Bioinformatics

Abstract

This invention relates to an apparatus and a method for identifying tumor antigens; tumor antigens identified after using the apparatus and / or method; pharmaceutical compositions comprising the tumor antigens; methods for treating cancer using the apparatus and / or method; methods for stratifying patients for cancer treatment using the apparatus and / or method; treatment regimens involving stratifying patients for cancer treatment using the apparatus and / or method followed by administration of cancer therapeutic agents; and the use of tumor antigens identified using the apparatus and / or method as cancer vaccines, immunogenic agents, or cancer therapies.

Description

Technical Field

[0001] This invention relates to an apparatus and a method for identifying tumor antigens; tumor antigens identified after using the apparatus and / or method; pharmaceutical compositions comprising the tumor antigens; methods for treating cancer using the apparatus and / or method; methods for stratifying patients for cancer treatment using the apparatus and / or method; treatment regimens involving stratifying patients for cancer treatment using the apparatus and / or method followed by administration of cancer therapeutic agents; and the use of tumor antigens identified using the apparatus and / or method as cancer vaccines, immunogenic agents, or cancer therapies. Background Technology

[0002] CD8 + T cells play a crucial role in detecting and eliminating cells that exhibit abnormal peptides on their surface due to pathogen infection (such as viral infection) or malignant transformation. T cell receptor (TCR) cross-reactivity refers to the ability of T cells to recognize a wide variety of different target peptides. This phenomenon allows a relatively small number of T cells to recognize a variety of pMHC (peptide: major histocompatibility complex) molecules that represent abnormal cells and thus potentially threaten health or life.

[0003] However, a less desirable side effect of this mechanism is that the immune response against pathogens may overcome the tolerance threshold to highly homologous self-antigens, resulting in harmful off-target effects mediated by T-cell cross-reactivity; this process is known as molecular mimicry. The potentially harmful consequences of this homology between self-peptides and pathogenic peptides are well-known in the field of autoimmunity; however, it has not yet been explored in cancer.

[0004] In fact, it has long been believed that the best prognostic marker for successful cancer immunotherapy is a high rate of tumor antigen mutations and abundant T-cell infiltration. This idea is based on the fact that tumors with a large number of mutations have a higher chance of being recognized and eliminated by infiltrating T cells.

[0005] However, some studies have shown that the quality characteristics of tumor antigens may be more important than their quantity. In addition, the presence of antiviral T cells in the tumor microenvironment has been observed

[28] , but it remains unclear whether their role is active or merely that of bystanders.

[0006] Tumor immunology and immunotherapy have completely transformed cancer treatment over the past decade, particularly with the use of checkpoint inhibitors (ICIs), which have shown remarkable clinical efficacy, unfortunately only in a small number of patients. It is becoming increasingly clear that immunotherapy using ICIs only works fully when targeting specific tumor antigens. However, there is currently no simple and rapid method to identify these tumor antigens.

[0007] Here, we hypothesize that tumors may exhibit high homology or affinity scores with pathogen-derived peptides (especially viral peptides), which could enable pathogen-generated cross-reactive T cells to recognize and kill tumor cells.

[0008] To this end, we developed a bioinformatics device called HEX (homology assessment of xenopeptides), which can automatically and very simply identify tumor antigens that are highly similar to viral peptides. Using this device, we observed that antiviral T-cell immunity mediated by peptides with high homology or affinity to cancer antigens can actively control tumor growth in both prophylactic and therapeutic cases. This observation indicates that activated T cells have cross-reactivity to homologous virus-derived peptides and tumor-derived peptides.

[0009] Subsequently, we also found that humoral responses to cytomegalovirus (CMV) can stratify the response of melanoma patients to checkpoint inhibitor therapy (anti-PD1). In fact, peptides homologous to CMV and melanoma, identified using the HEX device, were found to promote the release of Inf-g in peripheral blood mononuclear cells (PBMCs) of CMV seropositive melanoma patients. Summary of the Invention

[0010] According to a first aspect of the present invention, an apparatus for identifying tumor antigens is provided, comprising:

[0011] At least one flow channel containing a plurality of supports to which at least one molecule or at least one complex is attached, wherein at least one anti-MHC (major histocompatibility complex) antibody or at least one anti-human leukocyte antigen (HLA) antibody is bound, thereby enabling the extraction of pMHC (peptide: major histocompatibility complex) from the sample flowing through the channel using the at least one antibody.

[0012] The anti-pan-HLA antibodies mentioned in this article refer to antibodies that recognize or are specific to any different HLA present in mammals (especially humans).

[0013] More ideally, the antibody recognizes or is specific to a particular HLA type such as MHC-I, which is selected from at least one of the following groups: MHC I class A, B, and C.

[0014] Alternatively or alternatively, the antibody recognizes or is specific to a particular HLA type such as MHC-II, which is selected from at least one of the following: MHC class II DP, DM, DO, DQ and DR.

[0015] However, more preferably, the antibody is anti-human.

[0016] In a preferred embodiment of the invention, the molecule or complex is a complex of thiols and alkyl (“ene”) functional groups, ideally comprising a stoichiometric ratio of 1.5 to 1.0 in the range of 0.15:0.1-1500:1000 (tetrathiol:triallyl).

[0017] More ideally, the device is manufactured based on a photoreaction initiated by ultraviolet light between thiols and alkyl (“ene”) functional groups. In another preferred embodiment of the invention, the device is made by ultraviolet photopolymerization with biotin-PEG4-alkynyl (Sigma, 764213). This is followed by a reaction with avidin: streptavidin. Nevertheless, attaching avidin to the bio before attaching the biotic to the column is within the scope of the invention, and vice versa.

[0018] In another preferred embodiment, the device is functionalized by reacting the antibody with the streptavidin. Ideally, more than one antibody reacts with the streptavidin, such that each streptavidin-functionalized complex carries multiple (e.g., two or three) of the antibodies, such as multiple anti-pan-HLA antibodies.

[0019] In another preferred embodiment of the invention, after streptavidin functionalization and before antibody binding, the microcolumn array is pretreated with a protein such as bovine serum albumin (BSA) (ideally 100 μg / mL, incubated in 15 mM PBS for 10 minutes).

[0020] In a more preferred aspect of the invention, the support comprises a plurality of micropillars, such as those present in a microfluidic device, and preferably, the micropillars are arranged in an array within the device. Ideally, the micropillars are made of the same or similar components as those used in conventional microfluidic devices (e.g., for implementing immobilized enzyme reactions).

[0021] According to another aspect of the present invention, a method for identifying tumor antigens is provided, comprising:

[0022] i) Dissolve or suspend the tumor sample in a liquid;

[0023] ii) Passing the liquid through a device for tumor antigen identification, the device comprising: at least one flow channel containing a plurality of supports to which at least one molecule or at least one complex is attached, the molecule or complex being bound to at least one anti-MHC (major histocompatibility complex) antibody or at least one anti-pan-human leukocyte antigen (HLA) antibody, thereby enabling the extraction of pMHC (peptide: major histocompatibility complex) from the sample flowing through the channel using the at least one antibody;

[0024] iii) Bind the at least one antibody to at least one pMHC (peptide: major histocompatibility complex) in the sample;

[0025] iv) Optionally, remove at least one of the bound pMHC (peptide: major histocompatibility complex) from the device in part iii);

[0026] v) The peptide of the bound pMHC (peptide: major histocompatibility complex) is compared with a pathogen-derived antigen library to determine whether the peptide shows homology or affinity (molecular mimicry) with at least one pathogen-derived antigen or a portion thereof, and wherein greater than 60% homology / affinity is present.

[0027] vi) Identify the peptide as a tumor antigen for cancer therapy.

[0028] In a preferred embodiment of any aspect of the invention, the homology / affinity can be any one of the following percentages: 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, and 100%.

[0029] The homology / affinity mentioned in this article includes comparisons of the sequence structure of the above v) portion using one of the following: homology / affinity as defined herein; or identity, which is determined by the number of identical residues at a defined length in a given alignment; or similarity, which is determined by the number of identical residues or conservative substitutions at a defined length in a given alignment that have similar physicochemical properties.

[0030] In a preferred method of the present invention, the library is a human pathogen-derived antigen, comprising a curated library of antigens derived from known pathogens, ideally derived from pathogenic viruses, or more preferably their proteomes, which infect mammals, ideally humans, such as any one or more, or ideally any combination of, the following viruses:

[0031] Abyssoviridae; Ackermannviridae; Actantavirinae; Adenoviridae; Agantavirinae; Aglimvirinae; Alloherpesviridae; Alphaflexiviridae; Alphaherpesvirinae; Alphairidovirinae; Alphasatellitidae; Alphatetraviridae; Alvernaviridae; Amalgaviridae; Amnoonviridae;

[0032] Ampullaviridae; Anelloviridae; Arenaviridae; Arquatrovirinae; Arteriviridae; Artoviridae; Ascoviridae; Asfarviridae; Aspiviridae; Astroviridae; Autographivirinae; Avsunviroidae; Avulavirinae; Diatoms DNA Viridae (Bacilladnaviridae); Baculoviridae; Barnaviridae; Bastillevirinae; Bclasvirinae; Belpaoviridae; Benyviridae; Betaflexiviridae; Betaherpesvirinae; Betairidovirinae; Bicaudaviridae; Bidnaviviridae dae); Birnaviridae; Bornaviridae; Botourmiaviridae; Brockvirinae; Bromoviridae; Bullavirinae; Caliciviridae; Calvusvirinae; Carmotetraviridae; Caulimoviridae; Ceronivirinae; Chebruvirinae; Chordopoxvirinae irinae); Chrysoviridae; Chuviridae; Circoviridae; Clavaviridae; Closteroviridae; Comovirinae; Coronaviridae; Corticoviridae; Crocarterivirinae; Cruliviridae; Crustonivirinae; Cvivirinae; Cystoviridae; Dclasvirinae;Deltaflexiviridae; Densovirinae; Dicistroviridae; Endornaviridae; Entomopoxvirinae; Equarterivirinae; Eucampyvirinae; Euroniviridae; Filoviridae; Fimoviridae; Firstpapillomavirinae; Flaviviridae; Microspinifera Family: Fuselloviridae; Gammaflexiviridae; Gammaherpesvirinae; Geminialphasatellitinae; Geminiviridae; Genomoviridae; Globuloviridae; Gokushovirinae; Guernseyvirinae; Guttaviridae; Hantaviridae; Hepadnaviridae; Hepeviridae Herpesviridae; Herelleviridae; Heroarterivirinae; Herpesviridae; Hexponivirinae; Hypoviridae; Hytrosaviridae; Iflaviridae; Inoviridae; Iridoviridae; Jasinkavirinae; Kitaviridae; Lavidaviridae; Leishbuviridae; Letovirinae; Leviviridae Lipothrixviridae; Lispiviridae; Luteoviridae; Malacoherpesviridae; Mammantavirinae; Marnaviridae; Marseilleviridae; Matonaviridae; Mcleskeyvirinae; Mclasvirinae; Medioniviridae; Medionivirinae; Megabirnaviridae;Mesoniviridae; Metaparamyxovirinae; Metaviridae; Microviridae; Mimiviridae; Mononiviridae; Mononivirinae; Mymonaviridae; Myoviridae; Mypoviridae; Nairoviridae; Nanoalphasatellitinae; Nanoviridae; Naked RNAviridae; Nclasvirinae; Nimaviridae; Nodaviridae; Nudiviridae; Nyamiviridae; Nymbaxtervirinae; Okanivirinae; Orthocoronavirinae; Orthomyxoviridae; Orthoparamyxovirinae; Orthoretrovirinae;

[0033] Ounavirinae; Ovaliviridae; Papillomaviridae; Paramyxoviridae; Partitiviridae; Parvoviridae; Parvovirinae; Pclasvirinae; Peduovirinae; Peribunyaviridae; Permutotetraviridae; Phasmaviridae; Phenuiviridae; Phycodnaviridae ae); Picobirnaviridae; Picornaviridae; Picovirinae; Piscanivirinae; Plasmaviridae; Pleolipoviridae; Pneumoviridae; Podoviridae; Polycipiviridae; Polydnaviridae; Polyomaviridae; Portogloboviridae; Potato spindle tuber diseases Pospiviroidae; Potato Virus Y Family; Poxviridae; Procedovirinae; Pseudoviridae; Qinviridae; Quadriviridae; Quinvirinae; Regressovirinae; Remotovirinae; Reoviridae; Repantavirinae; Retroviridae; Rhabdoviridae; Roniviridae ae); Rubulavirinae; Rudiviridae; Sarthroviridae; Secondpapillomavirinae; Secoviridae; Sedovirinae; Sedoreovirinae; Sepvirinae; Serpentovirinae; Simarterivirinae; Siphoviridae; Smacoviridae; Solemoviridae; Solinviviridae; Sphaerolipoviridae;Spinareovirinae; Spiraviridae; Spounavirinae; Spumaretrovirinae; Sunviridae; Tectiviridae; Tevenvirinae; Tiamatvirinae; Tobaniviridae; Togaviridae; Tolecusatellitidae; Tombusviridae; Torovirinae; Tos poviridae; Totiviridae; Tristromaviridae; Trivirinae; Tunavirinae; Tunicanivirinae; Turriviridae; Twortvirinae; Tymoviridae; Vararterivirinae; Vequintavirinae; Virgaviridae; Wupedeviridae; Xinmoviridae; Yueviridae; and Zealarterivirinae.

[0034] More preferably, the pathogenic virus is cytomegalovirus (CMV) or Epstein-Barr virus (EBV), or even more preferably, herpesvirus, poxvirus, hepatotropic DNA virus, influenza virus, coronavirus, hepatitis virus, HIV, or Bunyavirus.

[0035] Most preferably, the virus is non-oncolytic, meaning its replication is not specifically confined to cancer cells.

[0036] In an alternative implementation, the virus is oncolytic, meaning it is capable of infecting and killing cancer cells by selectively replicating in both tumor and normal cells.

