expressed protein code from the personalized tumor genome sequence. The transcripts are translated by computer, thereby creating a personalized tumor proteome database. and generating the (e) A personalized normal proteome database is referenced to (i) RNA sequences from normal cells. comparing the normal RNA sequence with a genome sequence to identify single base mutations in the normal RNA sequence; (ii) inserting the single nucleotide variation identified in (i) into the reference genome sequence, thereby individualizing (iii) generating a normal genome sequence; and (iv) determining an expressed template from the individualized normal genome sequence. The protein-coding transcripts are then computer-translated, thereby generating personalized normal proteomic sequences. obtaining a game database; (f) Normal and tumor k-mer databases are compared with (i) the relevant RNA sequences from normal cells. and extracting a set of subsequences containing at least 24 nucleotides from the tumor RNA sequence. By producing, (g) The MAP sequences obtained in (a) were compared with the tumor-specific proteome database in (c). and (d) comparing the sequences in the personalized tumor proteome database to identify MAPs. And, (h) identifying candidate tumor antigens among the MAPs identified in (f), Original candidates are those whose (1) sequences are not present in the personalized normal proteome database and (2) (i) the sequence is present in a personalized tumor proteome database, and / or (ii) the code The sequence is compared to the normal k-mer database and the tumor k-mer database. Any one of items 1 to 13 corresponding to a MAP that is overexpressed or overrepresented in The method described in paragraph . 15. The method further comprises selecting a MAP having a length of 8 to 11 amino acids. 15. The method according to any one of items 1 to 14, comprising: 16. The method according to any one of items 1 to 15, wherein the normal cells are thymocytes. 17. The method according to item 16, wherein the thymocytes are medullary thymic epithelial cells (mTECs). . 18. Further comparing the coding sequence of the tumor antigen candidate with a sequence from normal tissue. 18. The method according to any one of items 1 to 17, comprising: 19. Any of items 1 to 18, wherein the MAP has a length of 8 to 11 amino acids. 10. The method according to claim 1. 20. Items 1 to 19, further comprising evaluating binding of the tumor antigen candidate to an MHC molecule. 10. The method according to any one of the preceding claims. 21. The binding is assessed using an MHC binding prediction algorithm, as described in item 20. How to post. 22. Further evaluate the frequency of T cells that recognize candidate tumor antigens in the cell population. 22. The method according to any one of items 1 to 21, comprising: 23. The frequency of T cells that recognize tumor antigen candidates is determined by comparing the tumor antigen candidates with their peptides. 23. The method of claim 22, wherein the method is evaluated using a multimeric MHC class I molecule containing the binding groove. 24. The method further comprising evaluating the ability of the tumor antigen candidate to induce T cell activation. 24. The method according to any one of 1 to 23. 25. The ability of tumor antigen candidates to induce T cell activation depends on their binding to MHC class I molecules. Cytokinesis by T cells contacted with cells bearing the tumor antigen candidate bound on the cell surface 25. The method according to item 24, wherein the activity is assessed by measuring steroid production. 26. The cytokine production includes interferon-gamma (IFN-γ) production. 2. The method according to item 25. 27. Tumor antigens that induce T cell-mediated tumor cell killing and / or inhibit tumor growth 27. The method of any one of items 1 to 26, further comprising assessing the performance of the candidate. 28. A tumor antigen peptide identified by the method defined in any one of items 1 to 27. Petite. 29. Contains one of the amino acid sequences shown in any one of SEQ ID NOs: 1 to 39 or a tumor antigen peptide consisting thereof. 30. Contains one of the amino acid sequences shown in any one of SEQ ID NOs: 17 to 39. 30. The tumor antigen peptide according to item 29, comprising or consisting of: 31. The tumor antigen peptide is a leukemia tumor antigen peptide, and is represented by SEQ ID NOs: 17 to 28. Item 1, which comprises or consists of one of the amino acid sequences shown in any one of A tumor antigen peptide described in item 30. 32. The leukemia is B-cell acute lymphoblastic leukemia (B-ALL), item 31 The tumor antigen peptide described in 33. The tumor antigen peptide is a human leukocyte antigen of the HLA-A*02:01 allele. (HLA) and is represented by any one of SEQ ID NOs: 17 to 19, 27, and 28. 33. The method according to item 31 or 32, comprising or consisting of one of the amino acid sequences Tumor antigen peptides. 34. The tumor antigen peptide is a human leukocyte antigen of the HLA-B*40:01 allele. (HLA) and comprising or consisting of the amino acid sequence set forth in SEQ ID NO: 20. 33. The tumor antigen peptide according to Item 31 or 32. 35. The tumor antigen peptide is a human leukocyte antigen of the HLA-A*11:01 allele. (HLA) and an amino acid sequence shown in any one of SEQ ID NOs: 21 to 23 33. The tumor antigen peptide according to item 31 or 32, comprising or consisting of one of: 36. The tumor antigen peptide is a human leukocyte antigen of the HLA-B*08:01 allele. (HLA) and comprises the amino acid sequence set forth in SEQ ID NO: 24 or 25; or 33. The tumor antigen peptide according to Item 31 or 32, consisting of the same. 37. The tumor antigen peptide is a human leukocyte antigen of the HLA-B*07:02 allele. (HLA) and comprising or consisting of the amino acid sequence set forth in SEQ ID NO: 26. 33. The tumor antigen peptide according to Item 31 or 32. 38. The tumor antigen peptide is a lung tumor antigen peptide and is any one of SEQ ID NOs: 29 to 39. Item 3, which comprises or consists of one of the amino acid sequences shown in any one of 1. A tumor antigen peptide according to claim 0. 39. The tumor antigen according to item 38, wherein the lung tumor is non-small cell lung cancer (NSCLC). peptide. 40. The tumor antigen peptide is a human leukocyte antigen of the HLA-A*11:01 allele. (HLA) and an amino acid sequence shown in any one of SEQ ID NOs: 29 to 35 40. The tumor antigen peptide according to item 38 or 39, comprising or consisting of one of: 41. The tumor antigen peptide is a human leukocyte antigen of the HLA-B*07:02 allele. (HLA) and comprising or consisting of the amino acid sequence set forth in SEQ ID NO: 36. 40. The tumor antigen peptide according to Item 38 or 39. 42. The tumor antigen peptide is a human leukocyte antigen of the HLA-A*24:02 allele. (HLA) and comprises the amino acid sequence set forth in SEQ ID NO: 38 or 39; or 40. The tumor antigen peptide according to Item 38 or 39, consisting of the same. 43. The tumor antigen peptide is a human leukocyte antigen of the HLA-C*07:01 allele. (HLA) and comprising or consisting of the amino acid sequence set forth in SEQ ID NO: 37. 40. The tumor antigen peptide according to Item 38 or 39. 44. Any one of items 29 to 43, derived from a non-protein-coding region of the genome. The described tumor antigen. 45. Non-protein-coding regions of the genome include intergenic regions, intronic regions, 5' untranslated region (5'UTR), 3' untranslated region (3'UTR), or endogenous retroelement 45. The tumor antigen according to Item 44, which is an endothelial growth factor receptor (ERE). 46. A nucleic acid encoding the tumor antigen peptide according to any one of items 28 to 45. 47. The nucleic acid according to item 46, which is an mRNA or a viral vector. 48. The tumor antigen peptide according to any one of items 28 to 45, or item 46. 48. A liposome comprising the nucleic acid according to claim 47. 49. The tumor antigen peptide according to any one of items 28 to 45, item 46 or 4 Item 7 or the liposome according to Item 48, and a pharmaceutically acceptable carrier. A composition comprising: 50. The tumor antigen peptide according to any one of items 28 to 45, item 46 or 4 Item 7, the liposome according to Item 48, or the composition according to Item 49, and azido. A vaccine comprising: 51. The tumor antigen peptide according to any one of items 28 to 45, in its peptide-binding groove. An isolated major histocompatibility complex (MHC) class I molecule comprising: 52. The isolated MHC class I molecule according to item 51, in the form of a multimer. 53. The isolated MHC class I molecule according to item 52, wherein the multimer is a tetramer. . 54. An isolated cell comprising a tumor antigen peptide according to any one of items 28 to 45. Cell. 55. The tumor antigen peptide according to any one of items 28 to 45, Isolate a major histocompatibility complex (MHC) class I molecule containing the ligation groove expressed on its surface The cells. 56. The cell according to item 55, which is an antigen-presenting cell (APC). 57. The cell according to item 56, wherein the APC is a dendritic cell. 58. The isolated MHC class I molecule and / or molecule according to any one of items 51 to 53. or an MHC class I molecule expressed on the surface of the cell according to any one of items 54 to 57. T cell receptor (TCR) specifically recognizes the antigen. 59. An isolated CD8 expressing the TCR according to item 58 on its cell surface. + T. Lin Pac-ball. 60. CD8 as defined in item 59 + A cell population containing at least 0.5% T lymphocytes Group. 61. A method for treating cancer in a subject, comprising administering to the subject an effective amount of (i) any of items 28 to 45. (ii) a tumor antigen peptide according to any one of items 46 and 47; and (iii) a nucleic acid according to item 48. (iii) the liposome according to item 48; (iv) the composition according to item 49; (v) (vi) a vaccine according to item 50, (vi) a cell according to any one of items 54 to 57, (vi i) CD8 as described in item 59 + (viii) a cell population according to item 60 The method comprises administering a 62. The method according to item 61, wherein the cancer is leukemia. 63. The leukemia is B-cell acute lymphoblastic leukemia (B-ALL), item 62 The method described below. 64. The method according to item 61, wherein the cancer is lung cancer. 65. The method according to item 64, wherein the lung tumor is non-small cell lung cancer (NSCLC). 66. The method further comprises administering to the subject at least one additional anti-tumor agent or therapy. 66. The method according to any one of Items 61 to 65. 67. The at least one additional anti-tumor agent or therapy is a chemotherapeutic agent, an immunotherapy, or an immunotherapy. 67. The method of item 66, wherein the treatment is an immune checkpoint inhibitor, radiation therapy, or surgery. 68. (i) a method according to any one of items 28 to 45 for treating cancer in a subject; (ii) a tumor antigen peptide according to Item 46 or 47; (iii) a nucleic acid according to Item 48 (iv) the liposome according to item 49; (v) the vaccine according to item 50. (vi) the cell according to any one of Items 54 to 57; (vii) the cell according to Item 59 CD8 + (viii) Use of T lymphocytes or a cell population according to item 60. 69. For the manufacture of a medicament for treating cancer in a subject, (i) items 28 to 45 (ii) a tumor antigen peptide according to any one of items 46 and 47; and (iii) a nucleic acid according to item 48. (iii) the liposome according to item 48; (iv) the composition according to item 49; (v) (vi) a vaccine according to item 50, (vi) a cell according to any one of items 54 to 57, (vi i) CD8 as described in item 59 + (viii) a cell population according to item 60 Use of "dan". 70. The use according to item 68 or 69, wherein the cancer is leukemia. 71. The leukemia is B-cell acute lymphoblastic leukemia (B-ALL), item 70 Use as described in. 72. The use according to item 68 or 69, wherein the cancer is lung cancer. 73. The use according to item 72, wherein the lung tumor is non-small cell lung cancer (NSCLC). 74. Items 68-7 further include the use of at least one additional anti-tumor agent or therapy. 3. The use according to any one of claims 3. 75. The at least one additional anti-tumor agent or therapy is a chemotherapeutic agent, an immunotherapy, or an immunotherapy. 75. The use according to item 74, wherein the treatment is an immune checkpoint inhibitor, radiation therapy, or surgery.

[0012] Other objects, advantages, and features of the present invention are described in the following non-limiting descriptions of specific embodiments of the invention. The invention will become more apparent from a reading of the description and is shown by way of example only in connection with the accompanying drawings, in which: do. [Brief explanation of the drawings]

[0013] Attached drawings.

[0014] [Figure 1A-C]The targeted proteogenomics workflow for identifying tumor-specific antigens (TSAs) is shown in Figure 1A and Figure 1B. A detailed schematic diagram shows how the standard cancer proteome (Figure 1A) and cancer-specific proteome (Figure 1B) were constructed for each analyzed sample. Figure 1C: The combination of these two proteomes, referred to as the global cancer database, was then used to identify MAPs, more specifically TSAs, sequenced by liquid chromatography-MS / MS (LC-MS / MS) from two well-characterized mouse cell lines, i.e., CT26 and EL4, and seven human primary samples, i.e., four B-ALL and three lung tumor biopsies (n = 2–4 per sample). Statistics for each part of the global cancer database can be found in Table 4a–b, and implementation details for constructing cancer-specific proteomes by k-mer profiling are shown in Figure 7. aa: amino acid, nt: nucleotide, th: sample-specific threshold at k-mer occurrence (see Example 1 below for k-mer filtering and generation of cancer-specific proteomes). [Figure 2A-D]Figure 2A shows the results of an experiment demonstrating that most TSAs originate from the translation of non-coding regions. Figure 2A: Flowchart illustrating the major validation steps involved in TSA discovery. Details regarding each step can be found in Figure 8. Figure 2B: Most TSA candidates originate from aberrantly expressed sequences. Bar plots showing the number of mTSA (m) and aeTSA candidates (ae) in the CT26 and EL4 tumor models. Figure 2C: Heatmap showing the expression of MCSs for aeTSA candidates in 22 tissues / organs for which RNA-Seq data are publicly available (see Table 5). Expression of MCSs in previously reported overexpressed EL4 TAAs is shown as a control. Expression values were normalized to rphm (reads per 100 million reads sequenced; see the Peripheral Expression of MCSs section in Example 1 for details) and averaged across all available RNA-Seq experiments for each tissue. Bold squares indicate tissues in which the relevant MCS was detected at >0 rphm. Adipose tissue (Adip.tissue): adipose tissue, mammary gland (mam.gland): mammary gland, and subcutaneous adipose tissue (scadip.tissue): subcutaneous adipose tissue. Figure 2D: Most ae / mTSAs originate from non-coding regions. Bar plot showing the number of TSAs derived from in-frame translation of coding exons (coding-in), out-of-frame translation of coding exons (coding-external), and translation of purportedly non-coding regions (non-coding). Numbers within the bars represent the number of aeTSAs / mTSAs. Percentages above the bars indicate the proportion of TSAs derived from atypical translation events, i.e., TSAs belonging to the coding-external and non-coding categories. Characteristics of CT26 and EL4 TSAs can be found in Tables 1a and 1b, respectively. [Figure 3A-C] 1 is a graph showing that immunization against individual TSAs confers different degrees of protection against EL4 cells.

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[0015] The terms and symbols of genetics, molecular biology, biochemistry, and nucleic acids used herein are Standard papers and texts in the field, e.g., Kornberg and B aker,DNA Replication,Second Edition(WH Freeman & Co, New York, 1992), Lehninger, Bioc. hemistry,Sixth Edition(WHFreeman&Co,Ne w York, 2012), Strachan and Read, Human Mol. ecular Genetics,fifth Edition(CRC Press, 2018), Eckstein, editor, Oligonucleotides a nd Analogs:A Practical Approach(Oxford U University Press, New York, 1991) All terms should be understood in accordance with their ordinary meaning as established in the relevant art.

[0016] The articles "a" and "an" are used herein to refer to one of the grammatical objects of the article or to Used to refer to a plurality (i.e., at least one). For example, "an element" "element" means one element or more than one element. , unless the context otherwise requires, the words "comprise", "comp "rises" and "comprising" refer to the steps stated. or element or step or group of elements, but does not include any other step It is understood that no exclusion of any element or step or group of elements is implied. It will be done.

[0017] The recitation of ranges of values herein is inclusive unless otherwise indicated herein. It is merely intended to serve as a shorthand way of referring individually to each alternative value that may be used. and each alternative value is incorporated herein as if it were individually recited herein. All subsets of values within ranges are also contemplated herein as if individually recited. It will be incorporated into the specification.

[0018] All methods described herein are intended to be illustrative unless otherwise indicated herein or by context. Thus, any suitable order may be performed unless clearly contradicted.

[0019] Any and all examples or exemplary phrases (e.g., " The use of "etc." is merely intended to better clarify the invention and is not intended to be limiting unless otherwise specified. Unless otherwise claimed, the scope of the invention is not limited.

[0020] No language in the specification shall be construed as indicative of any non-claimed element being essential to the practice of the invention. It should not be construed as indicating that it is essential.

[0021] As used herein, the term "about" has its ordinary meaning. is that a value may vary depending on the error variations inherent in the device or method used to determine the value. It is used to indicate that a value includes a range of values or is close to a range of values, e.g. For example, within 10% or 5% of the listed value (or range of values).

[0022] Considerable effort has been made to discover viable TSAs that can be used in therapeutic cancer vaccines. The most common strategy is reverse immunology. ) and i) exome sequencing is performed on tumor cells to identify mutations, ii) MHC Using binding prediction software tools, we identified which variant MAPs were good MHC binders. Identify the possibilities 11、12 Reverse immunology can enrich TSA candidates, Although available computational methods can predict MHC binding, other steps involved in MAP processing may be involved. Since it is impossible to predict the 14、15At least 90% of these candidates are false positives. Sex 5、13 To overcome this limitation, several studies have investigated the TSA findings. Mass spectrometry (MS) analysis is included in the pipeline. 16 , thereby causing some TSA leading to the rigorous molecular determination of 17、18 However, the yield of these approaches is extremely low. In melanoma, one of the most mutated tumor types, On average, two TSAs are verified by MS. 19 , whereas only a few other cancer types Only TSA is allowed 15 Infusion of TILs or immune checkpoint inhibitors TSA does not induce tumor regression if the tumor does not express the immunogenic antigen. The lack of 20 The exon mutation-based approach has two important It is believed that the TSA failed to identify the suspect because it did not take into account the factors. 1. Basically, there is currently no method for high-throughput identification of aeTSA. These approaches focus only on mTSA and neglect aeTSA. This means that mTSA is a unique antigen, whereas aeTSA is shared by multiple tumors. This makes them attractive targets for vaccine development. 7、9 Second, Focusing on the exome as the sole source of TSA is very limiting. The chromosome (i.e., all protein-coding genes) represents only 2% of the human genome. However, up to 75% of the genome can be transcribed and potentially translated. 22 .

[0023] In the work described herein, the inventors have demonstrated that they are whether derived from a code region, a simple or complex rearrangement, or simply a cancer-restrictive ERE. Develop a proteogenomics workflow that can identify non-tolerogenic TSAs without All RNA sequencing reads were mapped to identify non-tolerogenic sequences. Rather than trying to reconstruct the underlying mutations that are present, signal, i.e., mTEC hi One of the two is omitted from the cancer signal. Computer translation of the sequences obtained was used as a database in MS. Compared to the conventional method, the k-mer profiling workflow described here has several advantages: (i) It is fast. (ii) It is unbiased. This means that non- TSA derived from the chromosome region, and one TSA derived from a deletion of approximately 7,500 base pairs. capture all cancer-specific sequences, regardless of their nature, as demonstrated by the identification of (iii) It is modular. To enrich for non-tolerogenic sequences, mTEC hi This is an excellent surrogate for peripheral expression of antigens. otherwise, for example, by removing all ENCODE data or You can filter the data by adding dbSNP to the mix. A k-mer database was generated and added to the collection of normal samples to be filtered. can be obtained.

