Pancreatic cancer diagnostic composition

Abstract

Provided are a biomarker for diagnosing pancreatic cancer, a composition for diagnosing pancreatic cancer comprising a preparation capable of detecting the biomarker, and a method for diagnosing pancreatic cancer using the same.

Description

[Technical Field]

[0001] [CROSS-REFERENCE TO RELATED APPLICATIONS] This application claims the benefit of priority based on Korean Patent Application No. 10-2022-0123808 dated September 28, 2022, and all contents disclosed in the documents of this Korean patent application are incorporated herein by reference. The present invention relates to a biomarker for diagnosing pancreatic cancer, a composition for diagnosing pancreatic cancer that includes a preparation capable of detecting the biomarker, and a method for diagnosing pancreatic cancer that utilizes the same. [Background technology]

[0002] Biomarkers are indicators that can detect changes induced within living organisms by external influences, and research into their use in diagnosing various diseases such as cancer and nervous system disorders, and predicting the efficacy of specific therapeutic agents, is being actively conducted.

[0003] Meanwhile, the pancreas is an organ located posterior to the stomach, measuring approximately 20 cm in length, that secretes digestive juices and hormones. Pancreatic cancer generally refers to pancreatic ductal carcinoma. Pancreatic cancer has been gradually increasing as Western-style diets become more common, and it is known to occur primarily in men and has a high mortality rate. Pancreatic cancer is known to be caused by a history of smoking, coffee, alcohol consumption, a meat-based diet, diabetes, chronic pancreatitis, non-polyposis colorectal cancer syndrome, and substances such as beta-naphthylamine and benzidine.

[0004] Pancreatic cancer usually causes no particular symptoms in the early stages, but symptoms such as pain and weight loss usually appear after the cancer has already spread throughout the body, and the mortality rate is very high. For more effective treatment of pancreatic cancer, it is necessary to develop techniques for early diagnosis of pancreatic cancer, confirmation of the stage of progression, and / or differentiation from other similar diseases. Summary of the Invention [Problem to be solved by the invention]

[0005] One example provides a biomarker for diagnosing pancreatic cancer, comprising one or more selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, PTGES, and their encoding genes. The biomarker may be for detection or analysis in a buffy coat of blood.

[0006] Another example provides a diagnostic composition or kit for pancreatic cancer, comprising an agent capable of detecting one or more genes selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, PTGES, and their encoding genes. The diagnostic composition or kit for pancreatic cancer may be for use on a buffy coat of blood.

[0007] Another example provides a method for diagnosing pancreatic cancer or a method for providing information on the diagnosis of pancreatic cancer, comprising detecting one or more genes selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, PTGES, and their encoding genes, from a blood sample isolated from a subject. The blood sample may include a buffy coat of blood. The detecting step may include determining the presence, absence, and / or level of one or more selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, PTGES, and their encoding genes from a blood sample.

[0008] Another example provides a use of a preparation capable of detecting one or more proteins selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, PTGES, and the genes encoding these proteins for diagnosing pancreatic cancer and / or for producing a diagnostic composition or kit for diagnosing pancreatic cancer. The diagnosis of pancreatic cancer may be performed on a buffy coat of blood, or the diagnostic composition or kit for diagnosing pancreatic cancer may be for use on a buffy coat of blood. The pancreatic cancer may include early stage pancreatic cancer, late stage pancreatic cancer, or all of these. [Means for solving the problem]

[0009] Here's a more detailed explanation:

[0010] Pancreatic cancer diagnosis As used herein, "pancreatic cancer" collectively refers to tumors that occur in the pancreas, and examples thereof include cystic tumors (vesicles) such as enteric cystic tumors, mucinous cystic tumors, intraductal papillary mucinous tumors, solid papillary tumors, lymphoepithelial cysts, and cystic tumors (vesicles) such as cystic teratomas, as well as malignant tumors such as pancreatic ductal adenocarcinomas, acinar cell carcinomas, and neuroendocrine tumors. Pancreatic cancers that can be diagnosed using the biomarkers provided herein can be selected from the above pancreatic cancers, for example, selected from malignant tumors, but are not limited thereto.

[0011] Furthermore, in this specification, "pancreatic cancer" can also mean, based on the stage of progression, early stage pancreatic cancer (e.g., resectable pancreatic cancer, etc.), late stage pancreatic cancer (e.g., borderline resectable pancreatic cancer, locally advanced pancreatic cancer, metastatic pancreatic cancer, etc.), or all of these.

[0012] As used herein, "diagnosis" can include, but is not limited to, determining a subject's susceptibility to a particular disease or disorder, determining whether a subject currently has a particular disease or disorder, determining a subject's risk for developing a particular disease or disorder, determining the prognosis of a subject with a particular disease or disorder (e.g., identifying a pre-metastatic or metastatic cancer state, determining the stage of the cancer, determining the response of the cancer to treatment, etc.), and / or therametrics (e.g., monitoring a subject's condition to provide information on the efficacy of treatment), etc.

[0013] As used herein, diagnosing pancreatic cancer means confirming whether or not a subject has developed pancreatic cancer (e.g., early-stage pancreatic cancer, late-stage pancreatic cancer, or all of these), the possibility (risk) of the onset, and / or the degree of progression, and / or distinguishing it from normal or other similar diseases (e.g., positive pancreatic diseases (other pancreatic diseases (pancreatitis (chronic pancreatitis and / or acute pancreatitis)), pancreatic positive tumors, intraductal papillary mucinous neoplasms (IPMN), autoimmune pancreatitis (AIP) (pancreatic diseases excluding pancreatic cancer (pancreatic malignant tumors))), biliary tract cancer, etc.).

[0014] Biomarkers for diagnosing pancreatic cancer Provided herein as biomarkers for diagnosing pancreatic cancer are one or more proteins selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES, for example, a combination of any one or more proteins (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20) selected from the group. The biomarkers described herein may refer to the one or more proteins and / or the genes encoding them.

[0015] In one embodiment, the biomarker for diagnosing pancreatic cancer may be IFNL1, its encoding gene, or a combination thereof. The biomarker may be characterized by a high (increased) expression level and / or concentration in pancreatic cancer samples, e.g., early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer samples regardless of stage (e.g., early stage pancreatic cancer and late stage pancreatic cancer), compared to a comparison sample (e.g., a normal sample). The biomarker may be for use in diagnosing pancreatic cancer, e.g., early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer samples regardless of stage (e.g., early stage pancreatic cancer and late stage pancreatic cancer).