[0037] In a preferred method, the comparison of the bound pMHC (peptide: major histocompatibility complex) peptide with a pathogen-derived antigen library involves multiple scores (peptide affinity score, alignment score, similarity score, and MHC binding affinity score) to determine the homology / affinity, identity, or similarity. Most preferably, the score is a homology / affinity score as described below.

[0038] In one implementation, a matrix is ​​generated consisting of rows (or columns) representing amino acid positions in the tumor peptide and columns (or rows) representing each of 20 standard amino acids. Amino acid positions of the tumor peptide are assigned the same high score, while other positions are assigned the same low score as pathogen-derived antigens / peptides. Tumor peptides with the highest degree of homology / affinity to pathogen-derived antigens / peptides will receive the highest score in the following aspects (in descending order of priority):

[0039] a) The entire sequence structure (obviously, tumor peptides with 100% identity to pathogen-derived peptides will receive the highest score);

[0040] b) The identity of key amino acids in hotspots or critical binding sites; and

[0041] c) Hotspots or key binding sites contain the most key amino acids.

[0042] Alignment is calculated pairwise between the query (pathogen-derived) peptide group and the tumor group, and vice versa. For a given pair of peptides, their alignment is calculated by summing the distance scores between pairs of amino acids at the same position. The scores are weighted to give priority to similarity between more central amino acids in the peptide.

[0043] In addition, binding affinity for MHC class I was predicted. Methods to achieve the same effect are known in the art, such as using NetMHC (NetMHC 4.0 or NetMHCpan 4.1) via the application programming interface of IEDB (http: / / tools.iedb.org / main / tools-api / ), and then parsing and organizing within that tool.

[0044] In an alternative embodiment of the invention, the comparison involves inputting a list of tumor peptides of 8 to 12 amino acids in length into software. First, a BLAST tool is used to search for Hit (similar sequences) in a pathogen-derived antigen library. For this task, the PAM30 tool is generally used, but both BLOSUM and PAM substitution matrices support this at several evolutionary distances. Next, pairwise refinement alignments are performed using at least BLOSUM62, ideally with the substitution matrix developed by Kim et al. (described in BMC Bioinformatics. 2009; 10:394. Published 2009 Nov 30. doi:10.1186 / 1471-2105-10-394 Derivation of an amino acid similarity matrix for peptide: MHC binding and its application as a Bayesian prior. Kim Y, Sidney J, Pinilla C, Sette A, Peters B.) to refine the alignments in a position-weighted manner. Peptide pairs exhibiting high similarity in the TCR interaction region (the central portion of the peptide) received higher similarity scores. Finally, MHC binding affinity predictions for homologous peptides from tumors and viruses were performed using NetMHC4.0 or NetMHCpan4.1 as standalone command-line tools. These results were then automatically parsed and processed within the tools, creating a final score summarizing the analyses presented above.

[0045] According to another aspect of the invention, a cancer therapeutic agent, immunogenic agent, or cancer vaccine is provided, comprising a tumor antigen identified using any one or both of the above-described devices and / or methods.

[0046] According to another aspect of the invention, a tumor antigen for cancer treatment is provided, identified using any one or both of the above-described apparatus and / or methods.

[0047] According to another aspect of the invention, a tumor antigen is provided for manufacturing a medicament for treating cancer, wherein the antigen is identified using one or both of the above-described apparatus and / or methods.

[0048] Most preferably, the cancer therapeutic agent, immunogenic agent, cancer vaccine, or tumor antigen is any one or more listed in Tables 1-6.

[0049] According to another aspect of the present invention, a method for treating cancer patients is provided, comprising:

[0050] The tumor antigen is identified using the apparatus and / or method of the present invention, and then the tumor antigen is administered to an individual, or the tumor antigen is used to expand a population of T cells active against the tumor antigen, and then the T cells are administered to a patient.

[0051] In a preferred embodiment, the T cells are in vitro T cells and / or cultured T cells, whether allogeneic or autologous T cells.

[0052] According to another aspect of the invention, a pharmaceutical composition, immunogenic agent, or vaccine is provided, comprising the tumor antigen of the invention and a pharmaceutically acceptable carrier, adjuvant, diluent, or excipient.

[0053] Suitable pharmaceutical excipients are well known to those skilled in the art. Pharmaceutical compositions can be formulated and administered by any suitable route, such as intratumoral, intramuscular, intra-arterial, intravenous, intrapleural, intracystic, intracavitary, or intraperitoneal injection, oral, nasal, or bronchial (inhalation), transdermal, or parenteral administration, and can be prepared by any method well known in the pharmaceutical field.

[0054] This composition can be prepared by binding the aforementioned tumor antigen to a carrier. Generally, the preparation method involves uniformly and closely binding the tumor antigen to a liquid carrier or a small solid carrier, or both, and then shaping the product if necessary. This invention extends to methods for preparing pharmaceutical compositions comprising combining or binding a tumor antigen, as defined herein, to a pharmaceutically or veterinarily acceptable carrier or medium.

[0055] According to another aspect of the present invention, a combination therapeutic agent for treating cancer is provided, comprising: a tumor antigen identified using the device and / or method of the present invention and at least one additional cancer therapeutic agent.

[0056] Preferably, the additional cancer therapeutic agent includes cyclophosphamide, which is most suitable because it downregulates T regulatory cells. However, as those skilled in the art will understand, the additional therapeutic agent can be any anticancer agent known in the art.

[0057] Preferably, additional cancer treatment agents include checkpoint inhibitors (ICIs).

[0058] The optimal characteristic pathways for checkpoint inhibition are the cytotoxic T-lymphocyte protein 4 (CTLA-4) pathway and the programmed cell death protein 1 (PD-1 / PD-L1) pathway. Therefore, the present invention can be used in combination with at least one checkpoint modulator such as anti-CTLA-4, anti-PD1, or anti-PD-L1 molecules to counteract the immunosuppressive tumor environment and induce a strong anti-immune response.

[0059] According to another aspect of the present invention, a method for stratifying patients to receive checkpoint inhibitor cancer treatment is provided, comprising:

[0060] i) Extracting tumor samples from the patient;

[0061] ii) Dissolve or suspend the sample in a liquid;

[0062] iii) Passing the liquid through an apparatus for tumor antigen identification, the apparatus comprising: at least one flow channel containing a plurality of supports to which at least one molecule or at least one complex is attached, the complex being bound to at least one anti-MHC (major histocompatibility complex) antibody or at least one anti-pan-human leukocyte antigen (HLA) antibody, thereby enabling the extraction of pMHC (peptide: major histocompatibility complex) from the sample flowing through the channel using the at least one antibody;

[0063] iv) Bind the at least one antibody to at least one pMHC (peptide: major histocompatibility complex) in the sample;

[0064] v) Optionally, a portion of at least one bound pMHC (peptide: major histocompatibility complex) of iv) is removed from the device;

[0065] vi) The peptide of the bound pMHC (peptide: major histocompatibility complex) is compared with a library of human pathogen-derived antigens to determine whether the peptide shows sequence homology / affinity with at least one human pathogen-derived antigen or a portion thereof, and wherein there is greater than 60% homology / affinity.

[0066] vii) Identify the peptide as a tumor antigen; and

[0067] viii) When the peptide is detected, administer an effective amount of at least one checkpoint inhibitor (ICI) to the patient.

[0068] According to another aspect or embodiment of the present invention, a method for stratifying patients to receive checkpoint inhibitor cancer treatment is provided, comprising:

[0069] Determine if the patient is CMV seropositive; if so, select the patient to be treated with an effective dose of at least one checkpoint inhibitor (ICI).

[0070] According to another aspect of the present invention, a method for treating cancer is provided, comprising:

[0071] i) Extracting tumor samples from the patient;

[0072] ii) Dissolve or suspend the sample in a liquid;

[0073] iii) Passing the liquid through an apparatus for tumor antigen identification, the apparatus comprising: at least one flow channel containing a plurality of supports to which at least one molecule or at least one complex is attached, the molecule or complex being bound to at least one anti-MHC (major histocompatibility complex) antibody or at least one anti-pan-human leukocyte antigen (HLA) antibody, thereby enabling the extraction of pMHC (peptide: major histocompatibility complex) from the sample flowing through the channel using the at least one antibody;

[0074] iv) Bind the at least one antibody to at least one pMHC (peptide: major histocompatibility complex) in the sample;

[0075] v) Optionally, a portion of at least one bound pMHC (peptide: major histocompatibility complex) of iv) is removed from the device;

[0076] vi) The peptide of the bound pMHC (peptide: major histocompatibility complex) is compared with a library of human pathogen-derived antigens to determine whether the peptide shows sequence homology / affinity with at least one human pathogen-derived antigen or a portion thereof, and wherein there is greater than 60% homology / affinity.

[0077] vii) Identifying the peptide as a tumor antigen; and administering an effective amount of the peptide to the patient to stimulate or activate T cells against the tumor antigen and cancer samples extracted from it, or using the tumor antigen to expand a population of T cells active against the tumor antigen, and then administering the T cells to the patient.

[0078] According to another aspect or embodiment of the present invention, a method for treating cancer is provided, comprising:

[0079] Determine if the patient is CMV seropositive, and if so, administer an effective amount of at least one checkpoint inhibitor (ICI) to the patient.

[0080] According to another aspect of the present invention, a method for stratifying a patient for adenovirus cancer treatment is provided, comprising:

[0081] i) Extracting tumor samples from the patient;

[0082] ii) Dissolve or suspend the sample in a liquid;

[0083] iii) Passing the liquid through an apparatus for tumor antigen identification, the apparatus comprising: at least one flow channel containing a plurality of supports to which at least one molecule or at least one complex is attached, the molecule or complex being bound to at least one anti-MHC (major histocompatibility complex) antibody or at least one anti-pan-human leukocyte antigen (HLA) antibody, thereby enabling the extraction of pMHC (peptide: major histocompatibility complex) from the sample flowing through the channel using the at least one antibody;

[0084] iv) Bind the at least one antibody to at least one pMHC (peptide: major histocompatibility complex) in the sample;

[0085] v) Optionally, a portion of at least one bound pMHC (peptide: major histocompatibility complex) of iv) is removed from the device;

[0086] vi) The peptide of the bound pMHC (peptide: major histocompatibility complex) is compared with a library of human pathogen-derived antigens to determine whether the peptide shows homology / affinity with at least one human pathogen-derived antigen or a portion thereof, and wherein there is greater than 60% homology / affinity.

[0087] vii) Identify the peptide as a tumor antigen; and

[0088] viii) When the peptide is found, the peptide is attached to the capsid of the adenovirus vector, and an effective amount of the adenovirus vector is administered to the patient.

[0089] In a preferred embodiment, the peptide is linked to the adenovirus vector using known techniques such as those described in WO 2015 / 177098 and / or those contained herein, see PeptiCRAd preparation.

[0090] The “effective amount” mentioned in this article refers to the amount sufficient to achieve the desired biological effect (such as cancer cell death).

[0091] Understandably, the effective dose will depend on the recipient's age, sex, health condition, weight, the type of concurrent treatment (if any), the frequency of treatment, and the nature of the desired effect. Typically, the effective dose is determined by the person administering the treatment.

[0092] Most preferably, the cancers referred to herein include any one or more of the following cancers: nasopharyngeal carcinoma, synovial carcinoma, hepatocellular carcinoma, renal carcinoma, connective tissue carcinoma, melanoma, lung cancer, intestinal cancer, colon cancer, rectal cancer, colorectal cancer, brain cancer, laryngeal cancer, oral cancer, liver cancer, bone cancer, pancreatic cancer, choriocarcinoma, gastrinoma, pheochromocytoma, prolactinoma, T-cell leukemia / lymphoma, neuroma, Von Hippel-Lindau disease, Zollinger-Ellison syndrome, adrenal cancer, anal cancer, bile duct cancer, bladder cancer, ureteral cancer, oligodendroglioma, neuroblastoma, meningioma, spinal cord tumor, osteochondroma, chondrosarcoma, Ewing's sarcoma, cancer of unknown primary origin, carcinoid, gastrointestinal carcinoid, fibrosarcoma, breast cancer, Paget's disease, cervical cancer, esophageal cancer, gallbladder cancer, head cancer, and eye cancer. Cervical cancer, kidney cancer, Wilms' tumor, liver cancer, Kaposi's sarcoma, prostate cancer, testicular cancer, Hodgkin's disease, non-Hodgkin's lymphoma, skin cancer, mesothelioma, multiple myeloma, ovarian cancer, endocrine pancreatic cancer, glucagonoma, parathyroid cancer, penile cancer, pituitary cancer, soft tissue sarcoma, retinoblastoma, small intestine cancer, stomach cancer, thymic cancer, thyroid cancer, trophoblastic cancer, hydatidiform mole, uterine cancer, endometrial cancer, vaginal cancer, vulvar cancer, acoustic neuroma, mycosis fungoides, islet tumor, carcinoid syndrome, somatostatinoma, gingival cancer, heart cancer, lip cancer, meningeal cancer, oral cancer, nerve cancer, palate cancer, parotid gland cancer, peritoneal cancer, pharyngeal cancer, pleural cancer, salivary gland cancer, tongue cancer, and tonsil cancer.

[0093] In a particularly preferred embodiment of the invention, the sample is taken from melanoma, and the tumor antigen is homologous to the CMV antigen or peptide.

[0094] In the appended claims and the foregoing description of the invention, unless the context requires otherwise due to explicit language or necessary implication, the word “comprise”, or variations such as “comprises” or “comprising”, is used in the sense of inclusion, that is, explicitly indicating the presence of the stated feature, but not excluding the presence or addition of further features in various embodiments of the invention.

[0095] All references cited in this specification, including any patents or patent applications, are incorporated herein by reference. No reference is acknowledged to constitute prior art. Furthermore, no prior art is acknowledged to be part of common general knowledge in the art.

[0096] Preferred features of each aspect of the invention may be described in conjunction with any other aspect.

