Bioinformatics

Abstract

The present invention relates to a tumor antigen identification device and a tumor antigen identification method; a tumor antigen identified using such device and / or method; a pharmaceutical composition comprising such tumor antigen; a method for treating cancer using such device and / or method; a method for stratifying patients to treat cancer using such device and / or method; a therapeutic regimen comprising stratifying patients to treat cancer using such device and / or method and then administering a cancer treatment agent; and a tumor antigen identified using such device and / or method for use as a cancer vaccine or immunogenic substance or cancer therapy.

Description

Technology Field

[0001] The present invention relates to a tumor antigen identification device and a tumor antigen identification method; a tumor antigen identified using such device and / or method; a pharmaceutical composition comprising such tumor antigen; a method for treating cancer using such device and / or method; a method for stratifying patients to treat cancer using such device and / or method; a therapeutic regimen comprising stratifying patients to treat cancer using such device and / or method and then administering a cancer treatment agent; and a tumor antigen identified using such device and / or method for use as a cancer vaccine or immunogenic substance or cancer therapy. Background Technology

[0002] CD8 + T cells play a pivotal role in detecting and eliminating cells that present abnormal peptides on their surface as a result of pathogenic infections, such as viral infections, or malignant transformation. The cross-reactivity of T-cell receptors (TCRs) means that T cells can recognize a vast variety of target peptides. This phenomenon enables a relatively small number of T cells to recognize multiple pMHCs (Peptides: Major Histocompatibility Complexes) that indicate an abnormal cell and thus pose a potential threat to health or life.

[0003] However, an inappropriate side effect of this mechanism is that immune responses targeting pathogens can exceed the tolerance threshold for highly homologous self-antigens, leading to harmful non-target effects mediated by T-cell cross-reactivity, known as molecular mimicry. In the field of autoimmunity, the potentially harmful consequences resulting from this homology between self-peptides and pathogenic peptides are well known, but have not been analyzed in cancer.

[0004] In fact, the best prognostic markers signifying successful outcomes in cancer immunotherapeutic treatment have been considered to be a high tumor antigen mutation rate and significant T-cell infiltration. This idea is based on the assumption that tumors with a high number of mutations are more likely to be recognized and eliminated by infiltrating T-cells.

[0005] Nevertheless, some studies have shown that the qualitative characteristics of tumor antigens may be more important than their quantitative aspects. Additionally, it has been observed that while antiviral T-cells reside in the tumor microenvironment

[28] , it is still unclear whether their role is active or merely bystander.

[0006] Tumor immunology and immunotherapy have completely transformed cancer treatment methods over the past decade, achieving excellent clinical results, particularly with the use of checkpoint inhibitors (ICIs), but unfortunately, these results have been limited to a small number of patients. It is becoming clear that immunotherapy using ICIs works fully only when specific tumor antigens are targeted. However, there is currently no easy or rapid method to identify these tumor antigens. The problem to be solved

[0007] In the present invention, the inventors hypothesized that a tumor may present a peptide that shares a high level of homology or affinity with pathogen-derived peptides, particularly viral peptides, thereby enabling pathologically generated cross-reactive T cells to recognize and kill tumor cells.

[0008] To this end, the inventors developed a bioinformatics device referred to as HEX (Homogeneity Assessment of Xenopeptides) for automatically and very simply identifying tumor antigens that are very similar to viral peptides. Using this device, the inventors observed that antiviral T-cell immunity mediated by peptides with high levels of homology or affinity for cancer antigens can actively control tumor proliferation in prophylactic and therapeutic situations. These observations demonstrate the cross-reactivity of T-cells activated to both homologous virus-derived peptides and tumor-derived peptides.

[0009] Next, the inventors found that the response of melanoma patients to checkpoint inhibitor therapy (anti-PD1) can be stratified by the humoral response to cytomegalovirus (CMV). Indeed, peptides homologous to CMV and melanoma, identified using the HEX device, were found to promote Inf-g secretion in peripheral blood mononuclear cells (PBMCs) derived from CMV seropositive melanoma patients. means of solving the problem

[0010] In a first aspect, the present invention provides an apparatus for identifying a tumor antigen comprising:

[0011] At least one fluid-pass channel comprising a plurality of supports to which at least one molecule or at least one complex is attached, to which one or more anti-MHC (major histocompatibility complex) antibodies or one or more universal anti-human leukocyte antigen (HLA) (anti-pan-HLA) antibodies are bound, so as to be able to extract pMHC (peptide: major histocompatibility complex) within a sample flowing through the channel from a sample using at least one antibody.

[0012] In the present invention, the reference to anti-pan-HLA antibodies refers to antibodies that recognize any of the various HLAs present in mammals, particularly humans, or have specificity for them.

[0013] More ideally, these antibodies recognize a specific HLA type, such as MHC-I, selected from at least one of the following groups: MHC classes IA, B, and C, or have specificity for it.

[0014] Additionally or alternatively, these antibodies recognize a specific HLA type, such as MHC-II, selected from at least one of the following groups: MHC class II DP, DM, DO, DQ, and DR, or have specificity for it.

[0015] More preferably, these antibodies are anti-human.

[0016] In a preferred embodiment of the present invention, the molecule or complex described above is a complex of a thiol functional group and an alkyl ("en") functional group, ideally a complex of a thiol functional group and an alkyl ("en") functional group having a stoichiometric ratio of 1.5:1.0 in the range of 0.15:0.1 to 1500:1000 (tetrathiol:triallyl).

[0017] More ideally, the fabrication of the device is based on a UV-initiated photoreaction between a thiol functional group and an alkyl ("en") functional group. In another additional preferred embodiment of the present invention, the device is fabricated by UV photopolymerization with biotin-PEG4-alkyne (Sigma, 764213). Subsequently, a reaction with avidin:streptavid is carried out. However, the process of attaching avidin to biotin prior to attaching biotin to the pillar, and the reverse order, is also included within the scope of the present invention.

[0018] In another additional preferred embodiment, the above-described device is functionalized by reacting streptavidin with antibodies. Ideally, two or more antibodies are reacted with streptavidin so that multiple antibodies, such as two or three anti-pan-HLA antibodies, are loaded onto each complex functionalized with streptavidin.

[0019] In another preferred embodiment of the present invention, the micropillar array is pre-conditioned with a protein such as bovine serum albumin (BSA) (ideally 100 μg / mL in 15 mM PBS, incubated for 10 minutes) after being functionalized with streptavidin and before the antibody is bound.

[0020] In a more preferred aspect of the present invention, the support comprises a plurality of microprotrusions as found in a microfluidic device, and preferably, said protrusions are arranged in an array within said device. Ideally, said microprotrusions are fabricated with a configuration identical or similar to that used in conventional microfluidic devices to implement, for example, a fixed enzyme reaction.

[0021] The present invention provides a method for identifying tumor antigens comprising the following in additional aspects:

[0022] i) A step of dissolving or suspending a sample of the tumor in a fluid;

[0023] ii) a step of passing the fluid through a tumor antigen identification device, comprising at least one fluid-passing channel including a plurality of supports to which at least one molecule or at least one complex is attached, to which one or more anti-MHC (major histocompatibility complex) antibodies or one or more universal anti-human leukocyte antigen (HLA) (anti-pan-HLA) antibodies are bound, so that the device can extract pMHC (peptide:major histocompatibility complex) within the sample flowing through the channel from the sample using at least one antibody;

[0024] iii) a step of binding one or more pMHCs (peptide: major histocompatibility complex) in the sample to one or more antibodies;

[0025] iv) optionally, a step of recovering one or more of the bound pMHCs (peptide:major histocompatibility complex) of iii) from the device;

[0026] v) a step of comparing the peptide of the bound pMHC (peptide: major histocompatibility complex) with a pathogen-derived antigen library to determine whether the peptide exhibits homology or affinity (molecular mimicry) for one or more pathogen-derived antigens or parts thereof, and if the homology / affinity is higher than 60%;

[0027] vi) A step of identifying the above peptide as a tumor antigen for use in cancer therapy.

[0028] In a preferred embodiment of any aspect of the present invention, the homology / affinity may 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] In the present invention, references to homology / affinity include comparing sequence structures in step v) using one of the homology / affinity as defined herein; or identity determined by the number of identical residues over a length defined in a given alignment; or similarity determined by conservative substitutions with similar physicochemical properties over a length defined in a given alignment or by the number of identical residues.

[0030] In a preferred method of the present invention, the library is a human pathogen-derived antigen library, which is ideally a library selected from known pathogen-derived antigens derived from pathogenic viruses, or more suitably comprises the proteome of a virus infecting mammals, ideally humans, such as any one or more of the viruses below or any combination thereof:

[0031] 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; Basiladnaviridae; Baculoviridae; Barnaviridae; Bastillevirinae; Bclasvirinae; Belpaoviridae; Benyviridae; Betaflexiviridae; Betaherpesvirinae; Betairidovirinae;Bicaudaviridae; Bidnaviridae; Birnaviridae; Bornaviridae; Botourmiaviridae; Brockvirinae; Bromoviridae; Bullavirinae; Caliciviridae; Calvusvirinae; Carmotetraviridae; Caulimoviridae; Ceronivirinae; Chebruvirinae; Chordopoxvirinae; Chrysoviridae; Chuviridae; Circoviridae; Clavaviridae; Closteroviridae; Comovirinae; Coronaviridae; Corticoviridae; Crocarterivirinae; Cruliviridae; Crustonivirinae; Cvivirinae; Cystoviridae; Dclasvirinae; Deltaflexiviridae; Densovirinae; Dicistroviridae; Endornaviridae; Entomofoxvirinae; Equarterivirinae; Eucampyvirinae; Euroniviridae; Filoviridae; Fimoviridae;Firstpapillomavirinae; Flaviviridae; Fuselloviridae; Gammaflexiviridae; Gammaherpesvirinae; Geminialphasatellitinae; Geminiviridae; Genomoviridae; Globuloviridae; Gokushovirinae; Guernseyvirinae; Guttaviridae; Hantaviridae; Hepadnaviridae; Hepeviridae; Herelleviridae; Heroarterivirinae; Herpesviridae; Hexponivirinae; Hypoviridae; Hydrosaviridae; Iflaviridae; Inoviridae; Iridoviridae; Jasinkavirinae; Kitaviridae; Lavidaviridae; Leishbuviridae; Letovirinae; Leviviridae; Lipothrixviridae; Lispiviridae; Luteoviridae; Malacoherpesviridae; Mammantavirinae; Marnaviridae; Marseilleviridae; Matonaviridae;McCleskeyvirinae; McClasvirinae; 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; Papillomaviridae; Paramyxoviridae; Partitiviridae; Parvoviridae; Parvovirinae; Pclasvirinae; Peduovirinae;Peribunyaviridae; Permutotetraviridae; Phasmaviridae; Phenuiviridae; Phycodnaviridae; Picobirnaviridae; Picornaviridae; Picovirinae; Piscanivirinae; Plasmaviridae; Pleolipoviridae; Pneumoviridae; Podoviridae; Polycipiviridae; Polydnaviridae; Polyomaviridae; Portogloboviridae; Pospiviroidae; Potyviridae; Poxviridae; Procedovirinae; Pseudoviridae; Qinviridae; Quadriviridae; Quinvirinae; Regressovirinae; Remotovirinae; Reoviridae; Repantavirinae; Retroviridae; Rhabdoviridae; Roniviridae; Rubulavirinae; Rudiviridae; Sarthroviridae; Secondpapillomavirinae; Secoviridae; Sedoreovirinae; Sepvirinae; Serpentovirinae;Simarterivirinae; Siphoviridae; Smacoviridae; Solemoviridae; Solinviviridae; Sphaerolipoviridae; Spinareovirinae; Spiraviridae; Spounavirinae; Spumaretrovirinae; Sunviridae; Tectiviridae; Tevenvirinae; Tiamatvirinae; Tobaniviridae; Togaviridae; Tolecusatellitidae; Tombusviridae; Torovirinae; Tospoviridae; Totiviridae; Tristromaviridae; Trivirinae; Tunavirinae; Tunicanivirinae; Turriviridae; Twortvirinae; Tymoviridae; Variarterivirinae; Vequintavirinae; Virgaviridae; Wupedeviridae; Xinmoviridae; Yueviridae; and Zealarterivirinae.;

[0032] More preferably, the pathogenic virus is a cytomegalovirus (CMV) or an Epstein-Barr virus (EBV), or preferably, a herpesvirus, poxvirus, hepatitis virus, coronavirus, hepatitis virus, HIV, or strife virus (Bunyavirus).