[0016] In another embodiment, the biomarker for diagnosing pancreatic cancer may be IFNG, its encoding gene, or a combination thereof. The biomarker may be characterized by a low (decreased) expression level and / or concentration in pancreatic cancer samples, e.g., early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer samples regardless of stage (e.g., early stage pancreatic cancer and late stage pancreatic cancer), compared to a comparison sample (e.g., a normal sample). The biomarker may be for use in diagnosing pancreatic cancer, e.g., early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer samples regardless of stage (e.g., early stage pancreatic cancer and late stage pancreatic cancer).

[0017] In another embodiment, the biomarker for diagnosing pancreatic cancer may be CXCL11, its encoding gene, or a combination thereof. The biomarker may be characterized by a high (increased) expression level and / or concentration in pancreatic cancer, e.g., early-stage pancreatic cancer samples, and / or a low (decreased) expression level and / or concentration in late-stage pancreatic cancer samples, compared to a comparison sample (e.g., a normal sample). The biomarker may be for use in diagnosing pancreatic cancer, e.g., early-stage pancreatic cancer and / or late-stage pancreatic cancer.

[0018] In another embodiment, the biomarker for diagnosing pancreatic cancer may be TNF, its encoding gene, or a combination thereof. The biomarker may be characterized by a high (increased) expression level and / or concentration in pancreatic cancer samples, e.g., early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer samples regardless of stage (e.g., early stage pancreatic cancer and late stage pancreatic cancer), compared to a comparison sample (e.g., a normal sample). The biomarker may be for use in diagnosing pancreatic cancer, e.g., early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer samples regardless of stage (e.g., early stage pancreatic cancer and late stage pancreatic cancer).

[0019] In another embodiment, the biomarker for diagnosing pancreatic cancer may be CLEC7A, its encoding gene, or a combination thereof. The biomarker may be characterized by a high (increased) expression level and / or concentration in pancreatic cancer, e.g., late-stage pancreatic cancer samples, and / or a low (decreased) expression level and / or concentration in early-stage pancreatic cancer samples, compared to a comparison sample (e.g., a normal sample). The biomarker may be for use in diagnosing pancreatic cancer, e.g., late-stage pancreatic cancer and / or early-stage pancreatic cancer.

[0020] In another embodiment, the biomarker for diagnosing pancreatic cancer may be CXCL8, its encoding gene, or a combination thereof. The biomarker may be characterized by a high (increased) expression level and / or concentration in pancreatic cancer samples, e.g., late-stage pancreatic cancer, early-stage pancreatic cancer, or all pancreatic cancer samples regardless of stage (early-stage pancreatic cancer and late-stage pancreatic cancer), compared to a comparison sample (e.g., a normal sample). The biomarker may be for use in diagnosing pancreatic cancer, e.g., late-stage pancreatic cancer, early-stage pancreatic cancer, or all pancreatic cancer samples regardless of stage (early-stage pancreatic cancer and late-stage pancreatic cancer).

[0021] In another embodiment, the biomarker for diagnosing pancreatic cancer may be FOXP3, its encoding gene, or a combination thereof. The biomarker may be characterized by a low (decreased) expression level and / or concentration in pancreatic cancer, e.g., late-stage pancreatic cancer samples, and / or a high (increased) expression level and / or concentration in early-stage pancreatic cancer samples, compared to a comparison sample (e.g., a normal sample). The biomarker may be for use in diagnosing pancreatic cancer, e.g., late-stage pancreatic cancer and / or early-stage pancreatic cancer.

[0022] In another embodiment, the biomarker for diagnosing pancreatic cancer may be VEGFA, its encoding gene, or a combination thereof. The biomarker may be characterized by a high (increased) expression level and / or concentration in pancreatic cancer samples, e.g., late-stage pancreatic cancer, early-stage pancreatic cancer, or all pancreatic cancer samples regardless of stage (early-stage pancreatic cancer and late-stage pancreatic cancer), compared to a comparison sample (e.g., a normal sample). The biomarker may be for use in diagnosing pancreatic cancer, e.g., late-stage pancreatic cancer, early-stage pancreatic cancer, or all pancreatic cancer samples regardless of stage (early-stage pancreatic cancer and late-stage pancreatic cancer).

[0023] In another embodiment, the biomarker for diagnosing pancreatic cancer may be CCL2, its encoding gene, or a combination thereof. The biomarker may be characterized by a high (increased) expression level and / or concentration in pancreatic cancer samples, e.g., early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer samples regardless of stage (e.g., early stage pancreatic cancer and late stage pancreatic cancer), compared to a control sample (e.g., a normal sample). The biomarker may be for use in diagnosing pancreatic cancer, e.g., early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer samples regardless of stage (e.g., early stage pancreatic cancer and late stage pancreatic cancer).

[0024] In another embodiment, the biomarker for diagnosing pancreatic cancer may be CCL5, its encoding gene, or a combination thereof. The biomarker may be characterized by a low (decreased) expression level and / or concentration in pancreatic cancer, e.g., late-stage pancreatic cancer samples, early-stage pancreatic cancer, or all pancreatic cancers regardless of stage (early-stage pancreatic cancer and late-stage pancreatic cancer), compared to a comparison sample (e.g., a normal sample). The biomarker may be for use in diagnosing pancreatic cancer, e.g., late-stage pancreatic cancer, early-stage pancreatic cancer, or all pancreatic cancers regardless of stage (early-stage pancreatic cancer and late-stage pancreatic cancer).

[0025] In another embodiment, the biomarker for diagnosing pancreatic cancer may be CCR5, its encoding gene, or a combination thereof. The biomarker may be characterized by a low (decreased) expression level and / or concentration in pancreatic cancer, e.g., late-stage pancreatic cancer samples, and / or a high (increased) expression level and / or concentration in early-stage pancreatic cancer samples, compared to a comparison sample (e.g., a normal sample). The biomarker may be for use in diagnosing pancreatic cancer, e.g., late-stage pancreatic cancer and / or early-stage pancreatic cancer.

[0026] In another embodiment, the biomarker for diagnosing pancreatic cancer may be CXCR4, its encoding gene, or a combination thereof. The biomarker may be characterized by a high (increased) expression level and / or concentration in pancreatic cancer samples, e.g., late-stage pancreatic cancer, early-stage pancreatic cancer, or all pancreatic cancer samples regardless of stage (early-stage pancreatic cancer and late-stage pancreatic cancer), compared to a comparison sample (e.g., a normal sample). The biomarker may be for use in diagnosing pancreatic cancer, e.g., late-stage pancreatic cancer, early-stage pancreatic cancer, or all pancreatic cancer samples regardless of stage (early-stage pancreatic cancer and late-stage pancreatic cancer).