[0097] Other features of the invention will become apparent from the following examples. Generally, the invention extends to any novel one or any novel combination of features disclosed in this specification (including the appended claims and drawings). Therefore, features, integers, properties, compounds, or chemical portions described in conjunction with a particular aspect, embodiment, or example of the invention should be understood to be applicable to any other aspect, embodiment, or example described herein, unless incompatible therewith.

[0098] Furthermore, unless otherwise stated, any feature disclosed herein may be replaced by an alternative feature serving the same or similar purpose.

[0099] Throughout the description and claims of this specification, the singular includes the plural unless the context requires otherwise. In particular, where the indefinite article is used, this specification should be understood to take into account both the plural and the majority unless the context requires otherwise. Attached Figure Description

[0100] Embodiments of the invention will now be described by way of example only, wherein:

[0101] Figure 1. [A] Interior of PeptiCHIP. The interior of PeptiCHIP consists of thousands of columns coated with a binding agent to which biotin is attached. The biotin then reacts with streptavidin, which can subsequently react with three molecules of HLA-specific capture antibody. [B] Microchip technology serves as a novel immunopurification platform for the rapid discovery of antigens.

[0102] A schematic overview of the newly developed microchip method is provided. A thiol-ene microchip containing surface-free thiols was derivatized with biotin-PEG4-ethynylthiolene (step 1) and functionalized with a layer of streptavidin (step 2). Subsequently, a biotinylated pan-HLA antibody was immobilized on the micropillar surface (step 3), and cell lysates were loaded into the microchip (step 4). After sufficient incubation and washing, HLA molecules were eluted with 7% acetic acid (step 5).

[0103] Figure 2. Characterization of the selectivity of microchip functionalization using biotinylated pan-HLA antibodies.

[0104] A) Binding potency of AlexaFluor 488-streptavidin on thiol-ene micropillars pre-coated with biotin-PEG4-acetylene at two different streptavidin incubation times (15 min and 1 h). B) Effect of streptavidin (non-fluorescent) concentration on the amount of immobilized biotinylated pan-HLA antibody quantified by a secondary antibody labeled with AlexaFluor 488. C) Effect of BSA incubation on the amount of immobilized biotinylated pan-HLA antibody quantified by a secondary antibody labeled with AlexaFluor 488. The efficiency of BSA in blocking non-specific binding sites was assessed by pretreating the micropillar array with BSA before (BSA-pan-HLA) or after (pan-HLA-BSA) immobilization of biotinylated pan-HLA antibody. D) The total amount of biotinylated pan-HLA antibody bound to a single chip is a function of the loading cycle. For each cycle, a new batch with the same (constant) pan-HLA antibody concentration was used. Significance was assessed by a two-tailed unpaired Student's t-test, *P < 0.05.

[0105] Figure 3. Characteristics of the HLA-I peptidome dataset obtained from the JY cell line. A) From 50 × 10 6 10×10 6 and 1×10 6 A) The number of unique peptides eluted from JY cells. B) The overall peptide length distribution of HLA peptides in three datasets obtained from the JY cell line. C) The length distribution of HLA peptides at 50 × 10⁻⁶. 6 (C) 10×10 6 (D) and 1×10 6 (E) is described by the number of unique peptides (left y-axis) and the percentage of occurrence (right y-axis).

[0106] Figure 4. Precise analysis of HLA ligands isolated from the JY cell line. A) Binding affinity of the eluted 9mer peptides with HLA-A*02:01 and HLA-B*07:02 was analyzed. Bound groups (green dots) and unbound groups (black dots) were defined in the NetMHCpan 4.0 server (application level 2%). B) Common HLA-I binding motifs. Gibbs cluster analysis was performed to define common binding motifs in the eluted 9mer peptides. The reference motif is depicted in the upper right corner. Clusters with optimal fit are shown (higher KLD values, orange stars), with sequence markers represented by the number of HLA-I molecules in each cluster.

[0107] Figure 5AThe flowchart of the HEX algorithm is as follows: A matrix is ​​generated based on the amino acid composition of the tumor peptide (reference peptide). This matrix is ​​then used to scan a viral database, and the resulting viral peptides are sorted according to their log-likelihood of identification. Each viral peptide is assigned a permutation score and an MHC-I binding prediction score. Candidate viral peptides are ranked based on the following criteria: MHC-I binding prediction score > permutation score > B-score. The peptide with the highest score is then subjected to experimental analysis.

[0108] Figure 5B Flowchart of the existing software usage. A list of tumor peptides with a length of 8 to 12 amino acids can be used as input to the software. First, the BLAST tool is used to find Hits (similar sequences) in the pathogen-derived antigen library. For this task, PAM30 is usually used, but both BLOSUM and PAM substitution matrices are supported at several evolutionary distances. Next, at least BLOSUM62 is used, and ideally, the substitution matrix developed by Kim et al. (described in BMC Bioinformatics. 2009; 10:394, published November 30, 2009, doi:10.1186 / 1471-2105-10-394 Derivation of an amino acid similarity matrix for peptide: MHC binding and its application as a Bayesian prior. Kim Y, Sidney J, Pinilla C, Sette A, Peters B.) is used for pairwise refinement, thereby refining the alignment in a position-weighted manner. Peptide pairs exhibiting high similarity in the TCR interaction region (the central portion of the peptide) received higher similarity scores. Finally, MHC binding affinity predictions for homologous peptides from tumors and viruses were performed using NetMHC4.0 or NetMHCpan4.1 as standalone command-line tools. These results were then automatically parsed and processed within the tools, creating a final score summarizing the analyses presented above.

[0109] Figure 6 Immunization with viral peptides homologous to tumor antigens slowed tumor growth.

[0110] A: Animal experiment protocol: To assess whether viral peptides similar to tumor peptides can affect tumor growth, we constructed four groups of C57BL6 mice. One group of juvenile mice served as a mock tumor, while the other three groups were immunized with different viral peptide libraries. The mice were immunized at two time points before tumor transplantation: day 14 and day 7.

[0111] B: Two weeks after the first immunization, mice were subcutaneously injected with 3×10 5Mouse melanoma B16-OVA cells were transplanted. Tumor growth was tracked every other day using digital calipers for 19 days post-transplantation. P-values ​​were calculated using two-way ANOVA multiple comparisons and Tukey correction.

[0112] C: Mice were euthanized upon reaching the endpoint. Spleen cells from each group of mice were collected and pooled for ELISpot assay. Each pool was then pulsed with its respective viral peptide (a viral peptide homologous to TYR1, a viral peptide homologous to TRP2, and a viral peptide homologous to GP100) to assess response to treatment. Dashed lines represent background generated by negative controls.

[0113] Figure 7 Viral peptides with higher affinity for MHC are more immunogenic and can induce stronger cross-reactions.

[0114] A: To assess the response to their respective original tumor epitopes, spleen cells from each immune group were combined and pulsed with the corresponding tumor peptides.

[0115] B: Comparison between the responses induced by pulsation of combined viral peptides and corresponding primitive tumor peptides on spleen cells.

[0116] C: Predicted affinity of the original tumor and its respective similar viral peptide library for mouse MHC class I. 50 nM is considered the threshold for peptides with “high affinity” and “medium / low affinity” as defined according to the IEDB guidelines.

[0117] D: Correlation between data from IFN-γ responses and predicted affinity.

[0118] E: Peptides were stratified based on their affinity and ability to stimulate IFN-γ production. High-affinity peptides (IC50 < 50 nM) promoted IFN-γ production significantly more than medium / low-affinity peptides (IC50 > 50 nM). P-values ​​were calculated using t-tests and Mann-Whitney correction. P-value ranges are marked with an asterisk according to the following criteria: > 0.05 (ns), ≤ 0.05 (*), ≤ 0.01 (**), ≤ 0.001 (***), ≤ 0.0001 (****).

[0119] Figure 8 Viral peptides homologous to tumor antigens can reduce tumor growth in established tumors.

[0120] A: Animal experimental protocol: For each tumor cell line to be tested, four groups of C57BL mice were formed. On day 0, mice were subcutaneously injected with either B16-OVA or B16F10 cells. Once the tumor was palpable, mice were treated with saline solution (simulated group), uncoated adenovirus (uncoated virus group), adenovirus coated with a viral peptide library homologous to TRP2 (Viral PeptiCRAd, VPC), or adenovirus coated with the TRP2 peptide (TRP2 PeptiCRAd, TPC).

[0121] B: B16 OVA tumor individual growth. The threshold for defining treatment success is determined by the median volume of all tumors on the last day.

[0122] C: Endpoint B16 OVA tumor volume. The median tumor volume is shown as a dashed line, defining the threshold for treatment success.

[0123] D: B16 OVA contingency plot shows the number of responders for each treatment group.

[0124] E: B16 F10 tumor individual growth. The threshold for defining treatment success is determined by the median volume of all tumors on the last day.

[0125] F: Endpoint B16 F10 tumor volume. The median tumor volume is shown as a dashed line, defining the threshold for treatment success.

[0126] G: B16 OVA contingency plot shows the number of responders in each treatment group.

[0127] (CF): P-values ​​were calculated using one-way ANOVA and Tukey correction. The range of P-values ​​is marked with an asterisk according to the following criteria: >0.05 (ns), ≤0.05 (*), ≤0.01 (**), ≤0.001 (***), ≤0.0001 (****).

[0128] (DG): The p-value is calculated using the chi-square test of probability ratios (and Fischer exact test). The range of p-values ​​is marked with an asterisk according to the following criteria: >0.05 (ns), ≤0.05 (*), ≤0.01 (**), ≤0.001 (***), ≤0.0001 (****).

[0129] Figure 9. T-cell cross-reactivity between viruses and tumor antigens with high homology / affinity. PBMCs from patients with HLA-A*02:01 and high serum levels of anti-CMV antibodies were pulsed using peptides from Table 2. IFN-γ secretion levels activated by CD8+ T cells were detected by ELISpot assay. Dashed lines represent noise levels of non-specific CTL activation from the negative control (DMSO) (A). Anti-CMV reactivity was detected by ELISpot assay from PBMCs from patients with HLA-A*02:01 and high serum levels of anti-CMV antibodies and from CMV-reactive healthy donors (HS) using the CMV-specific HLA-A*02:01-restricted peptide NLVPMVATV. P-values ​​were calculated using t-tests and Mann-Whitney correction (B).

[0130] Figure 10. The microchip-based platform reveals an overview of immunopepetidomic in rare tumor biopsies. A) Here, the weight, total number, and unique peptides before sample processing, as well as enrichment in 7–13-mer samples, are summarized. B) The length distribution of peptides with respect to their absolute number and percentage is shown as a bar graph.

[0131] Figure 11. Immunopeptidomic analysis of ccRCC and bladder tumor-derived organoids (PDOs). A) Number of unique peptides detected in ccRCC and bladder PDOs. B) Length distribution of peptides shown as the total number of unique peptides (left Y-axis) and the percentage of occurrence in each PDO (right Y-axis) (small plot above ccRCC, small plot below bladder).

[0132] Figure 12. Peptide testing. Synthetic tumor model CT26 was subcutaneously injected into both sides of Balb / c mice on day 0. Figure 12A Once the tumor is established (day 7), Figure 12A Valo-mD901 was coated with each pair of polylysine-modified peptides (PeptiCRAd1, PeptiCRAd2, PeptiCRAd3, as listed in our table) and injected intratumorally only into the right-sided tumor. PeptiCRAd4 consisted of Valo-mD901 coated with gp70423-431 (AH1-5), the immunodominant antigen of CT26 known to be derived from an autoantigen encoded in the genome. The dummy group and the Valo-mD901 group were also used as controls. PeptiCRAd1 and PeptiCRAd2 improved control of tumor growth and also improved the concentration of Valo-MD901 in the injected lesion. Figure 12B(See right side of the figure), which also shows the growth of individual tumors in each mouse in each treatment group. Strictly speaking, only PeptiCRAd1 significantly improved antitumor activity in untreated tumors, while Valo-mD901 did not elicit any effect. Figure 12B (See left side of the image).

[0133] The peptides in PeptiCRAd1 were determined by HEX analysis. PeptiCRAd4 consists of Valo-mD901 coated with gp70 423-431 (AH1-5).

[0134] Figure 13 This section provides a schematic overview of the invention. The apparatus of the invention is depicted schematically and has previously been functionalized with multiple anti-MHC (major histocompatibility complex) antibodies or anti-pan-human leukocyte antigen (HLA) antibodies capable of capturing pMHC (peptide: major histocompatibility complex). Tumor lysates are passed through the apparatus, and the antibodies extract the pMHC. The pMHC is eluted, and the peptides in the pMHC complex are analyzed, for example by liquid chromatography-mass spectrometry (LC-MS / MS), resulting in a list of tumor peptides. Each tumor peptide is compared with a library of pathogen-derived proteins (including antigens) to determine the level of homology / affinity between each tumor peptide identified using the apparatus and pathogen-derived proteins (including pathogen antigens / pathogen peptides) in the library. This produces a candidate list, ideally prioritized in terms of homology / affinity, for use in cancer therapy.

[0135] Table 1. Peptides used in animal experiments. Known melanoma tumor peptides (TRP2180-188, hGP10025-33, and TYR208-216) were analyzed using HEX. The best viral candidate peptides proposed by the software were selected, and a library consisting of the best four xenopeptides for each original tumor epitope was tested in vivo.

[0136] Table 2. Peptides used for ELISpot assay of patient PBMCs. Known melanoma-associated antigens were analyzed using HEX. The best human CMV-derived candidate peptides for each antigen were selected for in vitro testing.

[0137] Table 3. Comparative analysis of microchip-based immunoprecipitation technology and standard procedures. This table reports the total amount of antibody coated onto the microchip-based IP technology and the standard procedure.

[0138] Table 4 shows the 13 tumor MHC-restricted peptides identified by HEX output and their corresponding pathogen-derived peptides.

[0139] Table 5. List of peptides tested in the ELISPOT assay.