[0033] Most preferably, the virus is non-oncolytic, meaning its replication is not specifically limited to cancer cells.

[0034] In an alternative embodiment, the virus is tumor-lytic, meaning it can infect and kill cancer cells due to selective replication in tumors compared to normal cells.

[0035] In a preferred method, the step of comparing the peptide of the bound pMHC (peptide: major histocompatibility complex) with a pathogen-derived antigen library involves a plurality of score evaluations (peptide affinity score evaluation, alignment score evaluation, similarity score evaluation, and MHC-binding affinity score evaluation) to determine homology / affinity or identity or similarity. Most preferably, the score evaluation is a homology / affinity score evaluation as described below.

[0036] In one embodiment, a matrix is ​​constructed consisting of columns (or rows) representing the amino acid positions of the tumor peptide and rows (or columns) representing each of the 20 standard amino acids, and the same high score is assigned to the amino acid positions of the tumor peptide, while the same low score is assigned to other positions as to the pathogen-derived antigen / peptide. The highest score will be assigned to the tumor peptide with the highest homology / affinity compared to the pathogen-derived antigen / peptide according to the following aspects (in descending order of preference):

[0037] a) Whole sequence structure (clearly, the highest score was given to the tumor peptide that is 100% identical to the pathogen-derived peptide);

[0038] b) Identity of key amino acids within the hot-spot or key binding site; and

[0039] c) The maximum number of key amino acids within a hot-spot or key binding site.

[0040] Alignment is calculated for pairs of peptides in the query (pathogen-derived) set versus the tumor set, or vice versa. For a given pair of peptides, their alignment is calculated by summing the distance scores between amino acid pairs at the same position. Weights are assigned to prioritize similarity between more central amino acids in the peptides when evaluating scores.

[0041] In addition, MHC class I binding affinity prediction is performed. Methods for implementing this are known in the art, such as using NetMHC (NetMHC 4.0 or NetMHCpan 4.1) through the application programming interface of IEDB (http: / / tools.iedb.org / main / tools-api / ), and are subsequently analyzed and collected by the tool.

[0042] In an alternative embodiment of the present invention, the comparison step involves inputting a list of tumor peptides 8 to 12 amino acids long into the software. First, hits (similar sequences) are searched for in a pathogen-derived antigen library using the tool BLAST. For this purpose, the PAM30 tool is typically used, but both BLOSUM and PAM substitution matrices over several evolutionary distances are supported. Next, to improve alignment in a position-weighted manner, pairwise fine alignment is performed using at least BLOSUM62, and ideally, also the substitution matrix developed by Kim et al. (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.). Higher similarity scores are assigned to peptide pairs with high similarity in the TCR-interaction region (the central region of the peptide). Finally, MHC-binding affinities for both oncogeneic and viral cognate peptides are predicted using NetMHC4.0 or NetMHCpan4.1 as standalone command-line tools. The results are ultimately automatically analyzed and collected by the tool, and a final score summarizing the aforementioned analysis is generated.

[0043] In another additional aspect of the present invention, a cancer therapeutic substance, an immunogenic substance, or a cancer vaccine comprising a tumor antigen identified using any one or both of the aforementioned apparatus and / or methods is provided.

[0044] In another additional aspect of the present invention, a tumor antigen identified using either or both of the aforementioned apparatus and / or method for use in cancer therapy is provided.

[0045] In another additional aspect of the present invention, a tumor antigen identified using either or both of the aforementioned apparatus and / or method is provided for use in the manufacture of a pharmaceutical product for cancer treatment.

[0046] Most preferably, these cancer therapeutic substances or immunogenic substances or cancer vaccines or tumor antigens are one or more of those listed in Tables 1-6.

[0047] In another additional aspect of the present invention, a method for treating a cancer patient is provided, comprising the following:

[0048] A step of identifying a tumor antigen using the apparatus and / or method of the present invention, and then administering the tumor antigen to an individual, or using the tumor antigen to amplify a population of T-cells active against the tumor antigen, and then administering the T-cells to a patient.

[0049] In a preferred embodiment, the T cells are in vitro T cells and / or cultured T cells as allogeneic or autologous T cells.

[0050] In another additional aspect of the present invention, a pharmaceutical composition or immunogenic substance or vaccine comprising a tumor antigen of the present invention and a pharmaceutically acceptable carrier, adjuvant, diluent, or excipient is provided.

[0051] Suitable pharmaceutical excipients are well known to those skilled in the art. The pharmaceutical composition may be formulated for administration by any suitable route, e.g., intratumoral, intra-arterial, intravenous, intrapleural, intravesicular, intracavitary, or peritoneal injection, cheek, nose, or bronchial (inhalation), transdermal, or parenteral, and may be prepared by any method well known in the pharmaceutical field.

[0052] A composition may be prepared by combining the above-mentioned tumor antigen with a carrier. Generally, a formulation is prepared by uniformly and closely combining the tumor antigen with a liquid carrier or a micronized solid carrier or both, and then forming it into a product as needed. The present invention extends to a method for preparing a pharmaceutical composition comprising combining or assembling the tumor antigen defined herein with a pharmaceutically or veterinarily acceptable carrier or vehicle.

[0053] In a further aspect of the present invention, a combination therapeutic agent for cancer treatment is provided, comprising a tumor antigen identified using the apparatus and / or method of the present invention; and one or more additional cancer therapeutic agents.

[0054] Preferably, the additional anticancer agent includes cyclophosphamide, which is most suitable as it downregulates T-regulatory cells. However, as understood by those skilled in the art, the additional agent may be any anticancer agent known in the art.

[0055] Preferably, additional cancer treatments include checkpoint inhibitors (ICIs).

[0056] The most specifically identified pathways for inhibiting checkpoints are the cytotoxic T-lymphocyte protein 4 (CTLA-4) pathway and the programmed cell death protein 1 pathway (PD-1 / PD-L1). Accordingly, the present invention may be used in combination with one or more checkpoint modifiers, such as anti-CTLA-4, anti-PD1, or anti-PD-L1 molecules, to induce a potent anti-immune response against an immunosuppressive tumor environment.

[0057] In another additional aspect of the present invention, a method for stratifying patients to treat cancer with a checkpoint inhibitor is provided, comprising:

[0058] i) Step of collecting a tumor sample from the patient;

[0059] ii) a step of dissolving or suspending the sample in a fluid;

[0060] iii) a step of passing the above fluid through a tumor antigen identification device comprising: at least one fluid-passing channel comprising a plurality of supports to which at least one molecule or at least one complex is attached, to which one or more anti-MHC (major histocompatibility complex) antibodies or one or more universal anti-human leukocyte antigen (HLA) (anti-pan-HLA) antibodies are bound, so as to enable the extraction of pMHC (peptide: major histocompatibility complex) within a sample flowing through the channel from a sample using at least one antibody;

[0061] iv) a step of binding one or more pMHCs (peptide: major histocompatibility complex) in the sample to one or more antibodies;

[0062] v) optionally, a step of recovering one or more of the bound pMHCs (peptide: major histocompatibility complex) of iv) from the device;

[0063] vi) a step of comparing the bound pMHC (peptide: major histocompatibility complex) with a human pathogen-derived antigen library to determine whether the peptide has sequence homology / affinity for one or more human pathogen-derived antigens or parts thereof, if the homology / affinity is higher than 60%;

[0064] vii) a step of identifying the above peptide as a tumor antigen; and

[0065] viii) When a peptide is detected, administer an effective amount of one or more checkpoint inhibitors (ICIs) to the patient.

[0066] In another additional aspect or embodiment of the present invention, a method for stratifying patients to treat cancer with a checkpoint inhibitor is provided, comprising:

[0067] A step of determining whether a patient is CMV-seropositive, and, if so, a step of selecting a patient to be treated with one or more checkpoint inhibitors (ICIs) at an effective dose.

[0068] In another additional aspect of the present invention, a cancer treatment method comprising the following is provided:

[0069] i) A step of obtaining a sample of the tumor from the patient;

[0070] ii) a step of dissolving or suspending the sample in a fluid;

[0071] iii) a step of passing the above fluid through a tumor antigen identification device comprising: at least one fluid-passing channel comprising a plurality of supports to which at least one molecule or at least one complex is attached, to which one or more anti-MHC (major histocompatibility complex) antibodies or one or more universal anti-human leukocyte antigen (HLA) (anti-pan-HLA) antibodies are bound, so as to enable the extraction of pMHC (peptide: major histocompatibility complex) within a sample flowing through the channel from a sample using at least one antibody;

[0072] iv) a step of binding one or more pMHCs (peptide: major histocompatibility complex) in the sample to one or more antibodies;

[0073] v) optionally, a step of recovering one or more of the bound pMHCs (peptide: major histocompatibility complex) of iv) from the device;

[0074] vi) a step of comparing the bound pMHC (peptide: major histocompatibility complex) with a human pathogen-derived antigen library to determine whether the peptide has sequence homology / affinity for one or more human pathogen-derived antigens or parts thereof, if the homology / affinity is higher than 60%;

[0075] vii) a step of identifying the above peptide as a tumor antigen; and a step of administering the above peptide in an effective amount to a patient to stimulate or activate T-cells against the tumor antigen, i.e., the cancer from which the sample was taken, or a step of amplifying a population of T-cells active against the tumor antigen using the tumor antigen and then administering the T-cells to the patient.

[0076] In another additional aspect or embodiment of the present invention, a cancer treatment method comprising the following is provided:

[0077] A step of determining whether the patient is CMV-seropositive, and, if so, a step of administering one or more checkpoint inhibitors (ICIs) to the patient in an effective amount.

[0078] In another additional aspect of the present invention, a method for stratifying patients to treat adenovirus cancer is provided, comprising:

[0079] i) A step of obtaining a sample of the tumor from the patient;

[0080] ii) a step of dissolving or suspending the sample in a fluid;

[0081] iii) a step of passing the above fluid through a tumor antigen identification device comprising: at least one fluid-passing channel comprising a plurality of supports to which at least one molecule or at least one complex is attached, to which one or more anti-MHC (major histocompatibility complex) antibodies or one or more universal anti-human leukocyte antigen (HLA) (anti-pan-HLA) antibodies are bound, so as to enable the extraction of pMHC (peptide: major histocompatibility complex) within a sample flowing through the channel from a sample using at least one antibody;

[0082] iv) a step of binding one or more pMHCs (peptide: major histocompatibility complex) in the sample to one or more antibodies;

[0083] v) optionally, a step of recovering one or more of the bound pMHCs (peptide: major histocompatibility complex) of iv) from the device;

[0084] vi) a step of comparing the bound pMHC (peptide: major histocompatibility complex) with a human pathogen-derived antigen library to determine whether the peptide has sequence homology / affinity for one or more human pathogen-derived antigens or parts thereof, if the homology / affinity is higher than 60%;

[0085] vii) a step of identifying the above peptide as a tumor antigen; and

[0086] viii) When the peptide is identified, attach the peptide to the capsid of the adenovirus vector and administer the adenovirus vector to the patient in an effective amount.