[0027] In another embodiment, the biomarker for diagnosing pancreatic cancer may be ARG1, its encoding gene, or a combination thereof. The biomarker may be characterized by a high (increased) expression level and / or concentration in pancreatic cancer, e.g., late-stage pancreatic cancer samples, early-stage pancreatic cancer, or all pancreatic cancers regardless of stage (early-stage pancreatic cancer and late-stage pancreatic cancer), compared to a comparison sample (e.g., a normal sample). The biomarker may be for use in diagnosing pancreatic cancer, e.g., late-stage pancreatic cancer, early-stage pancreatic cancer, or all pancreatic cancers regardless of stage (early-stage pancreatic cancer and late-stage pancreatic cancer).

[0028] In another embodiment, the biomarker for diagnosing pancreatic cancer may be CXCR2, its encoding gene, or a combination thereof. The biomarker may be characterized by a high (increased) expression level and / or concentration in pancreatic cancer, e.g., late-stage pancreatic cancer samples, and / or a low (decreased) expression level and / or concentration in early-stage pancreatic cancer samples, compared to a comparison sample (e.g., a normal sample). The biomarker may be for use in diagnosing pancreatic cancer, e.g., late-stage pancreatic cancer and / or early-stage pancreatic cancer.

[0029] In another embodiment, the biomarker for diagnosing pancreatic cancer may be PTGS2, its encoding gene, or a combination thereof. The biomarker may be characterized by a high (increased) expression level and / or concentration in pancreatic cancer samples, e.g., late-stage pancreatic cancer, early-stage pancreatic cancer, or all pancreatic cancer samples regardless of stage (early-stage pancreatic cancer and late-stage pancreatic cancer), compared to a comparison sample (e.g., a normal sample). The biomarker may be for use in diagnosing pancreatic cancer, e.g., late-stage pancreatic cancer, early-stage pancreatic cancer, or all pancreatic cancer samples regardless of stage (early-stage pancreatic cancer and late-stage pancreatic cancer).

[0030] In another embodiment, the biomarker for diagnosing pancreatic cancer may be PTGES2, its encoding gene, or a combination thereof. The biomarker may be characterized by a low (decreased) expression level and / or concentration in pancreatic cancer samples, e.g., early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer samples regardless of stage (e.g., early stage pancreatic cancer and late stage pancreatic cancer), compared to a comparison sample (e.g., a normal sample). The biomarker may be for use in diagnosing pancreatic cancer, e.g., early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer samples regardless of stage (e.g., early stage pancreatic cancer and late stage pancreatic cancer).

[0031] In another embodiment, the biomarker for diagnosing pancreatic cancer may be SLC27A2, its encoding gene, or a combination thereof. The biomarker may be characterized by a high (increased) expression level and / or concentration in pancreatic cancer, e.g., in an early stage pancreatic cancer sample, in a late stage pancreatic cancer, or in all pancreatic cancers regardless of stage (e.g., early stage pancreatic cancer and late stage pancreatic cancer), compared to a comparison sample (e.g., a normal sample). The biomarker may be for use in diagnosing pancreatic cancer, e.g., in early stage pancreatic cancer, in late stage pancreatic cancer, or in all pancreatic cancers regardless of stage (e.g., early stage pancreatic cancer and late stage pancreatic cancer).

[0032] In another embodiment, the biomarker for diagnosing pancreatic cancer may be PTGES, its encoding gene, or a combination thereof. The biomarker may be characterized by a high (increased) expression level and / or concentration in pancreatic cancer samples, e.g., early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer samples regardless of stage (e.g., early stage pancreatic cancer and late stage pancreatic cancer), compared to a comparison sample (e.g., a normal sample). The biomarker may be for use in diagnosing pancreatic cancer, e.g., early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer samples regardless of stage (e.g., early stage pancreatic cancer and late stage pancreatic cancer).

[0033] In another specific example, the biomarker for diagnosing pancreatic cancer may be one or more (one or two) selected from the group consisting of IFNB1 and IFNA1, their encoding genes, or a combination thereof. The biomarkers can be characterized by low (decreased) expression levels and / or concentrations in pancreatic cancer samples compared to samples of similar diseases (e.g., positive pancreatic diseases (e.g., other pancreatic diseases excluding pancreatic cancer (malignant pancreas)), such as pancreatitis (chronic pancreatitis and / or acute pancreatitis), pancreatic positive tumors, intraductal papillary mucinous neoplasm (IPMN), autoimmune pancreatitis (AIP))). The biomarkers may be for use in diagnosing pancreatic cancer, e.g., early stage pancreatic cancer, and / or distinguishing pancreatic cancer from positive pancreatic diseases (e.g., other pancreatic diseases excluding pancreatic cancer (malignant pancreas)), such as pancreatitis (chronic pancreatitis and / or acute pancreatitis), pancreatic positive tumors, intraductal papillary mucinous neoplasm (IPMN), autoimmune pancreatitis (AIP)) and / or biliary tract cancer.

[0034] The 20 biomarkers may be derived from mammals such as humans, primates including monkeys, and rodents including mice and rats, but are not limited thereto. Specific examples of the biomarkers are shown in Table 1 below: [Table 1]

[0035] Biomarker detectable formulation As used herein, detecting a biomarker can mean determining the presence or absence and / or level (concentration) of a biomarker in a sample.

[0036] As used herein, the agent capable of detecting one or more biomarkers selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, PTGES, and their encoding genes (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20) selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, PTGES, and their encoding genes) can be selected from all small molecule compounds, proteins, and nucleic acid molecules capable of binding to the biomarkers.

[0037] In one example, the biomarker is one or more selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES (e.g., any one or more selected from the group (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 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 In the case of a protein (e.g., 1, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20), the detectable preparation of the biomarker is one or more selected from the group consisting of proteins that bind to the protein (e.g., antibodies, antigen-binding fragments of antibodies, antibody analogs containing antigen-binding fragments of antibodies, receptors, etc.), peptides, nucleic acid molecules (e.g., polynucleotides, oligonucleotides, etc.), and small molecule compounds (chemicals, small molecules), but is not limited to these.

[0038] In another example, the biomarker is one or more selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES-encoding genes (e.g., any one or more selected from the group (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 24 genes)). In the case of a gene (full-length DNA, cDNA, or mRNA) of a target gene (e.g., 13, 14, 15, 16, 17, 18, 19, or 20), the detectable preparation of the biomarker is one or more selected from the group consisting of nucleic acid molecules (oligonucleotides, polynucleotides, etc.; for example, primers, probes, aptamers, antisense oligonucleotides, etc.) that can bind to (or hybridize with) the gene, small molecule compounds, proteins, peptides, etc., but is not limited thereto.