[0140] Table 6. A table of selected peptides used for the in vivo PeptiCRAd assay shown in Figure 12. Detailed Implementation

[0141] Methods and Materials

[0142] Equipment manufacturing

[0143] The device of this invention (called PeptiCHIP) is a flow configuration comprising thousands of columns coated with a linker to which biotin is attached. The biotin is then linked to streptavidin, which binds to an HLA-specific capture antibody, specifically a three-molecule HLA-specific capture antibody.

[0144] Using conventional microfluidic manufacturing techniques, PeptiCHIP is manufactured based on a photoreaction initiated by ultraviolet light between thiols and allyl (“ene”) functional groups in a non-stoichiometric ratio of 150:100 (tetrathiol:triallyl).

[0145] Following the above manufacturing process, PeptiCHIP was immediately derivatized using biotin-PEG4-alkyne (Sigma, 764213) via UV polymerization, and then reacted with avidin. The process was carried out as follows.

[0146] Step 1: We prepared a 1 mM biotin-PEG4-acetylene solution (a stock solution of 10 mM biotin-PEG4-acetylene in ethylene glycol). We took a small aliquot and added 1% (m / v) of photoinitiator ( TPO-L (BASF) uses a stock solution of 10% photoinitiator in methanol, so the final solution is 1 mM biotin + 1% Lucirin in EG-MeOH 9:1*.

[0147] We filled the chip with a solution of one volume of biotin-PEG4-acetylenic acid and 1% Lucirin in EG:MeOH 9:1 (v / v) and exposed it to UV light for 1 minute (using an LED UV lamp with λ = 365 nm and l = 15 mW / cm²). 2 ).

[0148] We first rinse thoroughly with methanol, then with milli-Q water, passing 1-2 mL of each solvent through the channel, and then dry and store (if necessary).

[0149] Step 2: After biotin derivatization, the chip was functionalized with streptavidin. We prepared a 0.01 mg / ml streptavidin stock solution in PBS and added it to the chip at room temperature, incubating in the dark for 15 minutes. We washed three times with 200 μL of PBS.

[0150] We added 100ug / ml BSA to 15mM in PBS and incubated at room temperature for 10 minutes.

[0151] Step 3: Reaction with anti-pan-HLA antibodies. We added 25 μL of biotinylated anti-human HLA-A, HLA-B, and HLA-C at 1.6 μg / μL (Biolegend CAT. No. 311434) and incubated at room temperature for 15 minutes. Then we washed three times with 200 μL of PBS and then chipped to prepare for immunoprecipitation of MHC complexes.

[0152] Tumor sample preparation: We isolated cells using 4 mM EDTA and washed them once with PBS. We added 1% Igepal + protease inhibitor to 25 μL of PBS. We centrifuged at 500 x g for 10 minutes at 4°C. Then we centrifuged at 20000 x g for 10 minutes at 4°C.

[0153] Optimized microfluidic column array

[0154] Immunopurification steps were performed within a single microfluidic chip by adding biotinylated pan-HLA antibodies to a streptavidin-prefunctionalized solid support structure (i.e., a micropillar array) and then immobilizing HLA on the solid surface coated with pan-HLA antibodies.

[0155] In summary, a micropillar array based on off-stoichiometric thiol-ene (OSTE) polymers was fabricated using a UV-replicamolding technique and then biotinylated. Next, the biotinylated micropillars were functionalized with streptavidin and infused with a biotinylated pan-HLA antibody. Cell lysates were then directly loaded into a microfluidic chip to selectively capture HLA-I complexes. After thorough washing, the captured HLA-I complexes were eluted at room temperature using 7% acetic acid. Figure 1B Subsequently, the protocol was followed according to standard immunopeptidomics workflows, including the use of... The eluted HLA peptides were purified in acetonitrile and evaporated to dryness by vacuum centrifugation.

[0156] The efficiency of streptavidin functionalization on micropillar arrays with two different incubation times (15 minutes and 1 hour) was examined with the aid of the fluorescent Alexa Fluor488-streptavidin. It was found that the shorter incubation time was sufficient to establish the first streptavidin layer. Figure 2A Furthermore, to determine the effect of streptavidin concentration on the final number of immobilized biotinylated pan-HLA antibodies, several concentrations of non-fluorescent streptavidin were tested in the presence of a fixed amount of biotinylated pan-HLA antibodies. In this case, the biotinylated pan-HLA antibodies were incubated for 15 minutes and then washed three times with PBS (200 μl each time). To quantify the number of immobilized biotinylated pan-HLA antibodies at each streptavidin concentration, the immobilized biotinylated pan-HLA antibodies were titrated using a fluorescently labeled Alexa Fluor 488 secondary antibody. Interestingly, even a 10-fold increase in streptavidin concentration did not significantly affect the number of immobilized biotinylated pan-HLA antibodies. Figure 2B This is likely due to steric hindrance limiting the number of available streptavidin binding sites. Based on this finding, the concentration of streptavidin was not further explored, but the highest streptavidin concentration tested (0.1 mg / mL) was used in all subsequent experiments to ensure maximum binding of biotinylated pan-HLA antibodies. However, to further investigate the selectivity of antibody binding to the streptavidin-functionalized micropillar surface, the effect of an additional bovine serum albumin (BSA) coating step on the number of immobilized biotinylated pan-HLA antibodies was investigated to eliminate nonspecific interactions. To this end, after streptavidin functionalization, the micropillar array was pretreated with BSA (100 μg / mL, incubated in 15 mM PBS for 10 min), and the efficiency of subsequent binding of biotinylated pan-HLA antibodies was re-determined with the aid of a fluorescently labeled secondary antibody. Compared to the untreated surface, this process significantly reduced the number of immobilized pan-HLA antibodies ( Figure 2C This indicates that nonspecific binding sites can be blocked by a simple BSA pre-incubation step. Therefore, the BSA incubation step is applicable to all further experiments.

[0157] Finally, we attempted to characterize the maximum amount of immobilized biotinylated pan-HLA antibody on a single chip using an optimized protocol. This was assessed by using multiple loading cycles of a new batch of antibody at the same concentration (0.5 mg / mL) on a single microfluidic chip. In this case, the amount of immobilized pan-HLA antibody was determined by comparing the amount of pan-HLA antibody in the injection and output solutions using ELISA. It was observed that the amount of immobilized antibody increased almost linearly with increasing loading cycles. Figure 2DThis allows for precise adjustment of the total amount of immobilized biotinylated pan-HLA antibody based on the number of loading cycles. After seven cycles, the amount of immobilized antibody reached approximately 45 μg, which is theoretically sufficient for immunopeptidome studies on scarce biological materials, as 10 mg of pan-HLA (3.88 × 10⁻⁶) is sufficient. 16 (10 antibody molecules) is a method used in existing technologies to study 10 9 The required [22A] for each cell (Table 3).

[0158] Through the microchip settings, 1.74×10 14 One antibody molecule can be immobilized, and technically, 4.5 × 10⁻⁶ can be studied. 6 Each cell.

[0159] Microchip-based antigen enrichment, performed within an immunopeptidomics workflow, can identify naturally occurring HLA-I peptides.

[0160] To evaluate whether the developed thiol-ene microchip could serve as a platform for antigen discovery, we immunopurified HLA peptides from the human B-cell lymphoblastoid line JY. The JY line highly expresses class I HLA and is homozygous for three common human alleles (HLA-A*02:01, HLA-B*07:02, and HLA-C*07:02), and has been widely used in ligandome analysis. Therefore, the JY cell line is considered a suitable model for evaluating microchip-based antigen enrichment immunoprecipitation techniques.

[0161] Therefore, the HLA-I complex was purified using a thiol-ene microarray via immunoaffinity and functionalized with the aforementioned amount of pan-HLA antibody. Furthermore, to determine the sensitivity of our method, we used a concentration as low as 50 × 10⁻⁶. 6 10×10 6 and 1×10 6 The protocol was challenged using a total cell count. Lysates were loaded into microarrays, thoroughly washed with PBS, eluted with 7% acetic acid, and analyzed by tandem mass spectrometry. The entire workflow, from streptavidin functionalization to elution of tumor peptides, took an average of <24 hours. A stringent false discovery rate threshold of 1% was used for peptide and protein identification to produce data with high confidence. We were able to analyze data from 50 × 10⁻⁶ cells. 6 10×10 6 and 1×10 6 5589, 2100, and 1804 unique peptides were identified in the cells, respectively. Figure 3A ).

[0162] Because we sought to carefully analyze the ability of microchip technology to enrich native HLA-I conjugates while avoiding potential co-eluting contaminants, we extensively characterized the eluted peptides. First, the eluted peptides from the JY cell line represent a typical length distribution for the ligand set dataset, with 9-mer being the most abundant peptide species. Figures 3B-3E Next, the predicted binding affinity of the two HLA-I alleles (HLA-A*0201 and HLA-B*0702) expressed in JY cells was determined. JY cells also have low levels of the HLA-C*0702 allele, but its binding motif overlaps with that of HLA-A*0201 and HLA-B*0702; therefore, only these alleles were considered in subsequent analyses.

[0163] In the unique 9mer, 78%, 83%, and 67% were predicted to be with 50×10 6 10×10 6 and 1×10 6 A conjugate of the HLA-A*0201 or HLA-B*0702 alleles in a single cell (described as a conjugate in NetMHCpan 4.0, application grade 2% [24A-26A]) Figure 4A Furthermore, Gibbs analysis was performed to deconvolve the common binding motifs of the respective HLA-I alleles from the eluted 9mer peptides; these motifs clustered in two distinct groups, tending to reduce the amino acid complexity of residues at the P2 and Ω positions, and closely matched the known motifs of HLA-A*0201 and HLA-B*0702. Figure 4B ).

[0164] Next, to determine the role of the identified peptides, we performed a Gene Ontology (GO) enrichment analysis on our list of 9mer-binding proteins. We observed enrichment of proteins in the nucleus and intracellular, primarily those that interact with DNA or RNA or are involved in catabolism. Finally, we established an in vitro killing assay to further demonstrate the ability of microarray technology to isolate peptides complexed with HLA-I. For this purpose, a set of three peptides from our JY dataset were selected to stimulate HLA-matched PBMCs; CD8+ T cells were purified from the PBMCs and co-cultured with JY cells as effector cells. To illustrate the non-specific cytotoxicity induced by the effector cells themselves, unstimulated PBMCs were used as controls. Cell lysis was then monitored in real time. Interestingly, CD8+ T cells pulsed with peptides QLVDIIEKV (SEQ ID NO:75; gene name PSME3) and KVLEYVIKV (SEQ ID NO:76; gene name MAGEA1) showed approximately 10% specific cell lysis, while CD8+ T cells pulsed with peptide ILDKKVEKV (SEQ ID NO:77; gene name HSP90AB3P) induced 15% specific cell lysis, indicating that specific lysis occurs in the presence of a defined peptide.

[0165] To evaluate the validity of our list of HLA-I peptides identified using microchip technology, we queried SysteMHC, a database of immunopeptidomics datasets generated by mass spectrometry. Of the unique 9-mer conjugates identified in our data, 69%, 77%, and 81% were also previously published in 50×10⁻⁶ microarrays. 6 10×10 6 and 1×10 6 The ligand set of the JY cell line (pride ID PXD000394) [3A] was found in the dataset. Figure 6 A). Furthermore, a positive correlation was confirmed between the abundance of the source protein and HLA presentation, with the most abundant protein being the main source of HLA peptides.

[0166] Therefore, these results demonstrate that chip-based approaches can serve as a reliable immunoprecipitation platform in the immunopeptidomics workflow.

[0167] Device use

[0168] The sample was applied to the chip and eluted for further analysis.

[0169] We applied samples through multiple cycles and incubated for 5 minutes (working at 4°C). We washed three times with 200 μL of PBS, aspirating the last wash to empty the chip. We prepared solutions of 50% MeOH and 50% MilliQ. We prepared a 7% acetic acid solution using the previous solutions. We applied this solution to the chip and collected the fractions. The elution time was 5 minutes. On the same day, we purified the collected fractions. We prepared SepPak cartridges for each tissue sample of HLA-I peptide and labeled them. Using a syringe and a dedicated adapter, we first washed the cartridges once with 80% ACN in 1 ml of 0.1% TFA, then twice with 1 ml of 0.1% TFA. We loaded each biological sample onto a SepPak cartridge. We passed them slowly (approximately 1 ml / 20 s). We washed the cartridges twice with 1 ml of 0.1% TFA. We eluted the HLA-binding peptide into the collection tube using 300 μL of 30% CAN in 0.1% TFA.

[0170] HEX (Homology Evaluation of Heteropeptides)

[0171] Heteropeptide homology ( / affinity) assessment (HEX) is a novel computer simulation platform that compares the similarity between tumor peptides (reference peptides) and pathogen-derived (e.g., viral) peptides (query peptides). It utilizes several metrics to accelerate the selection of candidate peptides. This is accomplished by combining novel methods (peptide scoring and permutation scoring algorithms) with integrated existing methods (MHC-I binding prediction). HEX comes with several pre-compiled databases of known proteins, such as those from viral pathogens and the human proteome (33).

[0172] The relevant scoring matrix was generated provisionally based on the amino acid composition of the reference peptide, rather than experimentally. Specifically, in the matrix rows representing the positions of amino acids in the peptide and the columns representing each of the 20 standard amino acids, the amino acid positions of the reference peptide were assigned the same high score, while other positions were assigned the same low score.

[0173] Permutations are calculated pairwise between peptides in the query set and peptides in the reference set. For a given pair of peptides, their permutations are calculated by summing the distance scores between pairs of amino acids at the same position. The scores are weighted, prioritizing similarity between more central amino acids in the peptides. HEX supports BLOSUM and PAM substitution matrices spanning several evolutionary distances. Specifically, BLOSUM 62 is the matrix chosen for this study.

[0174] The prediction of MHC class I binding affinity was performed using NetMHC

[27] via the IEDB application programming interface (http: / / tools.iedb.org / main / tools-api / ), and then parsed and processed within the tool. Users can specify their desired scoring method or return some recommended results. Prediction of some human and mouse MHC-I alleles is supported.