[0087] In a preferred embodiment, the peptide is attached to an adenovirus vector using a known technique as described in WO 2015 / 177098 and / or set forth herein, referring to the preparation of PeptiCRAd.

[0088] In this document, the reference to an "effective dose" refers to an amount sufficient to achieve a desired biological effect, such as cancer cell death.

[0089] The effective dose will be determined based on the recipient's age, gender, health and weight, type of concomitant therapy (if present), frequency of treatment, and characteristics of the desired efficacy. Typically, the effective dose is determined by the person administering the treatment.

[0090] Most preferably, the cancer referred to herein includes any one of the following cancers: nasopharyngeal cancer, synovial cancer, hepatocellular carcinoma, renal cancer, connective tissue cancer, melanoma, lung cancer, bowel cancer, colon cancer, rectal cancer, colorectal cancer, brain cancer, throat 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, cholangiocarcinoma, bladder cancer, ureteral cancer, oligodendroglioma, neuroblastoma, meningioma, spinal cord tumor, osteochondroma, chondrosarcoma, Ewing sarcoma, cancer of unidentified primary site, carcinoid tumor, carcinoid tumor of the gastrointestinal tract, fibrosarcoma, breast cancer, Paget's disease, cervical cancer, esophageal cancer, gallbladder cancer, head cancer, eye cancer, throat cancer, renal cancer, Wilms' disease Tumors, liver cancer, Kaposi's sarcoma, prostate cancer, testicular cancer, Hodgkin's disease, non-Hodgkin 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, thymoma, thyroid cancer, trophoblastic cancer, hydatidiform mole, uterine cancer, endometrial cancer, vaginal cancer, vulvar cancer, acoustic neuroma, mycosis fungoides, insulinoma, carcinoid syndrome, somatostatinoma, gingival cancer, heart cancer, lip cancer, meningeal cancer, mouth cancer, neurocarcinoma, palatine cancer, parotid cancer, peritoneal cancer, pharyngeal cancer, pleural cancer, salivary gland cancer, tongue cancer, and tonsil cancer.

[0091] In a particularly preferred embodiment of the present invention, a sample is taken from melanoma, and the tumor antigen is homologous to the CMV antigen or peptide.

[0092] In the claims set forth below and in the foregoing description of the present invention, except where otherwise required by context due to explicit expression or inevitable implication, terms such as “comprising,” “comprising,” or “comprising” are used in an inclusive sense, that is, to specify the existence of the mentioned features but not to exclude the existence or addition of additional features in various embodiments of the present invention.

[0093] All references, including any patents or patent applications cited herein, are incorporated herein by reference. No reference is to be recognized as constituting prior art. Furthermore, no prior art is to be recognized as constituting part of the common general knowledge of the art.

[0094] Preferred features for each aspect of the present invention may be as described in conjunction with any other aspects.

[0095] Other features of the present invention will become clear from the following examples. Generally speaking, the present invention extends to any new feature among the features disclosed herein (including the appended claims and drawings) or any new combination thereof. Accordingly, features, integers, properties, compounds, or chemical moiety described in connection with specific aspects, embodiments, or examples of the present invention should be understood to be applicable to any other aspects, embodiments, or examples described herein, provided they are not incompatible with one another.

[0096] In addition, unless otherwise noted, any feature disclosed herein may be replaced by an alternative feature that provides the same or similar purpose.

[0097] Throughout the description and claims of this specification, the singular encompasses the plural unless otherwise required by the context. Specifically, where an indefinite article is used, this specification should be understood to consider the singular as well as the plural unless otherwise required by the context. Brief explanation of the drawing

[0098] Embodiments of the present invention will now be described as simple examples with reference to the following: Fig. 1. [A] Internal PeptiCHIP. The interior of PeptiCHIP consists of thousands of protrusions coated with biotin-attached linkers. The biotin then reacts with streptavidin, which can subsequently react with three HLA-specific capture antibody molecules. [B] Microchip technology as a novel immunopurification platform for rapid antigen discovery. A schematic diagram describing a newly developed microchip method. A thiol-en microchip combined with a free surface thiol is derivatized with biotin-PEG4-alkyne thiolene (Step 1) and functionalized with a streptavidin layer (Step 2), then biotinized pan-HLA antibodies are immobilized on the microprotrusion surface (Step 3), and cell lysates are loaded onto the microchip (Step 4). After performing an appropriate incubation time and washing steps, 7% acetic acid is added to elute HLA molecules (Step 5). Fig. 2. Characterization of selectivity of microchip functionalization using biotinylated pan-HLA antibodies.A) Binding efficacy of AlexaFluor 488-streptavidin on thiol-en microprotrusions pre-coated with biotin-PEG4-alkyne according to two streptavidin incubation times (15 min and 1 hour). B) Effect of streptavidin (non-fluorescent) concentration on the amount of immobilized biotinized pan-HLA antibody quantified by AlexaFluor 488-labeled secondary antibody. C) Incubation effect of BSA on the amount of immobilized biotinized pan-HLA antibody quantified by AlexaFluor 488-labeled secondary antibody. The effect of BSA on blocking non-specific binding sites was evaluated by pre-treating the microprotrusion array with BSA before immobilizing biotinized pan-HLA antibody (BSA-panHLA) or after immobilization (panHLA-BSA). D) Total amount of biotinized pan-HLA antibodies bound to a single chip according to the number of loading cycles. In each cycle, a batch of fresh pan-HLA antibodies at the same (constant) concentration was used. Significance was analyzed by a two-tailed unpaired Student's t-test, * p<0.05. Fig. 3. Characteristics of the HLA-I peptidome dataset obtained from the JY cell line. A) 50x10 6 , 10x10 6 and 1x10 6 B) Number of unique peptides eluted from JY cells. B) Total peptide length distribution of HLA peptides in three datasets derived from JY cell lines. CE) 50x10 6 (C), 10x10 6 (D) and 1x10 6 (E) plots the length distribution of HLA peptides against the number of unique peptides (left y-axis) and the frequency of occurrence % (right y-axis). Fig. 4. Accurate analysis of HLA ligands isolated from JY cell line.A) The eluted 9mers were analyzed for HLA-A*02:01 and HLA-B*07:02 binding affinities. Binding substances (green dots) and non-binding substances (black dots) were defined on the NetMHCpan 4.0 server (2% accession). B) HLA-I consensus binding motifs. Gibbs clustering analysis was performed to define consensus binding motifs in the eluted 9mer peptides. Reference motifs are shown in the top right corner. Optimally fit clusters (high KLD values, orange asterisks) are indicated, and sequence logos are displayed along with the number of HLA-Is for each cluster. Fig. 5A. Flowchart of the HEX algorithm. A matrix was constructed based on the amino acid composition of tumor peptides (reference peptides). Using this matrix, a virus database is searched, and the obtained viral peptides are ranked in log-recognizability order. An alignment score and an MHC-I binding prediction score are assigned to each viral peptide. Candidate viral peptides are ranked according to the following criteria: MHC-I binding prediction score > alignment score > B-score, and the peptide with the highest score is analyzed experimentally. Fig. 5B. Flowchart of existing software usageA list of tumor peptides 8–12 amino acids long was used as input to the software. First, the tool BLAST is used to search for hits (similar sequences) in a library of pathogen-derived antigens. For this purpose, PAM30 is typically used, but BLOSUM and PAM substitution matrices across several evolutionary distances are supported. Next, to improve alignment in a position-weighted manner, pairwise fine alignment is performed using at least BLOSUM62, and ideally, the substitution matrix developed by Kim et al. (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.). Higher similarity scores are assigned to peptide pairs with high similarity in the TCR-interaction region (the central region of the peptide). Finally, NetMHC4.0 or NetMHCpan4.1 is used as a standalone command-line tool to predict MHC-binding affinities for both oncogeneic and viral cognate peptides. The results are ultimately automatically analyzed and collected by the tool, and a final score summarizing the aforementioned analysis is generated. Fig. 6: Immunization using a viral peptide homologous to a tumor antigen slows tumor proliferation. A: Schematic diagram of animal experiment: To evaluate whether viral peptides similar to tumor peptides could influence tumor proliferation, four populations consisting of C57BL6 mice were constructed. One group of naive mice was used as a mock population, and the remaining three populations were each immunized with different viral peptide pools. Mice were immunized twice, at 14 and 7 days prior to tumor engraftment. B: 3 x 10⁶ MURAIN melanoma B16-OVA cells in mice 2 weeks after primary immunization. 5Dogs were injected subcutaneously. After engraftment, tumor growth was tracked by measuring every 2 days using a digital caliper for 19 days. P-values ​​were calculated using two-way ANOVA multiple comparisons and Tukey's correction. C: Mice were euthanized upon reaching the endpoint. Splenocytes were collected from mice in each group and aggregated for ELISpot analysis. Subsequently, each pool was stimulated with each viral peptide (viral peptide homologous to TYR1, viral peptide homologous to TRP2, and viral peptide homologous to GP100) to evaluate the treatment response. The dotted line indicates the background obtained by the negative control. Fig. 7: Viral peptides with high affinity for MHC have higher immunogenicity and can cause stronger cross-reactivity reactions. A: To evaluate the response to each original tumor epitope, splenocytes derived from each immunization group were aggregated and stimulated with the corresponding tumor peptides. B: Comparison of responses generated by stimulating splenocytes with the viral peptide pool and the corresponding original tumor peptides. C: Prediction of affinity of the original tumor and each pseudoviral peptide pool for murine MHC class I. A threshold of 50 nM was applied to define peptides as "high-affinity" and "medium / low-affinity" in accordance with IEDB guidelines. D: Association between IFN-γ response data and affinity prediction. E: Stratification of peptides based on affinity and stimulating power for IFN-γ production. High-affinity peptides (IC50 <50 nM) significantly promote INF-γ production more highly compared to medium / low-affinity peptides (IC50 >50 nM). P-values ​​were calculated using the Mann-Whitney correction and t-test. P-value ranges are expressed as percentages according to the following criteria: > 0.05 (ns), ≤ 0.05 (*), ≤ 0.01 (**), ≤ 0.001 (***), ≤ 0.0001 (****). Fig. 8. Viral peptides homologous to tumor antigens can inhibit tumor proliferation in already established tumors.A: Schematic of animal experiment: Four C57BL mouse populations were established for each tumor cell line to be examined. On Day 0, B16-OVA or B16F10 cells were injected subcutaneously into mice. Once tumors became proliferable, mice were treated with saline (mock group), uncoated adenovirus (uncoated virus group), adenovirus coated with a TRP2 homologous viral peptide pool (Viral PeptiCRAd, VPC), or adenovirus coated with a TRP2 peptide (TRP2 PeptiCRAd, TPC). B: Individual B16 OVA tumor proliferation. The threshold defining therapeutic success was determined as the median of all tumor volumes on the last day. C: B16 OVA tumor volume at the endpoint. The median tumor volume, indicated by the dashed line, defines the threshold of treatment success. D: B16 OVA contingency plot shows the number of responders per treatment group. E: B16 F10 individual tumor proliferation. The threshold defining treatment success is identified by the median of all tumor volumes at the last day. F: B16 F10 tumor volume at the endpoint time. The tumor volume, indicated by the dashed line, defines the threshold of treatment success. G: B16 OVA contingency plot shows the number of responders per treatment group. (CF) P values ​​were calculated using one-way ANOVA and the Turkey correction. P-value ranges are indicated by * according to the following criteria: > 0.05 (ns), ≤ 0.05 (*), ≤ 0.01 (**), ≤ 0.001 (***), ≤ 0.0001 (****). (DG) P values ​​were calculated using the chi-square (and Fisher exact) test of odds ratios. The p-value ranges are indicated by * according to the following criteria: > 0.05 (ns), ≤ 0.05 (*), ≤ 0.01 (**), ≤ 0.001 (***), ≤ 0.0001 (****). Fig. 9. T-cell cross-reactivity between viral antigens and tumor antigens sharing high levels of homology / affinity.PBMCs derived from patients with HLA-A*02:01 and high serum anti-CMV antibody levels were stimulated with the peptides in Table 2. The levels of secreted IFN-γ activated by CD8+ T-cells were evaluated using ELISpot analysis. The dotted line indicates the noise level resulting from non-specific activation of CTLs in the negative control (DMSO) (A). PBMCs derived from patients with HLA-A*02:01 and high serum anti-CMV antibody levels, and from healthy donors (HS) confirmed to be CMV-positive, were tested for anti-CMV responses using ELISpot analysis with the CMV-specific HLA-A*02:01 restriction peptide NLVPMVATV. P-values ​​were calculated using T-tests and Mann-Whitney correction (B). Fig. 10. A microchip-based platform reveals immunopeptidomic profiles in rare tumor biopsies. A) Summarize the weight, total number, and unique peptides of the samples and the enrichment of 7-13mer samples before processing. B) Plot the length distribution of the peptides for absolute number and % as a bar graph. Fig. 11. Immunopeptidomic analysis of ccRCC and bladder tumor patient-derived organoids (PDO). A) Number of unique peptides detected in ccRCC and bladder PDO. B) Peptide length distribution is plotted against the total number of unique peptides (left y-axis) and the % occurrence frequency per PDC (right y-axis) (ccRCC top panel, bladder break panel). Fig. 12. Peptide test.The synonymic tumor model CT26 was subcutaneously injected into the left and right flanks of Balb / c mice (Day 0, Fig. 12A). Once the tumors were established (Day 7, Fig. 12A), Valo-mD901 was coated with each polylysine-modified peptide pair listed in the table (PeptiCRAd1, PeptiCRAd2, PeptiCRAd3, Table) and injected intratumorally only into the right tumor. PeptiCRAd4 consisted of Valo-mD901 coated with gp70423-431 (AH1-5), a known immunodominant antigen of CT26 derived from a self-antigen encoded in the genome. The mock group and the Valo-mD901 group were also used as controls. As confirmed in single tumor proliferation per mouse per treatment group, PeptiCRAd1 and PeptiCRAd2 improved tumor proliferation of Valo-mD901 as well as the control group in injected lesions (Fig. 12B, right side of graph panel). Strictly speaking, only PeptiCRAd1 significantly improved anti-tumor activity in untreated tumors, while Valo-mD901 did not trigger an effect (Fig. 12B, left side of graph panel). The peptides of PeptiCRAd1 were derived from the HEX assay. PeptiCRAd4 consists of Valo-mD901 coated with gp70 423-431 (AH1-5). Fig. 13. A schematic diagram of the present invention is shown.An apparatus of the present invention, pre-functionalized with multiple anti-MHC (major histocompatibility complex) antibodies or universal anti-human leukocyte antigen (HLA) antibodies capable of capturing pMHC (peptide: major histocompatibility complex), is illustrated in diagram form. Tumor cell lysates are passed through the apparatus, and antibodies extract the pMHC. The pMHC is eluted, and the peptides recovered from the pMHC complex are analyzed, for example, by liquid chromatography and mass spectrometry (LC-MS / MS), and a list of tumor peptides is generated as a result. Each tumor peptide is compared to a library of pathogen-derived proteins (including antigens) to determine the level of homology / affinity between each tumor peptide identified using the apparatus and the pathogen-derived proteins (containing pathogenic antigens / pathogenic peptides) in the library. This generates a list of candidate substances for use in cancer treatment, ideally prioritized in terms of homology / affinity. Table 1. Peptides used in animal experiments. The known melanoma tumor peptides (TRP2180-188, hGP10025-33, and TYR208-216) were analyzed using HEX. The candidate viral peptides suggested as the best by the software were selected, and a pool consisting of the four best xenopeptides per original tumor epitope was tested in vivo. Table 2. Peptide used for ELISpot analysis of the patient's PBMC. The announced melanoma-related antigens were analyzed by HEX. For each antigen, the best candidate peptide derived from human CMV was selected for in vitro testing. Table 3. Comparative analysis between microchip-based immunoprecipitation technology and standard processes. The table records the total coating content of antibodies according to microchip-based IP technology and standard processes. Table 4. HEX results identifying 13 tumor MHC restriction peptides and their corresponding pathogen-derived peptides. Table 5. Table of peptides tested in ELISPOT analysis. Table 6. A table listing the peptides selected for the in vivo PeptiCRAd analysis shown in Fig. 12. Specific details for implementing the invention

