Identification of common tumor-specific T cell receptors and antigens

Abstract

The present invention relates to methods for identifying tumor-specific T cell receptors (TCRs) and their corresponding antigens common to patients, and further relates to these TCR sequences, nucleic acids encoding the TCRs, and T cells comprising the TCRs and / or the encoding nucleic acids.

Description

[Technical field]

[0001] The present invention relates to methods for identifying tumor-specific T cell receptors (TCRs) and their corresponding antigens common to patients, and further relates to these TCR sequences, nucleic acids encoding the TCRs, and T cells comprising the TCRs and / or the encoding nucleic acids. [Background technology]

[0002] Since it has been shown that the immune system has the ability to fight and reject tumors, great efforts have been made to develop cancer therapeutic or preventive vaccines. Such efforts have faced a difficult challenge in antigen discovery. A tumor antigen suitable for vaccination must have three basic requirements: it must be immunogenic to elicit an effective therapeutic response; it must be tumor specific to allow safe treatment, especially in a preventive setting; however, cross-reactivity with pathogen-associated antigens is within the scope of the present invention; and finally, it is necessary to identify common antigens expressed in many patients' tumors.

[0003] In the past decade, two high-throughput platforms have been developed and widely used for tumor antigen discovery. However, both are only qualified to a limited extent. It is clear that whole-exome sequencing approaches can identify tumor-specific mutant antigens. However, apart from certain recurrent driver mutations, the majority of identified mutant-reactive antigens are patient-specific. On the other hand, mass spectrometry-based approaches can detect HLA-presented peptides common to tumors from different patients. However, proving the immunogenicity and tumor specificity of these peptides remains a challenging task.

[0004] Adoptive cell therapy (ACT) using T cells genetically engineered to express tumor-reactive chimeric antigen receptors (CAR-T cells) or T cell receptors (TCRs) is a promising treatment strategy for cancer patients. In contrast to hematological malignancies, where CAR-T cells against certain lineage-specific cell surface antigens have been approved due to their high efficacy with manageable side effects, in solid tumors, the application of CAR-T cells is (currently) not feasible due to the lack of cell surface target antigens exclusively expressed in tumors. (Patient) T cells genetically engineered to express tumor-specific genetically engineered TCRs (tsTCRtg-T cells) that recognize peptides of tumor-associated or tumor-specific antigens (TAA or TSA) presented by HLA molecules (pMHC) represent an attractive alternative. Although TAAs (e.g., cancer / germline antigens, differentiation antigens, overexpressed antigens, etc.) and viral (v)TSAs (in tumors with viral etiology) are widely shared between tumors, resulting in the presentation of common pMHC in HLA-matched patients, the majority of (non-viral)TSAs (neoantigens) are unique to each individual cancer. The resulting wide variety of pMHC must be considered as private antigens for each individual subject. However, in a few cases, TSAs resulting from point mutations or chromosomal translocations affecting common driver genes of malignancies and shared between tumors have been shown to be immunogenic (e.g., RAS mutations, TP53 mutations, BRAF mutations, PIK3CA mutations, and translocations involving ALK, ROS, NTRK, RET, etc.). Also, antigen categories that are so far less well defined, such as tumor-specific cryptic antigens ("dark matter") or aberrantly spliced ​​transcripts, may be shared between tumors and recognized by T cells.

[0005] Previously, we developed a method to identify tumor-specific T cell receptors by comparing CDR3 sequences obtained from TILs with T cells from adjacent tissues (WO2017 / 025564A1). Thus, it is possible to distinguish tumor specificity by the increased abundance of T cell clones in tumors and non-tumors of a patient. However, most tumor-specific antigens arise by mutations that are restricted to individual patients. While private neo-antigens can be targeted for personalized tsTCRtg-T cell therapy, shared TAAs or TSAs are ideal targets for commercial tsTCRtg-T cell therapy in patients with matched expression of HLA alleles. Personalized therapy is time-consuming, costly, and subject to strict FDA and EMA regulations (ATMP, Advanced Medicine; Gene Therapy Medicine). Moreover, many patients' disease progresses faster than personalized therapeutics can be produced. Therefore, it would be highly beneficial to develop methods to identify carriers of such common tumor-specific TCRs by scanning the TIL-repertoire for identical or highly similar antigen recognition domains (CDR3α and β), thus providing ready-made therapeutic receptors and at the same time providing the opportunity to identify shared tumor-specific antigens for new therapeutic options. Summary of the Invention [Problem to be solved by the invention]

[0006] Based on the above state of the art, the object of the present invention is to provide means and methods for identifying common tumor-specific TCR sequences and their corresponding antigens. This object is achieved by the subject matter of the independent claims herein, with further advantageous embodiments described in the dependent claims herein, in the examples, in the figures and in the general description. [Means for solving the problem]

[0007] Summary of the Invention Instead of starting with antigen candidates that require crucial validation with specificity and functionality tests, an alternative approach is to analyze the T cell repertoires of tumors from different cancer patients and search for specific effects derived from common tumor antigens. When T cells infiltrate the tumor and cause interaction with tumor antigens via specific receptors, this encounter is followed by activation, proliferation and enrichment of clones within the tumor. Thus, the preferred localization of this unique TCR clonotype, quantitatively determined by the ratio of TCR clonotype frequencies between tumor and adjacent non-tumor tissue, is a predictor of tumor specificity. This technique is described in WO2017 / 025564A1. If such unique tumor-specific TCR clonotypes, or structurally closely related TCR clonotypes, called TCR clusters, are detected in tumors of other patients, this indicates the presence of shared tumor antigens in these patients. This is particularly useful when TCR clusters are detected in HLA-matched patients, revealing the nature of the HLA alleles that present the shared antigen epitopes. As a final step, complete elucidation of clustered TCRs, for example by single-cell techniques, will yield α / β-TCRs with specificity for a shared antigen.

[0008] Such HLA-restricted α / β-TCRs with specificity for shared tumor antigens are the starting point for important applications.

[0009] As unprecedented novel tools, they can guide the targeted discovery of shared tumor antigens as specific probes in antigen discovery.

[0010] As "off the shelf" TCRs in vector format, these can be used to transduce autologous T cells of cancer patients for immunotherapeutic intervention in HLA-matched patients who are carriers of cluster TCRs or carriers of known shared tumor antigens.

[0011] Novel genetic engineering techniques (CRISPR / Cas9, TALEN, zinc finger nucleases) are increasingly enabling the production of allogeneic cell therapy preparations from healthy donors that are more readily available and more numerous than most patients, allowing one preparation to be used to treat multiple patients, since tsTCRtg-T cells (autologous and allogeneic) can be engineered to be less immunogenic (e.g., by knocking out endogenous HLA in an allogeneic setting), less susceptible to exhaustion / dysfunction (e.g., by knocking out checkpoint receptors), and less susceptible to graft-versus-host disease (GvHD) or unpredictable cross-reactivity by knocking out endogenous TCRs.

[0012] In addition to transducing conventional autologous or allogeneic CD4+ and CD8+ T cells with α / β-tsTCR, it is also an option to transduce additional types of adaptive or innate immune cells, such as γδ-T cells, NKT cells, and NK cells, that carry the receptor. The above genetic engineering techniques allow the co-transduction of NK cells that carry the tsTCR and the CD3 signaling domain required for cell activation upon engagement of the TCR with pMHC.

[0013] It would therefore be highly advantageous to find T cell receptors and / or shared tumor antigens common to multiple individuals.

[0014] Thus, there is a need to identify shared tumor-specific antigens and / or shared tumor-specific T cell receptors that would enable existing therapies against cancer, provided the patient's HLA is known to be a match.

[0015] To achieve this goal, it is necessary to develop methods to identify such shared tumor-specific TCRs and, concomitantly, to identify shared tumor-specific antigens.

[0016] A first aspect of the present invention relates to a method for identifying common tumor-specific T cell receptors (TCRs).

[0017] A second aspect of the invention relates to a method for identifying common tumor-specific antigens.

[0018] A third aspect of the invention relates to an isolated TCR identified by a method according to the first aspect.

[0019] A fourth aspect of the invention relates to a nucleic acid sequence encoding a TCR according to the third aspect.

[0020] A fifth aspect of the invention relates to an isolated autologous T cell comprising a TCR according to the third aspect and / or a nucleic acid sequence according to the fourth aspect.

[0021] A sixth aspect of the invention relates to a TCR according to the third aspect, a nucleic acid sequence according to the fourth aspect or an isolated autologous T cell according to the fifth aspect for use in the treatment of cancer. [Brief description of the drawings]

[0022] [Figure 1] Figure 1 is a schematic diagram of the tsTCR footprint table. From left to right, the tumor-specific TCR footprint table includes the following elements for each TCR clonotype: CDR3β amino acid sequence, CDR3α amino acid sequence, CDR3β sequence frequency (%), β chain V fragment ID, β chain J fragment ID, α chain V fragment ID, α chain J fragment ID, 4-digit HLA type (class I or II), set of marker genes in multiple columns with their respective expression rates for each clonotype. [Diagram 2] Figure 2 is a schematic diagram of TCR clustering (part I). These are steps in the analysis of TCR repertoires in tumors and non-tumors, which are finally condensed into a tumor-specific TCR footprint table. [Diagram 3]Figure 3 is a schematic diagram of TCR clustering (part II). For two, three or more different patients, one table represents TCR clusters with closely related TCRs. Columns 1-13 and NN are described below. 1: arbitrary patient ID. 2-3: amino acid sequences of both CDR3 chains. 4: ratio between TCR clonotype frequencies in tumor and adjacent non-tumor tissue. 5: frequency of each TCR in tumor. 6-9: V / J fragments of both chains. 10: HLA type (I / II) in 4 digits. 11-13: frequency of each T cell activation marker. These are measured by single cell sequencing gene expression techniques or, in some cases, cell sorting techniques, and each clonotype frequency is derived from TCR sequencing data. NN: any marker of T cell activation could be used as well. [Figure 4] FIG. 4 shows that CD8+ T cells from healthy donors were depleted of their endogenous TCR by CRISPR / CAS9-mediated knockout and transduced with TCR from cluster 0 clonotype. The transformed TCR-T cells were then tested against seven NSCLC cell lines by IFN-γ-Elispot assay (not shown). Of the three NSCLC lines expressing the cluster 0-associated MHC allele HLA-B*08:01, only NCI-H1703 was recognized by the TCR-T cells. In addition to NCI-H1703 cells, the TCR-T cells also recognized HLA-B*08:01-transduced K562 cells (but not HLA-free wild-type K562 cells) and HLA-B*08:01-expressing lymphoblastoid cell lines (LCLs) (not shown). Reactivity against NSCLC cells could be blocked with a pan-HLA-specific antibody, indicating peptide-MHC restricted reactivity (not shown). [Diagram 5]Figure 5 shows that CD8+ T cells from healthy donors were depleted of their endogenous TCR by CRISPR / CAS9-mediated knockout and transduced with TCR from cluster 2 clonotype. TCR-transduced (TCR-) T cells were tested against five HLA-A*02:01 positive NSCLC cell lines by IFN-γ-Elispot assay. All TCR-T cells recognized MZ-LC-16, NCI-H1703 and NCI-H1792 above background reactivity (TCR-T cells only, dotted lines). TCR-ID2.1-transduced TCR-T cells also showed a slight response to MOR / CPR. Further testing of TCR-T cell cross-reactivity revealed that HLA-A*02:01-transduced K562 cells (but not wild-type K562 cells) and HLA-A*02:01 positive T2 cells were also recognized (not shown). Reactivity against NSCLC cells could be blocked with an HLA-A02-specific antibody, indicating peptide-MHC restricted reactivity (not shown). DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0023] Terms and Definitions For the purposes of interpreting this specification, the following definitions shall apply, and where appropriate, terms used in the singular shall include the plural and vice versa. In the event that a definition set forth below conflicts with any document incorporated herein by reference, the definition set forth herein shall control.

[0024] As used herein, the terms "comprising," "having," "containing," "including," and other similar forms and their grammatical equivalents are intended to be equivalent in meaning and to be open-ended in that the item or items following any one of these words are not intended to be an exhaustive list of such item or items or are not limited to only the listed item or items. For example, an item "comprising" components A, B, and C can consist of components A, B, and C (i.e., contain only components A, B, and C), or can include not only components A, B, and C, but also one or more other components. Thus, "comprising" and similar forms and their grammatical equivalents are intended and understood to include disclosure of embodiments that "consist essentially of" or "consist of."

[0025] Where a range of values ​​is provided, unless the context clearly dictates otherwise, it is understood that each intervening value, to the tenth of the unit of the lower limit, between the upper and lower limit of that range, and any other stated or intervening value within that stated range, is encompassed within the disclosure, subject to any specifically excluded limit in the stated range. Where one or both of the limits are included in the stated range, ranges excluding either or both of those included limits are also included in the disclosure.

[0026] As used herein, reference to "about" a value or parameter includes (and describes) the variation directed to the value or parameter itself. For example, a statement referring to "about X" also includes the statement "X."

[0027] As used in this specification, including the appended claims, the singular forms "a," "or," and "the" include plural references unless the context clearly dictates otherwise.

[0028] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art (e.g., cell culture, molecular genetics, nucleic acid chemistry, hybridization techniques, and biochemistry). Standard techniques are used for molecular, genetic, and biochemical techniques (see generally Sambrook et al., Molecular Cloning: A Laboratory Manual, 4th ed. (2012) Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY, and Ausubel et al., Short Protocols in Molecular Biology (2002) 5th ed., John Wiley & Sons, Inc.) and chemical techniques.

[0029] array Sequences similar or homologous (e.g., at least about 70% sequence identity) to the sequences disclosed herein are also part of the present invention. In some embodiments, sequence identity at the amino acid level can be about 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or more than 99%. At the nucleic acid level, sequence identity can be about 70%, 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or more than 99%. Alternatively, substantial identity exists when a nucleic acid segment hybridizes under selective hybridization conditions (e.g., under very high stringency hybridization conditions) to the complement of the strand. The nucleic acids may be present in whole cells, in a cell lysate, or in a partially purified or substantially pure form.

[0030] In the present context, the terms "sequence identity" and "percentage of sequence identity" refer to a quantitative parameter that represents the result of sequence comparison, which is determined by comparing two aligned sequences position by position. Methods for aligning sequences for comparison are well known in the art. Aligning sequences for comparison can be performed by Smith and Waterman's local homology algorithm, Adv. Appl. Math. 2: 482 (1981), Needleman and Wunsch's global alignment algorithm, J. Mol. Biol. 48: 443 (1970), Pearson and Lipman's similarity search method, Proc. Nat. Acad. Sci. 85: 2444 (1988), or computerized implementations of these algorithms, including but not limited to CLUSTAL, GAP, BESTFIT, BLAST, FASTA, and TFASTA. Software for performing BLAST analysis is publicly available from the National Center for Biotechnology Information (http: / / blast.ncbi.nlm.nih.gov / ) and other sources.

[0031] An example of an amino acid sequence comparison is the BLASTP algorithm using default settings: Expect threshold: 10; Word size: 3; Max matches in a query range: 0; Matrix: BLOSUM62; Gap Costs: Existence 11, Extension 1; Compositional adjustments: Conditional compositional score matrix adjustment. One such example for nucleic acid sequence comparison is the BLASTN algorithm using default settings: Expect threshold: 10; Word size: 28; Max matches in a query range: 0; Match / Mismatch Scores: 1.-2; Gap costs: Linear. Unless otherwise indicated, sequence identity values ​​provided herein refer to values ​​obtained using the BLAST family of programs using the default parameters specified above for protein and nucleic acid comparisons, respectively (Altschul, J. Mol. Biol. 215: 403-410 (1990)).

[0032] Reference to identical sequences without specifying a percentage includes the meaning of 100% identical sequences (ie, the same sequence).

[0033] General biochemistry: peptides, amino acid sequences The term "polypeptide" in the context of this specification refers to a molecule consisting of 50 or more amino acids forming a linear chain in which the amino acids are connected by peptide bonds. The amino acid sequence of a polypeptide may represent the amino acid sequence of an entire protein (as found physiologically) or a fragment thereof. The terms "polypeptide" and "protein" are used interchangeably herein and include proteins and fragments thereof. Polypeptides are disclosed herein as amino acid residue sequences.

[0034] The term "peptide" in the present context relates to a molecule consisting of up to 50 amino acids, in particular of 8 to 30 amino acids, more in particular of 8 to 15 amino acids, which form a linear chain, the amino acids being connected by peptide bonds.

[0035] The sequence of amino acid residues is written from the amino terminus to the carboxyl terminus. The capital letters at the sequence positions refer to the L-amino acids in one-letter code (Stryer, Biochemistry, vol. 3, p. 21). The lower case letters indicating the positions in the amino acid sequence refer to the corresponding D- or (2R)-amino acids. The sequence is written from left to right from the amino terminus to the carboxyl terminus. In accordance with standard nomenclature, the sequence of amino acid residues is represented by either the three-letter or one-letter code as follows: Alanine (Ala, A), Arginine (Arg, R), Asparagine (Asn, N), Aspartic Acid (Asp, D), Cysteine ​​(Cys, C), Glutamine (Gln, Q), Glutamic Acid (Glu, E), Glycine (Gly, G), Histidine (His, H), Isoleucine (Ile, I), Leucine (Leu, L), Lysine (Lys, K), Methionine (Met, M), Phenylalanine (Phe, F), Proline (Pro, P), Serine (Ser, S), Threonine (Thr, T), Tryptophan (Trp, W), Tyrosine (Tyr, Y) and Valine (Val, V).