[0024] In one aspect, the present disclosure provides a method for identifying candidate tumor antigens in a tumor cell sample. , the method (a) Tumor-specific proteome databases (i) Tumor RNA sequencing (e.g., whole transcriptome sequencing of tumor cell samples) A subsequence (k-mer) containing at least 33 base pairs is selected from the RNA sequence obtained by Extracting the set; (ii) The set of tumor subsequences in (i) is compared to a set of RNA sequences extracted from normal cells. and comparing the sequence to a set of corresponding control subsequences containing at least 33 base pairs. , (iii) absent or at least Tumor subsequences that were also down-expressed by 4-fold were extracted, thereby obtaining tumor-specific subsequences. And, (iv) computer translation of the tumor-specific subsequences, thereby determining the tumor-specific obtaining a global proteome database; (b) A personalized tumor proteome database (i) comparing the tumor RNA sequence with a reference genome sequence to identify a specific region in the tumor RNA sequence; Identifying the base mutation; (ii) inserting the single nucleotide mutation identified in (i) into the reference genome sequence, thereby identifying the individual generating a differentiated genome sequence; (iii) Compiling expressed protein-encoding transcripts from the individualized genome sequence. and translating the resulting proteome data by computer, thereby obtaining a personalized proteome database. Thus, (c) a sequence of a major histocompatibility complex (MHC)-associated peptide (MAP) from the tumor; (a) Tumor-specific proteome database and (b) personalized tumor proteome comparing sequences with the genome database to identify MAPs; (d) identifying candidate tumor antigens among the MAPs identified in (c), Antigen candidates are those whose sequences and / or coding sequences are overexpressed in tumor cells compared to normal cells. It is a peptide that is expressed.

[0025] In one embodiment, the method comprises the step of: obtaining major histocompatibility complex (MHC) related proteins from a tumor cell sample; The method further includes isolating and sequencing a linked peptide (MAP).

[0026] In one embodiment, the method comprises performing whole transcriptome sequencing on a tumor cell sample. and thereby obtaining tumor RNA sequences.

[0027] As used herein, the term "candidate tumor antigen" refers to a tumor antigen that is associated with a major histocompatibility molecule (MHC) and bind to the surface of tumor cells only, or to the surface of tumor cells, and Significantly higher levels / frequency (at least 2-fold, preferably at least 4-fold, 5-fold) compared to the Such tumor antigen candidates refer to peptides that are present in a greater number of tumors than those present in the rest of the body (e.g., 10-fold or 10-fold higher). The antigen can be targeted to induce a T cell response against tumor cells expressing the antigen.

[0028] Methods for isolating MHC-associated peptides (MAPs) from cell samples are known in the art. The most commonly used technique is that described by Fortier et al. (J. Exp. Med. MHC from living cells as described by Another technique is mild acid elution (MAE) of related peptides. immunoprecipitation or affinity purification of the peptide followed by peptide elution (e.g., Geb reselassie et al.Hum Immunol.2006 Novemb er;67(11):894-906). Two hybrids based on the latter approach High-throughput strategies have been used. First, expression vectors encoding soluble and secreted MHC are Transfection of cell lines with vectors (lacking a functional transmembrane domain) and differentiation Based on the elution of peptides associated with secreted MHC (Barnea et al., Eur J Immunol.2002 Jan,32(1):213-22, and Hickm an HD et al.,J Immunol.2004 Mar 1;172(5) The second approach involves chemical or metabolic labeling and the detection of MHC-related It provides a quantitative profile of related peptides (Weinzierl AO et al. Mol Cell Proteomics.2007 Jan;6(1):102-13 .Epub 2006 Oct 29;Lemmel Cetal.,Nat Biot echnol.2004 Apr;22(4):450-4.Epub 2004 Ma r 7;Milne E,Mol Cell Proteomics.2006 Feb ;5(2):357-65.Epub 2005 Nov 4).

[0029] The eluted MAPs were analyzed by size exclusion chromatography or ultrafiltration before further analysis. Filtering (using a filter with a cutoff of about 5000 Da, e.g., about 3000 Da) , reversed-phase chromatography (hydrophobic chromatography), and / or ion-exchange chromatography any purification / enrichment method, including chromatography (e.g., cation exchange chromatography) The sequences of the eluted MAPs can be analyzed by mass spectrometry (Tan- Page 10 10 spectrometry (Tan- described below) peptide / protein analysis, including mass spectrometry (MS / MS) and Edman degradation reactions The sequence may be determined using any method known in the art for sequencing.

[0030] Whole transcriptome sequencing ("total RNA sequencing", "RNA sequencing", also RNA-seq (also called RNA-seq) is a method to analyze all the DNA present in a sample (tumor sample, normal cell sample). This refers to the sequencing of RNA, including coding RNA, as well as miRNA, snRNA, and It includes multiple types of non-coding RNAs such as tRNA. Whole transcriptome sequencing Methods for performing such determinations, for example, next generation sequencing (NGS), are well known in the art. These are commercially available (e.g., Illumina (NextSeq™), HiS eq(trademark)), Thermofisher(Ion Total(trademark) RNA-Se q kit), Clontech (SMARTer™), or as mentioned in the literature Several NGS platforms are available that can be used with the methods described herein. For example, Zhang et al. 2011: The impact of next -generation sequencing on genomics.J.Gen et Genomics 38(3),95-109, or Voelkerding et al.2009:Next generation sequencing:Fr om basic research to diagnostics.Clinica This is described in detail in I Chemistry 55,641-658.

[0031] Preferably, an RNA preparation serves as the starting material for NGS. From samples such as biological material, for example, fresh, flash-frozen or formalin-fixed paraffin from gel-embedded tumor tissue, from freshly isolated cells, or from the patient's peripheral blood. These can be easily obtained from circulating tumor cells (CTCs) present in normal or control The RNA can be extracted from normal somatic tissue or germ cells. These RNA sequences are obtained from different types of normal cells, e.g., normal cells from different tissues. RNA sequences from normal cells can also be collected from thymocytes, preferably from human thymocytes. MHC II high Medullary thymic epithelial cells (mTECs) hi ) and other medullary thymic epithelial cells (mTEC) hi Cells have unique promiscuous gene expression profiles They advantageously have a nucleotide sequence that expresses approximately 70-90% of the protein coding sequences in somatic cells, These MAPs are capable of inducing central immune tolerance.

[0032] The method described herein involves an alignment technique called k-mer profiling. Tumor-specific proteome databases using a free RNA-seq analysis workflow This includes generating structural variants (large insertions or deletions (InDels) or any type of mutation, including a mutation or fusion), and sequences derived from translation of non-coding regions. Tumor and normal RNA sequences (RNA-seq reads) were k-mers, i.e., k ≥ 3. The MHC class is "cut" or "split" into subsequences of length k, each having 3 nucleotides. Peptides that bind to the MAP molecule are generally 11 amino acids long (hence The RNA sequence is small because it does not exceed 33 nucleotides in length (encoded by a sequence of 33 nucleotides). Dividing the sequence into subsequences of at least 33 nucleotides eliminates the risk of missing potential MAPs. Those skilled in the art will minimize the size of the tumor-specific proteome database. To synthesize the RNA sequence, we split it into segments of 33 nucleotides (i.e., k = 33 nucleotides). It has been shown that dividing the nucleotide sequence into subunits is preferable for identifying MHC class I-restricted tumor antigens. Those skilled in the art will also appreciate that the most recent methods for identifying MHC class II restricted tumor antigens are well known. The small k-mer length is set to 33 to 54 nucleotides (k≧54 nucleotides), and the MHC II related It is understood that the length of the peptide should generally be increased to the range of 13-18 amino acids. The tumor subsequences would then be compared with the corresponding control subsequences (RNPs of normal cells). A sequence) in the corresponding control subsequence. or at least 4-fold (preferably at least 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, or In one embodiment, tumor subsequences that are down-expressed (10-fold or 10-fold) are extracted. To minimize the redundancy inherent in the genome, the method separates overlapping tumor-specific subsequences into This further involves assembling the sequences into longer tumor subsequences (typically called contigs). The tumor-specific subsequences or contigs are then computer translated to (e.g., depending on whether the subsequence or contig is derived from the coding or non-coding strand) (translated in three or six frames) to obtain tumor-specific proteome databases. In one embodiment, the peptide is less than 8 amino acids (the minimum length of an MHC class I peptide) or 1 Protein fragments of 3 amino acids (the minimum length of an MHC class II peptide) The tumor-specific proteome database is then removed.

[0033] In one embodiment, the method comprises extracting k=24 nucleic acids from RNA sequences (normal and tumor cells). nucleotide (for MHC class I peptides) or k=39 (for MHC class II peptides) A k-mer database with 24 kb of cancer / tumor and normal regions was generated. (or 39) nucleotide long k-mer database. These databases are used for comparison with MAP coding sequences (MCS), as described below. to determine whether MCSs are overexpressed or overrepresented in tumor cells. .

[0034] The method also includes generating a personalized tumor proteome database. Compare RNA sequences (tumor RNA-seq reads) with the reference genome sequence to identify tumor RNA sequences These mutations are then inserted into the reference genome to Obtaining the tumor genome and then performing standard translation of all expressed protein-coding transcript sequences. A corresponding personalized tumor proteome database containing product sequences can be obtained. WT MAP and mutant TSA (neo) encoded by the canonical frame of the exome The generation of personalized tumor proteome databases that allow for the identification of tumor antigens is also Over-basing the database on tumor-specific sequences would result in some false-positive identifications. This improves the reliability of the database used for MS analysis.

[0035] In one embodiment, the method also includes generating a personalized normal proteome database. To achieve this, RNA sequences from normal cells (normal RNA-seq reads) are compared with the reference genome sequence. These mutations are then compared with the reference genome to identify single base mutations in the normal RNA sequence. The genome is then inserted into a personalized normal genome, from which all expressed protein-coding sequences are obtained. The corresponding individualized normal proteome database containing the standard translation product sequences of the transcript sequences was Using this individualized normal proteome database, it is possible to obtain normal (non- MAPs expressed in tumor (cell) cells that are not suitable TSA candidates can be filtered out.

[0036] As used herein, the term "reference genome" refers to the human genome as reported in the literature. Refers to assemblies, e.g., Genome Reference Consortium Human Build 38 (GRCh38, RefSeq: Accession number GCF_00 0001405.37), Hs_Celera_WGSA(Celera Genomi cs, Istrail S.et al.Proc, Natl Acad Sci US A.2004;101(7):1916-21).Epub 2004 Feb 9), HuRef and HuRefPrime (J. Craig Venter Institute) ute, Levy S, et al.PLoS Biology.2007;5:211 3-2144), YH1 and BGIAF (Beijing Genomics Institute titute;Li R,et al.Genome Research.2010;2 0:265-272), HsapALLPATHS1 (Broad Institute ) and others. The list of reference human genome assemblies is available at the National Institute of Biotechnology Information (NIBI). In one embodiment, the DNA may be found in the National Center for Biological Information (NCBI) "Assembly" database. The reference genome is GRCh38.

[0037] The sequences of the MAPs obtained in step (a) of the method are then subjected to a sequence analysis that allows the identification of the MAPs. Sequences from the tumor-specific proteome database and personalized tumor proteome database Compare (e.g., BLAST).

[0038] Candidate tumor antigens can be identified in the MAPs described above. Such candidate tumor antigens include those of the sequence and / or the coding sequence is a peptide that is overexpressed in tumor cells compared to normal cells. handle.

[0039] In one embodiment, the method comprises determining whether the sequence is detected in a normal personalized proteome database. Further includes eliminating or abandoning the MAP.

[0040] In one embodiment, the method further comprises: In another embodiment, the method includes collecting 24 MCSs (M 39 (for MHC class I peptides) or 39 (for MHC class II peptides) nucleic acids In another embodiment, the MCS-derived k-mers are converted to a k-mer set of nucleic acids. These k-mer sets are then compared to the cancer / tumor and normal 24- (or 39-) nucleotide sequences. The sequences are compared with the k-mer database.

[0041] In one embodiment, the method comprises: (a) Isolating major histocompatibility complex (MHC)-associated peptides (MAPs) in tumor cell samples isolating and sequencing; (b) performing whole transcriptome sequencing on the tumor cell sample, thereby identifying the tumor obtaining tumor RNA sequences; (c) Tumor-specific proteome databases (i) a subsequence (km) containing at least 33 nucleotides from the tumor RNA sequence; er) and (ii) The set of tumor subsequences in (i) is compared to a set of RNA sequences extracted from normal cells. and comparing the sequence to a set of corresponding control subsequences containing at least 33 nucleotides. And, (iii) absent or at least Tumor subsequences that were also down-expressed by 4-fold were extracted, thereby obtaining tumor-specific subsequences. And, (iv) computer translation of the tumor-specific subsequences, thereby determining the tumor-specific obtaining a global proteome database; (d) a personalized tumor proteome database; (i) comparing the tumor RNA sequence with a reference genome sequence to identify a specific region in the tumor RNA sequence; Identifying the base mutation; (ii) inserting the single nucleotide mutation identified in (i) into the reference genome sequence, thereby identifying the individual generating a differentiated tumor genome sequence; (iii) coding expressed protein-coding transcripts from the personalized tumor genome sequence; and computer-translate the data to obtain a personalized tumor proteome database. and generating by (e) The individualized normal proteome database is (i) comparing an RNA sequence from a normal cell with a reference genome sequence to determine the normal RNA sequence; Identifying a single nucleotide mutation in (ii) inserting the single nucleotide mutation identified in (i) into the reference genome sequence, thereby identifying the individual generating a differentiated normal genome sequence; (iii) coding for expressed protein-coding transcripts from the individualized normal genome sequence; The resulting normal proteome is then translated by computer, thereby obtaining a personalized normal proteome database. and generating by (f)(i) determining at least one of the RNA sequences from the normal cell and the tumor RNA sequence; By extracting a set of subsequences containing 24 nucleotides, normal and tumor k- generating a mer database; (g) The MAP sequences obtained in (a) were compared with the tumor-specific proteome database in (c). (d) Comparison of the sequences and the personalized tumor proteome database to identify MAPs To do, (h) identifying candidate tumor antigens among the MAPs identified in (f), Antigen candidates are those whose (1) sequences are not present in the personalized normal proteome database, and (2) (i) the sequence is present in a personalized tumor proteome database, and / or (i) the code The sequence is compared to the normal k-mer database and the tumor k-mer database. These correspond to MAPs that are overexpressed or overrepresented in the

[0042] In one embodiment, the coding sequence is a set of MAP-derived k-mers (e.g., 24 nt k-mer) and MAP-derived k in the tumor and normal k-mer databases. As used herein, overexpression or overexpression of a -mer is determined. Over-represented means that a sequence is over-represented in the tumor k-mer database compared to the normal k-mer database. at least 2-fold, preferably at least 3, 4, or 5-fold, more preferably at least 2-fold, more preferably at least 3, 4, or 5 ... Preferably, it is present at a level that is at least 10 times higher. The code sequence or MAP-derived k-mer is not present in the normal k-mer database.

[0043] In one embodiment, with reference to FIG. 7A, identification and validation of TSA candidates is accomplished as follows: Each MAP and its associated MAP coding sequence(s) (MCS) are Cancer and normal personalized proteomes, or cancer and normal 24-nucleotide k-mers MAPs detected in the normal personalized proteome were excluded. MAPs present only in differentiated proteome and / or cancer k-mer databases are Identified / selected as SA candidates. For MAPs present in the mer database, they are compared to normal cells. overexpressed (e.g., at least 2-fold, preferably at least 5-fold) in cancer cells compared to 10-fold, more preferably at least 10-fold. If the CSs are coded by the MCSs, then their respective MCSs are consistent. If it is consistently flagged as a TSA candidate, In one embodiment, they are difficult to distinguish by MS. Therefore, TSA candidates with I / L variants are excluded as TSA candidates.

[0044] In one embodiment, the eluted MAPs are filtered to 8-11 MAPs prior to comparison. In another embodiment, the eluted MAP is selected for amino acid-long peptides prior to comparison. Filter to find NetMHC software version 4.0 (http: / / w www.cbs.dtu.dk / services / NetMHC-4.0)(Andre atta M,Nielsen M,Bioinformatics(2016)Feb 15;32(4):511-7;Nielsen M,et al.,Protein Sci., (2003) 12:1007-17) Select children with at least one percentile rank <2%.

[0045] In one embodiment, the method further comprises substituting the coding sequence of the candidate tumor antigen with a sequence derived from normal tissue. In embodiments, at least 5, 10, 15, 20, or 25 Sequences from different tissues are used. Sequences from normal tissues are las(Petryszak et al., Nucleic Acids Resea rch,Volume 44,Issue D1,4 January 2016,Pa ges D746-D752), scRNASeqDB (Cao Y, et al. (2 017).Genes8(12),368), RNA-Seq Atlas(Krupp et al.,Bioinformatics,Volume 28,Issue 8 ,15 April 2012,Pages 1184-1185), and Encod RNA sequencing can be obtained from public databases such as [e.g., ], or by performing RNA-seq on normal tissues. In one embodiment, the method comprises: (1) evaluating the coding sequence; If it is not expressed in any of the normal tissues examined, or if it is expressed in MHC class I-negative tissues, (2) if the coding sequence is expressed only in the MHC class in which it was evaluated; Less than 50%, preferably less than 45%, 40%, 35%, or 30% of the tissue is I-positive. If expressed, further comprising selecting the tumor antigen candidate. Candidates should be selected from fewer than 7, preferably 6, 5, 4, or 60 normal tissues whose coding sequences are to be evaluated. is selected if it is expressed in less than three copies.

[0046] In one embodiment, the method comprises determining the genomic location of a coding sequence of a candidate TSA; (1) the coding sequence matches the corresponding genomic location, and (2) the coding sequence is superimposed. No matching of variable regions (e.g., TCR genes H2, Ig) or multiple genes, and (3) selecting a TSA candidate if it does not overlap with a synonymous mutation. Such determinations are made by the UCSC Genome Browser (Kent WJ Genome e Res.2002 Apr;12(4):656-64) and / or Integ Intrative genomics viewer (IGV) tool (Robinson et al.Nat Biotechnol.2011 Jan;29(1):24-6 This can be done using the BLAT tool from

[0047] In one embodiment, the method comprises determining the MHC class I activity of identified tumor antigen candidates (TSA candidates). The binding further includes determining or predicting binding to a molecule. The predicted binding affinity (IC 50 ) and using tools such as NetMHC An overview of the various available MHC class I peptide binding tools can be found in Pe ters B et al.,PLoS Comput Biol 2006,2(6) :e65, Trost et al. Immunome Res 2007,3(1): 5, Lin et al., BMC Immunology 2008,9:8) The binding of identified TSA candidates to MHC class I molecules can be determined by other known methods, e.g. The T2 cell line lacks TAP and can be determined using a T2 peptide binding assay. Although they do express low amounts of MHC class I on the cell surface, T2 binding assay The study was based on the ability of the peptide to stabilize MHC class I complexes on the surface of the T2 cell line. T2 cells are incubated with a specific peptide (e.g., a TSA candidate) to induce pan-HL Use a class I antibody to detect stabilized MHC class I complexes and perform the analysis (e.g., flow -cytometry) and assess binding relative to a non-binding negative control. The presence of stabilized peptide / MHC class I complexes on the surface of the peptide (e.g., candidate T SA) binds to MHC class I molecules.