[0099] Method and materials

[0100] Device fabrication

[0101] The device (PeptiCHIP) of the present invention is a fluid-passing structure comprising thousands of protrusions coated with biotin-attached linkers. The biotin is linked to streptavidin, and to the streptavidin, HLA-specific capture antibodies, specifically three molecules of HLA-specific capture antibodies, are bound.

[0102] Using conventional microfluidic fabrication techniques, the fabrication of PeptiCHIP is carried out by a UV-initiated photoreaction between a thiol functional group and an allyl ("en") functional group according to the following off-stoichiometric ratio of 150:100 (tetrathiol:triallyl).

[0103] Immediately after preparation, PeptiCHIP is functionalized into biotin-PEG4-alkyne (Sigma, 764213) by UV photopolymerization followed by reaction with avidin. This is performed as follows.

[0104] Step 1: A 1 mM biotin-PEG4-alkyne solution (10 mM biotin-PEG4-alkyne stock solution in ethyl glycol) was prepared. A small amount was taken, and 1% (m / v) photoinitiator (Igracure® TPO-L, BASF) was added using a 10% photoinitiator stock solution in methanol, so the final solution was 1 mM biotin + 1% lucirin / EG-MeOH 9:1*.

[0105] One volume of biotin-PEG4-alkyne and 1% lucirin solution in EG:MeOH 9:1 (v / v) was placed on the chip and exposed to UV for 1 minute (LED UV lamp l=365 nm, l=15 mW / cm²). 2 use).

[0106] First, rinse thoroughly with methanol, then rinse with milli-Q water, wash the channels with 1-2 mL of each solvent, and store in a dry state (if necessary).

[0107] Step 2: After derivatization with biotin, the chip was functionalized with streptavidin. A 0.01 mg / ml stock solution of streptavidin in PBS was prepared and added to the chip at room temperature under dark conditions for 15 minutes. This was rinsed three times with 200 µl of PBS.

[0108] 15 mM BSA in PBS was added at a concentration of 100 μg / ml and left at room temperature for 10 minutes.

[0109] Step 3: Reacted with an anti-pan-HLA antibody. 25 µl of 1.6 µg / µl biotin anti-human HLA-A,B,C (Biolegend CAT. Number 311434) was added at room temperature for 15 minutes. Afterward, the chip was rinsed three times with 200 µl of PBS and prepared for the immunoprecipitation of MHC complexes.

[0110] Tumor sample preparation: Cells were desorbed using 4 mM EDTA and rinsed once with PBS. 25 µl of 1% Igepal / PBS + protease inhibitor was added. Centrifuged at 500xg for 10 minutes at +4°C. Centrifuged at 20,000xg for 10 minutes at +4°C.

[0111] Optimized microfluidics process Array

[0112] In a single microfluidic chip, a biotinylated pan-HLA antibody was added to a streptavidin-pre-functionalized solid support structure (i.e., a microprotrusion array), and then HLA was immobilized on a solid surface coated with the pan-HLA antibody to perform an immuno-purification step.

[0113] In summary, an array of microprotrusions based on off-stoichiometric thiol-en (OSTE) polymers was fabricated using a UV-replica molding technique and then biotinized. Subsequently, streptavidin functional groups were attached to the biotinized microprotrusions, biotinized pan-HLA antibodies were added, and cell lysates were directly loaded onto a microfluidic chip to selectively capture HLA-I complexes. After rinsing appropriately, the captured HLA-I complexes were eluted at room temperature using 7% acetic acid (Fig. 1b). Then, the protocol was carried out according to a standard immunopeptidomic workflow, which included purifying the eluted HLA peptides with acetonitrile using SepPak®-C18 and then evaporating them into a dry product using vacuum centrifugation.

[0114] The effect of streptavidin functionalization on the microprotrusion array was investigated with two incubation times (15 minutes and 1 hour) assisted by fluorescent AlexaFluor488-streptavidin. It was confirmed that the shorter incubation time was sufficient to build the first streptavidin layer (Fig. 2a). In addition, to determine the effect of streptavidin concentration on the final amount of biotinylated pan-HLA antibodies, non-fluorescent streptavidin was used at various concentrations while the amount of biotinylated pan-HLA antibodies was fixed. In this case, the biotinylated pan-HLA antibodies were incubated for 15 minutes, followed by three PBS washing steps (200 µl per step). To quantify the amount of immobilized biotinized pan-HLA antibodies at each streptavidin concentration, the immobilized biotinized pan-HLA antibodies were tightened using a fluorescently labeled AlexaFluor488 secondary antibody. Interestingly, even a tenfold increase in streptavidin concentration did not significantly affect the amount of immobilized biotinized pan-HLA antibodies (Fig. 2b), which may be due to steric hindrance limiting the number of available streptavidin binding sites. Based on these findings, additional concentrations of streptavidin were not investigated, and in all subsequent experiments, streptavidin was used at the highest concentration tested (0.1 mg / mL) to ensure maximum binding of biotinized pan-HLA antibodies. To further investigate the selectivity of antibody binding on the surface of streptavidin-functionalized microprotrusions, the effect of an additional coating step using bovine serum albumin (BSA) on the amount of immobilized biotinylated pan-HLA antibodies was investigated in terms of excluding non-specific interactions. To this end, the microprotrusion array was pre-treated with BSA (100 μg / mL in 15 mM PBS, incubated for 10 minutes) after streptavidin functionalization, and then the efficiency of biotinylated pan-HLA antibodies was reconfirmed using a fluorescently labeled secondary antibody.This process substantially reduced the amount of immobilized pan-HLA antibodies compared to the untreated surface (Fig. 2c), which means that non-specific binding sites can be blocked through a simple BSA pre-incubation step. Therefore, the BSA incubation step was applied to all subsequent experiments.

[0115] Finally, the inventors sought to determine the maximum amount of immobilized biotinylated pan-HLA antibodies that could be conjugated onto a single chip using an optimized protocol. This was evaluated by performing several cycles of loading a new batch of antibodies (0.5 mg / mL) at the same concentration per single microfluidic chip. In this case, the amount of immobilized pan-HLA antibodies was determined by comparing the amount of pan-HLA antibodies in the input solution versus the output solution using ELISA analysis. It was observed that the amount of immobilized antibodies increased nearly linearly with the number of loading cycles (Fig. 2d), allowing for the accurate titration of the total amount of immobilized biotinylated pan-HLA antibodies according to the number of loading cycles. After 7 cycles, the amount of immobilized antibodies reached an approximate content of 45 µg, which, according to the latest method, cell 10 9 When investigating dogs, pan-HLA (antibody molecules 3.88 x 10⁶ 16 Since 10 mg is required, this is theoretically sufficient to investigate immunopeptidomes against small amounts of biological material [22A](Table 3).

[0116] In the microchip setup, antibody molecules 1.74 x 10 14 We were able to fix the dog, and technically 4.5 x 10 cells 6 We were able to investigate the dog.