[0036] General molecular biology: nucleic acid sequence, expression The term "gene" refers to a polynucleotide that contains at least one open reading frame (ORF) that can encode a particular polypeptide or protein after being transcribed and translated. A polynucleotide sequence can be used to identify larger fragments or full-length coding sequences of the gene with which it is associated. Methods for isolating larger fragment sequences are known to those of skill in the art.

[0037] The term "gene expression" or "expression" or the term "gene product" may refer to either or both of the process of production of nucleic acids (RNA) or production of peptides or polypeptides - and their products - also called transcription and translation, respectively, or any of the intermediate processes that regulate the processing of genetic information to result in a polypeptide product. The term "gene expression" may also apply to the transcription and processing of RNA gene products, e.g., regulatory RNA or structural (e.g., ribosomal) RNA. When the expressed polynucleotide is derived from genomic DNA, expression can include splicing of mRNA in eukaryotic cells. Expression can be assessed at both the level of transcription and translation, i.e., mRNA and / or protein product.

[0038] The term "nucleotide" in the present context refers to a building block of a nucleic acid or a nucleic acid analog, which oligomer is capable of forming selective hybrids with an RNA or DNA oligomer based on base pairing. The term "nucleotide" in this context includes the building blocks of classical ribonucleotides adenosine, guanosine, uridine (and ribosylthymine), cytidine, and the building blocks of classical deoxyribonucleotides deoxyadenosine, deoxyguanosine, thymidine, deoxyuridine, and deoxycytidine. It also includes analogs of nucleic acids, such as phosphothioates, 2'O-methylphosphothioates, peptide nucleic acids (PNA; N-(2-aminoethyl)-glycine units linked by peptide bonds with the nucleic acid base attached to the alpha carbon of glycine) or locked nucleic acids (LNA; 2'O,4'C methylene bridged RNA building blocks). When referring to a "hybridization sequence" in the present specification, such a hybridization sequence may be composed of any of the above nucleotides, or a mixture thereof.

[0039] T cell biology The term "CDR3" in the present context refers to the hypervariable complementarity determining region 3. The size of a CDR3 is specifically characterized by the total number of amino acids (AA) and respective nucleotides from the conserved cysteine ​​in a Vβ, or Vα, or Vγ, or Vδ segment to the conserved phenylalanine position in a Jβ, or Jα, Jγ, or Jδ segment.

[0040] The term "T cell activation / exhaustion / differentiation marker" in the context of this specification refers to a molecule on a T cell, in particular a molecule on the surface of a T cell, that is indicative of T cell activation, exhaustion or differentiation.

[0041] (Cancer) Immunotherapy In the context of this specification, the terms "cancer immunotherapy", "biological therapy" or "immunomodulatory therapy" are meant to encompass types of cancer treatments that are useful for the immune system to fight cancer. Non-limiting examples of cancer immunotherapy include immune checkpoint inhibitors and agonists, T cell transfer therapy, cytokines and their recombinant derivatives, adjuvants, and vaccination with small molecules or cells.

[0042] The term "tumor sample" in the present context refers to a sample or pool of samples obtained from a patient's tumor. A tumor can also include a metastasis or a collection of metastases.

[0043] The term "non-tumor sample" in the context of this specification refers to a sample or pool of samples obtained from tissue adjacent to a patient's tumor.

[0044] The term "tumor-specific" in the present context specifically refers to T cells that arise in and exhibit a preferential distribution in a particular tumor.

[0045] The term "HLA" in the context of the present invention refers to human leukocyte antigens as a specific subset of the general term major histocompatibility complex (MHC).

[0046] HLA supertypes are defined based on grouping together MHC alleles that share similar binding specificities, i.e. peptides that have identical or similar so-called anchor amino acid residues (e.g. positions 2 and 9 or 10 for 9-mer and 10-mer peptides). HLA supertypes are further described in Sidney et al. (BMC Immunology 2008, 9:1).

[0047] The term "single-cell sequencing" in the context of this specification refers to a method that can identify multiple coding elements of a single cell. This includes sequencing of genomic elements such as nuclear or organ DNA, their transcripts, or a combination of both. Typically, the coding elements of a single cell are physically, spatially, or linked by cell-specific barcodes, allowing the elements to be correctly assigned to the cell after sequencing. In particular, single-cell RNA sequencing (scRNA-seq) is used to identify expression patterns and / or variable sequences of immune receptors. More particularly, the scRNA-seq method can identify the mRNAs of at least 1000 cells in parallel by droplet-based sorting, such as 10Xgenomics chromium technology. Other options for characterizing cellular expression patterns and / or TCR sequences are methods that can correlate this information with spatial distribution in samples such as FFPE (formalin fixed paraffin embedded), such as GeoMxTM or CosMxTM by NanoString Technologies, or Visium Spatial Gene Expression by 10XGenomics, or ZipSeq (WO2019 / 226631A1).

[0048] The term "correlation sequencing" in the context of this specification refers to a method that allows statistical correlation of multiple coding elements of a single cell. This can be achieved by pooling samples that contain T cells or pools of T cells and identifying the transcripts in said pool by sequencing. Those pools that contain combinations of two or more transcripts are likely to contain a common clonotype, and this combination can be assigned by statistical occurrence. Most preferred is the sequencing and correlation of the combination of TCR chains of clonotypes.

[0049] Clustering Clustering of T cell receptor (TCR) sequences described in the literature (CDHIT (Limin Fu et al. 2012 Dec 1;28(23):3150-2), iSMART (Hongyi Zhang et al. Clin Cancer Res. 2020 Mar 15;26(6):1359-1371), GLIPH (Jacob Glanville et al. Nature. 2017 Jul 6;547(7661):94-98.)) is usually performed on one of the two TCR chains alone. In the case of alpha / beta T cells, it is almost always the beta chain. Another prerequisite for the published TCR clustering approaches is the knowledge of the respective antigen peptide recognized by the TCR via the MHC molecule. In the case of known viral antigen epitopes, these were used as training sets for the optimization of clustering algorithms (GLIPH, iSmart), but in the case of cancer-specific antigen peptides, this is not possible due to the lack of known tumor-associated antigens.

[0050] The TCRpolyClust method uses a different approach. From the beginning, the clustering algorithm operates on TCRs with unknown antigenic peptides but experimentally measured scores that are tumor-specific in different patients. Furthermore, the algorithm explicitly utilizes both chains of the TCR and employs a multidimensional scoring that ranks TCR clusters between patients by HLA type overlap and expression of various activation / exhaustion / differentiation markers.

[0051] Schematic explanation of TCRpolyClust The basic method for providing tumor-specific TCRs (tsTCRs) for each individual patient is disclosed in WO2017 / 025564A1: by quantitative next generation sequencing (NGS) of the CDR3 region of T cells taken from tumor tissue and, at the same time, from healthy adjacent tissue, tsTCRs are identified with a frequency that is clearly enriched in tumor compared to non-tumor tissue: the tumor specificity ratio is the ratio of clonotype frequencies in tumor tissue and non-tumor tissue. The method introduced here to characterize tsTCRs for each individual patient comprises the following additional steps:

[0052] 1) Simultaneous identification of the beta and alpha chains of each tsTCR, preferably by correlated sequencing, more preferably by single-cell VDJ sequencing, preferably using 10XGenomics chromium technology. As a result, each tsTCR clonotype is composed of one beta chain and one or two alpha chain sequences covering the entire CDR3 region and the adjacent V and J segments. Based on this information, the TCR can be fully synthesized.

[0053] 2) Identifying multiple activation / exhaustion / differentiation markers simultaneously by single cell gene expression analysis, preferably using 10XGenomics chromium technology. Based on deep sequencing approaches of TILs and single cell sequencing projects, it has been shown that chronic antigen exposure during cancer progression generates tonic TCR signals that promote T cell exhaustion and suppress T cell effector function. Exhausted / dysfunctional T cells are "marked" with certain receptors. Including exhaustion / activation markers in the analysis allows differentiation between bystander and tumor-specific clonotypes. Well-known activation / exhaustion markers for CD4+ and CD8+ effector T cells are PD1, TIGIT, LAG3, TIM3, CTLA4, CD40, CD137 (4-1BB), CD69, or other genes that are significantly expressed in T cells upon activation by the respective antigens. With regard to CD4+ T cells, additional markers are very useful to distinguish between tumor-reactive Th1 and Tfh cells and immunosuppressive Th2, Treg and Th17 cells, which play a controversial role in the context of tumor development. Antitumor Th1 and Tfh cells are characterized by the expression of effector functions such as IFN-γ, TNF-α, GZMB, PRF, whereas Th2 cells express IL-4, IL-5, Th17 cells IL-17A, Tregs immunosuppressive cytokines TGF-β and IL-10, etc. Furthermore, T cell subtypes and / or differentiation states can be distinguished based on the expression of certain transcription factors, such as FOXP3 for Tregs, TBX21 (TBET), EOMES for effector T cells, RUNX3 for cytotoxic cells, TOX (an exhausted subpopulation of T cells that maintains proliferation and functionality), etc.

[0054] 3) HLA genotyping up to four orders of resolution is usually performed by analyzing a patient's blood sample using standard methods. Combined with the HLA type, all this information builds up a footprint of the tsTCR repertoire for each patient. The single steps for constructing the tsTCR footprint are shown in a flow diagram in Figure 2. The tsTCR footprints of a large number of patients form the basis of the TCRpolyClust method described below. Its overview is shown in Figure 3.

[0055] 4) Comparing a set of different tumor patients via sequence similarity of TCR CDR3 sequences. The algorithm works in two rounds: in the first round, it generates a number of seed clusters found by grouping all paired TCRs (treating alpha and beta chains as one sequence) with a Levenshtein distance of at most 3 (3 mismatches per chain), particularly at most 2, more particularly at most 1, and most particularly 0 in their respective beta and alpha chains. Several algorithms are available for efficiently comparing the pairwise sequences of thousands of TCRs, e.g., CDHIT, iSMART, BLASTP, etc. Once the seed clustering is completed, a consensus sequence covering the amino acid sequence of the beta-CDR3 is calculated. In the second round, all consensus sequences from the first round are subjected to clustering with similar parameters as in the first round.

[0056] 5) The minimum size of inter-patient clusters is 2, i.e., a cluster must contain alpha-beta vs. TCR from at least two different patients. Furthermore, the median tumor specificity ratio (i.e., the ratio between clonotype frequencies in tumors compared to non-tumor tissues) must be >2 (ideally >3, most preferably >5) and the median TCR-beta clonotype frequency in tumor tissues must be at least >0.005% (particularly >0.01%, more particularly >0.05%, most particularly >0.1%).

[0057] 6) TCR antigen specificity strictly depends on the patient's HLA genotype. Therefore, a prerequisite for a cluster between patients to be valid is a significant overlap of HLA types within a cluster. At least one HLA type (A, B or C) should be present in more than 50% (more preferably more than 60%, most preferably more than 80%) of all patients included in the cluster. In case of linkage disequilibrium, this also applies to HLA pairs up to the complete haplotype.

[0058] 7) Using single-cell RNA sequencing technology (e.g., 10XGenomics), both chains of the TCR of specialized T cells are identified, and gene expression profiles are measured by scRNAseq in the same step. The above-mentioned series of activation / exhaustion markers (e.g., PD1, CTLA4, TIGIT, LAG3, TIM3, etc.), transcription factors (e.g., FOXP3, RUNX3, EOMES, TBET, TOX, etc.), and effector functions (IFN-γ, TNF-α, IL-10, IL17, etc.) can be measured for expression frequency, thereby scoring each single T cell for the presence of a series of markers or combinations of markers. At least one marker must be found in 50% or more (more preferably 60% or more) of all patients found in the cluster.

[0059] A "shared T cell receptor" in the context of this specification relates to a T cell receptor (TCR) that is not present in only one patient, but is found in several different patients. Since the shared TCR is shared between patients, it is sometimes called a shared TCR. This shared TCR has the same or very similar CDR3 region between patients, so it is highly likely that the shared TCR will recognize the same antigen. If the shared TCR is HLA-dependent, it is highly likely that the same or nearly identical peptides bound to the MHC molecule in different patients will recognize the same MHC molecule. This peptide bound to the MHC molecule shared between patients is therefore a common antigen.

[0060] That all tested patients share (have at least one HLA gene in common) can be determined in another step of the method.

[0061] The term "common antigen" in the present context relates to an entity recognized by a common TCR. In a particular embodiment, this common antigen is a complex comprising an MHC molecule and a peptide bound to the MHC molecule.

[0062] The term "essentially identical" in the present context relates to nucleic acid sequences which are identical or have at least 95%, particularly at least 97%, more particularly at least 98%, more particularly at least 99%, and most particularly more than 99% identity.

[0063] The term "cross-reactive TCR" in the present context relates to an alpha / beta TCR that recognizes multiple defined peptide sequences presented on MHC molecules. Preferably, the recognized antigenic peptides are derived from substantially different polypeptide precursors, differing by at least one amino acid, more preferably two amino acids.

[0064] The term "frequency" in the context of this specification relates to the relative abundance of a particular sequence among a plurality of sequences. To determine the frequency of a sequence, essentially identical sequences are counted and this number is divided by the total number of sequences observed.

[0065] The term "same tissue type" in the context of this specification relates to tissue samples derived from the same tissue. For example, the tissue type of a metastasis is the tissue from which the metastatic cells originate, not the tissue in which the metastasis is found in the body.

[0066] The term "genes of the same HLA type" in the present context relates to HLA genes that code for MHC molecules. Same HLA type in the present context means that the HLA genes code for the same variants of MHC molecules. Due to the large variety of HLA genes present in the human population, in one embodiment of the method of the present invention, the HLA repertoire of the tested patients is determined and patients sharing at least one gene of the same HLA type are selected for further analysis.

[0067] The term expressing a sequence in an antigen-presenting cell is understood as follows: An antigen-presenting cell (APC) is transfected or transduced with a nucleic acid sequence encoding a peptide or protein. The nucleic acid sequence is present in an expression vector suitable for transfection or transduction of mammalian cells. When the nucleic acid sequence is introduced into the APC, the APC expresses the encoded peptide or protein. In a particular embodiment, the peptide is presented on the HLA molecule on the cell surface of the APC. In a particular embodiment, one or several peptides produced from a protein are presented on the HLA molecule on the cell surface of the APC. The expression of a recombinant antigen to be presented on an HLA class I molecule is a well-established procedure that can be achieved by transfecting an APC expressing said class I molecule with a nucleic acid encoding said antigen. In a particular embodiment, to efficiently present a recombinant antigen on an HLA class II molecule, each APC must express said class II molecule and undergo non-canonical autophagy. In particular, unorthodox macroautophagy is known to reroute intracellularly expressed antigens for processing to be presented on HLA class II molecules (Munz, Mol Aspects Med. 2021 Jun 16;100987).

[0068] "T cell activation" in the context of this specification refers to the state of T cells in which certain activation markers are expressed. T cells are specifically activated by the interaction of their TCR with a matching MHC that presents a certain peptide. Activation can be measured, for example, by T cell IFN-γ secretion.

[0069] The term "tumor cell line" in the context of this specification relates to a cell line derived from cancer tissue. Many tumor cell lines are known in the art (Gandhi et al., Nature. 2019 May; 569(7757):503-508.).

[0070] A "polymer" of a given set of monomers is a homopolymer (composed of more than one of the same monomer), and a copolymer of a given selection of monomers is a heteropolymer, composed of monomers from at least two sets of monomers.

[0071] As used herein, the term "pharmaceutical composition" refers to a compound of the present invention or a pharma- ceutically acceptable salt thereof, together with at least one pharma- ceutically acceptable carrier. In certain embodiments, the pharmaceutical composition of the present invention is provided in a form suitable for topical, parenteral, or injectable administration.

[0072] As used herein, the term "pharmaceutically acceptable carrier" includes any solvents, dispersion media, coatings, surfactants, antioxidants, preservatives (e.g., antibacterial agents, antifungal agents), isotonic agents, absorption delaying agents, salts, preservatives, drugs, drug stabilizers, binders, excipients, disintegrants, lubricants, sweeteners, flavorings, dyes, and the like, and combinations thereof, as known to those skilled in the art (see, e.g., Remington: the Science and Practice of Pharmacy, ISBN0857110624).