[0048] Binding of a peptide of interest (e.g., a TSA candidate) to MHC can also be monitored by radiolabeling the probe. The peptide can be evaluated based on its ability to inhibit binding to MHC molecules. are dissolved in detergent and purified by affinity chromatography. , in the presence of a cocktail of protease inhibitors, and the peptide of interest (e.g., TSA candidate) and an excess of radiolabeled probe peptide for 2 days at room temperature. At the end of the incubation period, the MHC-peptide complexes were analyzed by size exclusion gel filtration chromatography. The radiolabeled peptide was separated from the unbound radiolabeled peptide by chromatography and the percent bound radioactivity was determined. The binding affinity of a particular peptide at an MHC molecule is determined by varying doses of unlabeled competitor peptide. The peptides were determined by co-incubating them with MHC molecules and labeled probe peptides. The concentration of unlabeled peptide required to inhibit 50% of the binding of the labeled peptide can be determined. degree(IC 50 ) can be determined by plotting dose versus % inhibition (e.g. For example, Current Protocols in Immunology (1998) See 18.3.1~18.3.19, John Wiley & Sons, Inc. ).

[0049] Binding of identified TSA candidates to MHC class I molecules also correlates with ProImmune R EVEAL® & ProVE® T Cell Epitope Discovery System or can be determined using T cell epitope discovery systems / tools such as the NetMHC tool. (e.g., Desai and Kulkarni-Kale, Methods Mo l Biol.2014;1184:333-64).

[0050] In one embodiment, the method includes the step of: isolating a population of cells, e.g., a cell sample (e.g., PBM) from a subject; C) further comprising assessing the number or frequency of T cells that recognize the tumor antigen candidate in The number or frequency of T cells that recognize a given antigen can be determined using a variety of methods known in the art. For example, a cell population can be treated with multimeric MH containing the tumor antigen candidate in its peptide-binding groove. Contact with MHC class I molecules (e.g., MHC tetramers) and label with multimeric MHC class I molecules The number of cells that are stimulated by the multimeric MHC class I molecule can be assessed by determining the number of cells that are stimulated by the multimeric MHC class I molecule. They can be detectably labeled with a fluorophore (direct labeling) or with a labeled ligand (internal labeling). Alternatively, the TSA candidate may be tagged with a moiety that is recognized by a TSA candidate (direct or secondary tag). The number or frequency of T cells that recognize a TSA depends on the presence of a TSA candidate under conditions favorable for T cell activation. The number / frequency of activated T cells can be assessed by determining the number / frequency of activated T cells in the The number / frequency of cells is determined by the expression of cytokines induced by T cell activation, e.g., IFN-γ or The level of IL-1 secretion can be assessed by detecting cells secreting IL-2 or IL-2 (e.g., ELISA). ot or by flow cytometry).

[0051] In one embodiment, the method involves assessing the ability of a candidate tumor antigen to induce T cell activation, e.g., by: The T cell population is then subjected to immunoprecipitation using cells (e.g., dendritic cells) bearing candidate tumor antigens that bind to MHC class I molecules. contact with APCs (cells such as APCs) on their cell surface, leading to proliferation and cytokine / chemokine production. T cell activation, such as proliferation (e.g., IFN-γ or IL-2 production), cytotoxic killing, It further includes evaluating by measuring at least one parameter.

[0052] In one embodiment, the method comprises determining the ability of a candidate tumor antigen to T cell-mediated tumor cell killing and and / or inhibit tumor growth. This can be achieved in vitro using a suitable animal model, or in vivo using a suitable animal model.

[0053] In one embodiment, the candidate tumor antigens are comprised of about 7-20 amino acids, more particularly about 8-10 amino acids. A length of 8 amino acids, preferably 8 to 11 amino acids (for MHC class I tumor antigens) or 13-18 amino acids (for MHC class II tumor antigens) in length. do.

[0054] The methods described herein provide for the generation of whole transcriptome sequences for tumor / cancer cell samples of interest. Useful for identifying candidate tumor antigens for any type of cancer by performing sequencing. Examples of such cancers include, but are not limited to, carcinoma, lymphoma, blastoma, and sarcoma. , and leukemia, more particularly bone cancer, blood / lymphatic system cancers, e.g., leukemia (AML, CML, ALL), myeloma, lymphoma, lung cancer, liver cancer, pancreatic cancer, skin cancer, head and neck cancer, skin or intraocular melanoma, uterine cancer, ovarian cancer, rectal cancer, anal region cancer, stomach cancer, colon cancer, breast cancer, prostate cancer Cancer, uterine cancer, genital and reproductive organ cancer, esophageal cancer, small intestine cancer, endocrine system cancer, thyroid cancer, parathyroid cancer , adrenal cancer, soft tissue sarcoma, bladder cancer, kidney cancer, renal pelvis cancer, central nervous system (CNS) cancer, neuroectoderm These include cancer, spinal axis tumors, gliomas, meningiomas, and pituitary adenomas. In some embodiments, the tumor cell sample used in step (a) of the methods described herein may be prepared as described above. The sample contains cells of any of the above cancers.

[0055] In another aspect, the present disclosure provides a method for the treatment of tumor antigen peptides (or tumor-specific peptides), i.e., Tables 1a, 1b, 2a-2d, or 3a- 3c (SEQ ID NOs: 1 to 39), preferably Tables 2a to 2d or 3a to 3c (SEQ ID NOs: 1 7 to 39), or the sequences of SEQ ID NOs: 1 to 39. and variants thereof having one or more mutations.

[0056] Generally, peptides such as tumor antigen peptides presented in the context of HLA class I are expressed in approximately 7 Alternatively, the length may vary from 8 to about 15, or preferably from 8 to 14, amino acid residues. In some embodiments of the methods described herein, the method further comprises administering to the subject a tumor antigen comprising a tumor antigen peptide sequence as defined herein. Longer peptides can be artificially added to cells such as antigen-presenting cells (APCs) and then bound to the cells. The tumor antigen peptides are then processed and presented on the surface of APCs by MHC class I molecules. In this method, peptides / polypeptides longer than 15 amino acid residues (i.e. , tumor antigen precursor peptides) can be added to APCs, and proteins in the APC cytosol can be and the corresponding tumor antigen peptides as defined herein for presentation. In some embodiments, the tumor antigen peptides defined herein are produced. The precursor peptide / polypeptide used for this purpose may be, for example, 1000, 500, 4 00, 300, 200, 150, 100, 75, 50, 45, 40, 35, 30, 25, 20, or 15, or fewer amino acids. All methods and processes using the tumor antigen peptides described above are directed to the antigen-binding protein (APC)-mediated To induce the presentation of the final 8-14 tumor antigen peptides after treatment, longer peptides were used. peptides or polypeptides (including native proteins), i.e., tumor antigen precursor peptides In some embodiments, the use of a peptide / polypeptide is in accordance with the present invention. The tumor antigen peptides are about 8-14, 8-13, or 8-12 amino acids in length (e.g., 8 , 9, 10, 11, 12, or 13 amino acids in length) and are expressed in HLA class I molecules. In one embodiment, the tumor antigen peptide is 20 or fewer amino acids, preferably 15 or fewer amino acids, more preferably 14 or fewer amino acids In one embodiment, the tumor antigen peptide comprises at least 7 amino acids, preferably Preferably it contains at least 8 amino acids, more preferably at least 9 amino acids.

[0057] As used herein, the term "amino acid" refers to the L-isomers and amino acids of naturally occurring amino acids. Peptide chemistry to prepare both D- and C-isomers, as well as synthetic analogs of tumor antigen peptides Other amino acids (e.g., naturally occurring amino acids, non-naturally occurring amino acids, nucleic acid sequences) used in Examples of naturally occurring amino acids include glycine, glycerin, guanine, thiamin ... Other amino acids include leucine, alanine, valine, leucine, isoleucine, serine, and threonine. Amino acids include, for example, non-genetically encoded forms of amino acids, as well as conservative forms of L-amino acids. Naturally occurring, non-genetically encoded amino acids include, for example, beta-alanine. , 3-amino-propionic acid, 2,3-diaminopropionic acid, alpha-aminoisobutyric acid Citric acid (Aib), 4-amino-butyric acid, N-methylglycine (sarcosine), hydrochloride Hydroxyproline, ornithine (e.g., L-ornithine), citrulline, t-butylalanine glycine, t-butylglycine, N-methylisoleucine, phenylglycine, cyclohexyl Alanine, norleucine (Nle), norvaline, 2-napthylalanine (2-napt hylalanine), pyridylalanine, 3-benzothienylalanine, 4-chloro Phenylalanine, 2-fluorophenylalanine, 3-fluorophenylalanine, 4 -Fluorophenylalanine, penicillamine, 1,2,3,4-tetrahydroisoquinone thienylalanine, methionine sulfoxide, L-homoglycine Nin (Hoarg), N-acetyl lysine, 2-aminobutyric acid, 2-aminobutyric acid, 2,4, -diaminobutyric acid (D- or L-), p-aminophenylalanine, N-methylvaline, Homocysteine, homoserine (HoSer), cysteic acid, epsilon-aminohexyl These include amino acids such as benzoic acid, delta-aminovaleric acid, or 2,3-diaminobutyric acid (D- or L-). These amino acids are well known in the field of biochemistry / peptide chemistry. , the tumor antigen peptide contains only naturally occurring amino acids.

[0058] In embodiments, the tumor antigen peptides described herein are Variants having altered sequences containing substitutions of functionally equivalent amino acid residues compared to peptides, e.g., where one or more amino acid residues in a sequence act as functional equivalents replaced by another amino acid of similar polarity (having similar physicochemical properties) Substitution of an amino acid within a sequence results in a silent change to the class to which the amino acid belongs. For example, positively charged (basic) amino acids include arginine, These include lysine, and histidine (as well as homoarginine and ornithine). Polar (hydrophobic) amino acids include leucine, isoleucine, alanine, phenylalanine, These include valine, proline, tryptophan, and methionine. Contains serine, threonine, cysteine, tyrosine, asparagine, and glutamine The negatively charged (acidic) amino acids include glutamic acid and aspartic acid. The acid glycine is a member of the nonpolar amino acid family or the uncharged (neutral) polar amino acid family. Substitutions made within a family of amino acids are generally conservative. It is understood that the tumor antigen peptides referred to herein are all L-amino The acids may include all D-amino acids or a mixture of L- and D-amino acids. In embodiments, the tumor antigen peptides referred to herein comprise all L-amino acids.

[0059] In one embodiment, a tumor antigen peptide comprising one of the sequences set forth in SEQ ID NOs: 1 to 39. In the sequence of the code, amino acid residues that do not substantially contribute to the interaction with the T cell receptor are The incorporation of α-glucan does not substantially affect T cell reactivity and does not abrogate binding to relevant MHC molecules. In one embodiment, the tumor antigen peptide may be modified by substituting it with another amino acid. The variants are sequence-optimized to improve MHC binding, i.e., to the MHC molecule. one or more mutations (e.g., 1, 2, or 3 mutations) that enhance binding of The binding affinity of the tumor antigen peptide variants can be determined by, for example, NetMHC MHC such as 4.0, NetMHCpan4.0, and MHCflurry1.2.0 Sequence-optimized tumor antigen peptide variants can be evaluated using binding prediction tools. For example, predicted binding affinity for a particular HLA is similar to that of a native tumor antigen peptide. etc., or preferably strong cases can be considered. Then, the selected sequence is optimized. Target peptides can be synthesized using methods known in the art, for example, by Prolmmun The REVEAL assay was used to screen for in vitro binding to specific HLA. Can be cleaned.

[0060] The tumor antigen peptides may also be capped or modified at the N-terminus and / or C-terminus. , may prevent degradation, increase stability, affinity, and / or uptake, and thus , the present disclosure provides compounds of formula Z 1 -XZ 2 The present invention provides a variant of a tumor antigen peptide having the formula: X is a tumor antigen peptide sequence shown in SEQ ID NO: 1 to 39, preferably 17 to 39. In one embodiment, the amino terminal residue (i.e., the N-terminal free amino acid) of the tumor antigen peptide is The moiety / chemical group (Z 1 ) by covalent attachment (e.g., (For protection against 1 is a straight or branched alkyl group of 1 to 8 carbon atoms, or It can be a silyl group (R—CO—), where R is a hydrophobic moiety (e.g., acetyl, propionyl, aryl, butanyl, isopropionyl, or isobutanyl), or an aroyl group (Ar In one embodiment, the acyl group can be C 1-C 16 or C3-C 16 an acyl group (linear or branched, saturated or unsaturated), In a further embodiment, a saturated C1-C6 acyl group (linear or branched) or an unsaturated C3- C6 acyl group (linear or branched), e.g., acetyl group (CH3-CO-, Ac) In one embodiment, Z 1 The carboxy-terminal residue of the tumor antigen peptide (i.e., i.e., the free carboxy group at the C-terminus of the tumor antigen peptide) can be, for example, 2 ), for example by amidation (replacement of an OH group by an NH2 group). In such cases, Z2 is an NH group. In one embodiment, Z 2 is hydro oxamate group, nitrile group, amide (primary, secondary, or tertiary) group, methylamine, isopropyl 1 to 10 amines such as -butylamine, iso-valerylamine, or cyclohexylamine Carbon aliphatic amines, aniline, naphthylamine, benzylamine, cinnamylamine, or aromatic or arylalkylamines such as phenylethylamine, alcohols or CHOH. In one embodiment, Z 2 does not exist. The tumor antigen peptide is selected from the sequences disclosed in SEQ ID NOs: 1 to 39, preferably 17 to 39. In one embodiment, the tumor antigen peptide is selected from the group consisting of SEQ ID NOs: 1 to 39, preferably 17. 39, i.e., Z 1 and Z 2 does not exist .

[0061] In one embodiment, the present disclosure provides a method for identifying HLA-A2 alleles, preferably HLA-A*02: The present invention provides tumor antigen peptides that bind to HLA molecules of the 01 allele, and the peptides are represented by SEQ ID NOs: 17 to 19. 27, and 28, or consists of it.

[0062] In one embodiment, the present disclosure provides a method for detecting HLA-B40 alleles, preferably HLA-B*40 A tumor antigen peptide that binds to the HLA molecule of the 1:01 allele is provided, and is shown in SEQ ID NO: 20. The amino acid sequence comprises or consists of the amino acid sequence

[0063] In one embodiment, the present disclosure provides a method for identifying a human with an HLA-A11 allele, preferably HLA-A*11: The present invention provides tumor antigen peptides that bind to HLA molecules of the 01 allele, and the peptides are represented by SEQ ID NOs: 21 to 23. and 29 to 35, or It consists of:

[0064] In one embodiment, the present disclosure provides a method for detecting the HLA-B08 allele, preferably HLA-B*08 A tumor antigen peptide that binds to an HLA molecule of the :01 allele is provided, and is comprises or consists of the amino acid sequence shown in 25.

[0065] In one embodiment, the present disclosure provides a method for detecting the HLA-B07 allele, preferably HLA-B*07 A tumor antigen peptide that binds to an HLA molecule of the :02 allele is provided, and is comprises or consists of the amino acid sequence shown in FIG.

[0066] In one embodiment, the present disclosure provides a method for detecting the HLA-A24 allele, preferably HLA-A*24 A tumor antigen peptide that binds to an HLA molecule of the :02 allele is provided, and is comprises or consists of the amino acid sequence shown in FIG.

[0067] In one embodiment, the present disclosure provides a method for detecting the HLA-C07 allele, preferably HLA-C*07 A tumor antigen peptide that binds to the HLA molecule of the :01 allele is provided, and is shown in SEQ ID NO: 37. The amino acid sequence comprises or consists of the amino acid sequence

[0068] In one embodiment, the tumor antigen peptide is a leukemia tumor antigen peptide and is SEQ ID NO: 17 28 to 30. do.

[0069] In one embodiment, the tumor antigen peptide is a lung tumor antigen peptide, and is SEQ ID NO: 29-3 9. The amino acid sequence of the present invention may comprise or consist of one of the amino acid sequences shown in any one of Tables 1 to 9.

[0070] In one embodiment, the tumor antigen peptide is identified by a sequence located in a non-coding region of the genome. In one embodiment, the tumor antigen peptide is encoded by an untranslated transcribed region (UTR), i.e., i.e., encoded by sequences located in the 3'-UTR or 5'-UTR regions. In an embodiment, the tumor antigen peptide is encoded by a sequence located in an intron. In this embodiment, the tumor antigen peptide is encoded by a sequence located in an intergenic region. In one embodiment, the tumor antigen peptide is located in an endogenous retroelement (ERE). In another embodiment, the tumor antigen peptide is encoded by a sequence located in an exon. It is encoded by a sequence that confers a nucleotide sequence to the nucleotide sequence and results from a frameshift.

[0071] The tumor antigen peptides of the present disclosure are expressed in host cells containing nucleic acids encoding the tumor antigen peptides. by expression in vitro (recombinant expression) or by chemical synthesis (e.g., solid phase peptide synthesis). Peptides can be produced by manual and / or automated methods well known in the art. It can be readily synthesized by a chemical solid phase procedure. " or "Fmoc" procedures. Techniques for solid phase synthesis The procedure is described, for example, in IRL, Oxford University Press, 1 Solid Phase Peptide Syntheses published by 989 s:A Practical Approach, by E.Atherton and Alternatively, tumor antigen peptides may be segmented. They can be prepared by the method of tetrahydrofuran condensation, for example, by Liu et al., Tetrahydrofuran on Lett.37:933-936,1996, Baca et al.J.Am. Chem.Soc.117:1881-1887,1995, Tam et al.,I nt.J.Peptide Protein Res.45:209-216,1995 , Schnolzer and Kent, Science 256:221-225, 1992, Liu and Tam, J.Am.Chem.Soc.116:4149- 4153, 1994, Liu and Tam, Proc. Natl. Acad. Sci. .USA91:6584-6588,1994, and Yamashiro and L i,Int.J.Peptide Protein Res.31322-334,19 88). Another method useful for synthesizing tumor antigen peptides is the Na kagawa et al.J.Am.Chem.Soc.107:7087-7092 In one embodiment, the tumor antigen peptide is chemically synthesized. (synthetic peptides). Another embodiment of the present disclosure relates to non-naturally occurring peptides. The peptide consists of or consists essentially of an amino acid sequence as defined herein. , synthetically produced (e.g., synthesized) as a pharmaceutically acceptable salt. The salts of the tumor antigen peptides according to the disclosure are not salts, since the peptides produced in vivo are not salts. The non-natural nature of the peptides is substantially different from their state(s) in vivo. Salt forms are particularly useful in pharmaceutical compositions containing peptides, such as the peptide vaccines disclosed herein. In the context of cutin, the salts may modulate the solubility of the peptide. It is a pharmaceutically acceptable salt.

[0072] In one embodiment, the tumor antigen peptides referred to herein are substantially pure. A compound is "substantially pure" when it is separated from the components that naturally accompany it. Typically, the compound is at least 60% by weight of the total material in the sample, more commonly is 75%, 80%, or 85%, preferably greater than 90%, more preferably greater than 95% Thus, for example, a substance is substantially pure if it is chemically synthesized or recombinantly produced. Polypeptides produced by the method of the present invention will generally be free from their naturally associated components, e.g., their source macromolecules. The nucleic acid molecule will be substantially free of large molecule components. directly contiguous (i.e., covalently linked) with the coding sequences that are normally contiguous in the genome of A substantially pure compound is one that is free from any known or potential side effects, e.g., due to extraction from a natural source. Thus, peptide compounds can be synthesized by expression of recombinant nucleic acid molecules encoding them or by chemical synthesis. The purity can be confirmed by column chromatography, gel electrophoresis, and HPLC. In one embodiment, the tumor antigen can be measured using any suitable method, such as C. The peptide is in solution. In another embodiment, the tumor antigen peptide is in a solid form, e.g., For example, freeze-dried.