[0175] Users can select peptides according to their own criteria, or allow selection using a random forest model. The random forest is trained based on experimental results on peptides selected by the authors. The importance of features is determined by the increase in out-of-bag (OOB) mean squared error (MSE) and cross-validation is performed on unseen peptide samples. HEX is a web application developed using the R package Shiny and is available at https: / / picpl.arcca.cf.ac.uk / hex / app / without user registration. The source code is available at https: / / github.com / whalleyt / hex.

[0176] In an alternative embodiment of the invention, HEX supports BLOSUM and PAM substitution matrices spanning several evolutionary distances. Specifically, BLOSUM 62 is the matrix used in this study. HEX first performs a BLAST search using PAM30 to find Hits (similar sequences) in the reference library. Next, HEX performs pairwise refinement alignments using BLOSUM62 and the substitution matrix developed by Kim et al.

[0177] Reference: Kim Y, Sidney J, Pinilla C, Sette A, Peters B. Derivation of anamino acid similarity matrix for peptide: MHC binding and its application as a Bayesian prior. BMC Bioinformatics. 2009; 10:394, published November 30, 2009, doi:10.1186 / 1471-2105-10-394.

[0178] MHC class I binding affinity prediction is performed using NetMHC4.0 (or NetMHCpan4.1) as a standalone command-line tool, followed by parsing and processing within that tool. Users can specify their desired scoring method or return some recommended results. Prediction of some human and rodent MHC-I alleles is supported.

[0179] Patients and Samples

[0180] At the Comprehensive Cancer Center of University Central Helsinki (HUCH), 16 patients with stage 4 metastatic melanoma received anti-PD-1 monoclonal antibody therapy. Patients were randomly assigned to receive either nivolumab (n=7) infusions every other week or pembrolizumab (n=9) infusions every three weeks. The study was approved by the Ethics Committee of University Central Helsinki (HUCH) (Dnro115 / 13 / 03 / 02 / 15). Written informed consent was obtained from all patients, and the study was conducted in accordance with the Declaration of Helsinki.

[0181] Peripheral blood samples (3 ml EDTA blood, 50 ml heparin blood) were collected at three time points: before treatment, one month after treatment, and three months after treatment. Plasma was separated by centrifugation and then stored at -70°C. CMV and EBV IgG levels were measured from thawed EDTA plasma samples using the VIDAS CMV IgG kit (BioMérieux, Marcy-l'Etoile, France) and the Siemens Enzygnost anti-EBV / IgG kit (Siemens Healthcare Diagnostics, Marburg, Germany). Immunoglobulins (IgA, IgM, IgG) in thawed heparinized plasma were measured at the Central Laboratory (HUSLAB) of the University Hospital Helsinki.

[0182] Cell lines and human samples

[0183] The mouse melanoma cell line B16-F10 was purchased from the American Type Culture Collection (ATCC; Manassas, VA, USA). Cells were cultured in RPMI (Gibco, Thermo Fisher Scientific, US) containing 10% fetal bovine serum (FBS) (Life Technologies), 1% Glutamax (Gibco, Thermo Fisher Scientific, US), and 1% penicillin and streptomycin (Gibco, Thermo Fisher Scientific, US) at 37°C / 5% CO2.

[0184] The B16-OVA cell line is a modified mouse melanoma cell line constitutively expressing chicken ovalbumin (OVA), kindly provided by Professor Richard Vile (Mayo Clinic, Rochester, MN, USA). These cells were cultured at 37°C / 5% CO2 in RPMI low-glucose (Gibco, Thermo Fisher Scientific, US) containing 10% FBS (Gibco, Thermo Fisher Scientific, US), 1% Glutamax, 1% penicillin and streptomycin (Gibco, Thermo Fisher Scientific, US), and 1% genimycin (Gibco, Thermo Fisher Scientific, US).

[0185] Mycoplasma contamination of all cells was detected using a commercial detection kit (Lonza–Basel, Switzerland). Isolated human PBMCs were frozen in FBS supplemented with 10% DMSO and then stored in liquid nitrogen until use. The frozen PBMCs were thawed and incubated overnight at 37°C / 5% CO2 in complete RPMI medium supplemented with 10% FBS, 1% Glutamax, and 1% penicillin-streptomycin, then plated for ELISPOT.

[0186] peptides

[0187] All peptides used in this study were purchased from Zhejiang Hongtuo Biotechnology Co., Ltd. (Zhejiang, China), 5 mg, >90% purity. The sequences of all peptides used in this study are shown in Tables 1 and 2.

[0188] PeptiCRAd preparation

[0189] All PeptiCRAd complexes described in this work were prepared by mixing adenovirus and a peptide with a polyK tail according to the following protocol: 1 × 10 9 VP (viral particles) were mixed with 20 μg of a polyK-tailed peptide (resuspended in water); after vortexing, the mixture was incubated at room temperature for 15 minutes; after incubation, PBS was added to reach the injection volume (50 μL / mouse), and the solution was then vortexed again for assay or animal injection. For TRP2-PeptiCRAd, 1 × 10⁻⁶ 9 VP with 20ug 6K-TRP2 180-188 Peptide mixture, while virus-PeptiCRAd is used with 1×10 9 vp and 5ug and TRP2 180-188 It was prepared by mixing homologous 6K peptides from each virus.

[0190] Prepare fresh PeptiCRAd using fresh reagents before each experiment. Before incubation of PeptiCRAd, dilute all required viruses and peptides in sterile PBS or water. Then dilute PeptiCRAd in the buffer required for the assay.

[0191] The generation, reproduction and characterization of the virus are described elsewhere

[20] .

[0192] Animal testing and ethical permission

[0193] All animal experiments have been reviewed and approved by the Laboratory Animal Committee of the University of Helsinki and the government of the Southern Finland Province.

[0194] All experiments were conducted using C57BL / 6JOlaHsd mice obtained from Scanbur (Karlslunde, Denmark).

[0195] For the immunization experiment, 8- to 9-week-old immunized female C57BL / 6J mice were divided into four groups. N=3 mice served as the simulant group, and n=7 mice formed three different treatment groups. Each treatment group was inoculated with a different type of xenobiotic peptide. Mice were inoculated twice, one week apart (day 0 and day 7), with 40 μg of peptide and 40 μg of adjuvant (VacciGrade poly(I:C)-Invivogen) injected into the tail base, for a final injection volume of 100 μL. Naïve mice (injected with PBS) served as the simulant group. On day 14, 3*10 μL of PBS was injected into the right side of the mice. 5 One B16-OVA cell was used, and tumor growth was tracked until the endpoint was reached.

[0196] For the treatment of established tumors, we tested two different tumor cell lines: B16-OVA cells and the more aggressive B16F10 cells. 3*10 cells were subcutaneously injected into the right side of 8- to 9-week-old immunocompetent female C57BL / 6J mice. 5 1 B16-OVA cell and 1*10 5 B16-F10 cells were collected. These mice were then randomly divided into four groups of 7-8 mice each, for each tumor cell line. The simulant group was treated with PBS; the second group was treated with uncoated adenovirus; and the third group was treated with TRP2-coated cells. 180-188 The first group was treated with adenovirus (TRP2-PeptiCRAd); the last group was treated with adenovirus (Viral-PeptiCRAd) coated with TRP2 homologous viral peptide.

[0197] Mice received two intratumoral treatments, administered two days apart (days 10 and 12 from the start of tumor transplantation), and tumor growth was tracked until the endpoint was reached. The median tumor volume measurement on the final day determined the threshold for treatment success, shown as a dashed line. Mice with tumor volumes below the threshold at the endpoint were considered responders, while those above the threshold were considered non-responders.

[0198] Two dimensions of the tumor were measured using digital calipers to track its growth. The volume was then mathematically calculated using the following formula:

[0199] ((long side) × (short side)) 2 ) / 2

[0200] In all experiments, the tumor was measured every two or three days until the tumor size reached the maximum permissible value, at which point the mice were euthanized and the spleens were collected.

[0201] ELISpot measurement

[0202] To assess the number of active antigen-specific T cells, interferon-γ (IFN-γ) secretion was measured using the ELISPOT assay. IMMUNOSPOT (CTL, Ohio, USA) was used to measure mouse IFN-γ, and MABTECH (Mabtech AB, Nacka Strand, Sweden) was used to measure human IFN-γ.

[0203] Fresh mouse spleen cells collected at the end of the experiment were used. The procedure was performed according to the manufacturer's instructions. Briefly, for mouse IFN-γ, 3*10-1 cells were used on day 0. 5 One spleen cell per well was plated. Cells were stimulated with 2 μg of peptide per well. After incubation at 37°C / 5% CO2 for 3 days, the plates were developed according to the kit protocol.

[0204] For human IFN-γELISPOT, human PBMCs were thawed and incubated overnight at 37°C / 5% CO2 in complete culture medium. The next day, 3 × 10⁻⁶ cells were added. 5 One PBMC / well was coated onto a plate and stimulated with 2 μg / well of peptide. After incubation at 37°C / 5% CO2 for 48 hours, the plate was developed according to the manufacturer's protocol. The plate was then sent to CTL-Europe GmbH for analysis.

[0205] Cell lines and reagents

[0206] Epstein-Barr virus-transformed human lymphoblastic B cell line JY (ECACC HLA type collection, Sigma Aldrich) was cultured in RPMI 1640 (GIBCO, Invitrogen, Carlsbad, CA, USA) supplemented with 1% GlutaMAX (GIBCO, Invitrogen, Carlsbad, CA, USA) and 10% heat-inactivated fetal bovine serum (HI-FBS, GIBCO, Invitrogen, Carlsbad, CA, USA).

[0207] Streptomyces avidinii (affinity purified, lyophilized from 10 mm potassium dihydrogen phosphate, ≥13 U / mg protein) was purchased from Sigma-Aldrich (Saint Louis, Missouri, USA).

[0208] Biotin-conjugated anti-human HLA-A, B, C clone w6 / 32 was purchased from Biolegend (San Diego, CA, USA) and used for analysis.

[0209] The following peptides were purchased from Ontores Biotechnologies Co., Ltd. and used throughout the study: KVLEYVIKV (SEQ ID NO:75; gene name MAGE A1), ILDKKVEKV (SEQ ID NO:76; gene name HSP90) and QLVDIIEKV (SEQ ID NO:77; gene name PSME3).

[0210] In addition, the following peptides were purchased from Chempeptide (Shanghai, China):

[0211] VIMDALKSSY (SEQ ID NO:78; gene name NNMT), FLAEGGGVR (SEQ ID NO:79; gene name FGA) and EVAQPGPSNR (SEQ ID NO:80; gene name HSPG2).

[0212] Ovarian tumor biopsy and ethical considerations

[0213] Ovarian tumor biopsies were collected from patients with metastatic ovarian tumors (high-grade serous tumors) who had signed informed consent forms. The study was approved by the Research Ethics Committee of the North Savo Hospital District, approval number 350 / 2020. Samples were cut into small pieces and treated with a digestion buffer containing 1 mg / ml of type D collagenase (Roche), 100 μg / ml of hyaluronidase (Sigma Aldrich), and 1 mg / ml of DNase I (Roche) at 37°C for 1 hour. The cell suspension was then passed sequentially through 500 μm and 300 μm cell filters (pluriSelect) to obtain single cells.

[0214] Renal cell carcinoma and bladder tumor samples and ethical considerations

[0215] Patient tissue samples used for organoid culture were obtained from the DEDUCER study (Development of Diagnosis and Treatment of Urinary System Cancers) at Helsinki University Central Hospital, approval number HUS / 71 / 2017, 26.04.2017, ethics committee approval number 15.03.2017Dnro 154 / 13 / 03 / 02 / 2016, with patient consent obtained. Kidney samples were obtained from nephrectomy in adult men with clear cell renal cell carcinoma (ccRCC, pTNM stage pT3a G2). Benign kidney tissue samples were used for experiments. Urethra cancer (bladder cancer, high-grade, grade III, 1x1 cm) was obtained from adult women; cancer tissue samples were used for organoid culture.

[0216] Organoid culture of clear cell renal cell carcinoma and bladder tumor

[0217] Cells were immediately isolated from the original postoperative tissue by dissociating the tissue into small pieces and treating it with collagenase (40 units / mL) for 2–4 hours. Benign and cancerous cells of the kidney from clear cell renal cell carcinoma patients were grown as organoids in F-medium [3:1 (v / v) F-12 nutrient mixture (Ham)-DMEM (Invitrogen), 5% FBS, 8.4 ng / mL cholera toxin (Sigma), 0.4 μg / mL hydrocortisone (Sigma), 10 ng / mL epidermal growth factor (Corning), 24 μg / mL adenine (Sigma), 5 μg / mL insulin (Sigma), 10 μM ROCK inhibitor (Y-27632, Enzo Life Sciences, Lausen, Switzerland) and 1% penicillin-streptomycin with 10% Matrigel (Corning)]. Bladder tumor-derived organoids were grown in hepatocyte calcium medium supplemented with 5% CSFBS (Thermo Fisher Scientific), 10 μM Y-27632RHO inhibitor (Sigma), 10 ng / mL epidermal growth factor (Corning), 1% GlutaMAX (Gibco), 1% penicillin-streptomycin, and 10% matrix gel (Corning) [15A]. Organoids were collected by centrifugation at a concentration of 6 × 10⁶ cells / mL. 6 Cells were washed in PBS to remove matrix gel and then rapidly frozen before analysis.

[0218] HLA typing

[0219] Clinical HLA typing of tumor samples (ccRCC and bladder) was performed by the HLA laboratory of the Finnish Red Cross Blood Service, certified by the European Federation of Immunogenetics (EFI). Allele determination of the three typical HLA-I genes, HLA-A, HLA-B, and HLA-C, was conducted according to the manufacturer's provided protocol. Workflow, GenDx, Utrecht, Netherlands) conducted the study using next-generation sequencing (NGS) technology based on directional PCR.