[0073] As used herein, the term "treating" or "treatment" of any disease or disorder (e.g., cancer) refers, in one embodiment, to alleviating the disease or disorder (e.g., delaying, preventing, or reducing the onset of the disease or at least one of its clinical symptoms). In another embodiment, "treating" or "treatment" refers to alleviating or improving at least one physical parameter, including one that may not be discernible to the patient. In yet another embodiment, "treating" or "treatment" refers to modulating the disease or disorder, either physically (e.g., stabilization of a discernible symptom), physiologically (e.g., stabilization of a physical parameter), or both. Methods for assessing the treatment and / or prevention of a disease are generally known in the art, unless otherwise described herein below.

[0074] Detailed Description of the Invention A first aspect of the present invention relates to a method for identifying common tumor-specific T cell receptors (TCRs).

[0075] The method comprises the steps of: a. Obtaining multiple tumor-specific TCR sequences from each of n patients (n>1) by the following steps: i. determining the frequency of each of a plurality of tumor TCR sequences in a step based on the tumor sequence; ii. determining the frequency of each of the plurality of non-tumor TCR sequences in the step based on the non-tumor sequences; iii. in the tumor-specific selection step, if for any particular TCR sequence, the frequency of the tumor TCR within the plurality of tumor TCR nucleic acid sequences is higher than the frequency of the non-tumor TCR within the plurality of non-tumor TCR nucleic acid sequences, selecting the TCR nucleic acid sequence as a tumor-specific TCR sequence; b. Selecting a common tumor-specific TCR sequence by the steps of: i. translating the tumor-specific TCR nucleic acid sequence into a tumor-specific TCR amino acid sequence for a plurality of n patients; ii. determining the CDR3 region of said tumor-specific TCR amino acid sequence to obtain a tumor-specific CDR3 sequence for each of said n patients; iii. aligning the CDR3 regions of the plurality of tumor-specific TCR amino acid sequences of the n patients; iv. grouping TCR sequences into one TCR clonotype cluster if the CDR3 region differs by no more than 3 amino acids (AA) / CDR3, particularly no more than 2 amino acids / CDR3, more particularly no more than 1 amino acid / CDR3, and most particularly no differences; v. In the common TCR selection step, if the TCR clonotype cluster is present in at least two patients, selecting the cluster of TCR sequences as a common tumor-specific TCR sequence.

[0076] In certain embodiments, a cluster of TCR sequences is selected as a common tumor-specific TCR sequence if the TCR clonotype cluster is among the 200 most common tumor-specific TCR sequences, more particularly among the 100 most common tumor-specific TCR sequences, in at least two patients.

[0077] The tumor sequence based process comprises the steps of: I. providing an isolated tumor sample comprising T cells obtained from said patient; II. isolating tumor T cells from the isolated tumor sample to obtain isolated tumor T cells; isolating a tumor nucleic acid preparation from said isolated tumor T cells; III. Obtaining a plurality of tumor TCR nucleic acid sequences from said tumor nucleic acid preparation; IV. aligning the plurality of tumor TCR nucleic acid sequences, grouping essentially identical tumor TCR nucleic acid sequences into tumor TCR clonotype groups, and counting the tumor TCR nucleic acid sequences in each tumor TCR clonotype group to obtain the number of tumor TCR nucleic acid sequences in each tumor TCR clonotype group; V. Determining the frequency of each tumor TCR by dividing the number of tumor TCR nucleic acid sequences in each tumor TCR clonotype group by the total number of tumor TCR nucleic acid sequences obtained from the sample.

[0078] The process based on the non-tumor sequence comprises the steps of: I. providing an isolated non-tumor tissue sample comprising T cells obtained from said patient; II. isolating non-tumor T cells from the isolated non-tumor tissue sample to obtain isolated non-tumor T cells; isolating a non-tumor nucleic acid preparation from said isolated non-tumor T cells; III. Obtaining a plurality of non-tumor TCR nucleic acid sequences from said non-tumor nucleic acid preparation; IV. aligning the plurality of non-tumor TCR nucleic acid sequences, grouping the non-tumor TCR nucleic acid sequences into one essentially identical non-tumor TCR clonotype group, and counting the non-tumor TCR nucleic acid sequences in each non-tumor TCR clonotype group to obtain the number of non-tumor TCR nucleic acid sequences in each non-tumor TCR clonotype group; V. Determining the frequency of each non-tumor TCR by dividing the number of non-tumor TCR nucleic acid sequences in each non-tumor TCR clonotype group by the number of total non-tumor TCR nucleic acid sequences obtained from the sample.

[0079] In certain embodiments, the method of the first aspect is carried out in exactly the order of steps set out above.

[0080] In an alternative to the first aspect, the nucleic acid sequences are translated into amino acid sequences prior to the tumor-specific selection step, and the amino acid sequences are compared and selected in the tumor-specific selection step.

[0081] Another alternative to the method of the first aspect may be described as follows: a. Identifying a tumor-specific TCR sequence from a first patient via the steps of: i. sequencing the TCR gene from a tumor sample of the first patient; ii. sequencing the TCR gene from a non-tumor sample from the first patient; iii. selecting TCR genes as tumor-specific genes if these TCR genes are found more abundantly in tumor samples than in non-tumor samples; b. identifying tumor-specific TCR sequences from a second patient using the same steps i-iii with a sample from the second patient, and repeating the method for n patients; c. Comparing the tumor-specific TCR sequences among the n patients by the steps of: i. aligning the CDR3 regions of the identified tumor-specific TCR sequences at the amino acid level in all patients; ii. grouping TCR sequences into one cluster if the CDR3 region sequences differ by no more than 3 amino acids (AA) / CDR3, particularly no more than 2 amino acids / CDR3, more particularly no more than 1 amino acid / CDR3, and most particularly no difference; d. Selecting a TCR sequence as a common tumor-specific TCR sequence if the cluster is present in at least two patients, particularly three or more, four or more, five or more, ten or more, twenty or more or thirty or more patients.

[0082] In certain embodiments, the tumor samples from the n number of patients are of the same tissue type.

[0083] In certain embodiments, the non-tumor tissue sample is of the same tissue type as the tumor sample.

[0084] In certain embodiments, the T cells are sorted after isolation step II for their co-receptors CD4 and / or CD8 prior to obtaining a plurality of non-tumor TCR nucleic acid sequences in step III, thereby obtaining either HLA class I and / or HLA class II specific sequences.

[0085] In certain embodiments, a plurality of patients is determined to have at least one gene of the same HLA type in common.

[0086] In certain embodiments, multiple patients are determined to share at least one gene of the same HLA type, and the relevant HLA class can be assigned by prior sorting of T cells for CD4+ or CD8+.

[0087] In a particular embodiment, it is determined that multiple patients have in common the same HLA type gene, in particular exactly one gene of the same HLA type, and said common tumor-specific TCR is assigned to an HLA type-specific TCR.

[0088] In a particular embodiment, the common tumor-specific TCR is assigned to an HLA type-specific TCR via the following steps: a. Selecting all patients for whom a common tumor-specific TCR sequence is present; b. determining the HLA genes present in said selected patient; c. Assigning a common tumor-specific TCR to an HLA type-specific TCR when a common HLA gene, especially exactly one common HLA gene, is present in all selected patients.

[0089] In certain embodiments, in the tumor-specific selection step (a.iii.), a TCR sequence is selected as a tumor-specific TCR sequence if the frequency of the tumor TCR clonotype group is 2-fold, particularly 3-fold, more particularly 5-fold, and even more particularly 10-fold higher than the frequency of the non-tumor TCR clonotype group.

[0090] In a particular embodiment, the number of patients n is between 2 and 100, in particular n is between 10 and 50, more in particular n is between 20 and 30.

[0091] In a particular embodiment, the common TCR selection step (step bv) further comprises measuring T cell activation / exhaustion / differentiation markers, in particular markers selected from PDCD1 (PD1), TIGIT, LAG3, HAVCR2 (TIM3), CTLA4, IFNG, TNF, GZMB, TNFRSF9 (CD137, 4-1BB), CD45 (CD45RA / RO), CD69, LAMP1 (CD107a), TBX21 (T-BET), TCF7 (TCF-1), EOMES, TOX and RUNX3, and a TCR sequence is selected as a common tumor-specific TCR sequence if T cells bearing the TCR express one or more T cell activation / exhaustion / differentiation markers or a combination thereof.

[0092] A second aspect of the invention relates to a method for identifying common tumor-specific antigens.

[0093] The method comprises the steps of: a. identifying a common tumor-specific TCR according to a first aspect from a number n of patients, where n>1; b. Obtaining a plurality of tumor-specific polypeptides through the process: (1) obtaining a plurality of tumor-specific mRNA sequences from each of said patients via the steps of: i. in the step based on mRNA tumor sequences, determining a plurality of tumor mRNA sequences; ii. in the step based on mRNA non-tumor sequences, determining a plurality of non-tumor mRNA sequences; iii. in the step of selecting tumor-specific mRNA sequences, selecting tumor-specific mRNA sequences; (2) selecting a plurality of tumor-specific polypeptides via the steps of: i. translating said plurality of tumor-specific RNA sequences into a plurality of tumor-specific amino acid sequences; ii. aligning multiple tumor-specific amino acid sequences from multiple n patients; iii. grouping amino acid sequences into one polypeptide cluster if the amino acid sequences have a sequence identity of ≧80%, ≧85%, ≧90%, ≧92%, ≧94%, ≧96%, ≧98%, or ≧99%; iv. selecting a plurality of polypeptide clusters of amino acid sequences as tumor-specific polypeptides, where the tumor-specific amino acid sequences are present in all of the n patients (all patients for which a common tumor-specific TCR has been selected); c. for each member of the plurality of tumor-specific polypeptides, expressing said member of the plurality of tumor-specific polypeptides in an antigen-presenting cell that shares HLA genes for the patient for which a common tumor-specific TCR has been selected; d. for each antigen-presenting cell, detecting whether the antigen-presenting cell is capable of activating T cells expressing the common tumor-specific TCR; e. Selecting a tumor-specific polypeptide as a common tumor-specific antigen, where an antigen-presenting cell expressing the tumor-specific polypeptide is capable of activating the T cell expressing the common tumor-specific TCR.

[0094] The process based on the mRNA tumor sequence includes the following steps: I. isolating a tumor RNA preparation from a tumor sample from said patient; II. Obtaining a plurality of tumor mRNA sequences from said tumor RNA preparation.

[0095] The process based on mRNA non-tumor sequences includes the following steps: I. isolating a non-tumor RNA preparation from said non-tumor tissue sample from said patient; II. Obtaining a plurality of non-tumor mRNA sequences from said tumor RNA preparation;

[0096] The mRNA tumor-specific selection process comprises the following steps: I. Aligning multiple tumor mRNA sequences and multiple non-tumor mRNA sequences; II. Selecting mRNA sequences that are present in tumor samples and not present (not detected) in non-tumor samples as tumor-specific RNA sequences.

[0097] In certain embodiments, peptides presented by HLA molecules on antigen-presenting cells expressing said common tumor-specific antigens are further isolated from the HLA molecules and characterized by mass spectrometry (Freudenmann et al., 2018 Jul;154(3):331-345).

[0098] In certain embodiments, further a. fragmenting the antigens found by the method of the second aspect into peptides; b. Each peptide was loaded onto an HLA molecule on an antigen-presenting cell; c. For each antigen-presenting cell, determining whether the antigen-presenting cell is capable of activating T cells expressing a common tumor-specific TCR found by the method of the first aspect.

[0099] In certain embodiments, the tumor sample and the non-tumor tissue sample are derived from the same tissue sample, and isolation of a tumor RNA preparation from the tissue sample is performed separately from single tumor and non-tumor cells obtained from the tissue sample.

[0100] Single-cell sequencing is a convenient method to identify tumor-specific RNAs. Because tumors are always a mixture of cancer cells and normal cells, reference RNAs from normal tissues are automatically included. However, cells from adjacent tissues can also be used as references.

[0101] An alternative method of the second aspect relates to a method for identifying a common tumor specific antigen, the method comprising the steps of: a. identifying a common tumor-specific TCR according to a first aspect from a number n of patients, where n>1; b. contacting T cells expressing the common tumor-specific TCR with tumor cells, where the tumor cells are derived from a tumor cell line in which the common tumor-specific TCR expresses HLA genes shared between the selected patients, and detecting whether the tumor cells are capable of activating T cells that provide cells derived from the tumor cell line expressing the common tumor-specific antigen; c. optionally repeating step b with a different tumor cell line; d. preparing a cDNA library from cells derived from a tumor cell line expressing a common tumor-specific antigen; e. for each member of the cDNA, expressing said member in antigen presenting cells that have HLA genes shared between the patients for which a common tumor-specific TCR has been selected; f. for each antigen-presenting cell, detecting whether the antigen-presenting cell is capable of activating T cells expressing the common tumor-specific TCR; g. Selecting a cDNA as a common tumor-specific antigen, where an antigen-presenting cell expressing said cDNA is capable of activating said T cells expressing said common tumor-specific TCR.

[0102] Alternatively, tumor cell lines can be taken and individual sites or genes knocked out. Clones that are no longer recognized must then be identified. Transposon (random) or CRISPR-Cas (molecularly targeted) approaches are also possible.

[0103] Another alternative to the method of the second aspect can be described as follows: a. identifying a common tumor-specific TCR sequence via a first aspect; b. Identifying a common tumor-specific amino acid sequence by: i. sequencing the mRNA repertoire of a tumor sample from a first patient; ii. sequencing the mRNA repertoire of a non-tumor sample from the first patient; iii. selecting an mRNA sequence as tumor-specific in the first patient if the mRNA sequence is present in the tumor sample and absent in the non-tumor sample; iv. Repeating steps i-iii for all n patients; v. translating the tumor-specific mRNA sequences of all patients into amino acid sequences and aligning the tumor-specific amino acid sequences; vi. grouping amino acid sequences into one cluster if the amino acid sequences have a sequence identity of ≧80%, ≧85%, ≧90%, ≧92%, ≧94%, ≧96%, ≧98%, or ≧99%; vii. selecting sequences as common tumor-specific amino acid sequences if the respective clusters are present in all patients tested; c. Assessing the reactivity of the common tumor-specific TCR to the common tumor-specific amino acid sequence by the steps of: i. introducing each common tumor-specific amino acid sequence into an antigen-presenting cell; ii. contacting T cells expressing a common tumor-specific TCR separately with all of the antigen-presenting cells of step i, and measuring IFNγ release from the T cells; d. Selecting an amino acid sequence as a common tumor-specific antigen for which there was detectable IFNγ release of T cells in the previous step.

[0104] A third aspect of the invention relates to an isolated TCR identified by a method according to the first aspect.

[0105] In a particular embodiment, the TCR comprises a CDR3 alpha sequence and a CDR3 beta sequence, wherein the CDR3 alpha sequence and the CDR3 beta sequence are identical to the sequences shown below or have one or two amino acid substitutions per CDR3 sequence: Where: - for group a (cluster 0), the CDR3 alpha sequence is selected from the group of sequences comprising SEQ ID NOs: 6, 1, 59 and the CDR3 beta sequence is selected from the group of sequences comprising SEQ ID NOs: 38, 41, 20; or - for group b (cluster 1), the CDR3 alpha sequence is selected from the group of sequences comprising SEQ ID NOs: 11, 12, 18, 26, 55, 58 and the CDR3 beta sequence is selected from the group of sequences comprising SEQ ID NOs: 47, 72, 73, or - for group c (cluster 31), the CDR3 alpha sequence is selected from the group of sequences comprising SEQ ID NO: 62, 63, 71 and the CDR3 beta sequence is selected from SEQ ID NO: 28; or - for group d (cluster 2), the CDR3 alpha sequence is selected from the group of sequences comprising SEQ ID NO: 8, 51 and the CDR3 beta sequence is selected from the group of sequences comprising SEQ ID NO: 19, 45, 60; or - for group e (cluster 3), the CDR3 alpha sequence is selected from the group of sequences comprising SEQ ID NOs: 2, 21, 24, 32 and the CDR3 beta sequence is selected from the group of sequences comprising SEQ ID NOs: 15, 27, 31; or - for group f (cluster 4), the CDR3 alpha sequence is selected from the group of sequences comprising SEQ ID NO: 29, 52 and the CDR3 beta sequence is selected from SEQ ID NO: 9; or - for group g (cluster 5), the CDR3 alpha sequence is selected from the group of sequences comprising SEQ ID NO: 13, 65 and the CDR3 beta sequence is selected from SEQ ID NO: 61; or - for group h (cluster 6), the CDR3 alpha sequence is selected from the group of sequences comprising SEQ ID NOs: 5, 25, 46, and the CDR3 beta sequence is selected from the group of sequences comprising SEQ ID NOs: 7, 10, 17, 42, 44; In particular, the CDR3 alpha and CDR3 beta sequences are identified in the same row of Tables 1-8, In particular, the substitutions are selected according to the substitution rules set out below: where the substitution rules are as follows: - glycine (G) and alanine (A) are interchangeable; valine (V), leucine (L) and isoleucine (I) are interchangeable, and A and V are interchangeable; -Tryptophan (W) and phenylalanine (F) are interchangeable, and tyrosine (Y) and F are interchangeable; - Serine (S) and threonine (T) are interchangeable; - Aspartic acid (D) and glutamic acid (E) are interchangeable - Asparagine (N) and Glutamine (Q) are interchangeable; N and S are interchangeable; N and D are interchangeable; E and Q are interchangeable; - Methionine (M) and Q are interchangeable; - Cysteine ​​(C), A and S are interchangeable; - Proline (P), G and A are interchangeable; - Arginine (R) and lysine (K) are interchangeable.