[0117] Immunopep Tidomic Microchip-based antigens implemented in a workflow Nonghwaro cloth The HLA-I peptide presented as an example can be identified.

[0118] To evaluate whether the developed thiol-N microchip could be used as an antigen discovery platform, the inventors immunopurified HLA peptides from the human B-cell lymphoblastic cell line JY. The JY cell line expresses class I HLA at high levels, is homozygous for three alleles common in the human population (HLA-A*02:01, HLA-B*07:02, and HLA-C*07:02), and has been widely adopted for ligandome analysis. Consequently, the JY cell line was considered a suitable model for benchmarking microchip-based antigen-enriching immunoprecipitation technology.

[0119] Therefore, as described above, the HLA-I complex was purified by immunoaffinity using a thiol-N microchip functionalized with a predetermined amount of pan-HLA antibody. In addition, to confirm the sensitivity of the method of the present invention, the total number of cells was 50 x 10 6 , 10x10 6 and 1x10 6 The test was conducted using a small number of samples. Cell lysates were loaded onto a microchip, rinsed appropriately with PBS, and then peptides were eluted with 7% acetic acid and analyzed by tandem mass spectrometry. The entire workflow, from streptavidin functionalization to tumor peptide elution, took an average of <24 hours. Highly reliable data was established by applying a strict false discovery threshold of 1% for peptide and protein identification. The inventors used 50 x 10 cells. 6 , 10x10 6 and 1x10 6 5589, 2100, and 1804 unique peptides were identified from each dog, respectively (Fig. 3a).

[0120] The inventors intended to carefully analyze the ability of microchip technology to enrich natural HLA-I binding materials and avoid co-elution of potential contaminants, and thus extensively characterized the eluted peptides. First, the peptides eluted from the JY cell line exhibited a typical length distribution of the ligandome dataset, and the most enriched peptide species was 9mer (Fig. be). Next, the predicted binding affinities for two HLA-I alleles (HLA-A*0201 and HLA-B*0702) expressed in JY cells were determined. JY cells also had low levels of the allele HLA-C*0702, but its binding motif overlapped with the motifs of HLA-A*0201 and HLA-B*0702; therefore, only these alleles were considered in subsequent analysis.

[0121] 78%, 83%, and 67% of the unique 9mers were in cells 50x10 6 , 10x10 6 and 1x10 6 In each case, it was predicted to be a binding substance for the HLA-A*0201 or HLA-B*0702 allele (described as a binding substance in NetMHCpan4.0, with a ranking of 2% [24A-26A]) (Fig. 4a). Additionally, Gibbs analysis was performed to deconvolute the consensus binding motifs of each HLA-I allele from the eluted 9mer peptide; these were clustered into two distinct groups having a preference for reduced amino acid complexity for residues at the P2 and W positions that sufficiently matched those known for HLA-A*0201 and HLA-B*0702 (Fig. 4b).

[0122] Next, to confirm the role of the identified peptides, a gene ontology (G0) period enrichment analysis was performed on a list of 9mer binding source proteins. The inventors observed enrichment in nuclear and intracellular proteins, primarily in proteins that interact with DNA and RNA or participate in catabolic activity. Finally, the inventors established an in vitro apoptosis analysis to further demonstrate the ability of microchip technology to isolate peptides from complexes with HLA-I. To this end, a set consisting of three peptides was selected from the JY dataset to stimulate HLA-matched PMBCs; CD8+ T cells were purified from PBMCs and used as operator cells for co-culture with JY cells. Unstimulated PBMCs were used as a control to confirm non-specific cytotoxicity caused by the operator cells. Subsequently, real-time cell lysis was monitored. Interestingly, CD8+ T cells pulsed with the peptides QLVDIIEKV (SEQ No. 75; gene name PSME3) and KVLEYVIKV (SEQ No. 76; gene name MAGEA1) induced specific cell lysis of about 10%, whereas CD8+ T cells pulsed with the peptide ILDKKVEKV (SEQ No. 77; gene name HSP90AB3P) induced specific cell lysis of 15%, which means that specific cell lysis occurs in the presence of the defined peptide.

[0123] To evaluate the validity of the list of HLA-I peptides identified via microchip technology, the inventors investigated SysteMHC, a repository of immunopeptidome datasets generated through mass spectroscopic measurements. Of the unique 9-mer binding molecules identified in this data, 69%, 77%, and 81% were cells 50x10 6 , 10x10 6 and 1x10 6For each individual, it was found in a previously published ligandome dataset derived from the JY cell line (pride ID PXD000394)[3A](Fig. 6a). In addition, a positive correlation was verified between the frequency of source protein appearance and HLA presentation, and the most abundant protein was the major source of HLA peptides.

[0124] In other words, these results demonstrate that chip-based protocols can be utilized as a reliable immunoprecipitation platform in the immunopeptidome workflow.

[0125] Device usage

[0126] Application of samples to the chip and fraction elution for subsequent analysis

[0127] The inventors applied the samples in multiple cycles and incubated them for 5 minutes (operated at 4°C). The chips were rinsed three times with 200 µL of PBS, and the final wash was aspirated to empty the chip. 50% MeOH and 50% MilliQ solutions were prepared. A 7% acetic acid solution was prepared using the previous solutions. This solution was applied to the chip, and fractions were collected. The elution time was 5 minutes. On the same day, the collected fractions were purified. A SepPak cartridge was prepared and labeled for each tissue sample—specifically the HLA-I peptide sample. Using a syringe and a fitting adapter, the cartridge was first rinsed once with 1 ml of 80% ACN in 0.1% TFA, followed by a rinse with 1 ml of 0.1% TFA. Biological samples were loaded into the respective SepPak cartridges. They were passed through slowly (speed: approx. 1 ml / 20 seconds). The cartridges were rinsed twice with 1 ml of 0.1% TFA. HLA-binding peptides were eluted into a collection tube using 300 µl of 30% ACN in 0.1% TFA.

[0128] HEX ( of xenopeptide Homology evaluation)

[0129] Xenopeptide homology (affinity) evaluation (HEX) is a novel in silico platform that compares similarities between tumor peptides (reference peptides) and virus-derived pathogen-derived peptides (query peptides). It utilizes several matrices to perform candidate peptide screening. This is accomplished by integrating both novel methods (peptide score evaluation and alignment score evaluation algorithms) and integrated existing methods (MHC-I binding prediction). HEX is appended with several pre-compiled databases of known proteins, such as proteins derived from viral pathogens and the human proteome (33).

[0130] An associated scoring matrix was temporarily generated based on the amino acid composition of the reference peptide, in contrast to the experiment. Specifically, in a matrix consisting of columns representing amino acid positions in the peptide and rows representing each of the 20 standard amino acids, the same high score was assigned to the amino acid positions of the reference peptide, and the same low score was assigned to other positions.

[0131] Alignment is calculated based on peptide pairs in the query set relative to the reference set. For a given peptide pair, alignment is calculated by summing the distance scores between amino acid pairs at the same position. Weights were applied to the score evaluation to prioritize similarities between more central amino acids within the peptides. HEX supports both BLOSUM and PAM substitution matrices across several evolutionary distances. Specifically, the matrix selected for this experiment was BLOSUM 62.

[0132] MHC class I binding affinity prediction is performed using NetMHC

[27] through the application programming interface of IEDB (http: / / tools.iedb.org / main / tools-api / ) and then analyzed and collected by the tool. Users can specify the desired scoring method or retrieve several recommended results. Prediction for multiple human and murine MHC-I alleles is supported.

[0133] Users can select peptides based on their own criteria or through a Random Forest model. The Random Forest is trained on the experimental results of the peptides selected by the user. Feature importance is determined by the out-of-bag (OOB) increase in Mean Squared Error (MSE), and cross-validation is performed on unidentified peptide samples. HEX was developed as a web application using the R package Shiny and is available without user registration at https: / / picpl.arcca.cf.ac.uk / hex / app / . The source code is https: / / github.com / whalleyt / hex Available at.

[0134] In an alternative embodiment of the present invention, HEX supports both BLOSUM and PAM substitution matrices across several evolutionary distances. Specifically, the matrix used in this experiment is BLOSUM 62. HEX first performs a BLAST search using PAM30 to search for hits (similar sequences) in a reference library. Then, HEX performs pairwise fine alignment using both the substitution matrix developed by Kim et al. and BLOSUM62.

[0135] Reference: Kim Y, Sidney J, Pinilla C, Sette A, Peters B. Derivation of an amino acid similarity matrix for peptide: MHC binding and its application as a Bayesian prior. BMC Bioinformatics. 2009;10:394. Published 2009 Nov 30. doi:10.1186 / 1471-2105-10-394.

[0136] MHC class I binding affinity prediction is performed using NetMHC4.0 (or NetMHCpan4.1) as a standalone command-line tool, and then analyzed and collected within the tool. Users can specify the desired scoring method or retrieve various recommended results. Prediction for multiple human and murine MHC-I alleles is supported.

[0137] Patients and samples

[0138] A total of 16 patients with stage 4 metastatic melanoma were treated with anti-PD1 monoclonal antibodies at the Comprehensive Cancer Center of the University Hospital of Helsinki (HUCH). Patients were randomized to receive either nivolumab (n=7) every 2 weeks or pembrolizumab (n=9) every 3 weeks via infusion. The study was approved by the Ethics Committee of the University Hospital of Helsinki (HUCH) (Dnro 115 / 13 / 03 / 02 / 15). Informed written informed consent was obtained from all patients, and the study was conducted in accordance with the Declaration of Helsinki.

[0139] Peripheral blood samples (3 ml EDTA blood, 50 ml heparin blood) were collected at three time points: before the start of treatment, 1 month after treatment, and 3 months after treatment. Plasma was separated from these samples by centrifugation and stored at -70°C. CMV and EBV IgG levels in thawed EDTA plasma samples were measured using the VIDAS CMV IgG (BioMerieux, Marcy-l'Etoile, France) and Siemens Enzygnost anti-EBV / IgG kit (Siemens Healthcare Diagnostics, Marburg, Germany). Immunoglobulins (IgA, IgM, IgG) in thawed heparin plasma were measured at the central laboratory of the University Hospital of Helsinki (HUSLAB).

[0140] Cell lines and human samples

[0141] Muline melanoma cell lines B16-F10 were purchased from ATCC (American Type Culture Collection; Manassas, Virginia, USA). Cells were cultured at 37°C / 5% CO2 in RPMI (Gibco, Thermo Fisher Scientific, US) supplemented with 10% fetal bovine serum (FBS) (Life Technologies), 1% Glutamax (Gibco, Thermo Fisher Scientific, US), and 1% penicillin and streptomycin (Gibco, Thermo Fisher Scientific, US).

[0142] Cell line B16-OVA, a mouse melanoma cell line modified to constitutively express chicken ovalbumin (OVA), was kindly provided by Professor Richard Weil (Myo Clinic, Rochester, Minnesota, USA). The cells were sterilized in 10% FBS (Gibco, Incubated at 37°C / 5% CO2 in low glucose RPMI (Gibco, Thermo Fisher Scientific, US) supplemented with 1% Glutamax, 1% penicillin and streptomycin (Gibco, Thermo Fisher Scientific, US) and 1% Geneticin (Gibco, Thermo Fisher Scientific, US).

[0143] All cells were tested for Mycoplasma contamination using a commercially available detection kit (Lonza - Basel, Switzerland). Isolated human PBMCs were frozen in FBS supplemented with 10% DMSO and maintained in liquid nitrogen until use. The cryopreserved PBMCs were thawed and recovered overnight at 37°C / 5% CO2 in full RPMI medium supplemented with 10% FBS, 1% Glutamax, and 1% penicillin-streptomycin before plating for ELISPOT analysis.