[0220] Allele assignments at the 4-field resolution level were performed using NGSengine version 2.11.0.11444 (GenDx, Utrecht, Netherlands) with IPD IMGT / HLA database version 3.33.0 (https: / / www.ebi.ac.uk / ipd / imgt / hla).

[0221] Flow cytometry analysis

[0222] The following antibodies were used to analyze cell surface expression of HLA-A2 and HLA-A, B, and C: PE-conjugated anti-human HLA-A2 (clone BB7.2, BioLegend 343306, San Diego, CA, USA), PE-conjugated anti-human HLA-A, B, and C (clone W6 / 32, BioLegend 311406, San Diego, CA, USA), and human TruStain FcX block (BioLegend B247182, San Diego, CA, USA).

[0223] Data were obtained using the BDLSR Fortessa flow cytometer. Flow cytometry analysis of organoids derived from renal cell carcinoma and bladder tumors was performed using a BD Accuri 6plus (BDBiosciences) and analyzed using FlowJo software (Tree Star, Ashland, OR, USA).

[0224] result

[0225] Develop homology evaluation (HEX) tools for heteropeptides to identify viral and tumor-derived peptides with high molecular mimicry.

[0226] To investigate whether molecular mimicry between viruses and tumors affects tumor growth, we need to identify peptides with high homology / affinity. However, a tool is lacking in this area to facilitate the identification of relevant targets. Therefore, we developed HEX (Homology Assessment of Heteropeptides), a device that compares an input sequence with a database of pathogen-derived antigen / peptide or protein sequences and selects highly homologous candidate peptide pairs based on at least two of the following three criteria: 1) a B score corresponding to the probability that the peptide is recognized by a given TCR; 2) a position-weighted alignment score to prioritize similarity to TCR-interacting regions; 3) a predicted MHC class I binding affinity. Figure 5A In another case, traditional software, such as... Figure 5B As shown, and as stated above.

[0227] We begin with three melanoma-associated antigens that have been successfully used in several vaccination studies. TRP2 180-188 (Tyrosinase-associated protein 2), GP100 25-33 (Also known as PMEL; melanosome precursor protein) and TYR1 208-216 (Tyrosinase 1). It is predicted that TYR1... 208-216Not being a conjugate of mouse MHC, it was therefore considered an "irrelevant target." Using HEX, we identified viral peptides with high homology / affinity to the input tumor epitopes. Four virus-derived peptide libraries for each original tumor epitope (Table 1) were selected for further in vivo evaluation.

[0228] Antiviral immunity controls tumor growth through molecular mimicry of tumor antigens.

[0229] To assess whether virus-derived peptides affect tumor growth, we decided to immunize C57BL6 mice with a selected viral peptide library followed by tumor transplantation to mimic viral infection. Figure 6 A). Compared to the simulation, tumor growth was reduced in all immunized mice. Furthermore, significant differences were observed between the treatment groups. Mice immunized with a peptide virus library homologous to TRP2 or gp100 showed the greatest reduction in tumor growth ( Figure 6 B).

[0230] To further investigate the contribution of the selected viral peptides to reducing tumor growth, we collected mouse spleen cells at the endpoint for ELISpot assay. Figure 6 C). Compared with spleen cells from mice immunized with TYR1 homologous epitopes, spleen cells from mice immunized with viral peptide libraries homologous to TRP2 or gp100 promoted a higher IFN-γ response, which was associated with tumor growth.

[0231] We further investigated the reactivity of these spleen cells from virus-preimmunized mice to their respective homologous tumor antigens. Figure 7 A). When compared side-by-side, only viral peptides homologous to TRP2 showed higher IFN-γ secretion compared to homologous tumor peptides. Figure 7 B). Furthermore, we retrospectively evaluated the affinity of each tumor antigen and its homologous viral reservoir for C57BL / 6J MHC class I molecules ( Figure 7 C), and observed a significant correlation with their respective abilities to stimulate IFN-γ secretion (C). Figure 7 D). Following the guidelines of the Immune Epitope Database (IEDB), we used a 50 nM threshold to classify peptides into high-affinity and low-affinity peptides (http: / / tools.iedb.org / mhci / help / ) and observed that peptides with high MHC-I affinity promoted the production of more INF-γ compared to peptides with low MHC-I affinity. Figure 7 E). In summary, these results validate the predictive efficiency of the HEX tool in identifying homologous peptides and highlight the role of molecular mimicry between viruses and tumors in the antitumor immune response of cross-reactive T cells.

[0232] Viral epitopes that are highly similar to tumor epitopes can reduce the growth of established melanomas in vivo.

[0233] We have demonstrated that molecular mimicry between viruses and tumor antigens can influence tumor growth in pre-immunized mice. Next, we wanted to evaluate whether molecular mimicry-directed responses could affect established tumors in naïve mice. To this end, mice were implanted with either B16OVA tumors or the more aggressive and immunosuppressive B16F10 tumors, followed by treatment with the previously developed vaccine platform PeptiCRAd (20) to mimic viral infection. Figure 8A In short, PeptiCRAd is a vaccine technology consisting of adenoviruses coated with an MHC-I restricted peptide, which is a positively charged polyamino acid compound. In this case, we used the most effective peptide library from our first in vivo experiments. This was achieved using the original TRP2... 180-188 Adenoviruses are coated with epitopes (TRP2-PeptiCRAd) or corresponding TRP2-like viral-derived peptide libraries (viral PeptiCRAd) to prepare vaccines. For B16OVA ( Figure 8B-Figure 8 C) and B16F10 tumors ( Figure 8 E- Figure 8 Regarding F), intratumoral injection of PeptiCRAd significantly reduced tumor progression compared to treatment with saline-buffered or uncoated virus. Mice treated with the original tumor antigen or viral homolog showed significantly higher numbers of responders in both tumor models. Figure 8 D, Figure 8 (G). In both tumor models, when mice were treated with viral peptides similar to tumor peptides, we observed a significant reduction in tumor growth, again demonstrating that molecular mimicry may play a fundamental role in anti-tumor immunity involving cross-reactive T cells.

[0234] Can investigating the molecular mimicry between CMV and tumor antigens explain better prognosis?

[0235] We selected a melanoma-associated protein library

[21] and compared it with the CMV proteome using HEX, resulting in a list of tumor peptides highly similar to CMV (Table 2). The tumor peptides and their CMV counterparts were used in an ELISPOT assay, which showed that PBMCs consistently responded to both the virus and their corresponding tumor antigens in responding patients. This suggests that CMV infection expands the viral T-cell clone, which can attack and kill tumor cells, making seropositive patients more likely to respond to melanoma-specific epitopes similar to CMV. Figure 9A , Figure 9B While intriguing, this observation is limited by the lack of direct evidence that viral and tumor peptides amplify the same T-cell clones.

[0236] A novel microfluidic chip-based platform identified the immunopeptide profile in scarce tumor biopsy tissues.

[0237] We challenged the platform by studying the scarcity of tumor biopsies. Therefore, we collected ovarian metastatic tumors (high-grade serous) from patients, taking four samples from the tumor margins (S1, S2, S3, and S4); we also collected the central portion of the tumor (S5). Next, the samples were weighed, as follows... Figure 10A The samples, which were summarized, had an average size ranging from 0.01 g to 0.06 g. After sample digestion, the resulting single-cell suspensions were lysed and processed using a microarray. Peptide and protein identification was performed using a stringent false discovery rate threshold of 1%, and 916, 695, 172, 1128, and 256 unique peptides were identified in S1, S2, S3, S4, and S5, respectively. Figure 10A Consistent with typical ligand set profiles, widespread enrichment (over 70%) was observed in 7–13 mer samples. Figure 10A In terms of absolute quantity and percentage, the amino acid length distribution shows that the 9-mer specimen is the most representative. Figure 10B This confirms our findings and those of other previous immunopeptidome analyses. Next, we further investigated the source proteins identified in our data using Gene Ontology (GO) enrichment analysis. Consistent with typical ligandome profiles, metabolic processes were enriched in all examined samples. Furthermore, the analysis revealed an increase in proteins from skin development pathways, consistent with the epithelial nature of the ovarian serous tumors analyzed in this paper. Overall, these results underscore the feasibility of utilizing the developed microfluidic chip platform to analyze scarce tumor biopsies and obtain personalized antigenic peptides for cancer therapy.

[0238] A microchip-based approach reveals the immune peptide landscape in patient-derived organoids.

[0239] The challenge facing microchip technology is the availability of patient-derived organoids (PDOs) as small as 6 × 10⁻⁶. 6 Two patients were selected from an ongoing precision medicine study of urological cancers: one was a nephrectomy sample containing both benign and cancerous tissue from a patient with clear cell renal cell carcinoma (ccRCC), and the other was a 1x1cm sample from a patient with bladder cancer. These samples were further processed into 3D primitive organoid cultures.

[0240] By employing microchip technology and a stringent false discovery rate threshold of 1% for peptide and protein identification, we were able to identify a total of 576 and 2089 unique peptides in ccRCC and bladder PDO, respectively. Figure 11AThe number of peptides retrieved differed between the two samples, with the bladder sample producing more peptides than the ccRCC sample. It is well known that HLA expression influences the number of isolated HLA-I peptides [22A], and consistent with this, flow cytometry analysis showed higher surface levels of HLA-A, HLA-B, and HLA-C in our bladder sample than in our ccRCC sample, explaining the different yields of peptides retrieved in our samples. Peptide analysis showed a preference for 9–12-mer peptides (56.4% in ccRCC and 47.9% in bladder tumors), with enrichment in the 9-mer population, consistent with the typical length distribution observed in ligand analysis

[33] . Figure 11B To distinguish HLA-I binders from contaminants, Gibbs clustering and NetMHC 4.0 analysis were performed. First, deconvolution of the 9mers revealed that 55% and 67% of those in the bladder and ccRCCPDO, respectively, matched at least one HLA allele from the patient. Next, NetMHC 4.0 was applied to all 9mers identified in our datasets. Of these, 46% and 69% were predicted to be patient-specific HLA binders. Next, the source proteins present in both datasets were investigated. For this purpose, Gene Ontology (GO) enrichment analysis was performed. Consistent with our previous observations and published data, both samples showed enrichment of intracellular and nuclear proteins that interact with RNA and are involved in catabolic / metabolic processes.

[0241] To demonstrate that this technology can be used for the rapid development of therapeutic cancer vaccines, we established a lethality assay. Our analysis focused on ccRCC samples. We used transcriptomics to select putative tumor antigens, using PBMCs and healthy kidney tissue as reference sets. Next, PBMCs from healthy volunteers were pulsed with selected peptides, and CD8+ T cells isolated from these cells were used for the assay. T cells pulsed with the peptide EVAQPGPSNR (genetic name HSPG2) showed approximately 10% specific cell lysis.

[0242] Finally, we attempted to investigate the recall T-cell response in ccRCC patients. For this purpose, ungraded PBMCs from patients were stimulated in vitro with the peptide EVAQPGPSNR, while unstimulated PBMCs served as a control. The derived CD8+ T cells were then added to the ccRCC PDO, resulting in an approximately 7% increase in cytotoxic activity compared to the control group.

[0243] Peptides derived from patient organoids have been shown to have therapeutic effects in in vivo studies.

[0244] The peptide list was analyzed using HEX. First, the software prioritized peptides exhibiting both strong binding affinity (IC50 cutoff values ​​ranging from 50 nM to 500 nM according to NetMHC 4.0) and a high weighted ranking score (normalized weighted ranking score cutoff value of 0.8–1). The latter focused peptide similarity on interaction regions most likely to bind to the TCRs of CD8+ T cells to induce mediated immune responses; then, based on their overall percentage of identity with pathogen-derived antigens / peptides and IC50... 50 The peptides were further classified based on affinity scores. The final results consisted of 13 peptides and their corresponding pathogenic peptides (Table 4).

[0245] To determine the immunogenicity of the peptides, mice were pre-immunized by subcutaneous injection of each individual peptide in the presence of the adjuvant Poly(I:C); a control group of mice was injected with either Poly(I:C) or saline alone. Spleen cells from these mice were harvested, and IFNγ production under specific stimuli was tested in an ELISpot assay (Table 5).

[0246] Next, we sought to validate whether the candidate peptides could serve as cancer vaccines for treating established tumors. To this end, we employed PeptiCRAd, our previously developed cancer vaccine platform, which combines an oncolytic adenovirus with a polylysine-modified capsid linked (via a polylysine linker). The adenovirus used here was VALO-mD901, genetically modified to express mouse OX40L and CD40L, and previously demonstrated to induce tumor growth control and a systemic antitumor response in a mouse melanoma model. Therefore, Balb / c mice were subcutaneously injected with the syngeneic tumor model CT26 (day 0, ...) on the left and right sides. Figure 12A Once the tumor is established (day 7), Figure 12A Valo-mD901 was coated with each pair of polylysine-modified peptides (PeptiCRAd1, PeptiCRAd2, PeptiCRAd3, Table 6) from our list, and intratumoral injection was performed only in the right-sided tumor. PeptiCRAd4 consisted of Valo-mD901 coated with gp70423-431 (AH1-5). The mimic group and the Valo-mD901 group were also used as controls. PeptiCRAd1 and PeptiCRAd2, as well as Valo-mD901, improved tumor growth control in the injected lesion. Figure 12B (See right figure). Advantageously, PeptiCRAd1 improved anti-tumor growth control in untreated tumors, while Valo-mD901 did not elicit any effect.

[0247] Summarize

[0248] HEX is a bioinformatics tool that analyzes peptide sequences and compares them with curated databases of pathogen-derived viral proteomes to find sequences with high similarity.

[0249] Since the proposed peptides are primarily involved in interactions with anchor residues of the MHC

[25] , our software returns a permutation score that is position-weighted to prioritize similarities occurring at the center of the peptide, i.e., the position most involved in TCR interactions

[26] . Furthermore, to increase the chances that our target is the proposed epitope, we rank the resulting peptides according to their binding affinity to the selected MHC, in one instance using the IEDB NetMHC prediction tool API

[27] ; or NetMHC4.0 or NetMHCpan4.1b as separate tools.