[0106] A group of CDR3 sequences is sometimes called a cluster.

[0107] In certain embodiments, the CDR3 sequence is selected from the group a, b, f, g and h.

[0108] In certain embodiments, the TCR further comprises a variable (V) alpha sequence, a junction invariant (JC) alpha sequence, a V beta sequence, and a JC beta sequence, or sequences having >80%, >85%, >90%, >92%, >94%, >96%, >98%, or >99% sequence identity thereto, wherein the complete TCR sequence retains its biological activity; Where: a. for group a, the V alpha sequence is SEQ ID NO:67, the JC alpha sequence is SEQ ID NO:4, the V beta sequence is SEQ ID NO:23, and the JC beta sequence is SEQ ID NO:33, or b. for group b, the V alpha sequence is SEQ ID NO:3, the JC alpha sequence is SEQ ID NO:53, the V beta sequence is SEQ ID NO:64, and the JC beta sequence is SEQ ID NO:56; or c. for group c, the V alpha sequence is SEQ ID NO:54, the JC alpha sequence is SEQ ID NO:48, the V beta sequence is SEQ ID NO:43, and the JC beta sequence is SEQ ID NO:37; or d. For group d, the V alpha sequence is SEQ ID NO:68, the JC alpha sequence is SEQ ID NO:70, the V beta sequence is SEQ ID NO:30, and the JC beta sequence is SEQ ID NO:37; or e. For group e, the V alpha sequence is SEQ ID NO:57, the JC alpha sequence is SEQ ID NO:4, the V beta sequence is SEQ ID NO:16, and the JC beta sequence is SEQ ID NO:22; or f. For group f, the V alpha sequence is SEQ ID NO:49, the JC alpha sequence is SEQ ID NO:66, the V beta sequence is SEQ ID NO:39, and the JC beta sequence is SEQ ID NO:34; or g. For group g, the V alpha sequence is SEQ ID NO: 35, the JC alpha sequence is SEQ ID NO: 40, the V beta sequence is SEQ ID NO: 43, and the JC beta sequence is SEQ ID NO: 69; or h. For group h, the V alpha sequence is SEQ ID NO:14, the JC alpha sequence is SEQ ID NO:50, the V beta sequence is SEQ ID NO:36, and the JC beta sequence is SEQ ID NO:56.

[0109] The biological activity of a TCR is determined through the activation of TCR-containing T cells by tumor cells or APCs. A TCR maintains its biological activity even if it has a deviated sequence, provided that it can still recognize APCs that present a specific HLA-peptide complex.

[0110] A fourth aspect of the invention relates to a nucleic acid sequence encoding a TCR according to the third aspect.

[0111] A fifth aspect of the invention relates to an isolated autologous T cell comprising a TCR according to the third aspect and / or a nucleic acid sequence according to the fourth aspect.

[0112] In a particular embodiment, the isolated autologous T cells are recombinant T cells that recombinantly express said TCR.

[0113] A sixth aspect of the invention relates to a TCR according to the third aspect, a nucleic acid sequence according to the fourth aspect or an isolated autologous T cell according to the fifth aspect for use in the treatment of cancer.

[0114] A TCR according to the third aspect, a nucleic acid sequence according to the fourth aspect, or an isolated autologous T cell according to the fifth aspect for use in treating cancer in a patient having the same HLA type as the HLA type-specific TCR determined via the method of the first aspect.

[0115] A TCR according to a third aspect, a nucleic acid sequence according to a fourth aspect, or an isolated autologous T cell according to a fifth aspect, for use in a patient with the following HLA type: For group a, HLA-B*08:01 and / or HLA-C*07:01; or For the bb group, HLA-A*02:01-supertype (HLA-A*02:01 / 68:02); or c. For group c, HLA-A*02:01-supertype (HLA-A*02:01 / 02:35 / 02:05) and / or HLA-C*07:01 / 07:04; or d. For group d, HLA-A*01:01 and / or HLA-A*02:01; or e. For group e, HLA-A*02:01 and / or HLA-A*01-supertype (A*01:01 / 68:01); or f. For group f, HLA-C*07:01; or g. for group g, HLA-A*01:01 and / or HLA-A*02:01 and / or HLA-C*02:02; or h. For group h, HLA-B*15:01.

[0116] Medical Treatments, Preparations and Salts Similarly within the scope of the invention is a method of treating cancer in a patient in need thereof comprising administering to the patient a TCR according to the third aspect, a nucleic acid sequence according to the fourth aspect, or an isolated autologous T cell according to the fifth aspect.

[0117] Similarly, within the scope of the invention there is provided a formulation for preventing or treating cancer comprising a TCR according to the third aspect, a nucleic acid sequence according to the fourth aspect, or an isolated autologous T cell according to the fifth aspect.

[0118] Pharmaceutical Compositions and Administration Another aspect of the invention relates to a pharmaceutical composition comprising a TCR according to the third aspect, a nucleic acid sequence according to the fourth aspect, or an isolated autologous T cell according to the fifth aspect.

[0119] In certain embodiments of the present invention, the compounds of the present invention are typically formulated into pharmaceutical dosage forms to provide easily controllable administration of the drug and to provide the patient with a clear and easy to administer product.

[0120] The pharmaceutical composition may be formulated for parenteral administration, for example, by intravenous (iv) injection.

[0121] Manufacturing and treatment methods according to the present invention The present invention further encompasses, as a further aspect, the use of a TCR according to the third aspect, a nucleic acid sequence according to the fourth aspect, or an isolated autologous T cell according to the fifth aspect, as specified in detail above, for use in a method of manufacture of a medicament for the treatment or prevention of cancer.

[0122] Similarly, the invention encompasses a method of treating a patient diagnosed with a cancer-related disease, the method involving administering to the patient a TCR according to the third aspect, a nucleic acid sequence according to the fourth aspect, or an isolated autologous T cell according to the fifth aspect.

[0123] The present invention is further illustrated by the following examples and figures, from which further embodiments and advantages can be derived, which are intended to illustrate the invention without limiting its scope. EXAMPLES

[0124] A.1: Preparation of non-small cell lung cancer (NSCLC) tumor tissue and normal lung tissue samples and TCRSafe analysis Each tumor specimen is dissected free of surrounding normal tissue and necrotic areas. Approximately 1 g cubes from tumor and normal lung tissue are cut into small chunks of approximately 2-3 mm in each dimension. Sliced ​​tumor (and non-tumor) biopsies are subjected to a commercial mechanical / enzymatic tissue dissociation system (GentleMACS, Miltenyi Biotec, Bergisch Gladbach, Germany) using a tumor dissociation kit (Miltenyi Biotech) according to the manufacturer's instructions. After GentleMACS dissociation, the cell suspension is passed through a 70 μm cell strainer. Aliquots of tumor and lung cells are harvested and cryopreserved in 10% DMSO (Sigma-Aldrich) and 90% FCS (Life Technologies) for later use. The remaining cell suspension is subjected to density gradient centrifugation using a 40% / 80% step gradient of Percoll® (GE Healthcare Europe GmbH) in PBS / RPMI1640. T lymphocytes are harvested from the interphase and washed with complete medium (RPMI 1640, Lonza). Tumor-infiltrating T lymphocytes (TILs) and lymphocytes from normal lung tissue are then plated in 24-well tissue culture plates at 0.5x10 cells with 2 mL of recovery medium (RM). 6 Plates are plated at a concentration of 10 ... ·CD4+T cells ·CD8+T cells PD1+ cells (only from TILs) · PD1-negative cells (only from TILs).

[0125] Genomic DNA is extracted from the subpopulations and subjected to TCRsafe analysis (as disclosed in WO2014 / 096394A1). The resulting T cell clonotype frequencies are compared between the subpopulations and the identified tumor-specific clonotypes, as detailed in WO2017 / 025564A1.

[0126] All subsequent steps in these examples refer to CD8+ T cells isolated from tumor and non-tumor tissues as described above.

[0127] A.2: T-cell receptor (TCR) α / β pairing using 10xGenomics high-throughput single-cell sequencing Starting with TIL single cell suspensions, 5000-10000 T cells are subjected to high-throughput single cell RNASeq analysis using 10xGenomics Chromium Next GEM Single Cell V(D)J Reagent Kit in combination with Chromium Single Cell V(D)J Enrichment Kit (human). 10xGenomics® GemCodeTM Technology disperses thousands of individual cells into Gel Bead-in-EMulsion (GEM) droplets. Single cells captured in GEMs are lysed, and upon GEM lysis, bead-attached barcoded primers, oligos, master mix and lysed cellular components are mixed to generate full-length oligo-dT primed cDNA libraries by RT-PCR. First-stranded cDNA synthesis utilizing a template-switching mechanism is completed, including the barcode sequence attached to the beads. All cDNA molecules within a single GEM are labeled with the same barcode. The GEMs are disassembled and further library preparation continues as bulk reactions. After cDNA cleanup, the Chromium Single Cell V(D)J Enrichment Kit efficiently amplifies TCR sequences and generates sequencing libraries compatible with Illumina sequencing. Combined with total cDNA amplification, Illumina sequencing reveals paired α / β TCR sequences for each single T cell analyzed and the corresponding entire transcriptome for each cell. Both kits, 10xGenomics Chromium Next GEM Single Cell V(D)J Reagent Kit and Chromium Single Cell V(D)J Enrichment Kit (human), are used according to the manufacturer's instructions.

[0128] The identical sequences between the TCRs described in A.1 above and the TCRs derived from single cell VDJ pairings are used to establish a complete annotation of the TCRs with respect to α and β chains, frequency and tumor specificity.

[0129] A.3: TCR clustering (TCRpolyClust) As depicted in the schematic diagram of the TCRpolyClust method, once the combination of A.1 and A.2 is established, subsequent TCR cluster analysis identifies patients with common TCRs and matching HLA types, allowing screening for shared tumor antigens.

[0130] Synthesis, cloning and ectopic expression of clustered TCRs in T cells isolated from autologous patients or healthy donors The paired cluster TCRs are codon-optimized, synthesized, cloned as bicistronic chimeric constructs (βTCR-VDJ-mC_P2A-element_αTCR-VJ-mC; mC stands for murine constant region) into retroviral (or comparable) expression vectors and transduced into autologous or allogeneic T cells taken from the blood of the respective patient or healthy donor. Recipient T cells are pre-treated with CRISPR / Cas9 to knock out the endogenous TCR, preventing off-target immune responses mediated by mixed TCR dimers (endogenous x exogenous chains, autologous and allogeneic settings) or allo-responses due to endogenous TCR (in allogeneic settings). The chimeric (c)TCR-recombinant T cells are expanded in vitro and applied for functional experiments such as recognition of autologous tumor cells (if available), allogeneic tumor cell lines and / or antigen screening as described below.

[0131] Targeted approaches for screening for shared tumor antigens Comparative whole exome (WES) and whole transcriptome (WTS) sequencing of genomes and total RNA of tumor and corresponding normal tissues, including samples from all patients of each TCR cluster, is applied to identify shared neoantigens (SNV, MNV, InDels, fusion gene products, structural variations), aberrantly expressed canonical genes (cancer / germline antigens and overexpressed antigens), and aberrantly expressed and translated non-canonical transcripts (dark matter transcripts or cryptic transcripts). Candidates from all categories are then tested for recognition by cTCR-transduced recombinant T cells. Antigen formats are either expression plasmids encoding full-length antigen cDNAs or tandem minigenes (TMGs) encoding only the expected immunogenic peptide coding region of the candidate antigen. Both formats are tested by co-transfecting the antigen-encoding plasmid and the HLA-cDNA-encoding plasmid into 293T or COS-7 cells and subjecting the transformants to recognition testing by T cells in an IFN-γ ELISAt assay. Alternatively, antigen peptide candidates can be predicted to bind to relevant HLA alleles using published prediction algorithms (IEDB, NetMHC), peptides can be synthesized and pulsed into HLA-matched antigen-presenting cells. The latter are then subjected to an ELISpot assay to test recognition by recombinant T cells.

[0132] Screening approaches for tumor cDNA expression libraries Targeted identification of antigen candidates is not equally effective for all antigen categories. For example, screening of tumor cells for nonsynonymous somatic mutations using whole chromosome and transcriptome sequencing is sensitive, reproducible, and capable of generating a quantitative list of potential neoantigens, whereas identification of small translatable transcripts (dark matter antigens) is inefficient due to the general lack of specific traits to reliably identify them. This dilemma can be resolved by probing the complete transcriptome of tumor cells with a cDNA expression library screening approach. cDNA expression libraries generated from total RNA, either from sorted autologous tumor cells or from HLA-matched tumor cell lines previously shown to be recognized by cTCR-transduced T cells, are co-expressed with the appropriate HLA alleles in antigen-presenting cells (293T cells or COS-7 cells). Transfectants are then tested for recognition by cTCR-transduced T cells in an ELISpot assay. To have a chance of obtaining expression even for rare transcripts after transfection, the screening procedure requires a high-throughput approach to test highly fractionated cDNA libraries. For this purpose, a cDNA library is produced consisting of 2000 pools of 100 cDNAs per well prepared in a 96-well plate format. Transfection and ELISpot assays using cTCR-transduced T cells as effector cells are carried out in this 96-well format, and from the identified 100 pools, pools are reduced stepwise (e.g., 10 cDNAs / pool and well, cDNA clones / pool and well) and tested to select cDNA clones encoding antigens.

[0133] Since only a small number of patients can obtain a sufficiently pure and highly sufficient population of viable autologous tumor cells for RNA isolation and cDNA library preparation, a pre-screening can be performed to identify type-matched tumor cell lines. The cell lines can be selected for shared expression of HLA alleles or transduced with the HLA of interest. The recognized cell lines are used as proof of the presence of common antigens and as a source for RNA extraction and cDNA library generation.

[0134] array The TCR sequence is constructed as follows (N-terminus to C-terminus): [Table 1]

[0135] [Table 2]

[0136] Cluster ID 0: Cluster 0 is associated with HLA-B*08:01 and HLA-C*07:01. Beta chain, TRB: TRBV7-6*01, TRBJ2-7*01, TRBC2*02

[0137] Cluster 0 Block V ATGGGCACCAGTCTCCTATGCTGGGTGGTCCTGGGTTTCCTAGGGACAGATCACACAGGTGCTGGAGTCTCCCAGTCTCCCAGGTACAAAGTCACAAAGAGGGGACAGGATGTAGCTCTCAGGTGTGATCCAATTTCGGGTCATGTATCCCTTTATTGGTACCGACAGGCCCTGGGGCAGGGCCCAGAGTTTCTGACTTACTTCAATTATGAAGCCCAACAAGACAAATCAGGGCTGCCCAATGATCGGTTCTCTGCAGAGAGGCCTGAGGGATCCATCTCCACTCTGACGATCCAGCGCACAGAGCAGCGGGACTCGGCCATGTATCGC (SEQ ID NO: 96)

[0138] Seq-ID0.1b TGTGCCAGCAGCCCCGGACCCAACTACGAGCAGTACTTC (SEQ ID NO: 74) Seq-ID0.2b TGTGCCAGCAGTGCAGGGCCCAATTACGAGCAGTACTTC (SEQ ID NO: 139) Seq-ID0.3b TGTGCCAGCAGCTTAGGCCCGAATTACGAGCAGTACGTC (SEQ ID NO: 125)

[0139] Cluster 0 Block J / C GGGCCGGGCACCAGGCTCACGGTCACAGAGGACCTGAAAAACGTGTTCCCACCCGAGGTCGCTGTGTTTGAGCCATCAGAAGCAGAGATCTCCCACACCCAAAAGGCCACACTGGTGTGCCTGGCCACAGGCTTCTACCCCGACCACGTGGAGCTGAGCTGGTGGGTGAATGGGAAGGAGGTGCACAGTGGGGTCAGCACAGACCCGCAGCCCCTCAAGGAGCAGCCCGCCCTCAATGACTCCAGATACTGCCTGAGCAGCCGCCTGAGGGTCTCGGCCACCTTCTGGCAGAACCCCCGCAACCACTTCCGCTGTCAAGTCCAGTTCTACGGGCTCTCGGAGAATGACGAGTGGACCCAGGATAGGGCCAAACCTGTCACCCAGATCGTCAGCGCCGAGGCCTGGGGTAGAGCAGACTGTGGCTTCACCTCCGAGTCTTACCAGCAAGGGGTCCTGTCTGCCACCATCCTCTATGAGATCTTGCTAGGGAAGGCCACCTTGTATGCCGTGCTGGTCAGTGCCCTCGTGCTGATGGCCATGGTCAAGAGAAAGGATTCCAGAGGCTAG (SEQ ID NO: 151)