[0144] peptide

[0145] All peptides used in this experiment were purchased from Zhejiang Ontores Biotechnologies Co. (Zhejiang, China) at 5 mg, >90% purity. The sequences of all peptides used in this experiment are identified in Tables 1 and 2.

[0146] PeptiCRAd manufacturing

[0147] All PeptiCRAd complexes mentioned in this study were prepared by mixing adenovirus and polyK-tailed peptide according to the following protocol: 1x10 9vp (virus particles) were mixed with 20 µg of polyK-tailed peptide (suspended in water); after vortexing, the mixture was incubated at room temperature for 15 minutes; after incubation, PBS was added to the injection volume (50 µl / mouse), the solution was vortexed again, and then used for analysis or animal injection. For TRP2-PeptiCRAd, 1x10 9 vp 6K-TRP2 180 -188 It was mixed with 20 µg of peptide, and Viral-PeptiCRAd was 1 x 10 9 vp to TRP2 180 -188 It was prepared by mixing 5 μg of each homologous virus 6K-peptide with.

[0148] New PeptiCRAd was prepared before each experiment using fresh reagents. All necessary virus and peptide dilutions for incubation of the PeptiCRAd preparations were prepared using sterile PBS or water. Then, the PeptiCRAd was diluted with the buffer required for analysis.

[0149] Viruses were constructed, amplified, and characterized according to the methods described everywhere

[20] .

[0150] Animal Experimentation and Ethical Permission

[0151] All animal experiments were reviewed and approved by the Laboratory Animal Committee of the University of Helsinki and the Southern Finnish regional government.

[0152] All experiments were performed using C57BL / 6JOlaHsd mice obtained from Scanbur (Karlslunde, Denmark).

[0153] For the immunization experiment, 8–9-week-old immune-competent female C57BL / 6J mice were divided into four groups. The mock group consisted of n = 3 mice, and each of the three different treatment groups consisted of n = 7 mice. Each treatment group was vaccinated with the xenopeptide of the different group. Mice were vaccinated twice; the injections were administered at the base of the tail at 1-week intervals (days 0 and 7), with a final injection volume of 100 µl containing 40 µg of peptide and 40 µg of adjuvant (VacciGrade poly(I:C)-Invivogen). Naive mice (PBS injection) were used as the mock group. On day 14, 3 × 10⁶ B16-OVA cells were injected into the mice. 5 The dog was injected into the right flank, and tumor growth was tracked until the endpoint was reached.

[0154] To treat the established tumor, the inventors examined two tumor cell lines: B16-OVA cells and the more aggressive B16F10 cells. B16-OVA cells 3*10 5 Dog and B16-F10 cells 1*10 5 The mock was subcutaneously injected into the right flank of 8-9 week old, immunocompetent female C57BL / 6J mice. Subsequently, these mice were randomly assigned to four groups of 7-8 mice for each tumor cell line. The mock group was treated with PBS; the second group was treated with uncoated adenovirus; and the third group was treated with TRP2 180 -188 Adenoviruses coated with (TRP2-PeptiCRAd) were treated; the last group was treated with adenoviruses coated with TRP2-homologous viral peptide (Viral-PeptiCRAd).

[0155] Mice were treated twice intratumorally, with injections administered at 2-day intervals (10 and 12 days from tumor engraftment), and tumor growth was tracked until the endpoint was reached. The median tumor volume measured on the last day indicates the treatment success threshold, represented by the dotted line. Mice with a tumor volume below the threshold at the endpoint were considered responders, while those with a volume above the threshold were considered non-responders.

[0156] Tumor proliferation was tracked by measuring two dimensions of the tumor using digital calipers. Subsequently, the volume was mathematically calculated according to the following formula:

[0157] ((Longer side) x (Shorter side) 2 ) / 2

[0158] In all experiments, tumor size was measured at intervals of 2 or 3 days until it reached the maximum allowable value, after which the mice were sacrificed and the spleens were collected.

[0159] ELISpot analyze

[0160] To analyze the amount of active antigen-specific T-cells, interferon-γ (IFN-γ) secretion was measured using IMMUNOSPOT (CTL, Ohio, USA) for murine IFN-γ and ELISPOT assay at MABTECH (Mabtech AB, Nacka Strand, Sweden) for human IFN-γ.

[0161] Fresh mouse splenocytes collected at the end of the experiment were used. The procedure was performed according to the manufacturer's instructions. Briefly, for muline IFN-γ, 3 x 10 splenocytes per well 5 Dogs were inoculated on day 0. Cells were stimulated with peptide at 2 µg / well. After incubation at 37°C / 5% CO2 for 3 days, plates were developed according to the kit protocol.

[0162] For human IFN-γ elisopot, human PBMC was thawed and recovered overnight in complete medium at 37°C / 5% CO2. The next day, 3 x 10 PBMCs were used per well. 5 Dogs were inoculated and stimulated with 2 µg / well of peptide. After incubation for 48 hours at 37°C / 5% CO2, the plates were developed according to the manufacturer's protocol. The plates were transferred to CTL-Europe GmbH for analysis.

[0163] Cell lines and reagents

[0164] EBV-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).

[0165] Streptavidin (Streptomyces avidini, affinity purified, lyophilized from 10 mm potassium phosphate, ≥13 U / mg protein) was purchased from Sigma-Aldrich (Saint Louis, Missouri, USA).

[0166] Biotin-conjugated anti-human HLA-A, B, C clone w6 / 32 was purchased from Biolegend (San Diego, CA, USA) for analysis.

[0167] The following peptides were purchased from Ontores Biotechnologies Co., Ltd. and used throughout the experiment: KVLEYVIKV (SEQ No. 75; gene name MAGE A1), ILDKKVEKV (SEQ No. 76; gene name HSP90), and QLVDIIEKV (SEQ No. 77; gene name PSME3).

[0168] In addition, the following peptides were purchased from Chempeptide (Shangai, China):

[0169] VIMDALKSSY (SEQ No. 78; gene name NNMT), FLAEGGGVR (SEQ No. 79; gene name FGA) and EVAQPGPSNR (SEQ No. 80; gene name HSPG2).

[0170] ovarian tumor biopsy and ethical considerations

[0171] Ovarian tumor biopsies were collected from patients with metastatic ovarian tumors (high-grade severe) who had signed informed consent, under an experiment approved by the Research Ethics Committee of the Northern Savo Hospital District under approval number 350 / 2020. Samples were cut into small pieces and treated with a digestion buffer containing 1 mg / ml of collagenase type D (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 passed sequentially through 500 µm and 300 µm cell strainers (pluriSelect) to obtain single cells.

[0172] kidney cells carcinoma and bladder tumor samples and ethical considerations

[0173] Patient tissue samples for organoid cultures were obtained from DEDUCER (Development of Diagnostics and Treatment of Urological Cancers) at the University of Helsinki Central Hospital with approval number HUS / 71 / 2017, 26.04.2017, Ethics Committee approval number 15.03.2017 Dnro 154 / 13 / 03 / 02 / 2016, and with patient consent. Kidney samples were obtained from nephrectomy of an adult male with clear cell renal cell carcinoma (ccRCC, pTNM stage pT3a G2). Benign kidney tissue samples were used in the experiment. Carcinomatous urothelial cells (bladder cancer, high grade, stage III, 1x1 cm) were obtained from an adult female, and the cancer tissue samples were used for organoid culture.

[0174] Clear cell kidney cancer and bladder tumors Organoid culture

[0175] Cells were isolated from the original tissue immediately after surgery by breaking down the tissue into small fragments and treating them with collagenase (40 units / ml) for 2-4 hours. Positive and cancerous renal cells from clear cell renal cell carcinoma patients were cultured as organoids in F-medium [3:1 (v / v) of 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] and 10% Matrigel (Corning). Bladder tumor-derived organoids were cultured in hepatocyte calcium medium (Corning) supplemented with 5% CSFBS (Thermo Fisher Scientific), 10 μM Y-27632 RHO inhibitor (Sigma), 10 ng / mL epidermal growth factor (Corning), 1% GlutaMAX (Gibco), 1% penicillin-streptomycin, and 10% Matrigel [15A]. 6x10 cells 6 The dogs were collected by centrifugation, rinsed in PBS to remove Matrigel, and frozen before analysis.

[0176] HLA Typing

[0177] Clinical HLA typing of tumor samples (ccRCC and bladder) was performed at the European Federation for Immunogenetics (EFI)-certified HLA laboratory of the Finnish Red Cross Blood Service. Allele determination of the three classical HLA-I genes HLA-A, -B, and -C was performed using targeted PCR-based next-generation sequencing (NGS) techniques according to protocols provided by the manufacturer (NGSgo® Workflow, GenDx, Utrecht, The Netherlands).

[0178] Allele assignment at 4-field resolution was performed using NGSengine Version: 2.11.0.11444 (GenDx, Utrecht, The Netherlands) with the IPD IMGT / HLA database public 3.33.0, https: / / www.ebi.ac.uk / ipd / imgt / hla / .

[0179] Parenchyma Measurement Analysis

[0180] Cell surface expression of HLA-A2 and HLA-A, B, and C was analyzed using the following antibodies: 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).

[0181] Data were acquired using a BDLSR Fortessa flow cytometer. Flow cytometry analysis of renal cell carcinoma and bladder tumor-derived organoids was performed using a BD Accuri 6 plus (BD Biosciences) and analyzed with FlowJo software (Tree Star, Ashland, OR, USA).

[0182] result

[0183] Virus- and tumor-derived using excellent molecular mimicry peptides Development of Xenopeptide Homology Assessment (HEX) for Identification

[0184] To investigate whether molecular mimicry between viruses and tumors can influence tumor proliferation, it was necessary to identify peptides sharing high levels of homology / affinity. However, there is a lack of tools capable of identifying relevant targets at this level. Accordingly, the inventors developed HEX (Homology Assessment of Xenopeptides), a device that compares an input sequence against a database of pathogen-derived antigen / peptide or protein sequences and selects candidate peptide pairs with excellent homology based on at least two of the following three criteria: 1) corresponding to the peptide recognition potential by a given TCR B-score ; 2) Position-weighted alignment score to prioritize similarity in regions interacting with the TCR ( positional weighted alignment score ); 3) MHC Class I coupling affinity Prediction (Fig. 5a). Alternatively, conventional software as described above, as shown in Fig. 5b, can be used.

[0185] The inventors have set forth on three melanoma-associated antigens that have been successfully applied in various vaccination trials: TRP2 180 -188 ( Tyrosinase -Related protein 2) , GP100 25-33 ( PMEL; Primelanosomes protein)and TYR1 208 -216 ( Tyrosinase 1) . TYR1 208 -216 It was not predicted to be a binding molecule of murine MHC and was therefore considered an "irrelevant target." Using HEX, the inventors identified viral peptides that shared high levels of homology / affinity with the input tumor epitopes. A pool consisting of four virus-derived peptides for each original tumor epitope (Table 1) was selected for further in vivo evaluation.

[0186] Antiviral immunity promotes tumor proliferation through molecular mimicry using tumor antigens Control

[0187] To evaluate whether virus-derived peptides affect tumor proliferation, the inventors decided to mimic viral infection by immunizing C57BL6 mice with a selected viral peptide pool and then engrafting them into tumors (Fig. 6a). All immunized mice showed reduced tumor proliferation compared to the mock group. In addition, significant differences were observed between the treatment groups. Tumor proliferation was most significantly reduced in mice immunized with a viral pool of peptides homologous to TRP2 or gp100 (Fig. 6b).