[0039] The detectable preparation of the biomarker may be labeled with a conventional labeling substance such as a fluorescent substance, a chromogenic substance, a luminescent substance, a radioisotope, a heavy metal, or the like, or may be unlabeled.

[0040] In one example, the biomarker is one or more selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES (e.g., any one or more selected from the group (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 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 In the case of a protein (e.g., 1, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20), the detection of the biomarker can be carried out by a conventional protein detection (or measurement or analysis) method such as conventional enzyme reaction, fluorescence, luminescence, and / or radiodetection, and specifically, the detection can be carried out by a method selected from the group consisting of immunochromatography, immunohistochemical staining, enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (RIA), enzyme immunoassay (EIA), fluorescence immunoassay (FIA), luminescence immunoassay (LIA), Western blotting, microarray, flow cytometry, etc., but is not limited thereto.

[0041] In another example, when the biomarker is one or more genes (full-length DNA, cDNA, or mRNA) selected from the group consisting of genes encoding IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20) selected from the group, the biomarker can be detected using a conventional gene detection (or measurement or analysis) method. For example, the gene expression level can be measured using conventional gene analysis methods that use primers, probes, aptamers, or antisense oligonucleotides that can hybridize with the gene, specifically, polymerase chain reaction (PCR; e.g., qPCR, real-time PCR, real-timeq PCR, etc.), FISH (fluorescent in situ hybridization), Southern blotting, microarray, etc., but is not limited to these.

[0042] In one specific example, the primers may be a primer pair that can detect a gene fragment of 5 to 1000 bp, e.g., 10 to 500 bp, 20 to 200 bp, or 50 to 200 bp, from the base sequence of the gene (full-length DNA, cDNA, or mRNA), and that contains a base sequence that can hybridize (e.g., complementary to) a 5 to 100 bp, e.g., 5 to 50 bp, 5 to 30 bp, or 10 to 25 bp site at each of the 3'-end and 5'-end of the gene fragment. The probe, aptamer, or antisense oligonucleotide may have a total length of 5 to 1000 bp, 5 to 500 bp, 5 to 200 bp, 5 to 100 bp, 5 to 50 bp, 5 to 30 bp, or 5 to 25 bp, and may have a base sequence that is capable of binding to or hybridizing with a contiguous gene fragment of 5 to 1000 bp, 5 to 500 bp, 5 to 200 bp, 5 to 100 bp, 5 to 50 bp, 5 to 30 bp, or 5 to 25 bp within the base sequence of the marker gene (full-length DNA, cDNA, or mRNA). The term "capable of binding" means that it can bind to all or a part of the gene by a chemical and / or physical bond such as a covalent bond, and the term "capable of hybridization" means that it is capable of complementary binding by having 80% or more, for example, 90% or more, 95% or more, 98% or more, 99% or more, or 100% sequence complementarity with the base sequence of the gene site.

[0043] Biomarker detection As used herein, "detecting a biomarker" as explained above can mean determining the presence, absence, and / or level of said biomarker.

[0044] When the biomarker is a protein, the detection of the biomarker can be performed by a method selected from the group consisting of conventional protein detection methods, such as immunochromatography, immunohistochemical staining, enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (RIA), enzyme immunoassay (EIA), fluorescence immunoassay (FIA), luminescence immunoassay (LIA), Western blotting, microarray, and flow cytometry, but is not limited thereto.

[0045] When the biomarker is a gene, the detection of the biomarker is carried out by a method selected from the group consisting of a conventional gene detection method, for example, polymerase chain reaction (PCR; e.g., qPCR, real-time PCR, real-time qPCR, etc.), fluorescent in situ hybridization (FISH), Southern blotting, microarray method, etc., but is not limited thereto.

[0046] As used herein, "measurement of biomarker levels" can be performed by qualitatively and / or quantitatively analyzing the results obtained by the biomarker (protein and / or gene) detection methods described above.

[0047] In one example, when a labeled detection agent is used, the level of the biomarker is measured by, but is not limited to, a conventional qualitative analysis of the signal intensity obtained from the label (e.g., comparing the intensity (brightness) or area of ​​fluorescence and / or luminescence, the thickness and / or density of a gel electrophoresis band, etc., with a control sample), or a conventional quantitative analysis (e.g., quantifying the intensity (brightness) or area of ​​fluorescence and / or luminescence, the thickness and / or density of a gel electrophoresis band, etc.).

[0048] In another example, when a conventional polymerase chain reaction (PCR; e.g., qPCR, real-time PCR, real-time qPCR, etc.) is used, the level of the biomarker is measured by a conventional PCR quantification method, such as measuring the Ct (cycle threshold) value, ΔCt value (ΔCt = Ct (Gene) - Ct (Control gene)), and / or ΔΔCt value (ΔΔCt = ΔCt (Target gene) - ΔCt (Reference gene)), but is not limited thereto.

[0049] In yet another example, the measurement of the biomarker level may further include a step of performing a conventional statistical analysis on the quantified (quantified) biomarker level (e.g., Ct value, ΔCt value, and / or ΔΔCt value, etc., in the case of PCR). The term "statistical analysis" can be used to encompass all conventional statistical analysis means, such as various machine learning models and / or algorithms.

[0050] Examples of the statistical analysis include, but are not limited to, regression analysis (e.g., logistic regression analysis, stepwise logistic regression analysis, etc.), Ensemble, Decision Tree, Random Forest, Gradient Boosting, XGBoost, Light GBM (Light Gradient Boosting Machine), Gaussian Naive Bayes, SVM (Support Vector Machine), Bagging (Bootstrap Aggregating), Boosting, etc. For example, the statistical analysis can be performed by regression analysis (e.g., logistic regression analysis, stepwise logistic regression analysis, etc.), and if necessary, an appropriate statistical analysis (e.g., one or more selected from the statistical analysis methods described above) can be additionally performed.

[0051] Composition and kit for diagnosing pancreatic cancer The pancreatic cancer diagnostic compositions provided herein may comprise detectable preparations of the biomarkers described above.

[0052] The pancreatic cancer diagnostic kit (which may also be referred to as a biosensor) provided herein may include a detectable preparation of the biomarker described above or a pancreatic cancer diagnostic composition containing the same. In one example, the pancreatic cancer diagnostic kit may include the detectable preparation of the biomarker or the pancreatic cancer diagnostic composition containing the same in a conventional form such as a microarray or panel.

[0053] The pancreatic cancer diagnostic kit may further include a detection means. The detection means may be a means capable of qualitatively and / or quantitatively analyzing the presence or absence and / or level of a biomarker detected by a biomarker detectable preparation. In one example, the detection means may be selected from the means used in the protein and / or gene detection methods described above.