[0140] Cluster 0 Block V MGTSLLCWVVLGFLGTDHTGAGVSQSPRYKVTKRGQDVALRCDPISGHVSLYWYRQALGQGPEFLTYFNYEAQQDKSGLPNDRFSAERPEGSISTLTIQRTEQRDSAMYR (SEQ ID NO: 23)

[0141] Seq-ID0.1b CASSPGPNYEQYF (SEQ ID NO: 38) Seq-ID0.2b CASSAGPNYEQYF (SEQ ID NO: 41) Seq-ID0.3b CASSLGPNYEQYV (SEQ ID NO: 20)

[0142] Cluster 0 Block J / C GPGTRLTVTEDLKNVFPPEVAVFEPSEAEISHTQKATLVCLATGFYPDHVELSWWVNGKEVHSGVSTDPQPLKEQPALNDSRYCLSSRLRVSATFWQNPRNHFRCQVQFYGLSENDEWTQDRAKPVTQIVSAEAWGRADCGFTSESYQQGVLSATILYEILLGKATLYAVLVSALVLMAMVKRKDSRG (SEQ ID NO: 33) Alpha-chain, TRA: TRAV13-1*01, TRAJ23*01, TRAC*01

[0143] Cluster 0 Block V ATGACATCCATTCGAGCTGTATTTATATTCCTGTGGCTGCAGCTGGACTTGGTGAATGGAGAGAATGTGGAGCAGCATCCTTCAACCCTGAGTGTCCAGGAGGGAGACAGCGCTGTTATCAAGTGTACTTATTCAGACAGTGCCTCAAACTACTTCCCTTGGTATAAGCAAGAACTTGGAAAAAGACCTCAGCTTATTATAGACATTCGTTCAAATGTGGGCGAAAAGAAAGACCAACGAATTGCTGTTACATTGAACAAGACAGCCAAACATTTCTCCCTGCACATCACAGAGACCCAACCTGAAGACTCGGCTGTCTACTTC (SEQ ID NO: 108)

[0144] Seq-ID0.1a TGTGCAGGGGCGTATAACCAGGGAGGAAAGCTTATCTTC (SEQ ID NO: 85) Seq-ID0.2a TGTGCAGCAAGTTTTAACCAGGGAGGAAAGCTTATCTTC (SEQ ID NO: 106) Seq-ID0.3a TGTGCAGCAAGTAGTAACCAGGGAGGAAAGCTTATCTTC (SEQ ID NO: 123)

[0145] Cluster 0 Block J / C GGACAGGGAACGGAGTTATCTGTGAAACCCAATATCCAGAACCCTGACCCTGCCGTGTACCAGCTGAGAGACTCTAAATCCAGTGACAAGTCTGTCTGCCTATTCACCGATTTTGATTCTCAAACAAATGTGTCACAAAGTAAGGATTCTGATGTGTATATCACAGACAAAACTGTGCTAGACATGAGGTCTATGGACTTCAAGAGCAACAGTGCTGTGGCCTGGAGCAACAAATCTGACTTTGCATGTGCAAACGCCTTCAACAACAGCATTATTCCAGAAGACACCTTCTTCCCCAGCCCAGAAAGTTCCTGTGATGTCAAGCTGGTCGAGAAAAGCTTTGAAACAGATACGAACCTAAACTTTCAAAACCTGTCAGTGATTGGGTTCCGAATCCTCCTCCTGAAAGTGGCCGGGTTTAATCTGCTCATGACGCTGCGGCTGTGGTCCAGCTGA (SEQ ID NO: 87)

[0146] Cluster 0 Block V MTSIRAVFIFLWLQLDLVNGENVEQHPSTLSVQEGDSAVIKCTYSDSASNYFPWYKQELGKRPQLIIDIRSNVGEKKDQRIAVTLNKTAKHFSLHITETQPEDSAVYF (SEQ ID NO: 67)

[0147] Seq-ID0.1a CAGAYNQGGKLIF (SEQ ID NO: 6) Seq-ID0.2a CAASFNQGGKLIF (SEQ ID NO: 1) Seq-ID0.3a CAASSNQGGKLIF (SEQ ID NO: 59)

[0148] Cluster 0 Block J / C GQGTELSVKPNIQNPDPAVYQLRDSKSSDKSVCLFTDFDSQTNVSQSKDSDVYITDKTVLDMRSMDFKSNSAVAWSNKSDFACANAFNNSIIPEDTFFPSPESSCDVKLVEKSFETDTNLNFQNLSVIGFRILLLKVAGFNLLMTLRLWSS (SEQ ID NO:4)

[0149] [Table 3]

[0150] Cluster ID 1: Cluster 1 is associated with the HLA-A*02:01-supertype (HLA-A*02:01 / 68:02). Beta chain, TRB: TRBV28*01, TRBJ2-3*01, TRBC2*01

[0151] Cluster 1 Block V ATGGGAATCAGGCTCCTCTGTCGTGTGGCCTTTTGTTTCCTGGCTGTAGGCCTCGTAGATGTGAAAGTAACCCAGAGCTCGAGATATCTAGTCAAAAGGACGGGAGAGAAAGTTTTTCTGGAATGTGTCCAGGATATGGACCATGAAAATATGTTCTGGTATC GACAAGACCCAGGTCTGGGGCTACGGCTGATCTATTTCTCATATGATGTTAAAATGAAAGAAAAAGGAGATATTCCTGAGGGGTACAGTGTCTCTAGAGAGAAGAAGGAGCGCTTCTCCCTGATTCTGGAGTCCGCCAGCACCAACCAGACATCTATGTACCTC (Sequence number 97)

[0152] Seq-ID1.1b TGTGCCAGCAGTTTCGTCAGCGGCACAGATACGCAGTATTTT (SEQ ID NO:115) Seq-ID1.2b TGTGCCAGCAGTTTTGTGAGCGGCACAGATACGCAGTATTTT (SEQ ID NO:88) Seq-ID1.3b TGTGCCAGCAGTTTTCTTAGCGGCACAGATACGCAGTATTTT (SEQ ID NO: 157) Seq-ID1.4b TGTGCCAGCAGTTTTCTTTCAGGCACAGATACGCAGTATTTT (SEQ ID NO: 101) Seq-ID1.5b TGTGCCAGCAGTTTCCTAGCGGGCACAGATACGCAGTATTTT (SEQ ID NO: 136) Seq-ID1.6b TGTGCCAGCAGTTTCGTTTCAGGCACAGATACGCAGTATTTT (SEQ ID NO: 133)

[0153] Cluster 1 Block J / C GGCCCAGGCACCCGGCTGACAGTGCTCGAGGACCTGAAAAACGTGTTCCCACCCAAGGTCGCTGTGTTTGAGCCATCAGAAGCAGAGATCTCCCACACCCAAAAGGCCACACTGGTGTGCCTGGCCACAGGCTTCTACCCCGACCACGTGGAGCTGAGCTGGTGGGTGAATGGGAAGGAGGTGCACAGTGGGGTCAGCACAGACCCGCAGCCCCTCAAGGAGCAGCCCGCCCTCAATGACTCCAGATACTGCCTGAGCAGCCGCCTGAGGGTCTCGGCCACCTTCTGGCAGAACCCCCGCAACCACTTCCGCTGTCAAGTCCAGTTCTACGGGCTCTCGGAGAATGACGAGTGGACCCAGGATAGGGCCAAACCTGTCACCCAGATCGTCAGCGCCGAGGCCTGGGGTAGAGCAGACTGTGGCTTCACCTCCGAGTCTTACCAGCAAGGGGTCCTGTCTGCCACCATCCTCTATGAGATCTTGCTAGGGAAGGCCACCTTGTATGCCGTGCTGGTCAGTGCCCTCGTGCTGATGGCCATGGTCAAGAGAAAGGATTCCAGAGGCTAG (SEQ ID NO: 86)

[0154] Cluster 1 Block V MGIRLLCRVAFCFLAVGLVDVKVTQSSRYLVKRTGEKVFLECVQDMDHENMFWYRQDPGLGLRLIYFSYDVKMKEKGDIPEGYSVSREKKERFSLILESASTNQTSMYL (SEQ ID NO: 64)

[0155] Seq-ID1.1b CASSFVSGTDTQYF (SEQ ID NO:47) Seq-ID1.2b CASSFVSGTDTQYF (SEQ ID NO:47) Seq-ID1.3b CASSFLSGTDTQYF (SEQ ID NO:73) Seq-ID1.4b CASSFLSGTDTQYF (SEQ ID NO:73) Seq-ID1.5b CASSFLAGTDTQYF (SEQ ID NO:72) Seq-ID1.6b CASSFVSGTDTQYF (SEQ ID NO:47)

[0156] Cluster 1 J / C GPGTRLTVLEDLKNVFPPKVAVFEPSEAEISHTQKATLVCLATGFYPDHVELSWWVNGKEVHSGVSTDPQPLKEQPALNDSRYCLSSRLRVSATFWQNPRNHFRCQVQFYGLSENDEWTQDRAKPVTQIVSAEAWGRADCGFTSESYQQGVLSATILYEILLGKATLYAVLVSALVLMAMVKRKDSRG (SEQ ID NO:56) Alpha-chain, TRA: TRAV24*01, TRAJ18*01, TRAC*01

[0157] Cluster 1 Block V ATGGAGAAGAATCCTTTGGCAGCCCCATTACTAATCCTCTGGTTTCATCTTGACTGCGTGAGCAGCATACTGAACGTGGAACAAAGTCCTCAGTCACTGCATGTTCAGGAGGGAGACAGCACCAATTTCACCTGCAGCTTCCCTTCCAGCAATTTTTATGCCTTAC ACTGGTACAGATGGGAAACTGCAAAAAGCCCCGAGGCCTTGTTTGTAATGACTTTAAATGGGGATGAAAAGAAGAAAGGACGAATAAGTGCCACTCTTAATACCAAGGAGGGTTACAGCTATTTGTACATCAAAGGATCCCAGCCTGAAGACTCAGCCACATACCTC (Sequence number 131)

[0158] Seq-ID1.1a TGTGCCTTTATGGCCAGAGGCTCAACCCTGGGGAGGCTATACTTT (SEQ ID NO:134) Seq-ID1.2a TGTGCCTTTATGGAGAGAGGCTCAACCCTGGGGAGGCTATACTTT (SEQ ID NO:124) Seq-ID1.3a TGTGCCTTTCTTACCAGAGGCTCAACCCTGGGGAGGCTATACTTT (SEQ ID NO:119) Seq-ID1.4a TGTGCCTTTATGCCCAGAGGCTCAACCCTGGGGAGGCTATACTTT (SEQ ID NO:147) Seq-ID1.5a TGTGCCCCCCTCCCGAGAGGCTCAACCCTGGGGAGGCTATACTTT (SEQ ID NO:102) Seq-ID1.6a TGTGCCTTATTAAGCAGAGGCTCAACCCTGGGGAGGCTATACTTT (SEQ ID NO:132)

[0159] Cluster 1 Block J / C GGAAGAGGAACTCAGTTGACTGTCTGGCCTGATATCCAGAACCCTGACCCTGCCGTGTACCAGCTGAGAGACTCTAAATCCAGTGACAAGTCTGTCTGCCTATTCACCGATTTTGATTCTCAAACAAATGTGTCACAAAGTAAGGATTCTGATGTGTATATCACAGACAAAACTGTGCTAGACATGAGGTCTATGGACTTCAAGAGCAACAGTGCTGTGGCCTGGAGC AACAAATCTGACTTTGCATGTGCAAACGCCTTCAACAACAGCATTATTCCAGAAGACACCTTCTTCCCCAGCCCAGAAAGTTCCTGTGATGTCAAGCTGGTCGAGAAAAGCTTTGAAACAGATACGAACCTAAACTTTCAAAACCTGTCAGTGATTGGGTTCCGAATCCTCCTCCTGAAAGTGGCCGGGTTTAATCTGCTCATGACGCTGCGGCTGTGGTCCAGCTGA (Sequence number 138)

[0160] Cluster 1 Block V MEKNPLAAPLLILWFHLDCVSSILNVEQSPQSLHVQEGDSTNFTCSFPSSNFYALHWYRWETAKSPEALFVMTLNGDEKKKGRISATLNTKEGYSYLYIKGSQPEDSATYL (SEQ ID NO: 3)

[0161] Seq-ID1.1a CAFMARGSTLGRLYF (SEQ ID NO:58) Seq-ID1.2a CAFMERGSTLGRLYF (SEQ ID NO:12) Seq-ID1.3a CAFLTRGSTLGRLYF (SEQ ID NO:18) Seq-ID1.4a CAFMPRGSTLGRLYF (SEQ ID NO:55) Seq-ID1.5a CAPLPRGSTLGRLYF (SEQ ID NO:26) Seq-ID1.6a CALLSRGSTLGRLYF (SEQ ID NO:11)

[0162] Cluster 1 Block J / C GRGTQLTVWPDIQNPDPAVYQLRDSKSSDKSVCLFTDFDSQTNVSQSKDSDVYITDKTVLDMRSMDFKSNSAVAWSNKSDFACANAFNNSIIPEDTFFPSPESSCDVKLVEKSFETDTNLNFQNLSVIGFRILLLKVAGFNLLMTLRLWSS (SEQ ID NO:53)

[0163] [Table 4]

[0164] Cluster ID 31: Cluster 31 is combined with HLA-A*02:01-supertype (HLA-A*02:01 / 02:35 / 02:05) or HLA-C*07:01 / 07:04. Beta chain, TRB: TRBV5-1*01, TRBJ1-1*01, TRBC1*01

[0165] Cluster 31 Block V ATGGGCTCCAGGCTGCTCTGTTGGGTGCTGCTTTGTCTCCTGGGAGCAGGCCCAGTAAAGGCTGGAGTCACTCAAACTCCAAGATATCTGATCAAAACGAGAGGACAGCAAGTGACACTGAGCTGCTCCCCTATCTCTGGGCATAGGAGTGTATCCTGGTACC AACAGACCCCAGGACAGGGCCTTCAGTTCCTTTGAATACTTCAGTGAGACACAGAGAAACAAAGGAAACTTCCCTGGTCGATTCTCAGGGCGCCAGTTCTCTAACTCTCGCTCTGAGATGAATGTGAGCACCTTGGAGCTGGGGGACTCGGCCCTTTATCTT (Sequence number 116)

[0166] Seq-ID31.1b TGCGCCAGCAGTTTGGACGGGATGAACACTGAAGCTTTCTTT (SEQ ID NO: 98) Seq-ID31.2b TGCGCCAGCAGCTTGGACGGAATGAACACTGAAGCTTTCTTT (SEQ ID NO: 83) Seq-ID31.3b TGCGCCAGCAGCTTGGACGGCATGAACACTGAAGCTTTCTTT (SEQ ID NO: 129)

[0167] Cluster 31 Block J / C GGACAAGGCACCAGACTCACAGTTGTAGAGGACCTGAACAAGGTGTTCCCACCCGAGGTCGCTGTGTTTGAGCCATCAGAAGCAGAGATCTCCCACACCCAAAAGGCCACACTGGTGTGCCTGGCCACAGGCTTCTTCCCTGACCACGTGGAGCTGAGCTGGTGGGTGAATGGGAAGGAGGTGCACAGTGGGGTCAGCACGGACCCGCAGCCCCTCAAGGAGCAGCCCGCCCTCAATGACTCCAGATACTGCCTGAGCAGCCGCCTGAGGGTCTCGGCCACCTTCTGGCAGAACCCCCGCAACCACTTCCGCTGTCAAGTCCAGTTCTACGGGCTCTCGGAGAATGACGAGTGGACCCAGGATAGGGCCAAACCCGTCACCCAGATCGTCAGCGCCGAGGCCTGGGGTAGAGCAGACTGTGGCTTTACCTCGGTGTCCTACCAGCAAGGGGTCCTGTCTGCCACCATCCTCTATGAGATCCTGCTAGGGAAGGCCACCCTGTATGCTGTGCTGGTCAGCGCCCTTGTGTTGATGGCCATGGTCAAGAGAAAGGATTTCTGA (SEQ ID NO: 103)

[0168] Cluster 31 Block V MGSRLLCWVLLCLLGAGPVKAGVTQTPRYLIKTRGQQVTLSCSPISGHRSVSWYQQTPGQGLQFLFEYFSETQRNKGNFPGRFSGRQFSNSRSEMNVSTLELGDSALYL (SEQ ID NO: 43)

[0169] Seq-ID31.1b CASSLDGMNTEAFF (SEQ ID NO:28) Seq-ID31.2b CASSLDGMNTEAFF (SEQ ID NO:28) Seq-ID31.3b CASSLDGMNTEAFF (SEQ ID NO:28)

[0170] Cluster 31 Block J / C GQGTRLTVVEDLNKVFPPEVAVFEPSEAEISHTQKATLVCLATGFFPDHVELSWWVNGKEVHSGVSTDPQPLKEQPALNDSRYCLSSRLRVSATFWQNPRNHFRCQVQFYGLSENDEWTQDRAKPVTQIVSAEAWGRADCGFTSVSYQQGVLSATILYEILLGKATLYAVLVSALVLMAMVKRKDF (SEQ ID NO: 37) Alpha-chain, TRA: TRAV29 / DV5*01, TRAJ44*01, TRAC*01