[0188] To further investigate whether the selected viral peptide contributes to the reduction of tumor proliferation, the inventors collected mouse splenocytes at the endpoint for ELISpot analysis (Fig. 6c). Mouse splenocytes immunized with a viral peptide pool homologous to TRP2 or gp100 promoted a higher IFN-γ response as correlated with the outcome of tumor proliferation compared to mouse splenocytes immunized with a control TYR1-homologous epitope.

[0189] The inventors further investigated the reactivity of these splenocytes obtained from mice virally pre-immunized to each cognate tumor antigen (Fig. 7a). In a side-by-side comparison, viral peptides homologous to TRP2 exhibited higher IFN-γ secretion compared to cognate tumor peptides (Fig. 7b). In addition, the inventors retrospectively analyzed the affinity of each tumor antigen and its homologous viral pool to the C57BL / 6J MHC class I molecule (Fig. 7c) and observed a significant correlation with its ability to stimulate IFN-γ secretion (Fig. 7d). Following the guidelines of the Immunoepitope Database (IEDB), the inventors classified the peptides into high-affinity and low-affinity using a threshold of 50 nM ( http: / / tools.iedb.org / mhci / help / ), and it was observed that MHC-I high-affinity peptides promote more INF-γ production compared to MHC-I low-affinity peptides (Fig. 7e). In short, these results validate the predictive effect of the HEX tool for identifying homologous peptides and highlight that molecular mimicry between viruses and tumors plays a role in the anti-tumor immune response in cross-reactive T cells.

[0190] tumor In the epitope Viruses that share a high degree of similarity Epitope is It reduces the proliferation of established melanoma in vivo.

[0191] The inventors demonstrated that molecular mimicry between viral antigens and tumor antigens can influence tumor proliferation in pre-immunized mice. Next, the inventors sought to evaluate whether molecular mimicry-directed responses could also influence established tumors in naive mice. To this end, mice were implanted with B16OVA tumors or more aggressive immunosuppressive B16F10 tumors, and then treated with PeptiCRAd (20), a vaccine platform already developed to mimic viral infection (Fig. 8A). Briefly, PeptiCRAd is a vaccine technology consisting of an adenovirus coated with an MHC-I restricted peptide having a positively charged poly-amino acid tail. In this case, the inventors proceeded using the most effective peptide pool from primary in vivo experiments. The vaccine is an adenovirus with the original TRP2 180 -188 It was prepared by coating with a virus-derived peptide counterpart similar to the epitope (TRP2-PeptiCRAd) or TRP2 (Viral PeptiCRAd). For both B16OVA (Figs. 8B-C) and B16F10 tumors (Figs. 8E-F), intratumoral injection of PeptiCRAd significantly reduced tumor progression compared to treatment with saline buffer or uncoated viruses. Mice treated with the original tumor antigen or viral homologs showed a significantly higher number of responders in both tumor models (Figs. 8D, 8G). In both tumor models, the inventors observed a significant reduction in tumor proliferation when mice were treated with viral peptides similar to the tumor peptides, which again suggests that molecular mimicry may play a fundamental role in anti-tumor immunity associated with cross-reactive T cells.

[0192] CMV A study on whether molecular mimicry between and tumor antigens can better explain the prognosis

[0193] The inventors used HEX to generate a list of tumor peptides with high similarity to CMV (Table 2) to compare a melanoma-associated protein pool with the CMV proteome. [ 21 We selected the tumor peptide and its CMV counterpart for the ELISPOT analysis. It was confirmed that in responder patients, PBMCs always responded to both the virus and its counterpart tumor antigen, suggesting that CMV infection amplifies viral T cell clones that attack and kill tumor cells, making seropositive patients more responsive to melanoma-specific epitopes similar to CMV (Fig. 9a, b). Unfortunately, these observations had limitations in that they could not directly demonstrate whether the virus and the tumor peptide amplified the same T cell clones.

[0194] A new microfluidic chip-based platform is a rare tumor biopsy Immunopep in tissue T-dom Identify the profile.

[0195] The inventors challenged a platform for investigating rare tumor biopsies. Thus, ovarian metastatic tumors (high-grade serous) were collected from patients, and four fragments were obtained from the tumor boundaries (S1, S2, S3, and S4); of course, one was also collected from the center of the tumor (S5). Next, the samples were weighed, and as summarized in Fig. 10a, the size was on average 0.01 g to 0.06 g. After digesting the samples, the obtained single-cell suspensions were lysed and processed via a microchip. Applying a strict false discovery threshold of 1% for peptide and protein identification, 916, 695,172, 1,128, and 256 unique peptides were identified in S1, S2, S3, S4, and S5, respectively (Fig. 10a). Similar to typical ligandome profiles, general enrichment (>70%) was observed in 7-13mer samples (Fig. 10a). In terms of absolute number and percentage, 9mer samples were identified as the most representative in the amino acid length distribution (Fig. 10b), which validated the present invention and other previous immunopeptidome analyses. Next, the inventors applied gene ontology (GO) enrichment analysis to further investigate the source proteins found in the data of the present invention. Similar to typical ligandome profiles, metabolic processes were enriched in all investigated samples. Furthermore, the analysis revealed an increase in skin development pathway proteins consistent with the epithelial characteristics of ovarian serous tumors analyzed herein. In addition, the results highlighted the potential to utilize microfluidic-chip platforms developed to analyze rare tumor biopsies and obtain customized antigen peptides for tumor treatment.

[0196] microchips - The based protocol is patient-derived In organoids Immunopep T-dom It brightens the environment

[0197] Microchip technology uses 6 x 10 cells from patient-derived organoids (PDOs).6 Test investigations were conducted using a small number of samples. The inventors selected two patients from an ongoing precision medicine trial for urological cancers and further processed a nephrectomy sample containing both benign and cancerous tissues from a patient with clear cell renal cell carcinoma (ccRCC) and a 1x1 cm sample from a patient with bladder cancer as 3D primary organoid cultures.

[0198] By applying a strict upper discovery threshold of 1% to the developed microchip technology and the identification of peptides and proteins, the inventors were able to identify a total of 576 and 2089 unique peptides in ccRCC and bladder PDO, respectively (Fig. 11a). The number of recovered peptides differed between the two samples, with the bladder samples having more peptides than the ccRCC samples. It is well known that HLA expression affects the amount of isolated HLA-I peptides [22A], and similarly, flow cytometry analysis revealed that the surface levels of HLA-A, HLA-B, and HLA-C were higher in the bladder than in the ccRCC samples, which explains the difference in peptide yields recovered from the samples. Peptide analysis results showed a preference for 9-12mers, consistent with the typical length distribution of ligandome analysis

[33] (56.4% for ccRCC and 47.9% for bladder tumors) (Fig. 11b). To distinguish HLA-I binding substances from contaminants, Gibbs clustering and NetMHC4.0 analysis were performed. First, 9mer deconvolution confirmed that 55% and 67% of bladder and ccRCC PDOs, respectively, matched one or more of the patient's HLA alleles. Next, NetMHC4.0 was applied to all 9mers identified in the dataset. Of these, 46% and 69% were predicted to be binding substances of the patient's specific HLA. Next, source proteins present in both datasets were investigated. To this end, gene ontology (GO) enrichment analysis was performed. As with previous observations and disclosed data in this invention, enrichment of intracellular and nuclear proteins that interact with RNA and participate in catabolic / metabolic processes was confirmed in both samples.

[0199] To demonstrate that this technology can be used to rapidly develop therapeutic cancer vaccines, the inventors established a cell death assay. The inventors focused on the analysis of ccRCC samples. Using healthy kidney tissue and PBMCs as reference sets, the inventors utilized transcriptome levels to select putative tumor antigens. Next, PBMCs from healthy volunteers were stimulated with a selected peptide, and CD8+ T cells isolated from these cells were used for analysis. T cells stimulated with the peptide EVAQPGPSNR (gene name HSPG2) exhibited approximately 10% specific cytolysis.

[0200] Finally, the inventors intended to investigate recall T cell responses in ccRCC patients. To this end, unfractionated PBMCs derived from patients were stimulated in vitro with the peptide EVAQPGPSNR, and unstimulated PBMCs were used as a control. Subsequently, CD8+ T cells derived from the PBMCs were added to the ccRCC PDOs, and an increase in apoptotic activity of approximately 7% compared to the control group was confirmed.

[0201] patient Organoid origin Peptides In vivo It was proven to be therapeutically effective in experiments.

[0202] The peptide list was analyzed using HEX. First, priority was given to peptides that were simultaneously strong binders in the software (cutoff IC50 range of 50 nM–500 nM according to NetMHC 4.0) and exhibited higher weighted alignment scores (cutoff 0.8–1 standardized to weighted alignment scores). The latter focused on peptide similarity at interaction sites most likely to bind to the TCRs of CD8+ T cells to induce mediated immune responses; the obtained peptides were subsequently evaluated for total identity % and IC50 for pathogen-derived antigens / peptides. 50They were further classified based on binding affinity scores. The final product consisted of 13 peptides and their corresponding pathogenic peptides (Table 4).

[0203] To confirm the immunogenicity of the peptides, mice were pre-immunized by subcutaneous injection of each single peptide in the presence of the adjuvant poly(I:C); one group of mice was injected with poly(I:C) alone or saline as a control. Splenocytes derived from these mice were recovered, and IFNγ production upon specific stimulation was examined using the ELISpot assay (Table 5).

[0204] Next, the inventors sought to verify whether the candidate peptide could be used as a cancer vaccine to treat established tumors. To this end, the inventors adopted PeptiCRAd, a previously developed cancer vaccine platform in which a oncolytic adenovirus is combined with a capsid-attached poly-lysine modified peptide (via a poly-lysine linker). The adenovirus used herein is VALO-mD901, which is genetically modified to express murine OX40L and CD40L and has been previously identified to control tumor proliferation and induce a systemic anti-tumor response in a murine melanoma model. Accordingly, the synonymic tumor model CT26 was subcutaneously injected into the left and right flanks of Balb / c mice (Day 0, Fig. 12a). Once the tumor was established (Day 7, Fig. 12a), Valo-mD901 was coated with each poly-lysine-modified peptide pair from the list of the present invention (PeptiCRAd1, PeptiCRAd2, PeptiCRAd3, Table 6) and injected intratumorally only into the right tumor. PeptiCRAd4 consisted of Valo-mD901 coated with gp70423-431 (AH1-5). The mock group and the Valo-mD901 group were used as controls. PeptiCRAd1 and PeptiCRAd2 improved tumor proliferation in the injected lesions compared to Valo-mD901 as well as the controls (Fig. 12b, right panel). Interestingly, PeptiCRAd1 improved anti-tumor proliferation control in untreated tumors, in contrast to Valo-mD901, which did not trigger efficacy.

[0205] summation

[0206] HEX is a bioinformatics tool that analyzes peptide sequences and compares them to a curated database of pathogen-derived viral proteomes that searches for sequences with high similarity.

[0207] Since the presented peptides primarily participate in interactions with anchor residues of the MHC

[25] , the software of the present invention recovered position-weighted alignment scores to prioritize similarities in the central portion of the peptides, which are the locations most involved in interactions with the TCR

[26] . In addition, to increase the likelihood that the target of the present invention is the presented epitope, the inventors in the examples used the IEDB NetMHC prediction tool API

[27] ; or NetMHC4.0 or NetMHCpan4.1b as independent tools to rank the peptides obtained according to their binding affinity to the selected MHC.

[0208] The inventors used HEX to identify homologous virus-peptides for three types of broadly specified tumor-associated antigens.

[0209] The inventors have confirmed that pre-immunization using a selected viral peptide pool stimulates an anti-viral immune state before tumor establishment and effectively slows down the proliferation of melanoma tumor cells injected subcutaneously in mice, which means that pre-exposure to virus-derived peptides can affect tumor proliferation.