[0073] In another aspect, the present disclosure provides a method for the production of a tumor antigen peptide or tumor antigen precursor referred to herein. Further provided is an isolated nucleic acid encoding the endothelial-peptide. The acid may be from about 21 to about 45 nucleotides, from about 24 to about 45 nucleotides, e.g., Contains 24, 27, 30, 33, 36, 39, 42, or 45 nucleotides. As used herein, "isolated" means free from other components or constituents present in the molecule's natural environment. is separated from macromolecules of natural origin (e.g., other nucleic acids, proteins, lipids, sugars, etc.) As used herein, "synthetic" refers to a peptide or nucleic acid molecule that has been synthesized. not isolated from a natural source, e.g., produced through recombinant technology or using chemical synthesis The nucleic acids of the present disclosure refer to peptides or nucleic acid molecules that are synthesized from the tumor antigen peptides of the present disclosure. cloning vectors that can be used for recombinant expression and transfected into host cells In one embodiment, the gene may be contained in a vector or plasmid, such as a target or expression vector. The present disclosure also provides cloned or cloned vectors containing nucleic acid sequences encoding the tumor antigen peptides of the present disclosure. The present invention provides an expression vector or plasmid. Alternatively, the tumor antigen peptide of the present disclosure can be expressed by The loading nucleic acid may be integrated into the genome of the host cell. In either case, the host cell The tumor antigen peptide or protein encoded by the nucleic acid is expressed. The term "host cell" as used herein refers not only to the particular subject cell but also to the progeny of such a cell. or potential progeny. The host cell expresses the tumor antigen peptides described herein. Any prokaryotic cell (e.g., E. coli) or eukaryotic cell (e.g., insect The vector or plasmid can be: It contains elements necessary for the transcription and translation of the inserted coding sequence, and also contains resistance genes, cloning The peptide or polypeptide may contain other components such as a binding moiety. The polypeptide coding sequence and the appropriate transcription and translation sequences operably linked thereto. These methods include in vitro transcription and transcriptional regulation, and can be used to construct expression vectors containing translational control / regulatory elements. Such techniques include recombinant DNA techniques, synthetic techniques, and in vivo genetic recombination. The method is based on Sambrook et al. (1989) Molecular Cloning g,A Laboratory Manual,Cold Spring Harbor Press, Plainview, NY and Ausubel, FMet a l.(1989)Current Protocols in Molecular B iology, John Wiley & Sons, New York, NY. "Operably linked" means that components, particularly nucleotide sequences, are arranged in a contiguous arrangement. This means that the ingredients are able to perform their normal functions. Thus, a coding sequence that is operably linked to a regulatory sequence is one in which the coding sequence is under the regulatory control of the regulatory sequence. , i.e., a nucleotide sequence capable of being expressed under transcriptional and / or translational control As used herein, "regulatory / control region" or "regulatory / control sequence" refers to a sequence of " refers to non-coding nucleotide sequences involved in regulating the expression of an encoding nucleic acid. Therefore, the term regulatory region refers to the promoter sequence, regulatory protein binding sites, and upstream activating factors. In an embodiment, a nucleic acid (DNA) encoding the tumor antigen peptide of the present disclosure is used. , RNA) is contained or encapsulated within a vesicle such as a liposome.

[0074] In another aspect, the present disclosure includes (i.e., presents or binds to) tumor antigen peptides. In one embodiment, the MHC class I molecule is an HL In a further embodiment, the molecule is an HLA-A*02:01 molecule. In an embodiment, the MHC class I molecule is an HLA-A11 molecule, and in a further embodiment , HLA-A*11:01 molecule. In one embodiment, the MHC class I molecule is an HLA In a further embodiment, the molecule is an HLA-A*24:02 molecule. In an embodiment, the MHC class I molecule is an HLA-B07 molecule, and in a further embodiment In another embodiment, the MHC class I molecule is H In a further embodiment, it is an HLA-B*08:01 molecule. In another embodiment, the MHC class I molecule is an HLA-B40 molecule. In another embodiment, the MHC class I molecule is HLA-B*40:01. HLA-C07 molecule, and in a further embodiment, HLA-C*07:01 molecule. In one embodiment, the tumor antigen peptide is non-covalently bound to the MHC class I molecule (i.e., That is, tumor antigen peptides are loaded into the peptide-binding groove / pocket of MHC class I molecules. In another embodiment, the tumor antigen peptide is covalently or non-covalently linked. In such a construct, Therefore, tumor antigen peptides and MHC class I molecules (alpha chains) are typically short ( For example, 5 to 20 residues, preferably about 8 to 12, e.g., 10) flexible Synthetic fusion proteins with linkers or spacers (e.g., polyglycine linkers) In another aspect, the present disclosure provides a method for producing a protein fused to an MHC class I molecule (alpha chain). a nucleic acid encoding a fusion protein comprising a tumor antigen peptide as defined herein combined with the In one embodiment, the MHC class I molecule (alpha chain)-peptide complex comprises Thus, in another aspect, the present disclosure provides a method for the production of a tumor antigen as referred to herein. Multimers of peptide-loaded (covalently or noncovalently) MHC class I molecules Such multimers may be tagged with a tag, e.g., a fluorescent tag, that allows for detection of the multimer. Many strategies have been developed to prepare MHC multimers, including MHC dimers, tetramers, pentamers, octamers, etc. It has been developed for the production of steroid hormones (Bakker and Schumacher, Cu rrent Opinion in Immunology 2005,17:428- MHC multimers are used, for example, for the detection and characterization of antigen-specific T cells. Thus, in another aspect, the present disclosure provides a method for the preparation of a compound as defined herein, which is useful for the preparation and purification of a compound. CD8 specific for tumor antigen peptides + Detect or purify (isolate, enrich) T lymphocytes The present invention provides a method for enriching a cell population with M cells loaded with tumor antigen peptides. contact with a multimer of MHC class I molecules and binding by the MHC class I multimer. CD8 + and detecting or isolating T lymphocytes. CD8 bound by + T lymphocytes can be isolated by known methods, for example, by fluorescence activated cell sorting (FACS). Cells can be isolated using magnetic-activated cell sorting (MACS) or magnetic-activated cell sorting (MCS).

[0075] In yet another aspect, the present disclosure provides a tumor antigen peptide of the present disclosure, a nucleoside analog thereof, as referred to herein. an acid, vector, or plasmid, i.e., encoding one or more tumor antigen peptides A cell (e.g., a host cell), in one embodiment, an isolated cell, comprising the nucleic acid or vector. In another aspect, the present disclosure provides a method for producing a tumor antigen peptide conjugated to a tumor antigen peptide according to the present disclosure. or presenting an MHC class I molecule (e.g., an allele as disclosed above). In one embodiment, a host cell is provided that expresses a specific MHC class I molecule (one or more MHC class I molecules) on its surface. The cells are eukaryotic cells, such as mammalian cells, preferably human cells, cell lines, or immortalized cells. In another embodiment, the cells are dendritic cells (DCs) or monocytes / macrocytes, etc. In one embodiment, the host cell is a primary cell, a cell line, or an antigen-presenting cell (APC). or immortalized cells. Nucleic acids and vectors can be transformed or transfected using conventional methods. The term "transformation" and "transfection" refer to the transfer of a gene to a cell. The term "transfection" refers to a technique for introducing foreign nucleic acid into a host cell, and or calcium chloride co-precipitation, DEAE-dextran mediated transfection, Microinjection, electroporation, microinjection, and viruses Transforming or transfecting a host cell includes mediated transfection. Suitable methods for this purpose are described, for example, in Sambrook et al. (supra), and other laboratory manuals. Methods for introducing nucleic acids into mammalian cells in vivo are also known. and can be used to deliver the vectors or plasmids of the present disclosure to a subject for gene therapy. It can be used.

[0076] Cells such as APCs can be cultured in one or more tumor cells using a variety of methods known in the art. As used herein, a tumor antigen peptide can be loaded with a tumor antigen peptide. "Loading cells" means loading cells with RNA (mRNA) or Alternatively, DNA or tumor antigen peptides may be transfected into the cells. This means that the APC is transformed with a nucleic acid encoding a tumor antigen peptide. Alternatively, it may directly bind to MHC class I molecules present on the cell surface (e.g., peptide-pulsed cells). Loading by contacting the cells with an exogenous tumor antigen peptide capable of binding to the Tumor antigen peptides can also facilitate their presentation by MHC class I molecules. domains or motifs, e.g., endoplasmic reticulum (ER) retrieval signals, C-terminal Lys-As p-Glu-Leu sequence (Wang et al., Eur J Im munol.2004 Dec;34(12):3582-94).

[0077] In another aspect, the present disclosure provides a tumor antigen peptide as defined herein (or a peptide thereof). any one or any combination of the nucleic acids encoding the nucleic acid sequence(s) In one embodiment, the composition or peptide combination / pool comprises is any combination of tumor antigen peptides as defined herein (2, 3, 4, 5, 6, any combination of 7, 8, 9, 10 or more tumor antigen peptides), or Any combination of nucleic acids encoding the tumor antigen peptides as defined herein. Compositions comprising any combination / subcombination of tumor antigen peptides may be prepared in accordance with the present disclosure. In one embodiment, the composition or peptide combination / pool comprises the peptide sequence of SEQ ID NO: At least one of the tumor antigen peptides comprising or consisting of the sequences shown in 17 to 28. In one embodiment, the composition or peptide The combination / pool of peptides comprises or comprises the sequences set forth in SEQ ID NOs: 29 to 39. The present invention relates to a method for producing a tumor antigen comprising administering to a subject a tumor antigen preparation comprising at least 2, 3, 4, 5, 6, 7, 8, 9, or 10 of the tumor antigen peptides. In another embodiment, the combination or pool may include one or more known tumor antigens. do.

[0078] Thus, in another aspect, the present disclosure provides a tumor antigen peptide as defined herein. or any combination thereof, and an MHC class I molecule (e.g., and a cell expressing an MHC class I molecule (one of the alleles disclosed above). APCs for use in the present disclosure are not limited to specific cell types. First, dendritic cells (DCs), Langerhans cells, macrophages / monocytes, and B cells. These include CD8 + Recognized by T lymphocytes It is known that they present protein antigens on their cell surface, such as APCs are derived from peripheral blood monocytes either in vitro, ex vivo, or in vivo. C can be obtained by inducing the cells and then contacting (stimulating) them with tumor antigen peptides. APCs can also be activated to present tumor antigen peptides in vivo. One or more of the disclosed tumor antigen peptides are administered to a subject to produce tumor antigen peptide-presenting tumor antigen peptides. APCs that respond to the target gene are induced in the subject's body. "Inducing APCs" or "Stimulating APCs" The phrase refers to a cell that is transfected with one or more tumor antigen peptides or a molecule encoding a tumor antigen peptide. This involves contacting or loading the tumor with a nucleic acid that contains a tumor antigen peptide. The peptides are presented on their surface by MHC class I molecules. In accordance with the present disclosure, tumor antigen peptides can be indirectly synthesized, for example, as tumor antigen peptides (native Loading with longer peptides / polypeptides containing sequences of the The tumor antigen peptides can then be processed (e.g., by proteases) within the APC to produce tumor antigen peptides. The APC is loaded with tumor antigen peptides and generates MHC class I complexes on the cell surface. After allowing APCs to present tumor antigen peptides, the APCs can be used as vaccines. For example, ex vivo administration can involve (a) transferring APCs from a first subject to a (b) contacting / loading the APCs of step (a) with tumor antigen peptides. forming an MHC class I / tumor antigen peptide complex on the surface of an APC; c) administering the peptide-loaded APCs to a second subject in need of treatment. It can include.

[0079] the first subject and the second subject can be the same subject (e.g., an autologous vaccine); or Alternatively, in accordance with the present disclosure, antigen-presenting cells may be used to express the antigen-presenting cells. and (c) a method for producing a composition (e.g., a pharmaceutical composition) for inducing tumor growth, comprising administering to the subject a tumor growth factor receptor 5 (TCR)-1 ... In addition, the present disclosure provides for the use of tumor antigen peptides (or combinations thereof) in the treatment of cancer. The present invention provides a method or process for producing a pharmaceutical composition for inducing antigen-presenting cells. The method or process may be used to administer a tumor antigen peptide, or a combination thereof, to a pharmaceutically acceptable carrier. The tumor antigen peptide as defined herein may be mixed or formulated with an acceptable carrier. MHC class I molecules ( For example, HLA-A2, HLA-A11, HLA-A24, HLA-B07, HLA-B Cells such as APCs that express HLA-C08, HLA-B40, or HLA-C07 molecules D8 + T lymphocytes, e.g., autologous CD8 + Can be used to stimulate / expand T lymphocytes Thus, in another aspect, the present disclosure provides a method for producing a tumor antigen peptide (or peptides) as defined herein. or a nucleic acid or vector encoding the same), cells expressing MHC class I molecules, and and T lymphocytes, more specifically CD8 + T lymphocytes (e.g., CD8 + Contains T lymphocytes a composition comprising any one of the following, or any combination thereof: provide.

[0080] In one embodiment, the composition comprises a buffer, excipient, carrier, diluent, and / or medium (e.g., In further embodiments, the composition further comprises a buffer, excipient, carrier, diluent, etc. The agent, and / or medium may comprise pharmaceutically acceptable buffer(s), excipient(s), The term "carrier(s)", "diluent(s)" and / or "medium(s)" is used herein. When used, "a pharmaceutically acceptable buffer, excipient, carrier, diluent, and / or medium" is used. The "substance" must be physiologically compatible and not interfere with the effectiveness of the biological activity of the active ingredient(s). Any and all solvents, buffers, binders, lubricants, fillers, thickeners that are non-toxic to the subject , disintegrants, plasticizers, coatings, barrier layer formulations, lubricants, stabilizers, release retardants, dispersion Vehicles, coatings, antibacterial and antifungal agents, isotonic agents, etc. Pharmaceutically active substances The use of such media and agents for quality is well known in the art (Rowe, et al.Handbook of pharmaceutical excipie nts,2003,4 th edition, Pharmaceutical Press , London UK). Any conventional medium or agent can be used to culture the active compound (peptide, cell). Unless incompatible with any of the above, their use in the compositions of the present disclosure is contemplated. buffers, excipients, carriers, and / or media are non-naturally occurring buffers, excipients, carriers and / or culture medium. In one embodiment, the tumor antigen peptide as defined herein or a nucleic acid encoding said one or more tumor antigen peptides (e.g., The mRNA may be contained within a liposome, e.g., a cationic liposome, or may be attached to a liposome. complexed with the phosphodiesterase (e.g., Vitor MT et al. Recent t Drug Deliv Formula.2013 Aug;7(2):99-110 (See

[0081] In another aspect, the present disclosure provides a tumor antigen peptide (or peptides thereof) as defined herein. any one or any combination of nucleic acids encoding the desired gene(s) and a buffer, excipient, carrier, diluent, and / or medium. For compositions containing cells (e.g., APCs, T lymphocytes), the compositions may contain live cells. Representative examples of such media include physiological saline, Earl's Balanced Salt Solution(Life Techn ologies®) or PlasmaLyte® (Baxter In one embodiment, the composition (e.g., For example, a pharmaceutical composition) may be referred to as an "immunogenic composition," a "vaccine composition," or a "vaccine." As used herein, "immunogenic composition," "vaccine composition," or "vaccine" refers to a The term "vaccin" refers to a composition comprising one or more tumor antigen peptides or vaccine vectors. or formulation, which, when administered to a subject, In order to induce an immune response in a mammal, The vaccination method can be carried out by any conventional route known in the vaccine art, for example, by mucosal administration. via surfaces (e.g., ophthalmic, intranasal, pulmonary, oral, gastric, intestinal, rectal, vaginal, or urinary tract); parenteral via oral (e.g., subcutaneous, intradermal, intramuscular, intravenous, or intraperitoneal) routes or by topical administration vaccines or vaccines administered by transdermal delivery (e.g., via a transdermal delivery system such as a patch) In one embodiment, the tumor antigen peptide (or a combination thereof) is administered to a subject. ) is conjugated to a carrier protein (conjugate vaccine), and tumor antigen peptides are Thus, the present disclosure provides a method for the production of tumor antigen peptides (or peptides) that increase the immunogenicity of the tumor antigen peptide(s). or a combination thereof) and a carrier protein (conjugate). For example, tumor antigen peptide(s) may bind to Toll-like receptor (TLR) ligands (e.g., Zom et al.Adv,Immunol.2012,114:177-201 ), or polymers / dendrimers (see, e.g., Liu et al., Bio macromolecules.2013 Aug 12;14(8):2798-80 6). In one embodiment, the immunogenic composition or vaccine The vaccine further comprises an adjuvant. An "adjuvant" is an adjuvant that is administered to an antigen (such as a tumor antigen according to the present disclosure) or an adjuvant-containing vaccine. When added to an immunogenic agent (e.g., a soluble peptide and / or cells), exposure to the mixture refers to a substance that nonspecifically enhances or potentiates the immune response to a drug in a host. Examples of adjuvants currently used in the field of vaccines include: (1) mineral salts ( Aluminum salts such as aluminum phosphate and aluminum hydroxide, calcium phosphate (2) oil-based adjuvants such as oil-based emulsions and surfactant-based formulations Bunt, e.g., MF59 (microfluidic surfactant-stabilized oil-in-water emulsion), Q S21 (purified saponin), AS02 [SBAS2] (oil-in-water emulsion + MPL + QS -21), (3) particulate adjuvants, such as virosomes (influenza hemagglutinins), thiamin-incorporated unilamellar liposome vehicle), AS04 ([SBAS4], MPL-containing aluminum salts), ISCOMS (structural complexes of saponins and lipids), polylactides doco-glycolide (PLG), (4) microbial derivatives (natural and synthetic), e.g., mono Phosphoryl lipid A (MPL), Detox (MPL + M. Phlei cell wall skeleton), AG P[RC-529] (synthetic acylated monosaccharide), DC_Chol (self-assembling into liposomes) Lipid immunostimulator that can stimulate immune response), OM-174 (lipid A derivative), CpG motif F (synthetic oligonucleotides containing immunostimulatory CpG motifs), modified LT and CT (bacterial toxins genetically engineered to produce non-toxic adjuvant effects), (5) endogenous Human immunomodulators, such as hGM-CSF or hIL-12 (protein or cofactor) cytokines encoded by either the transduced plasmids), imidatulin (C3 d tandem array), and / or (6) an inert vehicle, such as gold particles. do.

[0082] In one embodiment, the tumor antigen peptide(s) or the composition comprising same are in lyophilized form. In another embodiment, the tumor antigen peptide(s) or the composition comprising the same are: In a further embodiment, the tumor antigen peptide(s) is / are in a liquid composition. In a further embodiment, the concentration is from about 0.01 μg / mL to about 100 μg / mL. The tumor antigen peptide(s) may be present in the composition at a concentration of about 0.2 μg / mL to about 50 μg / mL, about 0.5 μg / mL to approximately 10, 20, 30, 40, or 50 μg / mL, approximately 1 μg / mL ~ about 10 μg / mL, or about 2 μg / mL.