[0054] In one example, the kit is, but is not limited to, an RT-PCR kit, a DNA chip kit, an ELISA kit, a protein chip kit, a rapid kit, or an MRM (Multiple reaction monitoring) kit.

[0055] In one embodiment, the pancreatic cancer diagnostic composition and / or kit may comprise a detectable preparation of one or more genes selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES (e.g., any one or more genes selected from the group (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20)); their encoding genes; or a combination thereof. In this case, the diagnosable pancreatic cancer may be early-stage pancreatic cancer, late-stage pancreatic cancer, or all of these.

[0056] In one example, the composition and / or kit for diagnosing pancreatic cancer comprises one or more proteins selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, PTGES, IFNB1, and IFNA1 (e.g., any one or more proteins selected from the group (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 proteins) )) or one or more selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, or 18) selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES); their encoding genes; or a combination thereof. In this case, the pancreatic cancer that can be diagnosed may be early-stage pancreatic cancer, late-stage pancreatic cancer, or all of these.

[0057] In one embodiment, the pancreatic cancer diagnostic composition and / or kit may comprise a detectable preparation of one or more biomarkers selected from the following: one or more selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20) selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA), genes encoding same, or combinations thereof; One or more selected from the group consisting of SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2, and PTGS2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of IFNG, SLC27A2, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4, and IFNB1 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13) selected from the group), genes encoding same, or combinations thereof; One or more selected from the group consisting of SLC27A2, IFNG, CCL2, TNF, PTGES, FOXP3, PTGES2, CXCR4, and CXCR2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of IFNL1, IFNG, CXCL11, CCL2, PTGES2, SLC27A2, and PTGES (e.g., any one or more (two, three, four, five, six, or seven) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF, and FOXP3 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), their encoding genes, or combinations thereof; one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12) selected from the group), their encoding genes, or combinations thereof; one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, or 8) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13) selected from the group); their encoding genes; or a combination thereof; One or more selected from the group consisting of TNF, IFNG, CCL2, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES (e.g., any one or more (2, 3, 4, 5, 6, 7, or 8) selected from the group); their encoding genes; or a combination thereof; One or more selected from the group consisting of VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2, and CXCL8 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, or 11) selected from the group), their encoding genes, or combinations thereof; one or more selected from the group consisting of PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, IFNL1, and SLC27A2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15) selected from the group), genes encoding same, or combinations thereof; One or more selected from the group consisting of VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCR2, FOXP3, PTGS2, and CXCL8 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, and PTGES2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14) selected from the group), genes encoding same, or combinations thereof; a detectable preparation of one or more selected from the group consisting of CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF, and VEGFA (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A, and ARG1 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12) selected from the group), their encoding genes, or combinations thereof; one or more selected from the group consisting of IFNG, PTGES2, CCL5, SLC27A2, VEGFA, CCL2, TNF, FOXP3, CXCR4, IFNA1, IFNL1, PTGES, CCR5, CLEC7A, IFNB1, CXCR2, and PTGS2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17) selected from the group), genes encoding same, or combinations thereof; One or more selected from the group consisting of SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, and CLEC7A (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group), their encoding genes, or combinations thereof; one or more selected from the group consisting of IFNG, CCL2, and PTGES2 (e.g., one, two, or three selected from the group), their encoding genes, or a combination thereof; One or more selected from the group consisting of ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4, and CCL5 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, SLC27A2, and PTGES2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, or 11) selected from the group), their encoding genes, or combinations thereof; and One or more selected from the group consisting of IFNG, VEGFA, SLC27A2, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2, and CXCL11 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group), their encoding genes, or combinations thereof. For example, the pancreatic cancer diagnostic composition and / or kit may comprise a biomarker set selected from the following; its encoding genes; or detectable preparations of a combination thereof: ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA; SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2, and PTGS2; IFNG, SLC27A2, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4, and IFNB1; SLC27A2, IFNG, CCL2, TNF, PTGES, FOXP3, PTGES2, CXCR4, and CXCR2; IFNL1, IFNG, CXCL11, CCL2, PTGES2, SLC27A2, and PTGES; ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF, and FOXP3; CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3; CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11; CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF; TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES; TNF, IFNG, CCL2, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES; VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2, and CXCL8; PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, IFNL1, and SLC27A2; VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCR2, FOXP3, PTGS2, and CXCL8; IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, and PTGES2; CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF, and VEGFA; SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A, and ARG1; IFNG, PTGES2, CCL5, SLC27A2, VEGFA, CCL2, TNF, FOXP3, CXCR4, IFNA1, IFNL1, PTGES, CCR5, CLEC7A, IFNB1, CXCR2, and PTGS2; SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, and CLEC7A; IFNG, CCL2, and PTGES2; ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4, and CCL5; TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, SLC27A2, and PTGES2; and IFNG, VEGFA, SLC27A2, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2, and CXCL11.

[0058] More specifically, the pancreatic cancer diagnostic composition and / or kit may comprise a detectable preparation of one or more genes selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES (e.g., any one or more genes (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20) selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES); their encoding genes; or a combination thereof. In this case, the diagnosable pancreatic cancer may be early-stage pancreatic cancer. In one embodiment, the pancreatic cancer diagnostic composition and / or kit is for diagnosing early stage pancreatic cancer, (1-1) A detectable preparation of one or more selected from the group consisting of SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2, and PTGS2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13) selected from the group), its encoding gene, or a combination thereof; (1-2) A detectable preparation of one or more selected from the group consisting of IFNG, SLC27A2, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4, and IFNB1 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13) selected from the group), its encoding gene, or a combination thereof; (1-3) A detectable preparation of one or more selected from the group consisting of SLC27A2, IFNG, CCL2, TNF, PTGES, FOXP3, PTGES2, CXCR4, and CXCR2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), its encoding gene, or a combination thereof; (1-4) A detectable preparation of one or more selected from the group consisting of IFNL1, IFNG, CXCL11, CCL2, PTGES2, SLC27A2, and PTGES (e.g., any one or more (2, 3, 4, 5, 6, or 7) selected from the group), its encoding gene, or a combination thereof; (1-5) A detectable preparation of one or more selected from the group consisting of ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF, and FOXP3 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), its encoding gene, or a combination thereof; (1-6) A detectable preparation of one or more selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20) selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA), a coding gene thereof, or a combination thereof; (1-7) A detectable preparation of one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12) selected from the group), its encoding gene, or a combination thereof; (1-8) A detectable preparation of one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15) selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11), a coding gene thereof, or a combination thereof; (1-9) A detectable preparation of one or more selected from the group consisting of CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, or 8) selected from the group), a coding gene thereof, or a combination thereof; (1-10) One or more selected from the group consisting of TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13) selected from the group consisting of TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES); a coding gene thereof; or a detectable preparation of a combination thereof; and (1-11) One or more selected from the group consisting of TNF, IFNG, CCL2, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES (e.g., any one or more (2, 3, 4, 5, 6, 7, or 8) selected from the group); their encoding genes; or a detectable preparation of a combination thereof. The composition may contain one or more selected from the group consisting of:

[0059] For example, the pancreatic cancer diagnostic composition and / or kit may comprise a detectable preparation of a biomarker set selected from the following: a set of biomarkers; its encoding genes; or a combination thereof. In this case, the diagnosable pancreatic cancer may be early-stage pancreatic cancer: ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA; SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2, and PTGS2; IFNG, SLC27A2, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4, and IFNB1; SLC27A2, IFNG, CCL2, TNF, PTGES, FOXP3, PTGES2, CXCR4, and CXCR2; IFNL1, IFNG, CXCL11, CCL2, PTGES2, SLC27A2, and PTGES; ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF, and FOXP3; CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3; CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11; CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF; TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES; and TNF, IFNG, CCL2, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES.

[0060] In another embodiment, the pancreatic cancer diagnostic composition and / or kit may comprise a detectable preparation of one or more genes selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, or 18) selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES); their encoding genes; or a combination thereof. In this case, the diagnosable pancreatic cancer may be late-stage pancreatic cancer.

[0061] In one embodiment, the pancreatic cancer diagnostic composition and / or kit is for diagnosing late-stage pancreatic cancer, (2-1) A detectable preparation of one or more selected from the group consisting of VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2, and CXCL8 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, or 11) selected from the group), its encoding gene, or a combination thereof; (2-2) A detectable preparation of one or more selected from the group consisting of PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, IFNL1, and SLC27A2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15) selected from the group), its encoding gene, or a combination thereof; (2-3) A detectable preparation of one or more selected from the group consisting of VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCR2, FOXP3, PTGS2, and CXCL8 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group), its encoding gene, or a combination thereof; (2-4) A detectable preparation of one or more selected from the group consisting of IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, and PTGES2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14) selected from the group), its encoding gene, or a combination thereof; (2-5) A detectable preparation of one or more selected from the group consisting of CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF, and VEGFA (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), a coding gene thereof, or a combination thereof; (2-6) A detectable preparation of one or more selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20) selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA), a coding gene thereof, or a combination thereof; (2-7) A detectable preparation of one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12) selected from the group), its encoding gene, or a combination thereof; (2-8) one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15) selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11), a detectable preparation of a coding gene thereof, or a combination thereof; and (2-9) A detectable preparation of one or more selected from the group consisting of CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, or 8) selected from the group), its encoding gene, or a combination thereof. The composition may contain one or more selected from the group consisting of:

[0062] For example, the pancreatic cancer diagnostic composition and / or kit may comprise a detectable preparation of a biomarker set selected from the following: a set of biomarkers; its encoding genes; or a combination thereof. In this case, the diagnosable pancreatic cancer may be late-stage pancreatic cancer: ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA; VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2, and CXCL8; PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, IFNL1, and SLC27A2; VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCR2, FOXP3, PTGS2, and CXCL8; IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, and PTGES2; CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF, and VEGFA; CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3; CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11; and CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF.

[0063] In another embodiment, the pancreatic cancer diagnostic composition and / or kit may comprise a detectable preparation of one or more genes selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES (e.g., any one or more genes (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20) selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES); their encoding genes; or a combination thereof. In this case, the diagnosable pancreatic cancer may be any stage of pancreatic cancer, regardless of the progression stage, for example, early stage pancreatic cancer, late stage pancreatic cancer, or all of these.

[0064] In one embodiment, the pancreatic cancer diagnostic composition and / or kit is for diagnosing pancreatic cancer at all stages, (3-1) A detectable preparation of one or more selected from the group consisting of SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A, and ARG1 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12) selected from the group), its encoding gene, or a combination thereof; (3-2) A detectable preparation of one or more selected from the group consisting of IFNG, PTGES2, CCL5, SLC27A2, VEGFA, CCL2, TNF, FOXP3, CXCR4, IFNA1, IFNL1, PTGES, CCR5, CLEC7A, IFNB1, CXCR2, and PTGS2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17) selected from the group consisting of IFNG, PTGES2, CCL5, SLC27A2, VEGFA, CCL2, TNF, FOXP3, CXCR4, IFNA1, IFNL1, PTGES, CCR5, CLEC7A, IFNB1, CXCR2, and PTGS2), a coding gene thereof, or a combination thereof; (3-3) A detectable preparation of one or more selected from the group consisting of SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, and CLEC7A (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group), a coding gene thereof, or a combination thereof; (3-4) A detectable preparation of one or more selected from the group consisting of IFNG, CCL2, and PTGES2 (e.g., one, two, or three selected from the group), their encoding genes, or a combination thereof; (3-5) A detectable preparation of one or more selected from the group consisting of ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4, and CCL5 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), its encoding gene, or a combination thereof; (3-6) A detectable preparation of one or more selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20) selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA), a coding gene thereof, or a combination thereof; (3-7) A detectable preparation of one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12) selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3), a coding gene thereof, or a combination thereof; (3-8) A detectable preparation of one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15) selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11), a coding gene thereof, or a combination thereof; (3-9) A detectable preparation of one or more selected from the group consisting of CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, or 8) selected from the group), a coding gene thereof, or a combination thereof; (3-10) A detectable preparation of one or more selected from the group consisting of TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, SLC27A2, and PTGES2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, or 11) selected from the group), their encoding genes, or combinations thereof; or (3-11) A detectable preparation of one or more selected from the group consisting of IFNG, VEGFA, SLC27A2, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2, and CXCL11 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group), their encoding genes, or a combination thereof. In this case, the diagnosable pancreatic cancer may be pancreatic cancer at any stage regardless of the progression stage, for example, early stage pancreatic cancer, late stage pancreatic cancer, or both.