[0171] Cluster 31 Block V ATGGCCATGCTCCTGGGGGCATCAGTGCTGATTCTGTGGCTTCAGCCAGACTGGGTAAACAGTCAACAGAAGAATGATGACCAGCAAGTTAAGCAAAATTCACCATCCCTGAGCGTCCAGGAAGGAAGAATTTCTATTCTGAACTGTGACTATACTAACAGCATGTTTGATTATTTCCTATGGTACAAAAAATACCCTGCTGAAGGTCCTACATTCCTGATATCTATAAGTTCCATTAAGGATAAAAATGAAGATGGAAGATTCACTGTCTTCTTAAACAAAAGTGCCAAGCACCTCTCTCTGCACATTGTGCCCTCCCAGCCTGGAGACTCTGCAGTGTACTTC (SEQ ID NO: 79)

[0172] Seq-ID31.1a TGTGCAGCAAGACTTACCGGCACTGCCAGTAAACTCACCTTT (SEQ ID NO: 143) Seq-ID31.2a TGTGCAGCAAGGAATGCCGGCACTGCCAGTAAACTCACCTTT (SEQ ID NO: 148) Seq-ID31.3a TGTGCAGCAAGGAATACCGGCACTGCCAGTAAACTCACCTTT (SEQ ID NO: 152)

[0173] Cluster 31 Block J / C GGGACTGGAACAAGACTTCAGGTCACGCTCGATATCCAGAACCCTGACCCTGCCGTGTACCAGCTGAGAGACTCTAAATCCAGTGACAAGTCTGTCTGCCTATTCACCGATTTTGATTCTCAAACAAATGTGTCACAAAGTAAGGATTCTGATGTGTATATCACAGACAAAACTGTGCTAGACATGAGGTCTATGGACTTCAAGAGCAACAGTGCTGTGGCCTGGAGCAACAAATCTGACTTTGCATGTGCAAACGCCTTCAACAACAGCATTATTCCAGAAGACACCTTCTTCCCCAGCCCAGAAAGTTCCTGTGATGTCAAGCTGGTCGAGAAAAGCTTTGAAACAGATACGAACCTAAACTTTCAAAACCTGTCAGTGATTGGGTTCCGAATCCTCCTCCTGAAAGTGGCCGGGTTTAATCTGCTCATGACGCTGCGGCTGTGGTCCAGCTGA (SEQ ID NO: 158)

[0174] Cluster 31 Block V MAMLLGASVLILWLQPDWVNSQQKNDDQQVKQNSPSLSVQEGRISILNCDYTNSMFDYFLWYKKYPAEGPTFLISISSIKDKNEDGRFTVFLNKSAKHLSLHIVPSQPGDSAVYF (SEQ ID NO: 54)

[0175] Seq-ID31.1a CAARLTGTASKLTF (SEQ ID NO: 63) Seq-ID31.2a CAARNAGTASKLTF (SEQ ID NO: 71) Seq-ID31.3a CAARNTGTASKLTF (SEQ ID NO: 62)

[0176] Cluster 31 Block J / C GTGTRLQVTLDIQNPDPAVYQLRDSKSSDKSVCLFTDFDSQTNVSQSKDSDVYITDKTVLDMRSMDFKSNSAVAWSNKSDFACANAFNNSIIPEDTFFPSPESSCDVKLVEKSFETDTNLNFQNLSVIGFRILLLKVAGFNLLMTLRLWSS (SEQ ID NO:48)

[0177] [Table 5]

[0178] Cluster ID 2: Cluster 2 combines with HLA-A*01:01 or HLA-A*02:01. Beta chain, TRB: TRBV10-2, TRBJ1-1, TRBC1*01

[0179] Cluster 2 Block V ATGGGCACCAGGCTCTTCTTCTATGTGGCCCTTTGTCTGCTGTGGGCAGGACACAGGGATGCTGGAATCACCCAGAGCCCAAGATACAAGATCACAGAGACAGGAAGGCAGGTGACCTTGATGTGTCACCAGACTTGGAGCCACAGCTATATGTTCTGGTATC GACAAGACCTGGGACATGGGCTGAGGCTGATCTATTACTCAGCAGCTGCTGATATTACAGATAAAGGAGAAGTCCCCGATGGCTATGTTGTCTCCAGATCCAAGACAGAGAATTTCCCCCTCACTCTGGAGTCAGCTACCCGCTCCCAGACATCTGTGTATTTC (Sequence number 78)

[0180] Seq-ID2.1b TGCGCCAGCAGTGAGGACGGCATGAACACTGAAGCTTTCTTT (SEQ ID NO:77) Seq-ID2.2b TGCGCCAGCAGTTCCGACGGGATGAACACTGAAGCTTTCTTT (SEQ ID NO:107) Seq-ID2.3b TGCGCCAGCAGCCCGGACGGAATGAACACTGAAGCTTTCTTT (SEQ ID NO: 92)

[0181] Cluster 2 Block J / C GGACAAGGCACCAGACTCACAGTTGTAGAGGACCTGAACAAGGTGTTCCCACCCGAGGTCGCTGTGTTTGAGCCATCAGAAGCAGAGATCTCCCACACCCAAAAGGCCACACTGGTGTGCCTGGCCACAGGCTTCTTCCCTGACCACGTGGAGCTGAGCTGGTGGGTGAATGGGAAGGAGGTGCACAGTGGGGTCAGCACGGACCCGCAGCCCCTCAAGGAGCAGCCCGCCCTCAATGACTCCAGATACTGCCTGAGCAGCCGCCTGAGGGTCTCGGCCACCTTCTGGCAGAACCCCCGCAACCACTTCCGCTGTCAAGTCCAGTTCTACGGGCTCTCGGAGAATGACGAGTGGACCCAGGATAGGGCCAAACCCGTCACCCAGATCGTCAGCGCCGAGGCCTGGGGTAGAGCAGACTGTGGCTTTACCTCGGTGTCCTACCAGCAAGGGGTCCTGTCTGCCACCATCCTCTATGAGATCCTGCTAGGGAAGGCCACCCTGTATGCTGTGCTGGTCAGCGCCCTTGTGTTGATGGCCATGGTCAAGAGAAAGGATTTCTGA (SEQ ID NO: 103)

[0182] Cluster 2 Block V MGTRLFFYVALCLLWAGHRDAGITQSPRYKITETGRQVTLMCHQTWSHSYMFWYRQDLGHGLRLIYYSAAADITDKGEVPDGYVVSRSKTENFPLTLESATRSQTSVYF (SEQ ID NO: 30)

[0183] Seq-ID2.1b CASSEDGMNTEAFF (SEQ ID NO: 19) Seq-ID2.2b CASSSDGMNTEAFF (SEQ ID NO: 60) Seq-ID2.3b CASSPDGMNTEAFF (Sequence No. 45)

[0184] Cluster 2 Block J / C GQGTRLTVVEDLNKVFPPEVAVFEPSEAEISHTQKATLVCLATGFFPDHVELSWWVNGKEVHSGVSTDPQPLKEQPALNDSRYCLSSRLRVSATFWQNPRNHFRCQVQFYGLSENDEWTQDRAKPVTQIVSAEAWGRADCGFTSVSYQQGVLSATILYEILLGKATLYAVLVSALVLMAMVKRKDF (Sequence No. 37) Alpha-chain, TRA: TRAV21*01, TRAJ33*01, TRAC*01

[0185] Cluster 2 Block V ATGGAGACCCTCTTGGGCCTGCTTATCCTTTGGCTGCAGCTGCAATGGGTGAGCAGCAAACAGGAGGTGACACAGATTCCTGCAGCTCTGAGTGTCCCAGAAGGAGAAAACTTGGTTCTCAACTGCAGTTTCACTGATAGCGCTATTTACAACCTCCAGTGGTTTAGGCAGGACCCTGGGAAAGGTCTCACATCTCTGTTGCTTATTCAGTCAAGTCAGAGAGAGCAAACAAGTGGAAGACTTAATGCCTCGCTGGATAAATCATCAGGACGTAGTACTTTATACATTGCAGCTTCTCAGCCTGGTGACTCAGCCACCTACCTC (Sequence No. 145)

[0186] Seq-ID2.1a TGTGCTGTCCTAATGGATAGCAACTATCAGTTAATCTGG (Sequence No. 120) Seq-ID2.2a TGTGCTGTCTTAATGGATAGCAACTATCAGTTAATCTGG (Sequence No. 146) Seq-ID2.3a TGTGCTTTACTCATGGATAGCAACTATCAGTTAATCTGG (Sequence No. 90)

[0187] Cluster 2 Block J / C GGCGCTGGGACCAAGCTAATTATAAAGCCAGATATCCAGAACCCTGACCCTGCCGTGTACCAGCTGAGAGACTCTAAATCCAGTGACAAGTCTGTCTGCCTATTCACCGATTTTGATTCTCAAACAAATGTGTCACAAAGTAAGGATTCTGATGTGTATATCACAGACAAAACTGTGCTAGACATGAGGTCTATGGACTTCAAGAGCAACAGTGCTGTGGCCTGGAGCAACAAATCTGACTTTGCATGTGCAAACGCCTTCAACAACAGCATTATTCCAGAAGACACCTTCTTCCCCAGCCCAGAAAGTTCCTGTGATGTCAAGCTGGTCGAGAAAAGCTTTGAAACAGATACGAACCTAAACTTTCAAAACCTGTCAGTGATTGGGTTCCGAATCCTCCTCCTGAAAGTGGCCGGGTTTAATCTGCTCATGACGCTGCGGCTGTGGTCCAGCTGA (SEQ ID NO: 111)

[0188] Cluster 2 Block V METLLGLLILWLQLQWVSSKQEVTQIPAALSVPEGENLVLNCSFTDSAIYNLQWFRQDPGKGLTSLLLIQSSQREQTSGRLNASLDKSSGRSTLYIAASQPGDSATYL (SEQ ID NO: 68)

[0189] Seq-ID2.1a CAVLMDSNYQLIW (SEQ ID NO: 51) Seq-ID2.2a CAVLMDSNYQLIW (SEQ ID NO: 51) Seq-ID2.3a CALLMDSNYQLIW (SEQ ID NO: 8)

[0190] Cluster 2 Block J / C GAGTKLIIKPDIQNPDPAVYQLRDSKSSDKSVCLFTDFDSQTNVSQSKDSDVYITDKTVLDMRSMDFKSNSAVAWSNKSDFACANAFNNSIIPEDTFFPSPESSCDVKLVEKSFETDTNLNFQNLSVIGFRILLLKVAGFNLLMTLRLWSS (SEQ ID NO: 70)

[0191] [Table 6]

[0192] Cluster ID 3: Cluster 3 is associated with HLA-A*02:01 or HLA-A*01-supertype (A*01:01 / 68:01). Beta chain, TRB: TRBV29-1*01, TRBJ1-4*01, TRBC1*01

[0193] Cluster 3 Block V ATGCTGAGTCTTCTGCTCCTTCTCCTGGGACTAGGCTCTGTGTTCAGTGCTGTCATCTCTCAAAAGCCAAGCAGGGATATCTGTCAACGTGGAACCTCCCTGACGATCCAGTGTCAAGTCGATAGCCAAGTCACCATGATGTTCTGGTACCGTCAGCAAC CTGGACAGAGCCTGACACTGATCGCAACTGCAAATCAGGGCTCTGAGGCCACATATGAGAGTGGATTTGTCATTGACAAGTTTCCCATCAGCCGCCCAAACCTAACATTCTCAACTCTGACTGTGAGCAACATGAGCCCTGAAGACAGCAGCATATATCTC (Sequence number 112)

[0194] Seq-ID3.1b TGCAGCGTTGGGGCTCAGGGAACTAATGAAAAACTGTTTTTT (SEQ ID NO:84) Seq-ID3.2b TGCAGCGTTGGGTCCGGGGGCACTAATGAAAAACTGTTTTTT (SEQ ID NO:144) Seq-ID3.3b TGCAGCGTCGGAACAGGGGGGACTAATGAAAAACTGTTTTTT (SEQ ID NO: 89) Seq-ID3.4b TGCAGCGTTGGGACAGGGGGAACTAATGAAAAACTGTTTTTT (SEQ ID NO: 127) Seq-ID3.5b TGCAGCGTTGGGTCCGGGGGCACTAATGAAAAACTGTTTTTT (SEQ ID NO: 144) Seq-ID3.6b TGCAGCGTCGGAACAGGGGGGACTAATGAAAAACTGTTTTTT (SEQ ID NO: 89) Seq-ID3.7b TGCAGCGTTGGGACAGGGGGAACTAATGAAAAACTGTTTTTT (SEQ ID NO: 127)

[0195] Cluster 3 Block J / C GGCAGTGGAACCCAGCTCTCTGTCTTGGAGGACCTGAACAAGGTGTTCCCACCCGAGGTCGCTGTGTTTGAGCCATCAGAAGCAGAGATCTCCCACACCCAAAAGGCCACACTGGTGTGCCTGGCCACAGGCTTCTTCCCTGACCACGTGGAGCTGAGCTGGTGGGTGAATGGGAAGGAGGTGCACAGTGGGGTCAGCACGGACCCGCAGCCCCTCAAGGAGCAGCCCGCCCTCAATGACTCCAGATACTGCCTGAGCAGCCGCCTGAGGGTCTCGGCCACCTTCTGGCAGAACCCCCGCAACCACTTCCGCTGTCAAGTCCAGTTCTACGGGCTCTCGGAGAATGACGAGTGGACCCAGGATAGGGCCAAACCCGTCACCCAGATCGTCAGCGCCGAGGCCTGGGGTAGAGCAGACTGTGGCTTTACCTCGGTGTCCTACCAGCAAGGGGTCCTGTCTGCCACCATCCTCTATGAGATCCTGCTAGGGAAGGCCACCCTGTATGCTGTGCTGGTCAGCGCCCTTGTGTTGATGGCCATGGTCAAGAGAAAGGATTTCTGA (SEQ ID NO: 81)

[0196] Cluster 3 Block V MLSLLLLLLGLGSVFSAVISQKPSRDICQRGTSLTIQCQVDSQVTMMFWYRQQPGQSLTLIATANQGSEATYESGFVIDKFPISRPNLTFSTLTVSNMSPEDSSIYL (SEQ ID NO: 16)

[0197] Seq-ID3.1b CSVGAQGTNEKLFF (SEQ ID NO:15) Seq-ID3.2b CSVGSGGTNEKLFF (SEQ ID NO:27) Seq-ID3.3b CSVGTGGTNEKLFF (SEQ ID NO:31) Seq-ID3.4b CSVGTGGTNEKLFF (SEQ ID NO:31) Seq-ID3.5b CSVGSGGTNEKLFF (SEQ ID NO:27) Seq-ID3.6b CSVGTGGTNEKLFF (SEQ ID NO:31) Seq-ID3.7b CSVGTGGTNEKLFF (SEQ ID NO:31)

[0198] Cluster 3 Block J / C GSGTQLSVLEDLNKVFPPEVAVFEPSEAEISHTQKATLVCLATGFFPDHVELSWWVNGKEVHSGVSTDPQPLKEQPALNDSRYCLSSRLRVSATFWQNPRNHFRCQVQFYGLSENDEWTQDRAKPVTQIVSAEAWGRADCGFTSVSYQQGVLSATILYEILLGKATLYAVLVSALVLMAMVKRKDF (SEQ ID NO: 22) Alpha-chain, TRA: TRAV5*01, TRAJ23*01 / TRAJ37*01 / TRAJ31*01, TRAC*01

[0199] Cluster 3 Block V ATGAAGACATTTGCTGGATTTTCGTTCCTGTTTTTGTGGCTGCAGCTGGACTGTATGAGTAGAGGAGAGGATGTGGAGCAGAGTCTTTTCCTGAGTGTCCGAGAGGGAGACAGCTCCGTTATAAACTGCACTTACACAGACAGCTCCTCCACCTACTTATACT GGTATAAGCAAGAACCTGGAGCAGGTCTCCAGTTGCTGACGTATATTTTTTCAAATATGGACATGAAACAAGACCAAAGACTCACTGTTCTATTGAATAAAAAGGATAAACATCTGTCTCTGCGCATTGCAGACACCCAGACTGGGGACTCAGCTATCTACTTC (Sequence number 104)

[0200] Seq-ID3.1a TGTGCAGAGAGTACCTCCAGGGGAAAGCTTATCTTC (Sequence number 100) Seq-ID3.2a TGTGCAGAGAGTACTCCGGGAGGAAAGCTTATCTTC (SEQ ID NO:155) Seq-ID3.3a TGTGCAGAGAGCTCGCCGCAAGGCAAACTAATCTTT (SEQ ID NO:142) Seq-ID3.4a TGTGCAGAGTCAACTCCCCGGGGCAGACTCATGTTT (SEQ ID NO:110) Seq-ID3.5a TGTGCAGAGAGTACTCCGGGAGGAAAGCTTATCTTC (SEQ ID NO:155) Seq-ID3.6a TGTGCAGAGAGCTCGCCGCAAGGCAAACTAATCTTT (SEQ ID NO:142) Seq-ID3.7a TGTGCAGAGTCAACTCCCCGGGGCAGACTCATGTTT (SEQ ID NO:110)