[0083] As described herein, any of the tumor antigen peptides defined herein or one of them, or any combination thereof, loaded with or combined with Cells such as APCs that express C class I molecules can be expressed in vivo or ex vivo as CD8 + T It can be used to stimulate / proliferate lymphocytes. Thus, in another aspect, the present disclosure provides Interacting with or binding to the MHC class I molecule / tumor antigen peptide complexes referred to herein T cell receptor (TCR) molecules that can bind to the TCR molecule, and a method for encoding such a TCR molecule. The present disclosure provides nucleic acid molecules that encode the T cell receptor activator, as well as vectors containing such nucleic acid molecules. CRs are loaded onto or presented by MHC class I molecules. and a tumor antigen peptide, preferably on the surface of living cells in vitro or in vivo. The TCRs of the present disclosure, particularly those encoding TCRs, are capable of specifically interacting with or binding to the TCRs. The nucleic acid is, for example, a novel nucleic acid that specifically recognizes an MHC class I / tumor antigen peptide complex. T lymphocytes (e.g., CD8 + T lymphocytes) or other The present invention may be applied to genetically transform / modify lymphocytes of any type. In this study, T lymphocytes (e.g., CD8 + transforms T lymphocytes into tumors The transformed cells are then administered to the patient, expressing one or more TCRs that recognize tumor antigen peptides. (Autologous cell infusion). In certain embodiments, T lymphocytes (e.g., CD4+) obtained from a donor are used. 8 + T lymphocytes) to express one or more TCRs that recognize tumor antigen peptides In another embodiment, the transformed cells are administered to the recipient (allogeneic cell infusion). The disclosure provides a method for administering to T lymphocytes, e.g., vectors encoding tumor antigen peptide-specific TCRs or CD8 transformed / transfected by the plasmid + Provides T lymphocytes In a further embodiment, the present disclosure provides a method for the production of tumor antigen peptide-specific TCR-transformed autoantigens. In yet a further embodiment, a method of treating a patient with autologous or allogeneic cells is provided, comprising: The use of tumor antigen-specific TCRs in the production of autologous or allogeneic cells for the treatment of cancer Provided.

[0084] In some embodiments, a patient treated with a composition (e.g., a pharmaceutical composition) of the present disclosure , treatment with allogeneic stem cell transplantation (ASCL), allogeneic lymphocyte infusion, or autologous lymphocyte infusion. The compositions of the present disclosure include compositions that are administered ex vivo against tumor antigen peptides. Allogeneic T lymphocytes (e.g., CD8 + T lymphocytes), which are negative for tumor antigen peptides -loaded allogeneic or autologous APC vaccines, tumor antigen peptide vaccines, and tumor antigens Allogeneic or autologous T lymphocytes transformed with specific TCRs (e.g., CD8 + T lymphocytes These include lymphocytes or lymphocytes that can recognize tumor antigen peptides according to the present disclosure. The method for providing a T lymphocyte clone involves administering to a subject (e.g., a graft recipient), e.g., an A In SCT and / or donor lymphocyte infusion (DLI) recipients, tumor antigen receptors These peptides can be generated and specifically targeted to tumor cells that express the peptide. Therefore, the present disclosure provides a method for specifically recognizing or detecting a tumor antigen peptide / MHC class I molecule complex. CD8 encodes and expresses a T cell receptor capable of binding + Provides T lymphocytes The T lymphocytes (e.g., CD8 + T lymphocytes) can be recombinant (engineered) or natural Therefore, the present disclosure provides a method for the treatment of CD8 T lymphocytes. + T The present invention provides at least two methods for producing undifferentiated lymphocytes, wherein the undifferentiated lymphocytes are fused to tumor antigen receptors. peptide / MHC class I molecule complexes (typically expressed on the surface of cells such as APCs) contacting under conditions conducive to inducing T cell activation and proliferation. In vitro or in vivo (i.e., APCs are loaded with tumor antigen peptides) In patients receiving PC vaccines or treated with tumor antigen peptide vaccines Combinations of tumor antigen peptides bound to MHC class I molecules can be performed in patients. Using a combination or pool of CD4+ receptors capable of recognizing multiple tumor antigen peptides 8 + Alternatively, tumor antigen-specific or targeted T Lymphocytes express MHC class I molecule / tumor antigen peptide complexes (i.e., engineered or recombinant ECD8 + TCR (more specifically, alpha and beta receptors) that specifically bind to T lymphocytes by cloning one or more nucleic acids (genes) encoding the The tumor antigen peptide-specific TCRs of the present disclosure can be produced / generated in vitro or ex vivo. Nucleic acids encoding the tumor antigen peptides can be expressed ex vivo using methods known in the art. T lymphocytes activated against the peptide (e.g., APCs loaded with tumor antigen peptides) or from an individual that exhibits an immune response to the peptide / MHC molecule complex. The tumor antigen peptide-specific TCR of the present disclosure can be administered to the transplant recipient or the transplant recipient. Recombinantly expressed in host cells and / or host lymphocytes obtained from a donor and optionally differentiated in vitro to produce cytotoxic T lymphocytes (CTLs). Nucleic acid(s) encoding the TCR alpha and beta chains (transgene(s)) (possibly)) can be produced by transfection (e.g., electroporation) or transduction ( using any suitable method (e.g., treated with a viral vector). T cells (from the subject or another individual) specific for the tumor antigen peptide can be introduced into the subject. Engineered CD8 expressing TCR + T lymphocytes are cultured in vitro using well-known culture methods. It can be grown in the

[0085] The present disclosure provides tumor antigen peptides (i.e., peptides that bind to MHC class I molecules expressed on the cell surface). Specifically induced by a combination of tumor antigen peptides, or a combination of tumor antigen peptides , activated, and / or expanded (proliferated) isolated CD8 + Provides T lymphocytes The present disclosure also provides a tumor antigen peptide according to the present disclosure, or a combination thereof (i.e. , one or more tumor antigen peptides bound to MHC class I molecules) CD8 + A composition is provided that includes T lymphocytes and the tumor antigen peptide(s). In another aspect, the present disclosure provides one or more MHC class I molecule / tumor antigen pairs described herein. CD8 specifically recognizes peptide complex(es). + T lymphocyte-enriched cell population Groups or cell cultures (e.g., CD8 + Such enrichment provides a The population may be loaded with one or more of the tumor antigen peptides disclosed herein (e.g., (presenting) MHC class I molecules, such as APCs, are used to target specific T lymphocytes. As used herein, "enriched" refers to a cell that is capable of expressing a specific antigen and can be obtained by performing ex vivo expansion of lymphocytes. "Identification" refers to the differentiation of tumor antigen-specific CD8 + The percentage of T lymphocytes in the native population of cells , i.e., compared to a population that has not been subjected to the ex vivo expansion step of specific T lymphocytes In a further embodiment, the tumor antigen peptide in the cell population is Tido-specific CD8 + The proportion of T lymphocytes is at least about 0.5%, for example, at least about In some embodiments, the percentage of erythrocytes in the cell population is 1%, 1.5%, 2%, or 3%. Tumor antigen peptide-specific CD8 +The proportion of T lymphocytes is approximately 0.5 to 10%, Approximately 8%, approximately 0.5 to approximately 5%, approximately 0.5 to approximately 4%, approximately 0.5 to approximately 3%, approximately 1% to approximately 5%, approximately 1% to approximately 4%, approximately 1% to approximately 3%, approximately 2% to approximately 5%, approximately 2% to approximately 4%, approximately 2% to approximately 3%, approximately 3% to about 5%, or about 3% to about 4%. CD8 specifically recognizes a peptide (tumor antigen peptide) complex(es) + In T lymphocytes Enriched such cell populations or cultures (e.g., CD8 + T lymphocyte population) are As described in detail below, they can be used in tumor antigen-based cancer immunotherapy. In some embodiments, tumor antigen peptide-specific CD8 + Further enrichment of T lymphocyte populations and loaded (covalently linked) with, for example, a tumor antigen peptide(s) as defined herein. Using affinity-based systems such as multimers of MHC class I molecules (covalently or noncovalently) Therefore, the present disclosure provides a method for the production of tumor antigen peptide-specific CD8 + T lymphocyte purification or isolation provide an isolated population, e.g., tumor antigen peptide-specific CD8 + The proportion of T lymphocytes is At least about 50%, 60%, 70%, 80%, 85%, 90%, 95%, 96%, 97% %, 98%, 99%, or 100%.

[0086] The present disclosure provides a method for the preparation of any tumor anti-tumor compound according to the present disclosure as a medicament or in the manufacture of a medicament. Original peptide, nucleic acid, expression vector, T cell receptor, cell (e.g., T lymphocyte, APC) and / or compositions, or any combination thereof. In some embodiments, the medicament is for the treatment of cancer, e.g., a cancer vaccine. The present disclosure provides a method for the treatment of cancer, for example, for use in cancer vaccines (e.g., therapeutic cancer vaccines). Any tumor antigen peptide, nucleic acid, expression vector, T cell receptor, cell (e.g., T lymphocytes, APCs), and / or compositions (e.g., vaccine compositions), or The tumor antigen peptide sequences identified herein relate to any combination of: i) tumor antigens; for in vitro priming and expansion of tumor antigen-specific T cells to be infused into tumor patients. and / or ii) a vaccine that induces or enhances anti-tumor T cell responses in cancer patients. As a result, it can be used for the production of synthetic peptides, which is suitable.

[0087] In another aspect, the present disclosure provides a method for treating cancer in a subject, comprising administering to a subject a compound of the present invention as described herein, as a vaccine for treating cancer in a subject. or a combination thereof (e.g., a peptide pool) The present disclosure also provides the use of a vaccine for treating cancer in a subject. For use, the tumor antigen peptides described herein, or combinations thereof (e.g. In one embodiment, the subject is provided with tumor antigen peptide-specific CD4s. 8 + Thus, in another aspect, the present disclosure provides a method for treating cancer. and methods for treating tumors (e.g., reducing tumor cell numbers, killing tumor cells), The method comprises administering to a subject in need thereof one or more MHC class I molecule / tumor antigen peptide complexes. TCRs that recognize (i.e., bind to) the combined TCRs (expressed on the surface of cells such as APCs) (expressing) an effective amount of CD8 + In one embodiment, the T lymphocytes are administered (infused). In this embodiment, the method comprises: + After administration / infusion of T lymphocytes, tumor antigen peptides, if or combinations thereof, and / or MH loaded with tumor antigen peptide(s) an effective amount of cells (e.g., APCs such as dendritic cells) expressing C class I molecule(s) In yet a further embodiment, the method further comprises administering to said subject A subject in need thereof is administered a therapeutically effective amount of dendritic cells loaded with one or more tumor antigen peptides. In yet a further embodiment, the method comprises administering to a patient in need thereof a therapeutically effective amount of a recombinant protein that binds to a tumor antigen peptide presented by an MHC class I molecule; This involves administering allogeneic or autologous cells that express a TCR.

[0088] In another aspect, the present disclosure provides a method for treating cancer in a subject (e.g., reducing the number of tumor cells). To achieve this, tumor antigen peptides, or a combination thereof, are used to target tumor cells. CD8 recognizes one or more loaded (presenting) MHC class I molecules + T lymphocyte activity In another aspect, the present disclosure provides a method for treating cancer (e.g., tumor) in a subject. for the preparation / manufacture of medicines (for reducing the number of tumor cells and killing tumor cells) One or more MHC antigens loaded with (presenting) tumor antigen peptides, or a combination thereof CD8 recognizes class I molecules + In another aspect, the present disclosure provides a method for the treatment of a T lymphocyte. , for use in treating cancer in a subject (e.g., reducing the number of tumor cells and cells), tumor antigen peptides, or a combination thereof CD8 recognizes one or more MHC class I molecules (presenting) + T lymphocytes (cytotoxic In a further embodiment, the use provides a tumor antigen peptide-specific T lymphocyte. CD8 + After the use of T lymphocytes, an effective amount of tumor antigen peptide (or a combination thereof) ), and / or one or more MHC classes loaded (presenting) tumor antigen peptides It further includes the use of cells (e.g., APCs) that express I molecule(s).

[0089] The present disclosure also provides methods for administering to a subject the tumor antigen peptides disclosed herein or their Tumor cells expressing human class I MHC molecules loaded with either of the combinations The present invention provides a method for generating an immune response against a tumor antigen peptide or tumor antigen. Cytotoxic T cells that specifically recognize class I MHC molecules loaded with peptide combinations The present disclosure also relates to administering the tumor antigen peptides disclosed herein. or a combination of tumor antigen peptides. The present invention provides the use of cytotoxic T lymphocytes that specifically recognize tumor antigen peptides or combinations thereof. The combination induces an immune response against tumor cells expressing human class I MHC molecules. Jiru.

[0090] In one embodiment, the methods or uses described herein may be administered by the patient prior to treatment / use. Determining the HLA class I alleles expressed and the HLA expressed by the patient Administering or using tumor antigen peptides that bind to one or more class I alleles For example, if a patient suffering from B-ALL has HLA-A2*01 and and HLA-B*08:01, (i) SEQ ID NOs: 17-1 9, 27 and / or 28 (binding to HLA-A2*01), and (ii) the sequence Any combination of tumor antigen peptides No. 24 or 25 (binding to HLA-B08*01) The combination may be administered or used in a patient.

[0091] In one embodiment, the tumor cells of the cancer being treated, e.g., leukemia or lung cancer, are Express one or more of the disclosed tumor antigen peptides (SEQ ID NOs: 17 to 39). In embodiments, the methods or uses described herein involve the treatment of tumor cells from a patient with the method described herein. Determine whether the tumor expresses one or more of the tumor antigen peptides (SEQ ID NOS: 17 to 39). and the use of tumor antigen peptides expressed by tumor cells from patients to treat cancer. and administering or using one or more of (a) or (b) of the method.

[0092] In one embodiment, the cancer is a blood or hematological cancer, such as leukemia, lymphoma, and bone marrow cancer. In one embodiment, the cancer is a leukemia, including but not limited to, acute lymphoblastic leukemia. Leukemia (ALL), acute myeloid leukemia (AML), chronic lymphocytic leukemia (CLL), chronic myeloid leukemia (CML), hairy cell leukemia (HCL), T-cell prolymphocytic leukemia ( T-PLL), large granular lymphocytic leukemia, or adult T-cell leukemia. In embodiments, the cancer includes, but is not limited to, Hodgkin's lymphoma (HL), non-Hodgkin's lymphoma, (NHL), Burkitt's lymphoma, precursor T-cell leukemia / lymphoma, follicular lymphoma, diffuse large intestine malignant large B-cell lymphoma, mantle cell lymphoma, B-cell chronic lymphocytic leukemia / lymphoma In a further embodiment, the cancer is a lymphoma, such as B-ALL, or MALT lymphoma. It is a type of B-cell leukemia.

[0093] In another embodiment, the cancer is a solid cancer, such as lung cancer. In a further embodiment, the lung cancer is In one embodiment, the lung cancer is non-small cell lung cancer (NSCLC). ), adenocarcinoma, or large cell undifferentiated carcinoma (LCAC).

[0094] In one embodiment, the tumor antigen peptides, nucleic acids, vectors, and compositions disclosed herein are , chemotherapy, immunotherapy (e.g., CAR T / NK cell-based therapy, checkpoint inhibitor-based therapy, antibody-based therapy), radiation therapy, or other therapies such as surgery (e.g. Examples of immune checkpoint inhibitors include: , PD-1, PD-L1, CTLA-4, KIR, CD40, TIM-3, or LAG Examples of chemotherapy drugs include drugs that inhibit IL-3, such as blocking antibodies. For example, amsacrine, bleomycin, busulfan, capecitabine, carboplatin, Carmustine, chlorambucil, cisplatin, cladribine, clofarabine, crisazone Anticoagulant, cyclophosphamide, cytarabine, dacarbazine, dactinomycin, dacarbazine Unorubicin, docetaxel, doxorubicin, epirubicin, etoposide, fludarabine Fluorouracil (5-FU), gemcitabine, gradelimplant, hydroxybenzoates Rubamide, idarubicin, ifosfamide, irinotecan, leucovorin, liposomal Doxorubicin, liposomal daunorubicin, lomustine, melphalan, mercaptopropion Phosphorus, mesna, methotrexate, mitomycin, mitoxantrone, oxaliplatin Paclitaxel (Taxol), pemetrexed, pentostatin, procarbazine , raltitrexed, satraplatin, streptozocin, tegafur-uracil, temozolomide Romide, teniposide, thiotepa, thioguanine, topotecan, treosulfan, bimbap These drugs contain vincristine, vindesine, vinorelbine, or a combination of these. Alternatively, the chemotherapy agent may be a biologic agent, which targets the HER2 antigen. Herceptin® (trastuzumab), which targets VEGF; Avastin®, which targets VEGF; n® (bevacizumab), or Erbitux® (EGF receptor) anti-cancer drugs such as cetuximab, and Vectibix® (panitumumab) Such additional agents or treatments include those that bind to the tumor antigen peptides disclosed herein. administered / used before, during, and / or after the administration / use of the peptide, nucleic acid, vector, or composition It is possible.

[0095] Current treatments for ALL typically include vincristine, dexamethasone, or Prednisone and doxorubicin (Adriamycin) or daunorubicin Allogeneic stem cell transplantation (allo-SCT) is also available for high-risk patients and It is performed in patients with relapsed / refractory disease and in patients with B-ALL. Other agents in clinical development include anti-CD22, anti-CD20, and anti-CD19 antibodies, as well as protease inhibitors. roteasome inhibitor (bortezomib), JAK / STAT signaling pathway inhibitor (Ruki) These include rheumatoid arthritis drugs (solitinib), hypomethylating agents (decitabine), and PI3K / mTOR inhibitors. (e.g., Terwilliger and Abdul-Hay, Blood Ca Cancer J.2017 Jun;7(6):e577).

[0096] Current treatments for lung cancer typically involve surgery, radiation therapy, and small molecule tyrosine kinase inhibitors. Chemotherapy with inhibitors (erlotinib, crizotinib) and anti-PD1 antibodies (pembrolizumab) These include immunotherapy with checkpoint inhibitors such as lorizumab (e.g., Dho See laria et al.J, Hematol Oncol.2016;9:138. (Refer to the table below).

[0097] Mode(s) for carrying out the invention The present invention is further illustrated by the following non-limiting examples.

[0098] Example 1: Materials and Methods Mice. C57BL / 6 mice were obtained from the Jackson Laboratory (Barrington, MA, USA). Mice were obtained from the University of California, San Diego, Calif. (Harbor, ME). Mice were housed under specific pathogen-free conditions.

[0099] Cell lines: EL4 T lymphoblastic lymphoma cell line, CT26 colorectal carcinoma cell line, and B-cell hybridoma HB-124 was obtained from American Type Culture Collection (American Type Culture Collection). EL4 and CT26 cells were obtained from the American Type Culture Collection (ATCC). Activated fetal bovine serum, 1% L-glutamine, and 1% penicillin-streptomycin The cells were cultured in RPMI 1640 / HEPES supplemented with 1% non- Essential amino acids and 1% sodium pyruvate were added to EL4 cells and CT26 cells. The other two were supplemented with 1% sodium pyruvate only. To achieve this, HB-124 cells were cultured in IMDM supplemented with 10% heat-inactivated fetal bovine serum. Unless otherwise stated, all reagents were purchased from Gibco®.