[0250] We used HEX to identify viral peptides homologous to three widely characterized tumor-associated antigens.

[0251] We found that pre-immunization with our selected viral peptide library simulated an antiviral immune state before tumor formation and effectively slowed the growth of subcutaneously injected melanoma cells in mice, suggesting that pre-exposure to virus-derived peptides can influence tumor growth.

[0252] Next, we observed that when administered during tumor development, the tumor homologous virus-derived peptide had a similar effect on established tumors, indicating that viral infection occurring during tumor development can still influence its growth.

[0253] In summary, our results suggest that molecular mimicry between virus-derived antigens and tumor-derived antigens can exert a controlling effect on tumor growth, even without prior exposure or pre-acquired immunity.

[0254] Novel ICPIs have significantly improved patient survival for several solid tumors, particularly metastatic melanoma, compared to other commonly used therapies such as radiotherapy and chemotherapy. However, despite improvements in survival and response rates, it remains unclear why some patients do not benefit from ICPI therapy. Our results indicate that patients with high titers of CMV-specific IgG have significantly prolonged progression-free survival.

[0255] We observed that the PBMCs of patients with high anti-CMV-IgG titers reacted with melanoma antigens similarly to CMV peptides. This data suggests that CMV seropositivity contributes to melanoma-specific T-cell immunity, thus providing a clinical advantage for these patients receiving ICPI therapy.

[0256] Here we show that viral infection may influence tumor growth and clearance. Furthermore, we demonstrate the cross-reactivity of cytotoxic T cells to virus-derived antigens and homologous tumor-derived antigens selected using HEX. Based on our results, we conclude that molecular mimicry could be utilized in the future to develop new therapies, or, when used in conjunction with immunotherapy, potentially enhance the anti-tumor immune effects achieved by these therapies.

[0257] Furthermore, designing effective tumor rejection and protection strategies requires reliable identification of tumor peptides that bind to HLA-I. Direct identification of peptides from HLA-I complexes remains the best approach. However, the workflow of immunopeptidomics is relatively complex, thus representing a major bottleneck in antigen discovery. Currently, the inability to analyze immunopeptidomes of small amounts of biological material (such as tissue needle biopsies) on conventional platforms, sample throughput, cost, and the use of affinity matrices (which are both labor-intensive and expensive to produce) are identified as major technical challenges that need to be addressed.

[0258] In this work, we addressed several technical challenges that have hampered ligandome research, primarily focusing on the limited availability of analytical materials, the cost of consumables, and lengthy protocols.

[0259] By immobilizing biotinylated pan-HLA antibodies on streptavidin-functionalized surfaces using well-characterized biotin-streptavidin interactions, we were able to replace traditional techniques based on affinity matrices prepared via cross-linking reactions and a microchip platform. The limitations imposed by the scarcity of materials (such as needle biopsies) spurred our work on implementing microfluidic schemes. In this work, we employed a custom microchip scheme involving an array of thiol-olefin polymer-based micropillars as a solid support for further biofunctionalization, enabling the entire IP process to be executed on a single microfluidic chip.

[0260] The identified peptides were validated in an in vitro killing assay, confirming that the peptides identified during the implementation of this invention were indeed present on the surface of JY cells, as they were killed in a specific CD8+ T cell-dependent manner. The peptide ILDKKVEKV (SEQ ID NO:3) found in our dataset caused a high proportion of specific cell lysis.

[0261] Therefore, our method provides an undeveloped tool for immunoaffinity purification.

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[0277]

[0278] sequence list <110> University of Helsinki <120> Bioinformatics <130> 4649P / WO <150> GB2006760.9 <151> 2020-05-07 <160> 80 <170> PatentIn version 3.5 <210> 1 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISspot peptide 1 <400> 1 Ser Tyr His Pro Ala Leu Asn Ala Ile 1 5 <210> 2 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISpot peptide 2 <400> 2 Ser Tyr Leu Thr Ser Ala Ser Ser Leu 1 5 <210> 3 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISpot peptide 3 <400> 3 Tyr Tyr Val Arg Ile Leu Ser Thr Ile 1 5 <210> 4 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISpot peptide 4 <400> 4 Ser Tyr Leu Pro Pro Gly Thr Ser Leu 1 5 <210> 5 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISpot peptide 5 <400> 5 Arg Tyr Leu Pro Ala Pro Thr Ala Leu 1 5 <210> 6 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISpot peptide 6 <400> 6 Lys Tyr Ile Pro Ala Ala Arg His Leu 1 5 <210> 7 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISpot peptide 7 <400> 7 Ala Phe His Ser Ser Arg Thr Ser Leu 1 5 <210> 8 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISspot peptide 8 <400> 8 Asn Tyr Asn Ser Val Asn Thr Arg Met 1 5 <210> 9 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISpot peptide 9 <400> 9 Ser Tyr Ser Asp Met Lys Arg Ala Leu 1 5 <210> 10 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISpot peptide 10 <400> 10 Phe Tyr Glu Lys Asn Lys Thr Leu Val 1 5 <210> 11 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISpot peptide 11 <400> 11 Lys Gly Pro Asn Arg Gly Val Ile Ile 1 5 <210> 12 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISpot peptide 12 <400> 12 Phe Tyr Lys Asn Gly Arg Leu Ala Val 1 5 <210> 13 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISpot peptide 13 <400> 13 Leu Tyr Lys Glu Ser Leu Ser Arg Leu 1 5 <210> 14 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISpot peptide 14 <400> 14 Ser Tyr Arg Asp Val Ile Gln Glu Leu 1 5 <210> 15 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISspot peptide 15 <400> 15 Lys Phe Tyr Asp Ser Lys Glu Thr Val 1 5 <210> 16 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISpot peptide 16 <400> 16 Lys Tyr Leu Asn Val Arg Glu Ala Val 1 5 <210> 17 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISspot peptide 17 <400> 17 His Tyr Leu Pro Asp Leu His His Met 1 5 <210> 18 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISpot peptide 18 <400> 18 Ser Gly Pro Asn Arg Phe Ile Leu Ile 1 5 <210> 19 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISpot peptide 19 <400> 19 Ser Tyr Ile Ile Gly Thr Ser Ser Val 1 5 <210> 20 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISpot peptide 20 <400> 20 Arg Gly Pro Tyr Val Tyr Arg Glu Phe 1 5 <210> twenty one <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISpot peptide 21 <400> twenty one Phe Tyr Ala Thr Ile Ile His Asp Leu 1 5 <210> twenty two <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISpot peptide 22 <400> twenty two Gly Tyr Met Thr Pro Gly Leu Thr Val 1 5 <210> twenty three <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISpot peptide 23 <400> twenty three Ser Tyr Leu Ile Gly Arg Gln Lys Ile 1 5 <210> twenty four <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISpot peptide 24 <400> twenty four Ala Gly Ala Ser Arg Ile Ile Gly Ile 1 5 <210> 25 <211> 8 <212> PRT <213> Artificial sequence <220> <223> ELISspot peptide 25 <400> 25 Gln Pro Glu Tyr Ile Glu Arg Leu 1 5 <210> 26 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISpot peptide 26 <400> 26 Ser Tyr Ile His Gln Arg Tyr Ile Leu 1 5 <210> 27 <211> 9 <212> PRT <213> Artificial sequence <220> <223> ELISspot peptide 27 <400> 27 Ser Pro Ser Tyr Ala Tyr His Gln Phe 1 5 <210> 28 <211> 15 <212> PRT <213> Artificial sequence <220> <223> Polylysine peptide <400> 28 Lys Lys Lys Lys Lys Lys Ser Tyr Leu Pro Pro Gly Thr Ser Leu 1 5 10 15 <210> 29 <211> 15 <212> PRT <213> Artificial sequence <220> <223> Polylysine peptide <400> 29 Lys Lys Lys Lys Lys Lys Arg Tyr Leu Pro Ala Pro Thr Ala Leu 1 5 10 15 <210> 30 <211> 14 <212> PRT <213> Artificial sequence <220> <223> Polylysine Peptide <400> 30 Lys Lys Lys Lys Lys Lys Tyr Ile Pro Ala Ala Arg His Leu 1 5 10 <210> 31 <211> 15 <212> PRT <213> Artificial sequence <220> <223> Polylysine peptide <400> 31 Lys Lys Lys Lys Lys Lys Leu Tyr Lys Glu Ser Leu Ser Arg Leu 1 5 10 15 <210> 32 <211> 15 <212> PRT <213> Artificial sequence <220> <223> Polylysine peptide <400> 32 Lys Lys Lys Lys Lys Lys Lys Tyr Leu Asn Val Arg Glu Ala Val 1 5 10 15 <210> 33 <211> 16 <212> PRT <213> Artificial sequence <220> <223> Polylysine peptide <400> 33 Lys Lys Lys Lys Lys Lys Lys Phe Tyr Ala Thr Ile Ile His Asp Leu 1 5 10 15 <210> 34 <211> 15 <212> PRT <213> Artificial sequence <220> <223> Polylysine peptide <400> 34 Lys Lys Lys Lys Lys Lys Ser Pro Ser Tyr Ala Tyr His Gln Phe 1 5 10 15 <210> 35 <211> 9 <212> PRT <213> Artificial sequence <220> <223> Viral peptide herpesvirus 2 <400> 35 Leu Pro Trp His Arg Leu Phe Leu Leu 1 5 <210> 36 <211> 9 <212> PRT <213> Artificial sequence <220> <223> Viral peptide library 1 Orthoreovirus <400> 36 Phe Ala Trp Pro Arg Leu Phe Glu Leu 1 5 <210> 37 <211> 9 <212> PRT <213> Artificial sequence <220> <223> Viral peptide library 1 Orthoreovirus <400> 37 Leu Arg Trp Thr Arg Leu Ala Leu Leu 1 5 <210> 38 <211> 9 <212> PRT <213> Artificial sequence <220> <223> Viral peptide library 1 strain ad169 <400> 38 Leu Tyr Gly His Arg Leu Phe Arg Leu 1 5 <210> 39 <211> 9 <212> PRT <213> Artificial sequence <220> <223> Viral peptide library 1 lister <400> 39 Leu Phe Leu His Leu Leu Gln Leu Leu 1 5 <210> 40 <211> 9 <212> PRT <213> Artificial sequence <220> <223> trp2 <400> 40 Ser Val Tyr Asp Phe Phe Val Trp Leu 1 5 <210> 41 <211> 9 <212> PRT <213> Artificial sequence <220> <223> Viral peptide library 2 metapneumovirus <400> 41 Leu Asn Tyr Asp Phe Phe Glu Ala Leu 1 5 <210> 42 <211> 9 <212> PRT <213> Artificial sequence <220> <223> Viral peptide library 2 influenza <400> 42 Ser Val Asn Ser Phe Phe Ser Arg Leu 1 5 <210> 43 <211> 9 <212> PRT <213> Artificial sequence <220> <223> Viral peptide library 2 Viral core cysteine ​​protease cowpox <400> 43 Lys Val Tyr Thr Phe Phe Lys Phe Leu 1 5 <210> 44 <211> 9 <212> PRT <213> Artificial sequence <220> <223> Viral peptide library 2 protein ul32 herpes <400> 44 Ser Asn Tyr Ser Phe Phe Val Gln Ala 1 5 <210> 45 <211> 9 <212> PRT <213> Artificial sequence <220> <223> Viral peptide library 3 <400> 45 Lys Val Pro Arg Asn Gln Asp Trp Leu 1 5 <210> 46 <211> 9 <212> PRT <213> Artificial sequence <220> <223> Viral peptide library 3 capsid protein papillomavirus <400> 46 Lys Val Pro Leu Asn Ala Asp Val Leu 1 5 <210> 47 <211> 9 <212> PRT <213> Artificial sequence <220> <223> Viral peptide library 3 orfla protein enteric coronavirus <400> 47 Lys Ala Thr Arg Asn Asn Cys Trp Leu 1 5 <210> 48 <211> 9 <212> PRT <213> Artificial sequence <220> <223> Viral peptide library 3 Epstein-Barr virus <400> 48 Ala Val Ala Arg Asn Thr Asp Ile Leu 1 5 <210> 49 <211> 9 <212> PRT <213> Artificial sequence <220> <223> Viral peptide library 3 Echovirus <400> 49 Ile Val Val Arg Asn His Asp Asp Leu 1 5 <210> 50 <211> 9 <212> PRT <213> Homo sapiens <400> 50 Leu Leu Asp Thr Arg Thr Leu Glu Val 1 5 <210> 51 <211> 9 <212> PRT <213> Homo sapiens <400> 51 Ala Met Ala Ser Ala Ser Ser Ser Ala 1 5 <210> 52 <211> 9 <212> PRT <213> Homo sapiens <400> 52 Glu Ile Leu Asp Val Pro Ser Thr Val 1 5 <210> 53 <211> 9 <212> PRT <213> Homo sapiens <400> 53 Met Leu Ala Arg Leu Ala Ser Ala Ala 1 5 <210> 54 <211> 9 <212> PRT <213> Homo sapiens <400> 54 Asn Met Met Gly Leu Tyr Asp Gly Met 1 5 <210> 55 <211> 9 <212> PRT <213> Human cytomegalovirus <400> 55 Met Leu Asp Arg Arg Thr Val Glu Met 1 5 <210> 56 <211> 9 <212> PRT <213> Human cytomegalovirus <400> 56 Ala Met Ala Gly Ala Ser Thr Ser Ala 1 5 <210> 57 <211> 9 <212> PRT <213> Human cytomegalovirus <400> 57 Asp Met Met Glu Met Pro Ala Thr Met 1 5 <210> 58 <211> 9 <212> PRT <213> Human cytomegalovirus <400> 58 Phe Leu Thr Arg Leu Ala Glu Ala Ala 1 5 <210> 59 <211> 9 <212> PRT <213> Human cytomegalovirus <400> 59 Cys Met Met Thr Met Tyr Gly Gly Ile 1 5 <210> 60 <211> 9 <212> PRT <213> Molluscum contagiosum virus <400> 60 Ser Tyr His Ala Ala Leu Asn Ala Leu 1 5 <210> 61 <211> 9 <212> PRT <213> Human adenovirus type 31 <400> 61 His Phe Ser Thr Ser Arg Thr Ser Leu 1 5 <210> 62 <211> 9 <212> PRT <213> Macaque herpesvirus 1 <400> 62 Ala Tyr Gln Asp Thr Lys Arg Ala Leu 1 5 <210> 63 <211> 9 <212> PRT <213> Human herpesvirus 7 <400> 63 Phe Tyr Asn Ser Val Asn Thr Arg Asn 1 5 <210> 64 <211> 9 <212> PRT <213> Influenza A virus <400> 64 Thr Ile Trp Thr Ser Ala Ser Ser Ile 1 5 <210> 65 <211> 9 <212> PRT <213> Epstein-Barr virus <400> 65 Thr Tyr Leu Pro Pro Ser Thr Ser Ser 1 5 <210> 66 <211> 9 <212> PRT <213> Orf virus <400> 66 Asn Tyr Tyr Lys Asn Lys Ser Leu Val 1 5 <210> 67 <211> 9 <212> PRT <213> Human adenovirus type 41 <400> 67 Ala Tyr Met Asn Gly Arg Val Ala Val 1 5 <210> 68 <211> 9 <212> PRT <213> Smallpox virus <400> 68 Lys Asn Pro Asn Arg Phe Val Ile Phe 1 5 <210> 69 <211> 9 <212> PRT <213> Human cytomegalovirus <400> 69 Ser His Gln Pro Ala Ala Arg Arg Leu 1 5 <210> 70 <211> 9 <212> PRT <213> Influenza C virus <400> 70 Arg Asn Met Pro Ala Ala Thr Ala Leu 1 5 <210> 71 <211> 9 <212> PRT <213> Human cytomegalovirus <400> 71 Ser His Gln Pro Ala Ala Arg Arg Leu 1 5 <210> 72 <211> 9 <212> PRT <213> Molluscum contagiosum virus <400> 72 Tyr Val Phe Arg Leu Leu Ser Thr Ile 1 5 <210> 73 <211> 9 <212> PRT <213> Human cytomegalovirus <400> 73 Arg Tyr Ala Asp Val Ile Gln Glu Val 1 5 <210> 74 <211> 9 <212> PRT <213> Human adenovirus type 18 <400> 74 Asn Phe Tyr Asn Ser Lys Glu Thr Val 1 5 <210> 75 <211> 9 <212> PRT <213> Artificial sequence <220> <223> MAGE A1 gene <400> 75 Lys Val Leu Glu Tyr Val Ile Lys Val 1 5 <210> 76 <211> 9 <212> PRT <213> Artificial sequence <220> <223> HSP90 gene <400> 76 Ile Leu Asp Lys Lys Val Glu Lys Val 1 5 <210> 77 <211> 9 <212> PRT <213> Artificial sequence <220> <223> PSME3 <400> 77 Gln Leu Val Asp Ile Ile Glu Lys Val 1 5 <210> 78 <211> 10 <212> PRT <213> Artificial sequence <220> <223> NNMT gene <400> 78 Val Ile Met Asp Ala Leu Lys Ser Ser Tyr 1 5 10 <210> 79 <211> 9 <212> PRT <213> Artificial sequence <220> <223> FGA gene <400> 79 Phe Leu Ala Glu Gly Gly Gly Val Arg 1 5 <210> 80 <211> 10 <212> PRT <213> Artificial sequence <220> <223> HSPG2 gene <400> 80 Glu Val Ala Gln Pro Gly Pro Ser Asn Arg 1 5 10