[0065] For example, the pancreatic cancer diagnostic composition and / or kit may comprise a detectable preparation of a biomarker set selected from the following: a set of biomarkers; its encoding genes; or a combination thereof, wherein the diagnosable pancreatic cancer is pancreatic cancer at any stage regardless of progression, for example, early stage pancreatic cancer, late stage pancreatic cancer, or all of these: ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA; SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A, and ARG1; IFNG, PTGES2, CCL5, SLC27A2, VEGFA, CCL2, TNF, FOXP3, CXCR4, IFNA1, IFNL1, PTGES, CCR5, CLEC7A, IFNB1, CXCR2, and PTGS2; SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, and CLEC7A; IFNG, CCL2, and PTGES2; ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4, and CCL5; CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3; CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11; CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF; TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, SLC27A2, and PTGES2; and IFNG, VEGFA, SLC27A2, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2, and CXCL11.

[0066] In another specific example, the pancreatic cancer diagnostic composition and / or kit may comprise a detectable preparation of one or more (one or two) selected from the group consisting of IFNB1 and IFNA1, their encoding genes, or a combination thereof. In this case, the diagnostic composition and / or kit may be capable of distinguishing pancreatic cancer (e.g., early-stage pancreatic cancer and / or late-stage pancreatic cancer) from similar diseases (e.g., positive pancreatic diseases (other pancreatic diseases (pancreatitis (chronic pancreatitis and / or acute pancreatitis)), pancreatic positive tumors, intraductal papillary mucinous neoplasms (IPMN), autoimmune pancreatitis (AIP) (pancreatic diseases excluding pancreatic cancer (pancreatic malignant tumors))), biliary tract cancer, etc.).

[0067] Pancreatic cancer diagnosis method The compositions and methods for diagnosing pancreatic cancer (or methods that provide information for diagnosis) provided herein can include detecting one or more biomarkers selected from the group consisting of the biomarkers described above, i.e., IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20) selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES) and their encoding genes, from a blood sample isolated from a subject.

[0068] In one embodiment, the biomarkers may include one or more selected from the following: one or more selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20) selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA), genes encoding same, or combinations thereof; one or more selected from the group consisting of SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2, and PTGS2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of IFNG, SLC27A2, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4, and IFNB1 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13) selected from the group), genes encoding same, or combinations thereof; One or more selected from the group consisting of SLC27A2, IFNG, CCL2, TNF, PTGES, FOXP3, PTGES2, CXCR4, and CXCR2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of IFNL1, IFNG, CXCL11, CCL2, PTGES2, SLC27A2, and PTGES (e.g., any one or more (two, three, four, five, six, or seven) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF, and FOXP3 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), their encoding genes, or combinations thereof; one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12) selected from the group), their encoding genes, or combinations thereof; one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, or 8) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13) selected from the group); their encoding genes; or a combination thereof; One or more selected from the group consisting of TNF, IFNG, CCL2, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES (e.g., any one or more (2, 3, 4, 5, 6, 7, or 8) selected from the group); their encoding genes; or a combination thereof; One or more selected from the group consisting of VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2, and CXCL8 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, or 11) selected from the group), their encoding genes, or combinations thereof; one or more selected from the group consisting of PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, IFNL1, and SLC27A2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15) selected from the group), genes encoding same, or combinations thereof; One or more selected from the group consisting of VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCR2, FOXP3, PTGS2, and CXCL8 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, and PTGES2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14) selected from the group), genes encoding same, or combinations thereof; a detectable preparation of one or more selected from the group consisting of CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF, and VEGFA (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A, and ARG1 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12) selected from the group), genes encoding same, or combinations thereof; one or more selected from the group consisting of IFNG, PTGES2, CCL5, SLC27A2, VEGFA, CCL2, TNF, FOXP3, CXCR4, IFNA1, IFNL1, PTGES, CCR5, CLEC7A, IFNB1, CXCR2, and PTGS2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17) selected from the group), genes encoding same, or combinations thereof; One or more selected from the group consisting of SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, and CLEC7A (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group), their encoding genes, or combinations thereof; one or more selected from the group consisting of IFNG, CCL2, and PTGES2 (e.g., one, two, or three selected from the group), their encoding genes, or a combination thereof; One or more selected from the group consisting of ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4, and CCL5 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, SLC27A2, and PTGES2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, or 11) selected from the group), their encoding genes, or combinations thereof; and One or more selected from the group consisting of IFNG, VEGFA, SLC27A2, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2, and CXCL11 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group), their encoding genes, or combinations thereof.

[0069] For example, the biomarkers may be a set of biomarkers selected from the following; their encoding genes; or a combination thereof: ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA; SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2, and PTGS2; IFNG, SLC27A2, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4, and IFNB1; SLC27A2, IFNG, CCL2, TNF, PTGES, FOXP3, PTGES2, CXCR4, and CXCR2; IFNL1, IFNG, CXCL11, CCL2, PTGES2, SLC27A2, and PTGES; ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF, and FOXP3; CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3; CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11; CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF; TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES; TNF, IFNG, CCL2, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES; VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2, and CXCL8; PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, IFNL1, and SLC27A2; VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCR2, FOXP3, PTGS2, and CXCL8; IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, and PTGES2; CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF, and VEGFA; SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A, and ARG1; IFNG, PTGES2, CCL5, SLC27A2, VEGFA, CCL2, TNF, FOXP3, CXCR4, IFNA1, IFNL1, PTGES, CCR5, CLEC7A, IFNB1, CXCR2, and PTGS2; SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, and CLEC7A; IFNG, CCL2, and PTGES2; ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4, and CCL5; TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, SLC27A2, and PTGES2; and IFNG, VEGFA, SLC27A2, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2, and CXCL11.

[0070] More specifically, the biomarkers may include one or more selected from the following, and the diagnosable pancreatic cancer may be early stage pancreatic cancer: one or more selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20) selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA), genes encoding same, or combinations thereof; one or more selected from the group consisting of SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2, and PTGS2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of IFNG, SLC27A2, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4, and IFNB1 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13) selected from the group), genes encoding same, or combinations thereof; One or more selected from the group consisting of SLC27A2, IFNG, CCL2, TNF, PTGES, FOXP3, PTGES2, CXCR4, and CXCR2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of IFNL1, IFNG, CXCL11, CCL2, PTGES2, SLC27A2, and PTGES (e.g., any one or more (two, three, four, five, six, or seven) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF, and FOXP3 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), their encoding genes, or combinations thereof; one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12) selected from the group), their encoding genes, or combinations thereof; one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, or 8) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13) selected from the group); a gene encoding the same; or a combination thereof; and One or more selected from the group consisting of TNF, IFNG, CCL2, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES (e.g., any one or more (2, 3, 4, 5, 6, 7, or 8) selected from the group); their encoding genes; or a combination thereof.