[0100] Human primary samples. The primary leukemia samples used in this study (4 B-ALL specimens: 07 H103, 10H080, 10H118, and 12H018) are Cellules Leucemiques du Quebec (BCLQ) at Collected and frozen at Hopital Maisonneuve-Rosemont The primary leukemia samples were obtained from the previously reported 1a As shown, after transplantation in NSG mice Briefly, 1–2 × 10 6 Thawing B-ALL cells and sublethally irradiated (250 cGy, 137Cs-γ source) 8-12 week old NSG mice. Mice were sacrificed at the sign of disease and the cell suspension was transplanted into mice via intravenous injection. from experimentally destroyed spleens or a mixture of splenocytes, bone marrow, and ascites for 07H103. From this, a Ficoll™ gradient was used to separate the B -proteins prior to MAP isolation. -ALL cells were enriched (see MAP isolation section). Lung tumor biopsies (lc2, l c4, and lc6) were purchased from Tissue Solutions and used prior to MAP isolation. Homogenized (see MAP isolation section). HLA typing was performed on all samples. RNA sequencing (RNA-Seq) data were collected using Optitype version 1.0. The data were obtained by running the data with the default parameters (RNA extraction, library preparation, and See the Sequencing section).

[0101] Peptides. Native and 13 The C-labeled version of the TSA is available in GenScript. Purity was determined by the manufacturer and was native and13 C The results exceeded 95% and 75%, respectively, for the labeled peptides.

[0102] Mouse mTECs hi Thymus was extracted from 5-8 week old C57BL / 6 or Balb / c mice. The thymocytes were isolated from the thymus and mechanically disrupted to extract thymocytes. are 2a Thymic stromal cells were incubated with biotinylated Ulex europaeu s lectin1 (UEA1; Vector Laboratories), PE-C y7-conjugated streptavidin (BD Biosciences), and Staining was performed with the following antibodies: Alexa Fluor™ 700 anti-CD45, PE anti- IA b (BD Biosciences), allophycocyanin-Cy7 anti-EpCAM (BioLegend). Cell viability was measured using 7-aminoactinomycin D (7-AAD, Live, mature mTECs (mTECs) were evaluated using BD Biosciences. h i ) to 7-AAD - CD45 - EpCAM + UEA1 + MHC II hi As Gaeti mTEC hi A 3-laser FACS AriaIIIu (BD Biosciences) ences, Figure 13A).

[0103] Human TEC and mTEC extraction. Thymuses were extracted from 3-month-old to 7-year-old individuals undergoing cardiovascular correction surgery. Obtained from the body (CHU Saint Justine Research Ethic B (Board, Protocol and Biobank #2126). Briefly, the thymus is Within a few hours of surgical removal, the cells were placed in a 50 ml conical tube containing medium and kept at 4°C. For long-term storage, the thymus cubes were immersed in heat-inactivated human serum / They were frozen in cryovials containing 10% DMSO and kept in liquid nitrogen for up to 3 years. The cryopreserved thymus samples were transferred onto dry ice and subjected to the method described by C. Stoeckle et al. 3a was used to isolate human TECs and mTECs by a protocol adapted from. Thymus tissue was cut into small pieces and then diluted to 2 mg / m in RPMI-1640 (Gibco). Collagenase A (Roche) and 0.1 mg / ml DNase I (Sigma-Aldrich) were used. The digestion was performed three to five times using a solution of PEG-100 (Aldrich) at 37°C for 40 minutes. After incubation, a solution of trypsin / EDTA (Gibco) was added and its activity was confirmed by incubation. 15 minutes before the end of the reaction, the solution was neutralized by adding FBS (Invitrogen). For TEC and mTEC sorting (Figure 13B), cell suspensions were cultured in Pacific Blue -Conjugated anti-CD45 (BioLegend), PE-conjugated anti-HLA -DR (BioLegend), APC-conjugated anti-EpCAM (BioLegend) nd), Alexa 488-conjugated anti-CDR2 (HB-124 hybridoma - see cell lines section - and from Abcam for mTEC samples only Conjugated with Dylight 488 Fast Conjugation Kit Cell viability was assessed by staining with 7-AAD (BD Biosciences). It was used and evaluated.

[0104] RNA extraction, library preparation, and sequencing for EL4 and CT26 cells. 5×10 6 RNA sequencing was performed using a single replicate of C57BL / 6 cells. and Balb / c mTEC hi The minimum number of samples extracted from two females and two males was RNA sequencing was performed on 31,686 or 16,338 FACS-sorted cells. RNA-Seq was performed on 2.0–4.0 × 10 primary leukemia cells in duplicate. 6 A single replicate of 10 cells was performed per donor for human TECs and mTECs. RNA-Seq replicates were collected from 33,076 to 84,198 FACS-sorted TECs. The study was performed on 50,058 to 100,719 mTECs. In all cases, the total R NAs were isolated using TRIzol (Invitrogen) and the RNeasy kit Alternatively, use the RNeasy micro kit (QIAGEN) as recommended by the manufacturer. For each lung tumor biopsy (a total of three times), total RNA was extracted approximately 3 times and further purified using the same method. AllPrep DNA / RNA / miRNA Universal from 0 mg of tissue The samples were isolated using a kit (Qiagen) as recommended by the manufacturer. Each mouse sample (EL4, CT2) was used to perform one replicate of RNA-Seq. 6, and mouse mTECs hi ) and Nanodrop 2000 (Thermo Fi RNA quality was assessed by quantification using the 2100 Bioanalysis software (Sher Scientific). The RIN value (RNA int Human samples (B-ALL, lung tumor cells) with a cytology number of ≥ 9 were selected. Total RNA quantification was performed using QuBit (ABI) for the 1000-kDa ... The quality of the total RNA was checked using a 2100 BioAnalyzer (Agilent Genomics) and RIN (RNA integrity number) ≥7 samples were selected. The cDNA libraries were prepared from 2 to 100 samples of EL4 and CT26 cells. 4 μg mouse mTECs hi 50-100ng for B-ALL specimens and 500ng for B-ALL specimens ng for lung tumor biopsies, 4 μg for human TECs, or 8–13 ng for total RNA TruSeq Stranded Total for Human mTECs from 41-68ng l RNA Library Prep Kit (EL4 cells), KAPA Strand ed mRNA-Seq kit (CT26 cells, C57BL / 6 mTECs) hi , human m TEC, lung tumor, and B-ALL specimens), or KAPA RNA HyperPre pKit (Balb / c mTEC hi These were prepared using human TECs. The library was further amplified by 9–16 cycles of PCR before sequencing. Paired-end RNA sequencing was performed using Illumina NextSeq ( Trademark) 500 (Balb / c mTEC hi , human TECs, and mTECs) or Hi Seq™ 2000 (any other sample) and that per mouse and human sample. Averages are 175 and 199 x 10 6 Got a lead.

[0105] Generation of standard cancer and normal proteomes. RNA-Seq reads for all samples. Sequencing adapters and low-quality The nucleotide sequence was trimmed for the 3' base and then GRCm38.87 for the mouse sample and GRCm38.87 for the human sample. The reference genome for the sample is GRCh38.88, and the STAR version 2.5 was used. 1b 4a Use --alignSJoverhangMin, --alignMat esGapMax, --alignIntronMax, and --alignSJst In itchMismatchNmax, the parameters are set to the default values of 10 and 2 The default parameters are the same as before, except that they are replaced with 00,000, 200,000, and 5-155. The alignment was performed using a cytometer. Single base mutations with a minimum alternative count setting of 5 were counted as follows: freeBayes version 1.0.2-16-gd466dde[arXiv:12 07.3907] and export it as a VCF file. 5a The data was converted into an independent SNP file format compatible with GitHub (https: / / Available at github.com / tariqdaouda / pyGeno. Copy link to Tweet Embed Tweet Replying to @NicolasLBray Harold Pimentel, Pall Melsted and Lior Pa. chter,Near-Optimal probabilistic RNA-seq quantification,Nature Biotechnology 34, 525-527 (2016)] and run with default parameters, and It should be noted that the Kallisto index was , use the index function and download the appropriate *.cdn from Ensembl The standard proteome of each sample was constructed using the a.all.fa.gz file. To construct the pyGeno sequence, we used pyGeno to generate (i) high-quality sample-specific single-nucleotide variants (fre eBayes quality >20) into a reference genome, thereby creating a personalized exome and (ii) sample characteristics of known proteins produced by expressed transcripts (tpm>0). Export the target sequence(s). Export these protein sequences as a fasta file. Then, mass spectrometry (MS) database search (cancer standard proteome) and and / or MHC I-associated peptide (MAP) classification (cancer and normal standard proteome) See Figure 1B for an overview and Tables 4a-b for statistics.

[0106] Generation of cancer and normal k-mer databases. R1 Both the R1 and R2 fastq files were downloaded independently and run on Trimmoma. for sequencing adapters and low-quality 3' bases using tic version 0.35 To ensure that all reads were on the coding strand of the transcript, R1 lead is fastx_re of FASTX-Toolkit version 0.0.14 Reverse completion was performed using the verse_complement function. h 2.2.3 6a for k-mer profiling and MAP classification, respectively. The k-mer databases of 33 and 24 nucleotides in length were generated. (See Figure 7A for details.) Of note, multiple biological replicates (mouse SmTEC hi) or multiple samples from unrelated donors (human TECs and mTECs) When available, fastq files were concatenated to identify the conditions (C57BL / 6, Balb A single normal k-mer database was generated per mouse (i.e., mouse / c or human).

[0107] k-mer filtering and generation of cancer-specific proteomes. The analysis was performed using EL4 or CT to extract potential 33-nucleotide long k-mers. at least four times in 26k-mer cells, seven times in lung tumor biopsies, and one time in primary leukemia samples The cancer-specific k-mers were then restricted to those occurring 0 times. C hi or were not expressed in the k-mer database of human TEC / mTEC This cancer-specific k-mer set was obtained by selecting These sequences were further assembled into longer linear sequences called contigs. One of the 33-nucleotide long k-mers was randomly selected and then The seeds are extended from both ends with consecutive k-mers overlapping by 32 nucleotides on the same strand. (The -r option was disabled and used as a concatenated set of k-mers.) The assembly process is such that k-mers are not assembled, i.e., the 32-nucleotide overlap k Stops when either no k-mer is recognized or multiple k-mers match (-a1 option for linear assembly). In such cases, a new seed is selected. The assembly process resumes until all k-mers from the presented list have been used once. This step is performed using NEKTAR (https: / / bitbu cket.org / eaudemard / nektar) is an in-house development software This is done by the kmer_assembly function in the .jar file. Three-frame translations of contigs that were at least 34 nucleotides in length were performed using an in-house p This was done using a python script. The cancer-specific proteins were then inserted into the and any resulting subsequence of at least 8 amino acids in length is Each was given a unique ID before being included in the base (see Figure 7D). For a schematic, see Figure 1B. See Tables 4a-b for statistics.

[0108] MAP isolation. For EL4 and CT26 cells, 250 × 10 6 The exponential growth of Three biological replicates of each cell line were prepared from exponentially growing cells. For blood disease samples, approximately 450-700 × 10 6 Three biological replicates of each cell were MAP was prepared from leukemic cells collected in the same time period (see the Human Primary Samples section). Already reported 7a After mild acid elution (MAE), peptides were obtained with minor modifications to the method. The resulting solution was desalted on an Oasis HLB cartridge (30 mg, Waters) and purified using a 3 kDa filtration with a molecular weight cut-off (Amicon Ultra-4, Millipore); β2-mycoglobulin (β2M) protein For one of the primary leukemia samples (specimen 10H080), 100 × 10 6 Four additional replicates of cells were prepared and MAP was performed as previously reported. 1a Like exemption Finally, lung tumor biopsies (ranging from 771 to 1,825 mg) were isolated by immunoprecipitation (IP). wet weight, see section on human primary specimens) and cut into small pieces (approximately 3 mm in size) 5 ml of ice-cold PBS containing protein inhibitor cocktail (Sigma) was added to each well. The tissue was homogenized in an Ultra Turrax T25 homogenizer (20 First, two equalization runs were performed using an IKA-Labortechnik (IKA-Labortechnik) at 2,000 rpm for 20 seconds. The mixture was then homogenized in an Ultra Turrax T8 homogenizer (25,000 rpm for 2 min). The mixture was homogenized once using a 550 s IKA-Labortechnik (IKA-Labortechnik). μl of ice-cold 10x lysis buffer (10% w / v CHAPS) was added to each sample, and MAP was It has been reported 1 Covalently cross-linked with Protein A magnetic beads per sample. Immunoprecipitation was performed using 1 mg (1 ml) of the combined W6 / 32 antibody. Regardless, all MAP extracts were dried using a Speed-Vac prior to MS analysis. , and kept frozen.

[0109] Mass spectrometry analysis. All dried MAP extracts were resuspended in 0.2% formic acid. For CT26 and MAP extract, homemade C 18 Precolumn (C 18 Jupiter In addition to the Phenomenex-filled 5mm x 360μm inner diameter), homemade C 18 analysis Column (C 18 15cm x 150mm inner diameter filled with Jupiter Phenomenex μm) and analyzed by the nEasy-LC II system using 0–40% acetonitrile (0. 2% formic acid) over a 56-minute gradient, and 600 nl·min -1All were separated by a flow rate of For human samples, MAP extracts were prepared using homemade C 18 Analytical column (C 18 Jupiter Filled with Phenomenex (15cm x 150μm inner diameter), nEasy-LC II system, 0-40% acetonitrile (0.2% formic acid, O7H103, 10 A 56-minute gradient of H080-MAE, 10H118, and 12H018) or 5- 100 ml of 28% acetonitrile (0.2% formic acid, lung tumor biopsy and 10H080-IP) The sample was applied at a flow rate of 600 nl min-1 with a gradient of 1000 nl min-1. Plus (EL4, Thermo Fisher Scientific) or HF ( All other samples were analyzed by Thermo Fisher Scientific. - Exactive Plus captures each full MS spectrum at 70,000 resolution. The most abundant multiply charged ions were detected at 17,500 mcg, followed by 12 MS / MS spectra. resolution, 1e6 automatic gain control target, 50ms injection time, and 25% collision energy were selected for MS / MS sequencing. Each full MS spectrum acquired at 2,000 resolution was followed by 20 MS / MS spectra. The most abundant multiply charged ions were 15,000 (CT26, 07H103, 10H080) -MAE, 10H118, 12H018) or 30,000 (lung tumor biopsy, 10H08 0-IP) resolution, 5×10 4 an automatic gain control target of 100 ms, an injection time of 100 ms, and Peptides were selected for MS / MS sequencing at a collision energy of 25%. Identified using 8.5 (Bioinformatics Solution Inc.) The peptide sequences were then searched against relevant comprehensive cancer databases and standard cancer proteomic sequences were analyzed. The cancer-specific proteome was obtained by linking the standard cancer proteome and the positive Generation of normal proteomes and k-mer filters of cancer-specific proteomes (See the section on peptide identification and generation). The tolerances for the ion and fragment ions were set to 10 ppm and 0.01 Da, respectively. The occurrence of oxidation (M) and deamidation (NQ) was considered as post-translational modifications.

[0110] MAP identification. To select for MAP, unique identifications obtained from Peaks are used. Filter the list to find the Net for at least one of the relevant MHC I molecules MHC 4.0 8a have a percentile rank of ≦2%, as predicted by It contained peptides of 8 to 11 amino acids in length. Furthermore, it was found that the peaks score exceeded a given threshold. The local 5% false discovery rate (FDR), defined as the number of decoy identifications divided by the number of target identifications, was applied to limit the number of false positive identifications in the final MAP list.

[0111] Identifying and validating TSA candidates. To identify TSA candidates among all identified MAPs, To do this, an immunogenicity status was assigned to each MAP / protein pair. AP and its associated MAP coding sequence(s) (MCS), respectively, are used to identify cancer-associated and normal personalized proteome or cancer and normal 24-nucleotide k-mer data The MAPs detected in the normal standard proteome were compared with those in the control group, suggesting that they are tolerogenic. Patients were excluded regardless of their MCS detection status because they may be legitimate cancer patients. MAPs that were specific, i.e., not detected in the normal standard proteome or normal k-mers, MAPs that were not identified were flagged as TSA candidates. MAPs present in both k-mer databases but not in normal cells and having their MCSs overexpressed by at least 10-fold in cancer cells, It is flagged as such (see Figure 8A). Finally, some MCSs (different tongues) MAPs encoded by proteins (from proteins) have identical MCSs If this MAP is consistently flagged as a TSA candidate, The MS / MS spectra of all TSA candidates can be collected and flagged as TSA candidates. Manual review was performed to remove any false identifications. Further examination of the sequences displaying the potential I / L variant revealed that both variants were When they were distinguishable by MS, both variants were included, or when they were distinguishable. When this was not possible, only the most expressed variant was reported (see Figure 8B). Later, the genomic locations were identified using BLAT (a tool from the UCSC genome browser). CS-containing reads were mapped to the reference genome (GRCm38.87 or GRCh38.88). By performing a sequence matching, we assigned all of these MS-validated TSA candidates. There was no match to the corresponding genomic location or the hypervariable region (MHC, Ig, or TSA candidates who did not match the gene or multiple genes were excluded. For those with matching genomic locations, the Integrative Genome eViewer(IGV) 9awith respect to their associated normal counterparts, M TSA candidates with CS duplication synonymous mutations, or for human TSA candidates, known germline Exclude polymorphisms that overlap (i.e., listed in dbSNP v.149, Figure 8C ). The remaining peptides were classified into m and mC and mC, depending on whether their MCS overlapped with cancer-specific mutations. They were classified as TSA or aeTSA candidates.

[0112] Peripheral manifestations of MCS. To evaluate the peripheral manifestations of MCS in TAA and aeTSA candidates. (1) RNA ENCODE Consortium 10a、11a It has been sequenced by (2) 22 mouse tissues sequenced by the GTEx Consortium (Table 5), or Downloaded from the GTEx Portal on April 16, 2018 Eight peripheral human tissues (approximately 50 donors per tissue) (phs000424.v7.p2, Table 6), we used RNA-Seq data from the following tissues. Sequencing data was analyzed using Jellyfish 2.2.3 (using the -C option). Convert the k-mers into a 24-nucleotide long database and add the k-mers of each MCS to the database. For each RNA-Seq experiment, a given MC The number of reads that completely overlap with S (r overlap ) as the minimum occurrence of the k-mer set (k min ) was used to estimate the min ~r overlap The hypothesis is The results were consistent across all reads, excluding low-complexity RNA-Seq reads that may generate the same k-mer multiple times. This is because one k-mer always originates from a single RNA-Seq read. To compare MCS expression levels across all tissues, this overlap The value is Using the formula below, the sequenced 10 8 Number of detected reads per read (rphm ),

number

[0113] MS validation of TSA candidates. CT26 TSA candidate and two EL4 TSA candidates (AT QQFQQL-SEQ ID NO: 11 and SSPRGSSTL-SEQ ID NO: 13) The acquired MS / MS spectrum is related 12 Compared to the C analogue. In vivo testing The other five EL4 TSA candidates (IILEFHSL - SEQ ID NO: 12, TVPLNHN TL - SEQ ID NO: 14, VNYIHRNV - SEQ ID NO: 15, VNYLHRNV - SEQ ID NO: 1 5, VTPVYQHL-SEQ ID NO: 16), six additional EL4 replicates (per replicate) Approximately 450 to 1,400 x 10 6 MAPs were eluted from the cells and processed as described above. For absolute quantification, six samples were analyzed (see MAP isolation and mass spectrometry section). Three of the EL4 replicates were 13 500 fmol of C-labeled TSA was added. For proof, 12 C MS / MS spectra of TSA candidates were analyzed by PRM MS. Briefly, five peptides were monitored as planned. RM acquisition (each peptide was monitored only in a 10-minute window centered around its elution time) (obtained) consists of one MS1 scan followed by a targeted MS / MS scan in HCD mode. Automatic gain control and injection of survey scans and tandem spectra The times were 3e6-50ms and 2e5-100ms, respectively. Skyline 12a The intrinsic MS / MS spectrum of each TSA candidate was obtained using Extract and associate it 12 Compare with CMS / MS spectra (sequence verification) or Endogenous and related synthesis 13 The intensities of C-labeled peptides were extracted (absolute quantification). These intensities were further used to calculate TSA copies per cell for each replicate using the formula: Calculate the number (n 合成 ×I 内因性 ×N A / I 合成 )×(1 / N 細胞 ), where n 合成 I think Considered synthesis 13 the initial number of moles of C-labeled TSA added, I 内因性 and I 合成 teeth Intrinsic and related 13 Intensity of C-labeled TSA, N A is Avogadro's number, N 細胞 teeth This is the initial cell number used for the weak acid elution.