[0210] Next, the inventors observed that a tumor-homologous virus-derived peptide has a similar effect on an established tumor when administered during tumor progression, which means that a viral infection occurring during tumor progression can still affect its proliferation.

[0211] In short, the results of the present invention suggest that molecular mimicry between virus-derived antigens and tumor-derived antigens can exert control over tumor proliferation without even relying on prior-exposure or prior-acquired immunity.

[0212] The novel ICPI has significantly improved patient survival in several types of solid tumors, particularly metastatic melanoma, compared to other commonly used therapies such as radiation and chemotherapy. However, despite improvements in survival and effective response rates, the reason why ICPI therapy is not useful in some patients is not yet known. The results of this invention have shown that patients with high CMV-specific IgG titers have significantly longer progression-free survival.

[0213] The inventors observed that PBMCs derived from patients with high anti-CMV-IgG titers reacted with melanoma antigens similar to CMV peptides. This data demonstrates that CMV seropositivity contributes to melanoma-specific T-cell immunity, providing clinical benefits to patients undergoing ICPI therapy.

[0214] In this invention, the inventors have demonstrated that viral infection can affect tumor proliferation and elimination. Furthermore, the inventors have demonstrated the cross-reactivity of cytotoxic T-cells to selected virus- and homologous tumor-derived antigens using HEX. Based on the results of this invention, the inventors have concluded that molecular mimicry phenomena may be utilized in the future for the development of new therapies, or that when used in combination with immunotherapy, they may potentially enhance the anti-tumor immune effects achieved by these therapies.

[0215] Furthermore, it is essential to be able to reliably identify tumor peptides that bind to HLA-I in order to design effective tumor rejection and protection strategies. Direct peptide identification from the HLA-I complex is still the best method. Nevertheless, the immunopeptidome workflow is relatively complex and is therefore a major bottleneck in the antigen discovery process. Currently, the inability to analyze immunopeptidomes on existing platforms due to small amounts of biological material (e.g., tissue needle biopsies), sample processing, cost, and the adoption of affinity matrices (which are labor-intensive and expensive to build) has been cited as a major technical challenge to be addressed.

[0216] In this study, the inventors addressed several technical problems hindering ligandome research by focusing primarily on the limited availability of analytes, consumable costs, and lengthy protocols.

[0217] The inventors were able to replace conventional techniques based on affinity matrices prepared via cross-linking reactions with a microchip platform by utilizing well-specified biotin-streptavidin interactions to immobilize biotinized pan-HLA antibodies on streptavidin-functionalized surfaces. Limitations due to material scarcity (e.g., needle biopsies) inspired the development of a microfluidic protocol. In this study, the inventors utilized a custom microchip protocol comprising a thiol-ene polymer-based microprotrusion array as a solid support for additional bifunctionalization, which enables the entire IP process to be performed on a single microfluidic chip.

[0218] According to verification of the peptide identified in the in vitro cell death analysis, it was verified that the peptide identified by the performance of the present invention killed cells in a specific CD8+ T cell-dependent manner and was presented on the surface of actual JY cells. The peptide ILDKKVEKV (SEQ No. 3) discovered in the dataset of the present invention induced specific cell lysis at a higher percentage.

[0219] Therefore, the method of the present invention provides a tool that has been examined for immuno-affinity purification.

[0220] References

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[0224] 26. A. K. Sharma, J. J. Kuhns, S. Yan, R. H. Friedline, B. Long, R. Tisch, E. J. Collins, Class I Major Histocompatibility Complex Anchor Substitutions Alter the Conformation of T Cell Receptor Contacts, J. Biol. Chem. 276, 21443-21449 (2001).

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Claims

Claim 1 A method for identifying tumor-specific antigens comprising the following steps: i) dissolving or suspending a sample of a tumor in a fluid; ii) passing the fluid through a microfluidic device for tumor-specific antigen identification, wherein the tumor antigen identification device comprises at least one fluid-passing channel comprising a plurality of microprotrusions arranged in an array to which at least one molecule or at least one complex is attached, to which one or more anti-main histocompatibility complex antibodies or one or more universal anti-human leukocyte antigen (anti-pan-HLA) antibodies are bound, so that the peptide:main histocompatibility complex (pMHC) in the sample flowing through the channel can be extracted from the sample using at least one antibody; iii) binding one or more pMHCs in the sample to one or more antibodies; iv) recovering one or more bound pMHCs of iii) from the device; v) comparing the peptide of the bound pMHC with a pathogen-derived antigen library to determine whether the peptide is homologous or affine for one or more pathogenic antigens or parts thereof. If homology / affinity is higher than 60%; vi) a step of identifying the above peptide as a tumor-specific antigen for use in cancer therapy. Claim 2 A method according to claim 1, wherein the pathogen-derived antigen library comprises a carefully selected known pathogenic antigen library. Claim 3 A method according to claim 1, wherein the pathogenic antigen is a human pathogenic antigen. Claim 4 A method according to claim 1, wherein the pathogenic antigen is a viral antigen. Claim 5 The method of claim 1, wherein the pathogenic antigen is derived from one or more viruses selected from the following viruses and 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; Bacilladnaviridae; Baculoviridae; Barnaviridae; Bastillevirinae; Bclasvirinae; Belpaoviridae; Benyviridae; Betaflexiviridae;Betaherpesvirinae; Betairidovirinae; Bicaudaviridae; Bidnaviridae; Birnaviridae; Bornaviridae; Botourmiaviridae; Brockvirinae; Bromoviridae; Bullavirinae; Caliciviridae; Calvusvirinae; Carmotetraviridae; Caulimoviridae; Ceronivirinae; Chebruvirinae; Chordopoxvirinae; Chrysoviridae; Chuviridae; Circoviridae; Clavaviridae; Closteroviridae; Comovirinae; Coronaviridae; Corticoviridae; Crocarterivirinae; Cruliviridae; Crustonivirinae; Cvivirinae; Cystoviridae; Dclasvirinae; Deltaflexiviridae; Densovirinae; Dicistroviridae; Endornaviridae; Entomofoxvirinae; Equarterivirinae; Eucampyvirinae; Euroniviridae;Filoviridae; Fimoviridae; Firstpapillomavirinae; Flaviviridae; Fuselloviridae; Gammaflexiviridae; Gammaherpesvirinae; Geminialphasatellitinae; Geminiviridae; Genomoviridae; Globuloviridae; Gokushovirinae; Guernseyvirinae; Guttaviridae; Hantaviridae; Hepadnaviridae; Hepeviridae; Herelleviridae; Heroarterivirinae; Herpesviridae; Hexponivirinae; Hypoviridae; Hydrosaviridae; Iflaviridae; Inoviridae; Iridoviridae; Jasinkavirinae; Kitaviridae; Lavidaviridae; Leishbuviridae; Letovirinae; Leviviridae; Lipothrixviridae; Lispiviridae; Luteoviridae; Malacoherpesviridae; Mammantavirinae; Marnaviridae; Marseilleviridae;Matonaviridae; McCleskeyvirinae; McClasvirinae; 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; Papillomaviridae; Paramyxoviridae; Partitiviridae; Parvoviridae; Parvovirinae; Pclasvirinae;Peduovirinae; Peribunyaviridae; Permutotetraviridae; Phasmaviridae; Phenuiviridae; Phycodnaviridae; Picobirnaviridae; Picornaviridae; Picovirinae; Piscanivirinae; Plasmaviridae; Pleolipoviridae; Pneumoviridae; Podoviridae; Polycipiviridae; Polydnaviridae; Polyomaviridae; Portogloboviridae; Pospiviroidae; Potyviridae; Poxviridae; Procedovirinae; Pseudoviridae; Qinviridae; Quadriviridae; Quinvirinae; Regressovirinae; Remotovirinae; Reoviridae; Repantavirinae; Retroviridae; Rhabdoviridae; Roniviridae; Rubulavirinae; Rudiviridae; Sarthroviridae; Secondpapillomavirinae; Secoviridae; Sedoreovirinae; Sepvirinae;Serpentovirinae; Simarterivirinae; Siphoviridae; Smacoviridae; Solemoviridae; Solinviviridae; Sphaerolipoviridae; Spinareovirinae; Spiraviridae; Spounavirinae; Spumaretrovirinae; Sunviridae; Tectiviridae; Tevenvirinae; Tiamatvirinae; Tobaniviridae; Togaviridae; Tolecusatellitidae; Tombusviridae; Torovirinae; Tospoviridae; Totiviridae; Tristromaviridae; Trivirinae; Tunavirinae; Tunicanivirinae; Turriviridae; Twortvirinae; Tymoviridae; Variarterivirinae; Vequintavirinae; Virgaviridae; Wupedeviridae; Xinmoviridae; Yueviridae; and Zealarterivirinae.; Claim 6 A method according to claim 1, wherein the pathogenic antigen is a cytomegalovirus antigen, an Epstein-Barr virus antigen, a herpesvirus antigen, a poxvirus antigen, a hepardonevirus antigen, an influenza virus antigen, a coronavirus antigen, a hepatitis virus antigen, an HIV antigen, or a field virus antigen. Claim 7 The method of claim 1, wherein the step of comparing the peptide of the bound pMHC with a pathogenic antigen library comprises peptide score evaluation and alignment score evaluation to determine homology / affinity. Claim 8 The method of claim 1, wherein the step of comparing the bound pMHC peptide with a pathogenic antigen library comprises determining: a) similarity or identity of the overall sequence structure of the peptide and the pathogenic antigen; and / or b) similarity or identity of key amino acids at the core binding site of the peptide and the pathogenic antigen; and / or c) the greatest number of similar or identical key amino acids at the core binding site of the peptide and the pathogenic antigen. Claim 9 A microfluidic device comprising at least one fluid-passing channel comprising a plurality of microprotrusions arranged in an array to which at least one molecule or at least one complex is attached, to which one or more anti-main histocompatibility complex antibodies or one or more universal anti-human leukocyte antigen (HLA) antibodies are bound, so as to be able to extract a peptide:main histocompatibility complex (pMHC) within a sample flowing through the channel from a sample using at least one antibody; and a processor suitable for identifying the peptide bound to the main histocompatibility complex, comparing the peptide of the bound pMHC with a pathogen-derived antigen library, determining whether the peptide is homologous or affineable to one or more pathogenic antigens or parts thereof when the homology / affinity is higher than 60%, and identifying the peptide as a tumor-specific antigen for use in cancer therapy. Claim 10 In claim 9, the device wherein the universal anti-human leukocyte antigen (HLA) antibody is selected from the group comprising MHC classes IA, B, and C. Claim 11 A device according to claim 9, wherein the universal anti-human leukocyte antigen (HLA) antibody is selected from the group comprising MHC class II DP, DM, DO, DQ, and DR. Claim 12 A device according to any one of claims 9 to 11, wherein the antibody is anti-human. Claim 13 In claim 9, the device wherein the molecule or complex is a complex of a thiol functional group and an alkene functional group. Claim 14 In claim 9, the device wherein the molecule or complex comprises biotin and streptavidin. Claim 15 In claim 9, the device comprising two or more antibodies bound to streptavidin, wherein the molecule or complex comprises the molecule or complex. Claim 16 In claim 9, the device is conditioned by coating the molecule or complex with a protein such as bovine serum albumin before binding to the antibody. Claim 17 In claim 9, the device is suitable for performing the method according to any one of claims 1 to 8. Claim 18 delete Claim 19 delete Claim 20 delete Claim 21 delete Claim 22 delete Claim 23 delete Claim 24 delete Claim 25 delete Claim 26 delete Claim 27 delete Claim 28 delete Claim 29 delete Claim 30 delete Claim 31 delete Claim 32 delete Claim 33 delete

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