[0201] Cluster 3 Block J / C GGACAGGGAACGGAGTTATCTGTGAAACCCAATATCCAGAACCCTGACCCTGCCGTGTACCAGCTGAGAGACTCTAAATCCAGTGACAAGTCTGTCTGCCTATTCACCGATTTTGATTCTCAAACAAATGTGTCACAAAGTAAGGATTCTGATGTGTATATCACAGACAAAACTGTGCTAGACATGAGGTCTATGGACTTCAAGAGCAACAGTGCTGTGGCCTGGAGC AACAAATCTGACTTTGCATGTGCAAACGCCTTCAACAACAGCATTATTCCAGAAGACACCTTCTTCCCCAGCCCAGAAAGTTCCTGTGATGTCAAGCTGGTCGAGAAAAGCTTTGAAACAGATACGAACCTAAACTTTCAAAACCTGTCAGTGATTGGGTTCCGAATCCTCCTCCTGAAAGTGGCCGGGTTTAATCTGCTCATGACGCTGCGGCTGTGGTCCAGCTGA (Sequence number 87)

[0202] Cluster 3 Block V MKTFAGFSFLFLWLQLDCMSRGEDVEQSLFLSVREGDSSVINCTYTDSSSTYLYWYKQEPGAGLQLLTYIFSNMDMKQDQRLTVLLNKKDKHLSLRIADTQTGDSAIYF (SEQ ID NO:57)

[0203] Seq-ID3.1a CAESTSRGKLIF (SEQ ID NO:24) Seq-ID3.2a CAESTPGGKLIF (SEQ ID NO:2) Seq-ID3.3a CAESSPQGKLIF (SEQ ID NO:21) Seq-ID3.4a CAESTPRGRLMF (SEQ ID NO:32) Seq-ID3.5a CAESTPGGKLIF (SEQ ID NO:2) Seq-ID3.6a CAESSPQGKLIF (SEQ ID NO:21) Seq-ID3.7a CAESTPRGRLMF (SEQ ID NO:32)

[0204] Cluster 3 Block J / C GQGTELSVKPNIQNPDPAVYQLRDSKSSDKSVCLFTDFDSQTNVSQSKDSDVYITDKTVLDMRSMDFKSNSAVAWSNKSDFACANAFNNSIIPEDTFFPSPESSCDVKLVEKSFETDTNLNFQNLSVIGFRILLLKVAGFNLLMTLRLWSS (SEQ ID NO:4)

[0205] [Table 7]

[0206] Cluster ID 4: Cluster 4 is associated with HLA-C*07:01. Beta chain, TRB: TRBV6-5*01 / TRBV6-1*01, TRBJ2-2*01, TRBC2*01

[0207] Cluster 4 Block V ATGAGCATCGGCCTCCTGTGCTGTGCAGCCTTGTCTCTCCTGGGCAGGTCCAGTGAATGCTGGTGTCACTCAGACCCCAAAATTCCAGGTCCTGAAGACAGGACAGAGCATGACACTGCAGTGTGCCCAGGATATGAACCATGAATACATGTCCTGGTATC GACAAGACCCAGGCATGGGGCTGAGGCTGATTCATTACTCAGTTTGGTGCTGGTATCACTGACCAAGGAGAAGTCCCCAATGGCTACAATGTCTCCAGATCAACCACAGAGGATTTCCCGCTCAGGCTGCTGTCGGCTGCTCCCTCCCAGACATCTGTGTACTTC (Sequence number 154)

[0208] Seq-ID4.1b TGTGCCAGCAGTTATGACAGCGGAACCGGGGAGCTGTTTTTT (SEQ ID NO: 121) Seq-ID4.2b TGTGCCAGCAGTTACGACAGTGGGACCGGGGAGCTGTTTTTT (SEQ ID NO: 140) Seq-ID4.3b TGTGCCAGCAGTTACGACTCAGGGACCGGGGAGCTGTTTTTT (SEQ ID NO: 141) Seq-ID4.4b TGTGCCAGCAGTTACGACTCAGGGACCGGGGAGCTGTTTTTT (SEQ ID NO: 141)

[0209] Cluster 4 Block J / C GGAGAAGGCTCTAGGCTGACCGTACTGGAGGACCTGAAAAACGTGTTCCCACCCAAGGTCGCTGTGTTTGAGCCATCAGAAGCAGAGATCTCCCACACCCAAAAGGCCACACTGGTGTGCCTGGCCACAGGCTTCTACCCCGACCACGTGGAGCTGAGCTGGTGGGTGAATGGGAAGGAGGTGCACAGTGGGGTCAGCACAGACCCGCAGCCCCTCAAGGAGCAGCCCGCCCTCAATGACTCCAGATACTGCCTGAGCAGCCGCCTGAGGGTCTCGGCCACCTTCTGGCAGAACCCCCGCAACCACTTCCGCTGTCAAGTCCAGTTCTACGGGCTCTCGGAGAATGACGAGTGGACCCAGGATAGGGCCAAACCTGTCACCCAGATCGTCAGCGCCGAGGCCTGGGGTAGAGCAGACTGTGGCTTCACCTCCGAGTCTTACCAGCAAGGGGTCCTGTCTGCCACCATCCTCTATGAGATCTTGCTAGGGAAGGCCACCTTGTATGCCGTGCTGGTCAGTGCCCTCGTGCTGATGGCCATGGTCAAGAGAAAGGATTCCAGAGGCTAG (SEQ ID NO: 128)

[0210] Cluster 4 Block V MSIGLLCCAALSLLWAGPVNAGVTQTPKFQVLKTGQSMTLQCAQDMNHEYMSWYRQDPGMGLRLIHYSVGAGITDQGEVPNGYNVSRSTTEDFPLRLLSAAPSQTSVYF (SEQ ID NO:39)

[0211] Seq-ID4.1b CASSYDSGTGELFF (SEQ ID NO:9) Seq-ID4.2b CASSYDSGTGELFF (SEQ ID NO:9) Seq-ID4.3b CASSYDSGTGELFF (SEQ ID NO:9) Seq-ID4.4b CASSYDSGTGELFF (SEQ ID NO:9)

[0212] Cluster 4 Block J / C GEGSRLTVLEDLKNVFPPKVAVFEPSEAEISHTQKATLVCLATGFYPDHVELSWWVNGKEVHSGVSTDPQPLKEQPALNDSRYCLSSRLRVSATFWQNPRNHFRCQVQFYGLSENDEWTQDRAKPVTQIVSAEAWGRADCGFTSESYQQGVLSATILYEILLGKATLYAVLVSALVLMAMVKRKDSRG (SEQ ID NO: 34) Alpha-chain, TRA: TRAV19*01, TRAJ49*01, TRAC*01

[0213] Cluster 4 Block V ATGCTGACTGCCAGCCTGTTGAGGGCAGTCATAGCCTCCATCTGTGTTGTATCCAGCATGGCTCAGAAGGTAACTCAAGCGCAGACTGAAATTTCTGTGGTGGAGAAGGAGGATGTGACCTTGGACTGTGTGTATGAAACCCGTGATACTACTTATTACTTATTCT GGTACAAGCAACCACCAAGTGGAGAATTGGTTTTCCTTATTCGTCGGAACTCTTTTGATGAGCAAAATGAAATAAGTGGTCGGTATTCTTGGAACTTCCAGAAATCCACCAGTTCCTTCAACTTCACCATCACAGCCTCACAAGTCGTGGACTCAGCAGTATACTTC (Sequence number 149)

[0214] Seq-ID4.1a TGTGCTCTGAGTGAAACCGGTAACCAGTTCTATTTT (SEQ ID NO:114) Seq-ID4.2a TGTGCTCTGAGTGAGACCGGTAACCAGTTCTATTTT (SEQ ID NO:91) Seq-ID4.3a TGTGCTCTGAGTGACACCGGTAACCAGTTCTATTTT (SEQ ID NO:99) Seq-ID4.4a TGTGCTCTGAGTGACACCGGTAACCAGTTCTATTTT (SEQ ID NO:99)

[0215] Cluster 4 Block J / C GGGACAGGGACAAGTTTGACGGTCATTCCAAATATCCAGAACCCTGACCCTGCCGTGTACCAGCTGAGAGACTCTAAATCCAGTGACAAGTCTGTCTGCCTATTCACCGATTTTGATTCTCAAACAAATGTGTCACAAAGTAAGGATTCTGATGTGTATATCACAGACAAAACTGTGCTAGACATGAGGTCTATGGACTTCAAGAGCAACAGTGCTGTGGCCTGGAGCAACAAATCTGACTTTGCATGTGCAAACGCCTTCAACAACAGCATTATTCCAGAAGACACCTTCTTCCCCAGCCCAGAAAGTTCCTGTGATGTCAAGCTGGTCGAGAAAAGCTTTGAAACAGATACGAACCTAAACTTTCAAAACCTGTCAGTGATTGGGTTCCGAATCCTCCTCCTGAAAGTGGCCGGGTTTAATCTGCTCATGACGCTGCGGCTGTGGTCCAGCTGA (SEQ ID NO: 76)

[0216] Cluster 4 Block V MLTASLLRAVIASICVVSSMAQKVTQAQTEISVVEKEDVTLDCVYETRDTTYYLFWYKQPPSGELVFLIRRNSFDEQNEISGRYSWNFQKSTSSFNFTITASQVVDSAVYF (SEQ ID NO: 49)

[0217] Seq-ID4.1a CALSETGNQFYF (SEQ ID NO: 52) Seq-ID4.2a CALSETGNQFYF (SEQ ID NO: 52) Seq-ID4.3a CALSDTGNQFYF (SEQ ID NO: 29) Seq-ID4.4a CALSDTGNQFYF (SEQ ID NO: 29)

[0218] Cluster 4 Block J / C GTGTSLTVIPNIQNPDPAVYQLRDSKSSDKSVCLFTDFDSQTNVSQSKDSDVYITDKTVLDMRSMDFKSNSAVAWSNKSDFACANAFNNSIIPEDTFFPSPESSCDVKLVEKSFETDTNLNFQNLSVIGFRILLLKVAGFNLLMTLRLWSS (SEQ ID NO: 66)

[0219] [Table 8]

[0220] Cluster ID 5: Cluster 5 combines with HLA-A*01:01, HLA-A*02:01 or HLA-C*02:02. Beta chain, TRB: TRBV5-1*01, TRBJ2-7*01, TRBC2*01

[0221] Cluster 5 Block V ATGGGCTCCAGGCTGCTCTGTTGGGTGCTGCTTTGTCTCCTGGGAGCAGGCCCAGTAAAGGCTGGAGTCACTCAAACTCCAAGATATCTGATCAAAACGAGAGGACAGCAAGTGACACTGAGCTGCTCCCCTATCTCTGGGCATAGGAGTGTATCCTGGTACC AACAGACCCCAGGACAGGGCCTTCAGTTCCTCTTTGAATACTTCAGTGAGACACAGAGAAACAAAGGAAACTTCCCTGGTCGATTCTCAGGGCGCCAGTTCTCTAACTCTCGCTCTGAGATGAATGTGAGCACCTTGGAGCTGGGGGACTCGGCCCTTTATCTT (Sequence number 116)

[0222] Seq-ID5.1b TGCGCCAGCAGCTTGGAAGGACAGGCGAGCTCCTACGAGCAGTACTTC (SEQ ID NO:75) Seq-ID5.2b TGCGCCAGCAGCTTGGAGGGTCAGGCCAGCTCCTACGAGCAGTACTTC (SEQ ID NO:156)

[0223] Cluster 5 Block J / C GGGCCGGGCACCAGGCTCACGGTCACAGAGGACCTGAAAAACGTGTTCCCACCCAAGGTCGCTGTGTTTGAGCCATCAGAAGCAGAGATCTCCCACACCCAAAAGGCCACACTGGTGTGCCTGGCCACAGGCTTCTACCCCGACCACGTGGAGCTGAGCTGGTGGGTGAATGGGAAGGAGGTGCACAGTGGGGTCAGCACAGACCCGCAGCCCCTCAAGGAGCAGCCCGCCCTCAATGACTCCAGATACTGCCTGAGCAGCCGCCTGAGGGTCTCGGCCACCTTCTGGCAGAACCCCCGCAACCACTTCCGCTGTCAAGTCCAGTTCTACGGGCTCTCGGAGAATGACGAGTGGACCCAGGATAGGGCCAAACCTGTCACCCAGATCGTCAGCGCCGAGGCCTGGGGTAGAGCAGACTGTGGCTTCACCTCCGAGTCTTACCAGCAAGGGGTCCTGTCTGCCACCATCCTCTATGAGATCTTGCTAGGGAAGGCCACCTTGTATGCCGTGCTGGTCAGTGCCCTCGTGCTGATGGCCATGGTCAAGAGAAAGGATTCCAGAGGCTAG (SEQ ID NO: 80)

[0224] Cluster 5 Block V MGSRLLCWVLLCLLGAGPVKAGVTQTPRYLIKTRGQQVTLSCSPISGHRSVSWYQQTPGQGLQFLFEYFSETQRNKGNFPGRFSGRQFSNSRSEMNVSTLELGDSALYL (SEQ ID NO: 43)

[0225] Seq-ID5.1b CASSLEGQASSYEQYF (SEQ ID NO: 61) Seq-ID5.2b CASSLEGQASSYEQYF (SEQ ID NO: 61)

[0226] Cluster 5 Block J / C GPGTRLTVTEDLKNVFPPKVAVFEPSEAEISHTQKATLVCLATGFYPDHVELSWWVNGKEVHSGVSTDPQPLKEQPALNDSRYCLSSRLRVSATFWQNPRNHFRCQVQFYGLSENDEWTQDRAKPVTQIVSAEAWGRADCGFTSESYQQGVLSATILYEILLGKATLYAVLVSALVLMAMVKRKDSRG (SEQ ID NO: 69) Alpha-chain, TRA: TRAV25*01, TRAJ28*01, TRAC*01

[0227] Cluster 5 Block V ATGCTACTCATCACATCAATGTTGGTCTTATGGATGCAATTGTCACAGGTGAATGGACAACAGGTAATGCAAATTCCTCAGTACCAGCATGTACAAGAAGGAGAAGACTTCACCACGTACTGCAATTCCTCAACTACTTTAAGCAATATACAGTGGTATAAGCAAAGGCCTGGTGGACATCCCGTTTTTTTGATACAGTTAGTGAAGAGTGGAGAAGTGAAGAAGCAGAAAAGACTGACATTTCAGTTTGGAGAAGCAAAAAAGAACAGCTCCCTGCACATCACAGCCACCCAGACTACAGATGTAGGAACCTACTTC (SEQ ID NO: 105)

[0228] Seq-ID5.1a TGTGCAGGATCTGGGGCTGGGAGTTACCAACTCACTTTC (SEQ ID NO: 126) Seq-ID5.2a TGTGCTGGGGCTGGGGCTGGGAGTTACCAACTCACTTTC (SEQ ID NO: 135)

[0229] Cluster 5 Block J / C GGGAAGGGGACCAAACTCTCGGTCATACCAAATATCCAGAACCCTGACCCTGCCGTGTACCAGCTGAGAGACTCTAAATCCAGTGACAAGTCTGTCTGCCTATTCACCGATTTTGATTCTCAAACAAATGTGTCACAAAGTAAGGATTCTGATGTGTATATCACAGACAAAACTGTGCTAGACATGAGGTCTATGGACTTCAAGAGCAACAGTGCTGTGGCCTGGAGCAACAAATCTGACTTTGCATGTGCAAACGCCTTCAACAACAGCATTATTCCAGAAGACACCTTCTTCCCCAGCCCAGAAAGTTCCTGTGATGTCAAGCTGGTCGAGAAAAGCTTTGAAACAGATACGAACCTAAACTTTCAAAACCTGTCAGTGATTGGGTTCCGAATCCTCCTCCTGAAAGTGGCCGGGTTTAATCTGCTCATGACGCTGCGGCTGTGGTCCAGCTGA (SEQ ID NO: 153)

[0230] Cluster 5 Block V MLLITSMLVLWMQLSQVNGQQVMQIPQYQHVQEGEDFTTYCNSSTTLSNIQWYKQRPGGHPVFLIQLVKSGEVKKQKRLTFQFGEAKKNSSLHITATQTTDVGTYF (SEQ ID NO: 35)

[0231] Seq-ID5.1a CAGSGAGSYQLTF (SEQ ID NO: 13) Seq-ID5.2a CAGAGAGSYQLTF (SEQ ID NO: 65)