[0114] Cumulative number of transcripts detected in human TEC and mTEC samples. Analysis was performed on six samples. tpm>1 in at least one of the samples (2 TECs and 6 mTECs) Restricted to expressed transcripts, Spearman's rank correlation coefficient was calculated for the 1:1 TEC / mTEC ratio. These same sets of expressed transcripts were then used to calculate the detected The cumulative number of transcripts detected (cT) was calculated as each additional sample was analyzed. The order in which the cT values are introduced can affect the cT values, so the cT values across all sample exchanges The T values were averaged and these average data points were used to fit the following predicted curve: (using the "nls" function in R),

number

number

[0115] Generation of bone marrow-derived dendritic cells (DCs), mouse immunization, and EL4 cell injection. Bone marrow-derived DCs C has already been reported 13a、14a For mouse immunization, male C DCs from 57BL / 6 mice were pulsed with 2 μM of selected peptides for 3 hours, followed by 8-12 week old female C57BL / 6 mice were inoculated with irradiated EL4 cells ( 14 days, 7 days, or simultaneously with the administration of 10,000cGy 6 Individual peptides As a negative control, C57BL / 6 female mice were injected intravenously with doped-pulsed DCs. Mice were immunized with unpulsed DCs. On days 0 and 150, mice were immunized with 5 × 10 5 EL 4 cells were injected intravenously and monitored for weight loss, paralysis, or tumor growth.

[0116] IFN-γ ELISpot assay and avidity assay. ELISpot assay The binding and binding activity assays were performed as previously reported. 14a It was carried out as follows. Millipore MultiScreen PVDF plates were then washed with 35% ethanol. The cells were permeabilized with IFN-γ ELISpot Ready-SET-G. The mice were coated overnight using a reagent set (eBioscience). On day 0 after immunization, splenocytes were harvested from immunized or naive mice. x10 6 Splenocytes were incubated at 37°C / mL with FITC-conjugated anti-CD8α (BD Biosciences) The cells were stained with FACSAria™ II for 30 minutes at 4°C, washed, and then analyzed by FACSAria™ II. u or FACSAria™ IIIu instrument (BD Biosciences, Figure 1 3C). Selected CD8 + T cells were seeded and administered the relevant peptide (EL 4 μM for ISpot assays and 10 μM for binding activity assays -4 ~10 -14 M In the presence of irradiated splenocytes (4,000 cGy) from syngeneic mice pulsed with The cells were incubated at 37°C for 48 hours. CD8 + T cells were incubated with peptide-pulsed splenocytes. Reveal and test the ImmunoSpot S5 UV using the set manufacturer's protocol. Counting was performed using an analyzer (Cellular Technology Ltd). IFN-γ production was measured by 10 6 CD8 + as the number of spot-forming units per T cell Represents EC 50 was calculated using a dose-response curve.

[0117] Cell isolation and tetramer-based enrichment protocol from lymphoid tissues: spleen and inguinal Axillary, brachial, cervical, and mesenteric lymph nodes were collected from C57BL / 6 mice. The cell suspension was incubated with Fc block and 10 nM PE- or APC-labeled pMHC I tetramers. 30 min at 4°C by tetramerization (NIH Tetramer Core Facility) After washing with ice-cold sorting buffer (PBS supplemented with 2% FBS), the cells were stained for 2 h. of selection buffer and 50 μL of anti-PE and / or anti-APC antibody-conjugated magnetic The cells were resuspended in soluble microbeads (Miltenyi Biotech) and incubated at 4°C for 20 min. The cells were then washed and incubated for 1 min. 15a、16a Yo Sea urchin tetramer + Cells were magnetically enriched. The resulting tetramers + The enriched fraction contains APC Fire 750 conjugated anti-B220, F4 / 80, CD19, CD11b, C D11c (BioLegend), PerCP-conjugated anti-CD4 (BioLegend end), BV421-conjugated anti-CD3 (BD Biosciences), B B515-conjugated anti-CD8 (BD Biosciences), BV510-conjugated Conjugated anti-CD44 (BD Biosciences) antibody, and Zombie By NIR Fixable Viability Kit (BioLegend) Anti-CD11b and CD11c staining was performed. These markers were expressed in several activated cells. can be expressed by T cells 17a、18a Regarding the analysis of post-immunization repertoires, The entire stained sample was then run on a FACSCanto™ II cytometer. The samples were analyzed using fluorescent counting beads (Thermo Fischer, BD Biosciences). The results were normalized using the Her Scientific (Her Scientific) as a negative control. , three virally derived antigens, lymphocytic choriomeningitis virus (LCMV) proteins gp-33 (KAVYNFATC - SEQ ID NO: 40, H-2D b ), Mau M45 (HGIRNASFI - SEQ ID NO: 1) from the cytomegalovirus protein M45 41. H-2D b ), and B8R (TSY) from vaccinia virus protein B8R KFESV-SEQ ID NO: 42, H-2K b ) targeting antigen-specific CD8 + T cell replicator Tree enriched.

[0118] Data. Information about all samples used in this study is listed in Table 7. The sequencing and expression data are available from NCBI's Sequence Read Arc Deposited at hive and GEO, both with SuperSeries accession code G The mouse or human sequencing data can be accessed from GEO under SE113992. GSE111092 and GSE113972 for determination and expression data, respectively The SuperSeries record contains the token cnutscacj within the box. bkzteb by entering https: / / www.ncbi.nlm.ni h.gov / geo / query / acc.cgi?acc=GSE113992 The MS raw data and associated database used in Figure 1 are available at http: / / www.pscp.tv / w / cQXFJJJJ RIDE 19a ProteomeXchange Consortium via partner repositories The data has been deposited with the National Institute of Standards and Technology (NIS) and has the following dataset identifiers: PXD009065 and 10 .6019 / PXD009065 (CT26 cell line), PXD009064 and 10. 6019 / PXD009064 (EL4 cell line), PXD009749 and 10.60 19 / PXD009749(07H103), PXD009753 and 10.6019 / PXD009753 (10H080, weak acid elution), PXD007935-Assay #8 1756 and 10.6019 / PXD007935 (10H080, immunoprecipitation) 1a , PXD009750 and 10.6019 / PXD009750(10H118), PX D009751 and 10.6019 / PXD009751(12H018), PXD0 09752 and 10.6019 / PXD009752(lc2), PXD009754 and 10.6019 / PXD009754(lc4), and PXD009755 and and 10.6019 / PXD009755(lc6).

[0119] Example 2: Rationale and design of a proteogenomics approach for TSA discovery. Attempts to predict TSA computationally using various algorithms have been extremely with a high false discovery rate 27Therefore, a systems-level molecular definition of the MAP repertoire can only be achieved by high-throughput MS studies 3 Current Approach Peaks 28 Using MS / MS software tools such as A user-defined protein database is used to match S spectra to peptide sequences. Because the reference proteome does not contain TSAs, MS-based TSA discovery work The flow uses a proteogenomics strategy to identify tumor RNA-sequencing (RNA-Seq). q) A customized database derived from the data must be built. 29 , consideration Ideally, it should include all proteins, even unannotated, that are expressed in available tumor samples. Current MS / MS software tools translate all RNA-Seq reads. This is because it cannot cope with the large search space created by all the frames. 30、31 In this study, proteogenomic strategies were devised to enrich for cancer-specific sequences, and all genomes were analyzed. To comprehensively characterize the landscape of TSAs encoded by the genome region. The database consists of two customizable parts called the Comprehensive Cancer Database. The first part, called the canonical cancer proteome (Figure 1A), is a collection of expressed proteins. obtained by computer translation of the code transcripts in their normal frame, Therefore, it is possible to distinguish between exon sequences that are normal or contain single-base mutations. The second part contains the cancer-specific proteome (Figure 1B) and the proteins encoded by the cancer-specific proteome (Figure 1C). It is said that current mappers and variant callers do not adequately identify structural variants. Therefore, an alignment-free RNA-Seq technique called k-mer profiling is being developed. This second dataset was generated using a workflow. of peptides encoded by any reading frame (including structural variants) detection was possible as long as they were cancer-specific (i.e., not present in normal cells) Here, mTEChi was chosen to be used as a "normal control" and They express the most known genes and their vast transcriptomes 32 By Ko This is because it induces central tolerance to the MAPs that are administered. To identify RNA sequences that are involved, cancer RNA-Seq reads are divided into three groups called k-mers. Cut into 3-nucleotide sequences 33 , k-mers were removed from the isogenic mTEChi ( Figure 7 A-B). The inherent redundancy in the k-mer space allows overlapping cancer-specific k-mers to be They are removed by assembling them into long sequences called TIGs, and then computer-generated The results were then translated in three frames (Figure 1B and Figures 7C-D). and cancer-specific proteomes are linked to generate one comprehensive cancer data set for each analyzed sample. Using such an optimized database, two well-characterized A mouse tumor cell line, CT26, a colorectal carcinoma from Balb / c mice, was used. and eluted from EL4, a T-lymphoblastic lymphoma from C57BL / 6 mice. The MAPs were sequenced and identified by MS (Figure 1C).

[0120] Example 3: Non-coding regions are the major source of TSA. At a false discovery rate of 5%, 1,875 MAP and 7 EL4 cells were used for CT26 cells. We identified 83 MAPs. Among these, mTEC hi MA not present in the proteome P is defined as (i) those 33 nucleotides derived from a complete cancer-restricted 33-nucleotide-long k-mer; Otid-length MAP coding sequences (MCS) are absent from the mTEChi transcriptome or (ii) those 24-nucleotide sequences derived from cancer-restricted 33-nucleotide-long k-mers. The 30-nucleotide-long MCS is hi Cells in the cancer transcriptome Proteins that were overexpressed at least 10-fold in the MS sample were considered as TSA candidates (Figure 8A). Following the association validation step and genomic location assignment (Figure 8B-C), a total of six m We obtained 15 TSA and 15 aeTSA candidates, 14 of which were presented by CT26 cells and 7 These were expressed by EL4 cells (Figure 2A-B). MAPs were included in the mTSA category. All of these MAPs are considered novel and are Mune Epitope Database 36 There is only one, AH1 The peptide (SPSYVYHQF) was previously identified on CT26 cells using reverse immunology 150 aeTSA 9、37 It is excluded because it is one of the

[0121] mTECs from cancer k-mers hi Strict database construction strategy based on k-mer removal To assess the density of MCS encoding aeTSA across a panel of 22 tissues, Peripheral expression was assessed 38、39 (Table 5). Four of the 15 aeTSA candidates These MCSs were expressed in most or all tissues, and thus the previously reported "overexpression" Tumor-associated antigens (TAA) 40、41 had a similar expression profile to that of the control (Fig. 2C). Therefore, these four peptides were excluded from the TSA list. In contrast, 11 MAPs are characterized by the fact that their MCSs are completely absent or present in trace amounts in some tissues. Since the transcripts were present, they were considered to be true aeTSAs (Fig. 2C). because MAPs are preferentially derived from highly abundant transcripts 42、43 , it's not important. This concept is supported by the fact that despite the weak expression of MCS in the liver, thymus, and bladder, no adverse effects were observed. This is exemplified by AH1 TSA, which induces a strong antitumor response without adverse effects. 9、37 (figure 2C). These results suggest that mTEC hi Subtracting mRNA sequences found in cancer The entire mouse TSA dataset (6 m Considering the 11 aeTSAs and 11 TSAs, the most striking finding is that most of them However, atypical translation events include out-of-frame translation of coding exons or non-coding exons. Furthermore, all identified TSAs were derived from the translation of the TSA domain (Fig. 2D). With the exception of two, their source sequences are protein cores. are not annotated as encoded and therefore are not seen by classical exome-based approaches. Interestingly, any type of non-coding region, intergenic and intronic sequences, non-coding exons, UTR / exon junctions, and EREs. It has also been noted that cereals such as cereals containing glutamic acid (Glycine max) can produce TSA (Table 1), making them a particularly rich source of TSA. (8 aeTSAs and 1 mTSA). The described approach efficiently captures structural variants and significantly increases the expression of IL-1 in EL4 cells. An antigen derived from an intergenic deletion (approximately 7,500 bp), VTPVYQHL, was identified. (Table 1b). Overall, these results suggest that non-coding regions are the major source of TSA, and that confirms that these have the potential to significantly expand the TSA landscape of tumors.

[0122] Further testing will be carried out on the TSA that appears to be the most attractive, namely, the one presented by EL4 cells. This was performed on some of the TSAs whose MCS is not expressed by any normal tissue. To assess their immunogenicity, C57BL / 6 mice were cultured in a 20-well plate. Before loading live EL4 cells, the cells were either unpulsed (control group) or pulsed with TSA. The mice were immunized twice with either DCs against IILEFHSL or TVPLNHNTL. Priming prolonged survival in 10% of mice and in 10% of TVPLNHNTL-immunized mice. Only one TSA survived up to 150 days (Figure 3A). The other three TSAs survived up to 20% (VNYIHRNV) ), 30% (VTPVYQHL), and 100% (VNYLHRNV) 150-day survival To evaluate the long-term efficacy of TSA vaccination, we performed a survival and mortality study. The mice were rechallenged with live EL4 cells on day 150 and monitored for signs of disease. Two VNYIHRNV-immunized surviving mice died of leukemia within 50 days, whereas all others (immunized against TVPLNHNTL, VTPVYQHL, or VNYLHRNV) Thus, immunization with individual TSAs was not associated with the proliferation of EL4 cells. It was concluded that different degrees of protection are afforded to different individuals and that in most cases this protection is long-lasting. It can be done.

[0123] Example 4: Frequency of TSA-specific T cells in naive and immunized mice. In various models, the strength of the in vivo immune response is determined by the number of antigen-reactive T cells. is adjusted 44、45 Therefore, TSA-specific responses in naive and immunized mice 4. Tetramer-based Enrichment Protocol for Targeted T Cell Frequencies 46、47 Evaluate and game using The screening strategy and one representative experiment can be seen in Figure 9A-C. Its role is specific for three viral epitopes (gp-33, M45, and B8R). We used a very large amount of CD8 T cells, and their frequency was compared with that of previous studies. 45 observed in In naive mice, the levels of TVPLNHNT were within the range of 1.0 (Fig. 4A). CD8 T cells specific for L, VTPVYQHL, and IILEFHSL were rare ( 10 6 Fewer than one tetramer+ cell per CD8 T cell) was detected in ERE TSA (VNY CD8 T cells specific for IHRNV and VNYLHRNV are involved in viral control. The frequency of TSA-pulsed leukemia was similar to that of TSA-pulsed leukemia (Fig. 4A and Fig. 10A). In mice immunized with DCs, tetramer staining or IFN-γ ELISpot assay T cell frequencies to two ERE TSAs assessed by SE (Figure 9C-D and 1 0A) was significantly higher than TVPLNHNTL, VTPVYQHL, and IILEFHSL. Furthermore, both naive and immunized mice showed high levels of IL-1 (Fig. 4B-C). It was found that the frequency of antigen-specific T cells was highly correlated with the number of T cells (FIGS. 11A to 11C). Finally, the functional avidity of VNYIHRNV- and VNYLHRNV-specific T cells was , two highly immunogenic non-self antigens, the minor histocompatibility antigens H7a and H13a. The TSAs were evaluated as being similar to those of specific T cells (Figure 4D). , derived from a supposedly non-coding region, but with highly abundant T with high functional binding activity. VNYIHRNV was recognized by the cells because it has the unmutated germline sequence. Particular attention should be paid to aeTSA.

[0124] Taken together, these results suggest that the frequency of TSA-specific T cells is generally a significant factor in TSA immunogenicity. However, VTPVYQHL is not associated with its cognate T cells. Although the frequency of EL4 loads was very low, the second-to-best protection was achieved. 3 and 4A-C), further highlighting the importance of T cell proliferation in leukemia protection. To further evaluate the effect of EL4 cells on the survival of long-term surviving mice after rechallenge with EL4 cells at day 150, mer + The frequency of CD8 T cells was assessed (Figure 3). These analyses were performed on day 210 and was performed at the time of death (in the case of VNYIHRNV-primed mice). All long-term survivors, including HL-immunized mice, expressed TSA-specific (tetramer + )CD8 T VNYIHRNV showed a large population of tetramer+ cells (Fig. 10B-C). This was recognized by the group as a result of the large increase in the number of mice reloaded under the experimental conditions used herein. It wasn't enough to protect the animals.

[0125] Example 5: Importance of antigen expression for protection against EL4 cells. Next, the effect of antigen expression on immunogenicity was examined in the EL4 cell population injected on day 0. The amount of TSA was evaluated by assessing the RNA level (Figure 3). The sequence encoding the TSA that confers the best protection (VNYLHRNV) is It was found that VNYLH was expressed at a much higher level than VNYLH (Fig. 5A). It is possible that RNV is "clonal" (expressed by all EL4 cells) and highly is expressed at high levels, whereas other TSAs are subclonal and / or expressed at low levels. Next, parallel reaction monitoring (PRM) MS was used to investigate the reactivity of The number of TSA copies per cell in the EL4 cell population used for loading was analyzed (150 There was no linear relationship between TSA abundance in RNA and peptide levels. Was 40 (Fig. 5A-B). In particular, the best TSA, VNYLHRNV, was the most was one of the most abundant TSAs (>500 copies per cell), but in the experiments used herein VNYIHRNV (Figure 3B), which did not confer significant protection upon rechallenge under EL conditions, 4 cells, the virus was no longer detected in the subclonal TS. A, and antigen loss is the most likely explanation for the lack of significant protection upon rechallenge. Finally, TSA was immunogenic when presented by DCs, but not by E It was noted that the antibody was not immunogenic when presented by L4 cells, i) pre-immune Injection of live EL4 cells without TSA did not induce significant proliferation of TSA-specific T cells, and ii) Immunization with irradiated EL4 cells did not confer significant protection against live EL4 cells. This indicates that in the absence of immunity, highly immunogenic TSA (e.g., VNYLHRNV) was ineffective because it was not efficiently cross-presented by DCs. This highlights the importance of efficient T cell priming in cancer immunotherapy. Suggest.