Claims

1. A method for identifying tumor-specific antigens, the method comprising: i) Dissolve or suspend the tumor sample in a liquid; ii) Passing the liquid through a microfluidic device for tumor-specific antigen identification, the microfluidic device comprising: at least one flow channel containing a plurality of microcolumns arranged in an array, the microcolumns being attached to at least one molecule or at least one complex, the molecule or complex being bound to at least one antibody against major histocompatibility complex (pMHC) or at least one antibody against pan-human leukocyte antigen (PVA), thereby enabling the extraction of peptides from the sample flowing through the channel using the at least one antibody; iii) Binding the at least one antibody to at least one pMHC in the sample; iv) Remove at least one of the bound pMHCs from the device in part iii); v) The peptide of the bound pMHC is compared with a pathogen-derived antigen library to determine whether the peptide shows homology with at least one pathogen antigen or a portion thereof, and wherein there is greater than 90% homology. vi) Identify the peptide as a tumor-specific antigen for cancer therapy.

2. The method of claim 1, wherein the pathogen-derived antigen library comprises a planned library of known pathogen antigens.

3. The method according to claim 1 or 2, wherein the pathogen antigen is a human pathogen antigen.

4. The method according to claim 1, wherein the pathogen antigen is a virus.

5. The method of claim 1, wherein the pathogen antigen is derived from at least one virus selected from the group consisting of, and includes any combination thereof: Abyssoviridae; Ackermannviridae; Actantavirinae; Adenoviridae; Agantavirinae; Aglimvirinae; Alloherpesviridae; Alphaflexiviridae; Alphaherpesvirinae; Alphairidovirinae; Alphasatellitidae; Alphatetraviridae; Alvernaviridae; Amalgaviridae; Amnoonviridae; Ampullaviridae; Anelloviridae; Arenaviridae; Arquatrovirinae; Arteriviridae; Artoviridae; Ascoviridae; Asfarviridae; Aspiviridae; Astroviridae; Autographivirinae; Avsunviroidae; Avulavirinae; Diatoms DNA Viridae (Bacilladnaviridae); Baculoviridae; Barnaviridae; Bastillevirinae; Bclasvirinae; Belpaoviridae; Benyviridae; Betaflexiviridae; Betaherpesvirinae; Betairidovirinae; Bicaudaviridae; Bidnaviviridae dae); Birnaviridae; Bornaviridae; Botourmiaviridae; Brockvirinae; Bromoviridae; Bullavirinae; Caliciviridae; Calvusvirinae; Carmotetraviridae; Caulimoviridae; Ceronivirinae; Chebruvirinae; Chordopoxvirinae irinae); Chrysoviridae; Chuviridae; Circoviridae; Clavaviridae; Closteroviridae; Comovirinae; Coronaviridae; Corticoviridae; Crocarterivirinae; Cruliviridae; Crustonivirinae; Cvivirinae; Cystoviridae; Dclasvirinae;Deltaflexiviridae; Densovirinae; Dicistroviridae; Endornaviridae; Entomopoxvirinae; Equarterivirinae; Eucampyvirinae; Euroniviridae; Filoviridae; Fimoviridae; Firstpapillomavirinae; Flaviviridae; Microspinifera Family: Fuselloviridae; Gammaflexiviridae; Gammaherpesvirinae; Geminialphasatellitinae; Geminiviridae; Genomoviridae; Globuloviridae; Gokushovirinae; Guernseyvirinae; Guttaviridae; Hantaviridae; Hepadnaviridae; Hepeviridae Herpesviridae; Herelleviridae; Heroarterivirinae; Herpesviridae; Hexponivirinae; Hypoviridae; Hytrosaviridae; Iflaviridae; Inoviridae; Iridoviridae; Jasinkavirinae; Kitaviridae; Lavidaviridae; Leishbuviridae; Letovirinae; Leviviridae Lipothrixviridae; Lispiviridae; Luteoviridae; Malacoherpesviridae; Mammantavirinae; Marnaviridae; Marseilleviridae; Matonaviridae; Mcleskeyvirinae; Mclasvirinae; Medioniviridae; Medionivirinae; Megabirnaviridae;Mesoniviridae; Metaparamyxovirinae; Metaviridae; Microviridae; Mimiviridae; Mononiviridae; Mononivirinae; Mymonaviridae; Myoviridae; Mypoviridae; Nairoviridae; Nanoalphasatellitinae; Nanoviridae; Narnaviridae Nclasvirinae; Nimaviridae; Nodaviridae; Nudiviridae; Nyamiviridae; Nymbaxtervirinae; Okanivirinae; Orthocoronavirinae; Orthomyxoviridae; Orthoparamyxovirinae; Orthoretrovirinae; Ounavirinae; Ovaliviridae; Papilloma viridae); Paramyxoviridae; Partitiviridae; Parvoviridae; Parvovirinae; Pclasvirinae; Peduovirinae; Peribunyaviridae; Permutotetraviridae; Phasmaviridae; Phenuiviridae; Phycodnaviridae; Picobirnaviridae; PicRNAviridae ornaviridae); Picovirinae; Piscanivirinae; Plasmaviridae; Pleolipoviridae; Pneumoviridae; Podoviridae; Polycipiviridae; Polydnaviridae; Polyomaviridae; Portogloboviridae; Pospiviroidae; Potato Y Viridae;Poxviridae; Procedovirinae; Pseudoviridae; Qinviridae; Quadriviridae; Quinvirinae; Regressovirinae; Remotovirinae; Reoviridae; Repantavirinae; Retroviridae; Rhabdoviridae; Roniviridae; Rubulavirinae; Archaphageidae iviridae); Sarthroviridae; Secondpapillomavirinae; Secoviridae; Sedoreovirinae; Sepvirinae; Serpentovirinae; Simarterivirinae; Siphoviridae; Smacoviridae; Solemoviridae; Solinviviridae; Sphaerolipoviridae; Spinare ovirinae); Spiraviridae; Spounavirinae; Spumaretrovirinae; Sunviridae; Tectiviridae; Tevenvirinae; Tiamatvirinae; Tobaniviridae; Togaviridae; Tolecusatellitidae; Tombusviridae; Torovirinae; Tospoviridae e; Totiviridae; Tristromaviridae; Trivirinae; Tunavirinae; Tunicanivirinae; Turriviridae; Twortvirinae; Tymoviridae; Vararterivirinae; Vequintavirinae; Virgaviridae; Wupedeviridae; Xinmoviridae; Yueviridae; and Zealarterivirinae.

6. The method according to claim 1, wherein the pathogen antigen is a cytomegalovirus antigen or an Epstein-Barr virus antigen, or a herpesvirus antigen, or a poxvirus antigen, or a hepatotropic DNA virus antigen, or an influenza virus antigen, or a coronavirus antigen, or a hepatitis virus antigen, or an HIV antigen, or a Bunyavirus antigen.

7. The method of claim 1, wherein comparing the peptide of the bound pMHC with a pathogen antigen library involves peptide scoring and / or arrangement scoring to determine the homology.

8. The method of claim 1, wherein comparing the peptide bound to pMHC with a pathogen antigen library involves determining: a) The similarity or identity of the entire sequence structure of the peptide and the pathogen antigen; and / or b) The similarity or identity of key amino acids at the key binding sites of the peptide and the pathogen antigen; and / or c) The maximum number of similar or identical key amino acids in the key binding sites of the peptide and the pathogen antigen.

9. An apparatus for identifying tumor-specific antigens, the apparatus comprising: A microfluidic device comprising at least one flow channel containing a plurality of micropillars arranged in an array, wherein at least one molecule or at least one complex is attached to the micropillars, and the molecule or complex is bound to at least one antibody against major histocompatibility complex (pMHC) or at least one antibody against pan-human leukocyte antigen (PUA), thereby enabling the extraction of peptides from a sample flowing through the channel using the at least one antibody. The processor is adapted to identify the peptide bound to the major histocompatibility complex (MHC) and compare the bound pMHC peptide with a pathogen-derived peptide antigen library to determine whether the peptide bound to or bound to the MHC shows homology / affinity with at least one pathogen antigen or a portion thereof, and wherein greater than 90% homology is present; and to identify the peptide bound to or bound to the MHC as a tumor-specific antigen for cancer treatment.

10. The apparatus of claim 9, wherein the human leukocyte antigen is selected from the group consisting of MHC class I A, B and C.

11. The device of claim 9, wherein the human leukocyte antigen is selected from the group consisting of MHC class II DP, DM, DO, DQ and DR.

12. The apparatus of claim 9, wherein the antibody is anti-human.

13. The apparatus of claim 9, wherein the molecule or complex is a complex of thiols and alkene functional groups.

14. The apparatus of claim 9, wherein the molecule or complex comprises biotin and streptavidin.

15. The apparatus of claim 9, wherein the molecule or complex comprises one or more antibodies that bind to streptavidin.

16. The apparatus of claim 9, wherein the molecule or complex is modulated by coating with bovine serum albumin prior to binding with the antibody.

17. The apparatus of claim 9, wherein the apparatus is adapted to perform the method of any one of claims 1-8.

18. A method for generating an isolated population of T cells for cancer treatment, the method comprising: i) Extracting tumor samples from the patient; ii) Dissolve or suspend the sample in a liquid; iii) Passing the liquid through a microfluidic device for tumor-specific antigen identification, the microfluidic device comprising: at least one flow channel containing a plurality of microcolumns arranged in an array, wherein at least one molecule or at least one complex is attached to the microcolumns, and the molecule or complex is bound to at least one antibody against major histocompatibility complex (pMHC) or at least one antibody against pan-human leukocyte antigen (PVA), thereby enabling the extraction of peptides from the sample flowing through the channel using the at least one antibody; iv) Bind the at least one antibody to at least one pMHC in the sample; v) Remove at least one of the bound pMHCs from the device (iv); vi) The peptide of the bound pMHC is compared with a human pathogen-derived antigen library to determine whether the peptide shows homology with at least one human pathogen antigen or a portion thereof, and wherein there is greater than 90% homology. vii) Identifying the peptide as a tumor-specific antigen; and viii) Administer an effective amount of the peptide to the isolated T cell population of the patient to stimulate or activate the T cells against tumor-specific antigens, thereby combating cancer from which the sample was taken; or use the tumor-specific antigens to expand the isolated T cell population of the patient that is active against the tumor-specific antigens.

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