[0232] Cluster 5 Block J / C GKGTKLSVIPNIQNPDPAVYQLRDSKSSDKSVCLFTDFDSQTNVSQSKDSDVYITDKTVLDMRSMDFKSNSAVAWSNKSDFACANAFNNSIIPEDTFFPSPESSCDVKLVEKSFETDTNLNFQNLSVIGFRILLLKVAGFNLLMTLRLWSS (SEQ ID NO:40)

[0233] [Table 9]

[0234] Cluster ID 6: Cluster 6 is associated with HLA-B*15:01. Beta chain, TRB: TRBV19*01, TRBJ2-1*01, TRBC2*01

[0235] Cluster 6 Block V ATGAGCAACCAGGTGCTCTGCTGTGGTCCTTTGTTTCCTGGGAGCAAACACCGTGGATGGTGGAATCACTCAGTCCCCAAAGTACCTGTCAGAAAGGAAGGACAGAATGTGACCCTGAGTTGTGAACAGAATTTGAACCACGATGCCATGTACTGGTACC GACAGGACCCAGGGCAAGGGCTGAGATTGATCTACTACTCACAGATAGTAAATGACTTTCAGAAAGGAGATATAGCTGAAGGGTACAGCGTCTCTCGGGAAGAAGGAATCCTTTCCTCTCACTGTGACATCGGCCCAAAAGAACCCGACAGCTTTCTATCTC (Sequence number 109)

[0236] Seq-ID6.1b TGTGCCAGTAGTATTGGCAGCGGGAGTTACAATGAGCAGTTCTTC (SEQ ID NO:118) Seq-ID6.2b TGTGTGGTGAGCGCCGGGAGGGAATATGGAAACAAACTGGTCTTT (SEQ ID NO:94) Seq-ID6.3b TGTGCCAGTAGTCGGACTAGCGGGAGTCTTAATGAGCAGTTCTTC (Sequence number 93) Seq-ID6.4b TGTGCCAGTACCGTAACAAGCGGGAGCTACAATGAGCAGTTCTTC (Sequence number 117) Seq-ID6.5b TGTGCCAGTAGTCTCACTAGCGGTTCCTACAATGAGCAGTTCTTC (Sequence number 95)

[0237] Cluster 6 Block J / C GGGCCAGGGACACGGCTCACCGTGCTAGAGGACCTGAAAAACGTGTTCCCACCCAAGGTCGCTGTGTTTGAGCCATCAGAAGCAGAGATCTCCCACACCCAAAAGGCCACACTGGTGTGCCTGGCCACAGGCTTCTACCCCGACCACGTGGAGCTGAGCTGGTGGGTGAATGGGAAGGAGGTGCACAGTGGGGTCAGCACAGACCCGCAGCCCCTCAAGGAGCAGCCCGCCCTCAATGACTCCAGATACTGCCTGAGCAGCCGCCTGAGGGTCTCGGCCACCTTCTGGCAGAACCCCCGCAACCACTTCCGCTGTCAAGTCCAGTTCTACGGGCTCTCGGAGAATGACGAGTGGACCCAGGATAGGGCCAAACCTGTCACCCAGATCGTCAGCGCCGAGGCCTGGGGTAGAGCAGACTGTGGCTTCACCTCCGAGTCTTACCAGCAAGGGGTCCTGTCTGCCACCATCCTCTATGAGATCTTGCTAGGGAAGGCCACCTTGTATGCCGTGCTGGTCAGTGCCCTCGTGCTGATGGCCATGGTCAAGAGAAAGGATTCCAGAGGCTAG (Sequence number 113)

[0238] Cluster 6 Block V MSNQVLCCVVLCFLGANTVDGGITQSPKYLFRKEGQNVTLSCEQNLNHDAMYWYRQDPGQGLRLIYYSQIVNDFQKGDIAEGYSVSREKKESFPLTVTSAQKNPTAFYL (Sequence number 36)

[0239] Seq-ID6.1b CASSIGSGSYNEQFF (SEQ ID NO:10) Seq-ID6.2b CASSLTSGNYNEQFF (SEQ ID NO:42) Seq-ID6.3b CASSRTSGSLNEQFF (SEQ ID NO:7) Seq-ID6.4b CASTVTSGSYNEQFF (SEQ ID NO:44) Seq-ID6.5b CASSLTSGSYNEQFF (SEQ ID NO:17)

[0240] Cluster 6 Block J / C GPGTRLTVLEDLKNVFPPKVAVFEPSEAEISHTQKATLVCLATGFYPDHVELSWWVNGKEVHSGVSTDPQPLKEQPALNDSRYCLSSRLRVSATFWQNPRNHFRCQVQFYGLSENDEWTQDRAKPVTQIVSAEAWGRADCGFTSESYQQGVLSATILYEILLGKATLYAVLVSALVLMAMVKRKDSRG (SEQ ID NO:56) Alpha-chain, TRA: TRAV10*01, TRAJ47*01, TRAC*01

[0241] Cluster 6 Block V ATGAAAAAGCATCTGACGACCTTCTTGGTGATTTTGTGGCTTTATTTTTATAGGGGGAATGGCAAAAACCAAGTGGAGCAGAGTCCTCAGTCCCTGATCATCCTGGAGGGAAAGAACTGCACTCTTCAATGCAATTATACAGTGAGCCCCTTCAGCAACTTAAGG TGGTATAAGCAAGATACTGGGAGAGGTCCTGTTTCCCTGACAATCATGACTTTCAGTGAGAACACAAAGTCGAACGGAAGATATACAGCAACTCTGGATGCAGACACAAAGCAAAGCTCTCTGCACATCACAGCCTCCAGCTCAGCGATTCAGCCTCCTACATC (Sequence number 150)

[0242] Seq-ID6.1a TGTGTGGTGAGCGCGGGGAGGGAATATGGAAACAAACTGGTCTTT (SEQ ID NO:122) Seq-ID6.2a TGTGTGGTGAGCGCCGGGAGGGAATATGGAAACAAACTGGTCTTT (SEQ ID NO:94) Seq-ID6.3a TGTGTGGTGACCGCGGGGAGGGAATATGGAAACAAACTGGTCTTT (SEQ ID NO:130) Seq-ID6.4a TGTGTGGTGAGCGCGGGGAGGGAATATGGAAACAAACTGGTCTTT (SEQ ID NO:122) Seq-ID6.5a TGTGTGGTGAGCGTTGGAAGGGAATATGGAAACAAACTGGTCTTT (SEQ ID NO:82)

[0243] Cluster 6 Block J / C GGCGCAGGAACCATTCTGAGAGTCAAGTCCTATATCCAGAACCCTGACCCTGCCGTGTACCAGCTGAGAGACTCTAAATCCAGTGACAAGTCTGTCTGCCTATTCACCGATTTTGATTCTCAAACAAATGTGTCACAAAGTAAGGATTCTGATGTGTATATCACAGACAAAACTGTGCTAGACATGAGGTCTATGGACTTCAAGAGCAACAGTGCTGTGGCCTGGAGC AACAAATCTGACTTTGCATGTGCAAACGCCTTCAACAACAGCATTATTCCAGAAGACACCTTCTTCCCCAGCCCAGAAAGTTCCTGTGATGTCAAGCTGGTCGAGAAAAGCTTTGAAACAGATACGAACCTAAACTTTCAAAACCTGTCAGTGATTGGGTTCCGAATCCTCCTCCTGAAAGTGGCCGGGTTTAATCTGCTCATGACGCTGCGGCTGTGGTCCAGCTGA (Sequence number 137)

[0244] Cluster 6 Block V MKKHLTTFLVILWLYFYRGNGKNQVEQSPQSLIILEGKNCTLQCNYTVSPFSNLRWYKQDTGRGPVSLTIMTFSENTKSNGRYTATLDADTKQSSLHITASQLSDSASYI (SEQ ID NO: 14)

[0245] Seq-ID6.1a CVVSAGREYGNKLVF (SEQ ID NO:25) Seq-ID6.2a CVVSAGREYGNKLVF (SEQ ID NO:25) Seq-ID6.3a CVVTAGREYGNKLVF (SEQ ID NO:5) Seq-ID6.4a CVVSAGREYGNKLVF (SEQ ID NO:25) Seq-ID6.5a CVVSVGREYGNKLVF (SEQ ID NO:46)

[0246] Cluster 6 Block J / C GAGTILRVKSYIQNPDPAVYQLRDSKSSDKSVCLFTDFDSQTNVSQSKDSDVYITDKTVLDMRSMDFKSNSAVAWSNKSDFACANAFNNSIIPEDTFFPSPESSCDVKLVEKSFETDTNLNFQNLSVIGFRILLLKVAGFNLLMTLRLWSS (SEQ ID NO: 50)

Claims

1. A method for identifying a common tumor-specific T cell receptor (TCR), said method comprising the following steps: a. Obtaining a plurality of tumor-specific TCR sequences from each of n (n>1) patients by the following steps: i. In a step based on tumor sequences, determining the frequency of each of the plurality of tumor TCR sequences by the following steps; I. Providing an isolated tumor sample obtained from said patient; II. Isolating tumor T cells from said tumor sample; III. Obtaining a plurality of tumor TCR nucleic acid sequences; IV. Grouping tumor TCR nucleic acid sequences that are essentially identical into tumor TCR clone type groups and counting the tumor TCR nucleic acid sequences of each tumor TCR clone type group; V. Determining the frequency of each tumor TCR by dividing the number of tumor TCR nucleic acid sequences in each tumor TCR clone type group by the number of all tumor TCR nucleic acid sequences; ii. In a step based on non-tumor sequences, determining the frequency of each of the plurality of non-tumor TCR sequences by the following steps; I. Providing an isolated non-tumor tissue sample obtained from said patient; II. Isolating non-tumor T cells from said non-tumor tissue sample; III. Obtaining a plurality of non-tumor TCR nucleic acid sequences; IV. Grouping non-tumor TCR nucleic acid sequences into one non-tumor TCR clone type group that is essentially identical and counting the non-tumor TCR nucleic acid sequences of each tumor TCR clone type group; V. Determining the frequency of each non-tumor TCR by dividing the number of non-tumor TCR nucleic acid sequences in each non-tumor TCR clone type group by the number of all non-tumor TCR nucleic acid sequences; iii. In a tumor-specific selection step, selecting a TCR nucleic acid sequence as a tumor-specific TCR sequence if the frequency of the tumor TCR is higher than the frequency of the non-tumor TCR; b. Selecting a common tumor-specific TCR sequence by the following steps: i. Translating the tumor-specific TCR nucleic acid sequence into a tumor-specific TCR amino acid sequence; ii. Determining the CDR3 region of said tumor-specific TCR amino acid sequence of said n patients; iii. Aligning the CDR3 regions of said plurality of tumor-specific TCR amino acid sequences of said n patients; iv. Grouping TCR sequences into one TCR clone type cluster if the CDR3 region differs by 3 amino acids (AA) / CDR3 or less, particularly 2 amino acids / CDR3 or less, more particularly 1 amino acid / CDR3 or less, and most particularly if there is no difference; v. In the common TCR selection step, when TCR clone type clusters are present in at least two patients, select the cluster of TCR sequences as the common tumor-specific TCR sequences.

2. The method according to claim 1, wherein the tumor samples of the number of n patients are of the same tissue type.

3. The method according to any one of claims 1 to 2, wherein the non-tumor tissue sample is of the same tissue type as the tumor sample.

4. The method according to any one of claims 1 to 3, wherein it is determined that a plurality of patients commonly have at least one gene of the same HLA type.

5. The method according to claim 4, wherein a plurality of patients are determined to commonly have the genes of the same HLA type, particularly exactly one gene of the same HLA type, and the common tumor-specific TCR is assigned to the HLA type-specific TCR.

6. The method according to any one of claims 1 to 5, wherein the common tumor-specific TCR is assigned to the HLA type-specific TCR by the following steps: a. Selecting all patients in whom the common tumor-specific TCR sequences are present; b. Determining the HLA genes present in the selected patients; c. Assigning the common tumor-specific TCR to the HLA type-specific TCR when a common HLA gene, particularly exactly one common HLA gene, is present in all the selected patients.

7. In the tumor-specific selection step (a.iii.), when the frequency of the tumor TCR clone type group is 2 times, particularly 3 times, more particularly 5 times, and even more particularly 10 times higher than the frequency of the non-tumor TCR clone type group, the TCR sequence is selected as the tumor-specific TCR sequence. The method according to any one of claims 1 to 6.

8. The method according to any one of claims 1 to 7, wherein the number of patients n is 2 to 100, particularly n is 10 to 50, and more particularly n is 20 to 30.

9. The common TCR selection step (step b.v) further includes measuring markers selected from T cell activation / exhaustion / differentiation markers, particularly PDCD1 (PD1), TIGIT, LAG3, HAVCR2 (TIM3), CTLA4, IFNγ, TNF, GZMB, TNFRSF9 (CD137, 4-1BB), CD45 (CD45RA / RO), CD69, LAMP1 (CD107a), TBX21 (T-BET), TCF7 (TCF-1), EOMES, TOX, and RUNX3, and the TCR sequence is selected as a common tumor-specific TCR sequence when T cells having the TCR express one or more T cell activation / exhaustion / differentiation markers or combinations thereof. The method according to any one of claims 1 to 8.

10. A method for identifying a common tumor-specific antigen, said method comprising the following steps: a. Identifying the common tumor-specific TCR according to any one of claims 1 to 9 from a number n (n>1) of patients; b. Obtaining a plurality of tumor-specific polypeptides by the following steps: (1) Obtaining a plurality of tumor-specific mRNA sequences from each of said patients from said patients by the following steps: i. In a step based on the mRNA tumor sequence, determining a plurality of tumor mRNA sequences by the following steps: I. Isolating a tumor RNA preparation from a tumor sample from said patient; II. Obtaining a plurality of tumor mRNA sequences from said tumor RNA preparation; ii. In a step based on the mRNA non-tumor sequence, determining a plurality of non-tumor mRNA sequences by the following steps: I. Isolating a non-tumor RNA preparation from said non-tumor tissue sample from said patient; II. Obtaining a plurality of non-tumor mRNA sequences from said tumor RNA preparation; iii. In the mRNA tumor-specific selection step, selecting tumor-specific mRNA sequences by the following steps; I. Aligning a plurality of tumor mRNA sequences and a plurality of non-tumor mRNA sequences; II. Selecting as tumor-specific RNA sequences the mRNA sequences that are present in the tumor sample and absent in the non-tumor sample; (2) Selecting a plurality of tumor-specific polypeptides by the following steps: i. Translating said plurality of tumor-specific RNA sequences into a plurality of tumor-specific amino acid sequences; ii. Aligning the plurality of tumor-specific amino acid sequences from a plurality of n patients; iii. Grouping amino acid sequences into one polypeptide cluster when the amino acid sequences have sequence identity of ≧80%, ≧85%, ≧90%, ≧92%, ≧94%, ≧96%, ≧98%, or ≧99%; iv. Selecting multiple polypeptide clusters of amino acid sequences as tumor-specific polypeptides when the tumor-specific amino acid sequences are present in all of n patients; c. For each member of the multiple tumor-specific polypeptides, expressing the member in an antigen-presenting cell; d. For each antigen-presenting cell, detecting whether the antigen-presenting cell can activate T cells expressing the common tumor-specific TCR; e. Selecting a tumor-specific polypeptide as a common tumor-specific antigen, the selection being made when an antigen-presenting cell expressing the tumor-specific polypeptide can activate the T cells expressing the common tumor-specific TCR.

11. The method according to claim 10, further isolating a peptide presented on an HLA molecule on an antigen-presenting cell expressing the common tumor-specific antigen and characterizing it by mass spectrometry.

12. Thereafter a. Fragmenting the antigen found by the method of claim 10 into peptides; b. Loading each peptide onto an HLA molecule on an antigen-presenting cell; c. The method according to claim 10, for each antigen-presenting cell, detecting whether the antigen-presenting cell can activate T cells expressing a common tumor-specific TCR.

13. The tumor sample and the non-tumor tissue sample are derived from the same tissue sample, and isolating the tumor RNA preparation from the tissue sample is performed separately from the single tumor cells and non-tumor cells obtained from the tissue sample, the method according to claim 10, 11 or 12.

14. A method for identifying a common tumor-specific antigen, the method comprising the following steps: a. Identifying the common tumor-specific TCR according to any one of claims 1 to 13 from the number n (n>1) of patients; b. Contacting T cells expressing the common tumor-specific TCR with tumor cells, where the tumor cells are from a tumor cell line, and detecting whether the tumor cells can activate T cells resulting in cells from a tumor cell line expressing a common tumor-specific antigen; c. Optionally repeating step b using different tumor cell lines; d. preparing a cDNA library from cells derived from a tumor cell line expressing a common tumor-specific antigen; e. for each member of the cDNA, expressing the member in an antigen-presenting cell; g. for each antigen-presenting cell, detecting whether the antigen-presenting cell can activate T cells expressing the common tumor-specific TCR; h. selecting cDNA as a common tumor-specific antigen, the selection being made when the antigen-presenting cell expressing the cDNA can activate the T cells expressing the common tumor-specific TCR.

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