[0126] Example 6: Non-coding regions expand the TSA landscape of human primary tumors. It was established that non-coding regions are the major source of TSA in two mouse cell lines. The proteogenomic approach described herein was performed on seven human primary tumor samples: We applied this to four B-lineage ALL and three lung cancers. hi Rather than using RNA-Seq data from 6 patients undergoing cardiovascular corrective surgery, Transcripts of whole TECs (n=2) and purified mTECs (n=4) from related donors Notably, minimal inter-individual variation was observed, and this cohort The size of the dataset is sufficient to cover nearly the entire mTEC transcriptome landscape. These RNA-Seq data are shown in Figure 1. The three mTs were used as the normal k-mer repertoire for the workflow. We identified 27 aeTSA candidates (Figure 6A). This also ensured that the mTSA did not overlap with known germline polymorphisms. To further validate the status, we analyzed a Expression of eTSA MCSs (6–50 per tissue, Figure 6B and Table 6) was measured using mouse aeT Based on these data, six ae were analyzed in the same manner as that performed for SA (Fig. 2C). We excluded TSA candidates, i) three of which were widely expressed and the most previously reported overexpressed TAs; A 48 and ii) three were expressed at significant levels in a single organ, the liver. Therefore, a total of 3 mTSA and 20 non-redundant aeTSA candidates were identified (Figure 6B). (Fig. 6C and Tables 2a-d and 3a-c). ALVFHV aeTSA is shared by two HLA-A*02:01-positive ALLs This aeTSA is a gene involved in lymphoid malignancies. The results are consistent with the results of the protein synthesis described herein. A genomics approach will identify the repertoire of mTSA and aeTSA in individual tumors. can be characterized in about two weeks.

[0127] table

[0128] [Table 1a]

[0129] [Table 1b]

[0130] [Table 2a]

[0131] [Table 2b]

[0132] [Table 2c]

[0133]

Table 2d

[0134]

Table 3a

[0135]

Table 3b

[0136]

Table 3c

[0137]

Table 4a

[0138]

Table 4b-1

[0139]

Table 4b-2

[0140]

Table 4b-3

[0141]

Table 4b-4

[0142]

Table 5

[0143]

Table 6-1

[0144]

Table 6-2

[0145]

Table 6-3

[0146]

Table 6-4

[0147]

Table 6-5

[0148]

Table 6-6

[0149]

Table 7a-1

[0150]

Table 7a-2

[0151]

Table 7a-3

[0152]

Table 7b-1

[0153] [Table 7b-2]

[0154] [Table 7b-3]

[0155] While the present invention has been described above with reference to specific embodiments thereof, it is to be understood that the invention is not limited to the disclosed embodiments and may be modified in any way without departing from the spirit and scope of the invention. As will be appreciated, variations may be made without departing from the spirit and nature of the invention. In the claims, the word "including" is used interchangeably with the phrase "including but not limited to." The singular forms "a," "an," and "t" are used as equivalent, open-ended terms. "he" includes corresponding plural references unless the context clearly indicates otherwise.

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Claims

1. 1. A method for identifying candidate tumor antigens in a tumor cell sample, comprising: (a) A tumor-specific proteome database (i) from the tumor RNA sequence, a subsequence (k-mer) containing at least 33 base pairs; Extracting the set; (ii) extracting the set of tumor subsequences of (i) from RNA sequences from normal cells; and comparing the sequence to a corresponding set of control subsequences containing at least 33 base pairs of the sequence. And, (iii) extracting the tumor subsequence that is not present in the corresponding control subsequence; thereby obtaining tumor-specific subsequences; (iv) computer-translating the tumor-specific subsequence, thereby Obtaining a tumor-specific proteome database; (b) a personalized tumor proteome database; (i) comparing the tumor RNA sequence with a reference genome sequence to identify the Identifying the single nucleotide mutation that (ii) inserting the single base mutation identified in (i) into the reference genome sequence; thereby generating a personalized tumor genome sequence; (iii) coding expressed protein-encoding transcripts from the personalized tumor genomic sequence; and translating the resulting personalized tumor proteome database. and generating by (c) the sequence of a major histocompatibility complex (MHC)-associated peptide (MAP) from the tumor. (a) the tumor-specific proteome database and (b) the personalized tumor proteome database. Identifying said MAP by comparing it with sequences in a roteome database; (d) identifying candidate tumor antigens among the MAPs identified in (c); Candidate tumor antigens are those whose sequences and / or coding sequences are overexpressed in tumor cells compared to normal cells. The method is an overexpressed or overpresented peptide.

2. The method includes: (1) extracting major histocompatibility complex (MHC)-associated peptides from the tumor cell sample; and / or (2) isolating and sequencing a MAP protein from said tumor cell sample. and further performing whole transcriptome sequencing to obtain the tumor RNA sequence. The method of claim 1 , comprising:

3. The isolation of the MAPs may involve (i) releasing the MAPs from the cell sample by treatment with a mild acid. and (ii) subjecting the released MAP to chromatography. The method of claim 2.

4. The method further comprises separating the released peptides into a size exclusion column prior to the chromatography.

4. The method of claim 3, further comprising filtering through a filter.

5. The method of any one of claims 1 to 4, wherein the subsequence comprises 33 to 54 base pairs. 。

6. Assembling overlapping tumor-specific subsequences into longer tumor subsequences (contigs) The method of any one of claims 1 to 5, further comprising:

7. The method of claim 6, wherein the size exclusion column has a cutoff of about 3000 Da. Law.

8. Sequencing of the MAPs may be accomplished by subjecting the isolated MAPs to mass spectrometry (MS) sequencing analysis. The method of any one of claims 1 to 7, comprising:

9. The method generates a personalized normal proteome database using corresponding normal cells. The method of any one of claims 1 to 8, further comprising:

10. The identification in (d) is performed by identifying the MAP by determining whether its sequence is consistent with the normal individualized proteome data.

10. The method of claim 9, further comprising excluding the stubborn ...

11. The method comprises determining whether 24 or 39 RNA sequences from the tumor RNA sequences and RNA sequences from normal cells are identical. Nucleotide k-mer databases were generated to compare tumor k-mer databases and normal Obtaining a k-mer database and comparing the tumor k-mer database and normal k-mers. The mer database was analyzed using 24 or 39 nucleotide kb sequences derived from the MAP coding sequence. and comparing the normal k-mers with the normal k-mer database. The k-mer derived from the MAP coding sequence in the tumor k-mer database overexpression or overexpression of r indicates that the corresponding MAP is a candidate tumor antigen. Item 11. The method according to any one of Items 1 to 10.

12. The k-mers derived from the MAP coding sequence are included in the normal k-mer database. or The method of claim 11 , wherein the gene is over-represented.

13. The k-mers derived from the MAP coding sequence are included in the normal k-mer database.

13. The method of claim 11 or 12, wherein the

14. The method comprises: (a) isolating and sequencing MAPs in a tumor cell sample; (b) performing whole transcriptome sequencing on said tumor cell sample, thereby identifying tumor obtaining a tumor RNA sequence; (c) a tumor-specific proteome database; (i) a set of subsequences comprising at least 33 nucleotides from said tumor RNA sequence; and extracting the (ii) extracting the set of tumor subsequences of (i) from RNA sequences from normal cells; and comparing the resulting sequence to a set of corresponding control subsequences containing at least 33 nucleotides. To do, (iii) the corresponding control subsequence is absent or has few The tumor subsequences that are down-expressed at least four-fold are extracted, thereby forming tumor-specific subsequences. Obtaining a sequence; (iv) computer-translating the tumor-specific subsequence, thereby Obtaining a tumor-specific proteome database; (d) a personalized tumor proteome database; (i) comparing the tumor RNA sequence with a reference genome sequence to identify the Identifying the single nucleotide mutation that (ii) inserting the single base mutation identified in (i) into the reference genome sequence; thereby generating a personalized tumor genome sequence; (iii) coding expressed protein-encoding transcripts from the personalized tumor genomic sequence; and translating the resulting personalized tumor proteome database. and generating by (e) The personalized normal proteome database is (i) comparing an RNA sequence from a normal cell with a reference genome sequence to identify the normal RNA sequence; Identifying a single nucleotide mutation in (ii) inserting the single base mutation identified in (i) into the reference genome sequence; Thus, an individualized normal genome sequence is generated, and (iii) coding for expressed protein-encoding transcripts from the individualized normal genome sequence; and translating the data by computer to obtain the individualized normal proteome database. and generating by (f) normal and tumor k-mer databases are compared with (i) the RNA sequences from normal cells; and a set of subsequences comprising at least 24 nucleotides from the tumor RNA sequence. generating by extracting; (g) The sequence of the MAP obtained in (a) is subjected to the tumor-specific proteome database of (c). database and (d) the sequences of the personalized tumor proteome database; Identifying the MAP; (h) identifying candidate tumor antigens among the MAPs identified in (f); A tumor antigen candidate is one whose sequence is not present in the personalized normal proteome database, or (2) (i) the sequence is present in said personalized tumor proteome database; and / or (ii) the coding sequence is compared to the normal k-mer database to determine whether the tumor k-mer is a MAPs according to claims 1 to 5, which correspond to MAPs that are overexpressed or overrepresented in the database.

14. The method of any one of claims 13.

15. The method further comprises selecting MAPs having a length of 8 to 11 amino acids. The method according to any one of claims 1 to 14.

16. The method according to any one of claims 1 to 15, wherein the normal cells are thymocytes.

17. 17. The method of claim 16, wherein the thymocytes are medullary thymic epithelial cells (mTECs).

18. and comparing the coding sequence of the candidate tumor antigen with a sequence from normal tissue. The method according to any one of claims 1 to 17.

19. 19. Any one of claims 1 to 18, wherein the MAP has a length of 8 to 11 amino acids. The method described below.

20. The method of any one of claims 1 to 19, further comprising evaluating the binding of the tumor antigen candidate to an MHC molecule.

10. The method according to any one of the preceding claims.

21. 21. The method of claim 20, wherein the binding is assessed using an MHC binding prediction algorithm. method.

22. The method further comprises assessing the frequency of T cells that recognize the candidate tumor antigen in the cell population. The method according to any one of claims 1 to 21.

23. The frequency of T cells that recognize the candidate tumor antigens is determined by comparing the candidate tumor antigens with their peptides.

23. The method of claim 22, wherein the method is evaluated using a multimeric MHC class I molecule containing a nucleotide in its binding groove. Law.

24. and evaluating the ability of the candidate tumor antigen to induce T cell activation.

24. The method of any one of 1 to 23.

25. The ability of the tumor antigen candidates to induce T cell activation is determined by their binding to MHC class I molecules. Cytokines are produced by T cells contacted with cells having the tumor antigen candidate bound to the cell surface.

25. The method of claim 24, wherein the activity is assessed by measuring insulin production.

26. The cytokine production comprises interferon-gamma (IFN-γ) production. Item 26. The method according to item 25.

27. The tumor antigen candidates that induce T cell-mediated tumor cell killing and / or inhibit tumor growth. The method of any one of claims 1 to 26, further comprising assessing said ability of a complement. 。

28. A tumor antigen peptide identified by the method defined in any one of claims 1 to 27. Do.

29. comprising one of the amino acid sequences set forth in any one of SEQ ID NOs: 1 to 39, or is a tumor antigen peptide consisting of the same.

30. It contains one of the amino acid sequences shown in any one of SEQ ID NOs: 17 to 39, or 30. The tumor antigen peptide of claim 29, comprising or consisting of:

31. The tumor antigen peptide is a leukemia tumor antigen peptide, and is any one of SEQ ID NOs: 17 to 28.

3. A method for producing a polypeptide comprising: A tumor antigen peptide according to claim 0.

32. 32. The method according to claim 31, wherein the leukemia is B-cell acute lymphoblastic leukemia (B-ALL). Tumor antigen peptides listed.

33. The tumor antigen peptide is a human leukocyte antigen (HLA) of the HLA-A*02:01 allele. A) and an amino acid sequence shown in any one of SEQ ID NOs: 17 to 19, 27, and 28.

33. The tumor of claim 31 or 32, comprising or consisting of one of the following sequences: Antigenic peptides.

34. The tumor antigen peptide is a human leukocyte antigen (HLA) of the HLA-B*40:01 allele. A) and comprising or consisting of the amino acid sequence set forth in SEQ ID NO:

20. The tumor antigen peptide according to claim 31 or 32.

35. The tumor antigen peptide is a human leukocyte antigen (HLA) of the HLA-A*11:01 allele. A) and one of the amino acid sequences set forth in any one of SEQ ID NOs: 21 to 23.

33. The tumor antigen peptide of claim 31 or 32, comprising or consisting of:

36. The tumor antigen peptide is a human leukocyte antigen (HLA) of the HLA-B*08:01 allele. A) and comprises or has the amino acid sequence set forth in SEQ ID NO: 24 or 25. The tumor antigen peptide of claim 31 or 32, comprising:

37. The tumor antigen peptide is a human leukocyte antigen (HLA) of the HLA-B*07:02 allele. A) and comprising or consisting of the amino acid sequence set forth in SEQ ID NO:

26. The tumor antigen peptide according to claim 31 or 32.

38. The tumor antigen peptide is a lung tumor antigen peptide, and is any one of SEQ ID NOs: 29 to 39.

31. The method of claim 30, comprising or consisting of one of the amino acid sequences shown in The described tumor antigen peptide.

39. The tumor antigen peptide of claim 38, wherein the lung tumor is non-small cell lung cancer (NSCLC). Chid.

40. The tumor antigen peptide is a human leukocyte antigen (HLA) of the HLA-A*11:01 allele. A) and one of the amino acid sequences set forth in any one of SEQ ID NOs: 29 to 35.

40. The tumor antigen peptide of claim 38 or 39, comprising or consisting of:

41. The tumor antigen peptide is a human leukocyte antigen (HLA) of the HLA-B*07:02 allele. A) and comprising or consisting of the amino acid sequence set forth in SEQ ID NO:

36. The tumor antigen peptide according to claim 38 or 39.

42. The tumor antigen peptide is a human leukocyte antigen (HLA) of the HLA-A*24:02 allele. A) and comprises or has the amino acid sequence set forth in SEQ ID NO: 38 or 39. The tumor antigen peptide of claim 38 or 39, comprising:

43. The tumor antigen peptide is a human leukocyte antigen (HLA) of the HLA-C*07:01 allele. A) and comprising or consisting of the amino acid sequence set forth in SEQ ID NO:

37. The tumor antigen peptide according to claim 38 or 39.

44. 44. The method according to any one of claims 29 to 43, which is derived from a non-protein-coding region of the genome. The described tumor antigen.

45. The non-protein coding regions of the genome include intergenic regions, intronic regions, 5' non-coding regions, The 5' untranslated region (5'UTR), the 3' untranslated region (3'UTR), or the endogenous retroelement The tumor antigen of claim 44, which is ERE.

46. A nucleic acid encoding the tumor antigen peptide according to any one of claims 28 to 45.

47. 47. The nucleic acid of claim 46, which is an mRNA or a viral vector.

48. A tumor antigen peptide according to any one of claims 28 to 45, or claim 46 or 48. A liposome comprising the nucleic acid according to 47.

49. The tumor antigen peptide according to any one of claims 28 to 45, claim 46 or 47 or the liposome of claim 48, and a pharmaceutically acceptable carrier. A composition comprising:

50. The tumor antigen peptide according to any one of claims 28 to 45, claim 46 or 47 48, or the composition of claim 49, A vaccine comprising adjuvant.

51. A tumor antigen peptide according to any one of claims 28 to 45, which is contained in its peptide-binding groove. , an isolated major histocompatibility complex (MHC) class I molecule.

52. 52. The isolated MHC class I molecule of claim 51 in the form of a multimer.

53. 53. The isolated MHC class I molecule of claim 52, wherein the multimer is a tetramer.

54. An isolated cell comprising the tumor antigen peptide of any one of claims 28 to 45.

55. The tumor antigen peptides according to any one of claims 28 to 45 are combined with their peptide-binding grooves. An isolated antibody expressing on its surface major histocompatibility complex (MHC) class I molecules, including Cells.

56. 56. The cell of claim 55, which is an antigen-presenting cell (APC).

57. The cell of claim 56, wherein the APC is a dendritic cell.

58. An isolated MHC class I molecule according to any one of claims 51 to 53 and / or An MHC class I molecule expressed on the surface of a cell according to any one of claims 54 to 57. T cell receptor (TCR) specifically recognizes

59. An isolated CD8 antigen expressing the TCR of claim 58 on its cell surface. ＋ T lymphocytes 。

60. CD8 as defined in claim 59 ＋ A cell population comprising at least 0.5% T lymphocytes.

61. 46. A method of treating cancer in a subject, comprising administering to said subject an effective amount of (i) (ii) a tumor antigen peptide according to any one of claims 46 and 47; an acid, (iii) a liposome according to claim 48, (iv) a composition according to claim 49, ( (v) a vaccine according to claim 50; (vi) a cell according to any one of claims 54 to 57. (vii) the CD8 cell of claim 59 ＋ (viii) a T lymphocyte; or (viii) claim 60. A method comprising administering the cell population described in claim 1.

62. 62. The method of claim 61, wherein the cancer is leukemia.

63. 63. The method according to claim 62, wherein the leukemia is B-cell acute lymphoblastic leukemia (B-ALL). How to post.

64. 62. The method of claim 61, wherein the cancer is lung cancer.

65. 65. The method of claim 64, wherein the lung tumor is non-small cell lung cancer (NSCLC).

66. further comprising administering to said subject at least one additional anti-tumor agent or therapy.

66. The method of any one of claims 61 to 65.

67. The at least one additional anti-tumor agent or therapy may be a chemotherapeutic agent, an immunotherapy, an immune therapy, or a combination thereof.

67. The method of claim 66, wherein the treatment is a checkpoint inhibitor, radiation therapy, or surgery.

68. (i) a tumor inhibitor according to any one of claims 28 to 45 for treating cancer in a subject (ii) a tumor antigen peptide; (ii) a nucleic acid according to claim 46 or 47; (iii) a nucleic acid according to claim 48 (iv) the composition of claim 49; (v) the liposome of claim 50; (vi) the cell according to any one of claims 54 to 57; (vii) claim 59 CD8 described in ＋ (viii) the use of a cell population according to claim 60. 。

69. (i) for the manufacture of a medicament for treating cancer in a subject; Any of claims 28 to 45 (ii) a tumor antigen peptide according to any one of claims 46 and 47; (iii) a nucleic acid according to claim 46 or 47; iii) (iv) the liposome of claim 48; (v) the composition of claim 49; (vi) a vaccine according to claim 50; (vi) a cell according to any one of claims 54 to 57; (vi) vii) CD8 according to claim 59 ＋ (viii) a T lymphocyte; or (viii) the antibody of claim 60. Use of cell populations.

70. 70. The use of claim 68 or 69, wherein the cancer is leukemia.

71. 71. The method according to claim 70, wherein the leukemia is B-cell acute lymphoblastic leukemia (B-ALL). Use of the above.

72. 70. The use of claim 68 or 69, wherein the cancer is lung cancer.

73. 73. The use of claim 72, wherein the lung tumor is non-small cell lung cancer (NSCLC).

74. 74. The method of claim 68, further comprising the use of at least one additional anti-tumor agent or therapy.

10. The use according to any one of claims 1 to 9.

75. The at least one additional anti-tumor agent or therapy may be a chemotherapeutic agent, an immunotherapy, an immune therapy, or a combination thereof.

75. The use of claim 74, wherein the treatment is a checkpoint inhibitor, radiation therapy, or surgery.

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