[0071] More specifically, for example, the biomarkers may be a biomarker set selected from the following; their encoding genes; or a combination thereof, and in this case, the diagnosable pancreatic cancer may be early-stage pancreatic cancer: ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA; SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2, and PTGS2; IFNG, SLC27A2, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4, and IFNB1; SLC27A2, IFNG, CCL2, TNF, PTGES, FOXP3, PTGES2, CXCR4, and CXCR2; IFNL1, IFNG, CXCL11, CCL2, PTGES2, SLC27A2, and PTGES; ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF, and FOXP3; CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3; CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11; CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF; TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES; and TNF, IFNG, CCL2, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES.

[0072] In another embodiment, the biomarkers may include one or more selected from the following, and the diagnosable pancreatic cancer may be late-stage pancreatic cancer: one or more selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20) selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA), genes encoding same, or combinations thereof; One or more selected from the group consisting of VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2, and CXCL8 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, or 11) selected from the group), genes encoding same, or combinations thereof; one or more selected from the group consisting of PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, IFNL1, and SLC27A2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15) selected from the group), genes encoding same, or combinations thereof; One or more selected from the group consisting of VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCR2, FOXP3, PTGS2, and CXCL8 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, and PTGES2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14) selected from the group), genes encoding same, or combinations thereof; a detectable preparation of one or more selected from the group consisting of CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF, and VEGFA (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), their encoding genes, or combinations thereof; one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12) selected from the group), their encoding genes, or combinations thereof; one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15) selected from the group), their encoding genes, or combinations thereof; and One or more selected from the group consisting of CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, or 8) selected from the group), their encoding genes, or combinations thereof.

[0073] For example, the biomarkers may be a biomarker set selected from the following; their encoding genes; or a combination thereof, and the diagnosable pancreatic cancer may be late-stage pancreatic cancer: ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA; VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2, and CXCL8; PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, IFNL1, and SLC27A2; VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCR2, FOXP3, PTGS2, and CXCL8; IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, and PTGES2; CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF, and VEGFA; CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3; CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11; and CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF.

[0074] In another embodiment, the biomarker may include one or more selected from the following, wherein the diagnosable pancreatic cancer is pancreatic cancer at any stage, regardless of progression stage, for example, early stage pancreatic cancer, late stage pancreatic cancer, or all of these: one or more selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20) selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA), genes encoding same, or combinations thereof; One or more selected from the group consisting of SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A, and ARG1 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12) selected from the group), genes encoding same, or combinations thereof; one or more selected from the group consisting of IFNG, PTGES2, CCL5, SLC27A2, VEGFA, CCL2, TNF, FOXP3, CXCR4, IFNA1, IFNL1, PTGES, CCR5, CLEC7A, IFNB1, CXCR2, and PTGS2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17) selected from the group), genes encoding same, or combinations thereof; One or more selected from the group consisting of SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, and CLEC7A (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group), their encoding genes, or combinations thereof; one or more selected from the group consisting of IFNG, CCL2, and PTGES2 (e.g., one, two, or three selected from the group), their encoding genes, or a combination thereof; One or more selected from the group consisting of ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4, and CCL5 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), their encoding genes, or combinations thereof; one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12) selected from the group), their encoding genes, or combinations thereof; one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, or 8) selected from the group), their encoding genes, or combinations thereof; One or more selected from the group consisting of TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, SLC27A2, and PTGES2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, or 11) selected from the group), their encoding genes, or combinations thereof; and One or more selected from the group consisting of IFNG, VEGFA, SLC27A2, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2, and CXCL11 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group), their encoding genes, or combinations thereof.

[0075] For example, the biomarkers may be a biomarker set selected from the following; its encoding genes; or a combination thereof, and the diagnosable pancreatic cancer is pancreatic cancer at any stage regardless of progression stage, for example, early stage pancreatic cancer, late stage pancreatic cancer, or all of these: ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA; SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A, and ARG1; IFNG, PTGES2, CCL5, SLC27A2, VEGFA, CCL2, TNF, FOXP3, CXCR4, IFNA1, IFNL1, PTGES, CCR5, CLEC7A, IFNB1, CXCR2, and PTGS2; SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, and CLEC7A; IFNG, CCL2, and PTGES2; ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4, and CCL5; CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3; CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11; CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF; TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, SLC27A2, and PTGES2; and IFNG, VEGFA, SLC27A2, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2, and CXCL11.

[0076] In the method, the step of detecting the biomarker may be a step of confirming the presence or absence of the biomarker in the sample, measuring the level (concentration) of the biomarker, or both. In the method, if the biomarker is present in the sample at a higher and / or lower level than a comparison sample (e.g., a normal sample, a sample with a similar disease, etc.), the sample or the subject from which the sample was derived can be diagnosed (or confirmed or determined) as a pancreatic cancer patient. The diagnosis of a pancreatic cancer patient may confirm or determine that the patient is a pancreatic cancer patient and / or distinguish the pancreatic cancer patient from patients with a similar disease. The pancreatic cancer may mean early stage pancreatic cancer, late stage pancreatic cancer, or all of these, the normal individual may mean an individual who does not have pancreatic cancer (early stage pancreatic cancer, late stage pancreatic cancer, or all of these), and the similar disease may mean positive pancreatic diseases (pancreatitis (chronic pancreatitis and / or acute pancreatitis), pancreatic positive tumors, intraductal papillary mucinous neoplasms (IPMN), autoimmune pancreatitis (AIP), and other pancreatic diseases (pancreatic diseases excluding pancreatic cancer (pancreatic malignant tumors))) and / or biliary tract cancer.

[0077] In one example, the methods of diagnosing or informing pancreatic cancer diagnosis provided herein include: (a) detecting one or more of the biomarkers described above in a blood sample isolated from the subject; and (b) diagnosing (or confirming or determining) the sample or the subject from which the sample was derived as having pancreatic cancer (early stage pancreatic cancer, late stage pancreatic cancer, or all of these) if the biomarkers are present in the blood sample at higher and / or lower levels than in a comparison sample (e.g., a normal sample, a sample with a similar disease, etc.). may include:

[0078] Step (b) can include one or more (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20) steps selected from the following: - if the level of IFNL1, its encoding gene, or a combination thereof in said blood sample is higher (increased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) said sample or the subject from whom said sample was derived as a pancreatic cancer patient, for example, a patient with early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer regardless of stage (early stage pancreatic cancer and / or late stage pancreatic cancer); - if the level of IFNG, its encoding gene, or a combination thereof in said blood sample is lower (decreased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) said sample or the subject from whom said sample was derived as a pancreatic cancer patient, for example, a patient with early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer regardless of stage (early stage pancreatic cancer and / or late stage pancreatic cancer); - if the level of CXCL11, its encoding gene, or a combination thereof in the blood sample is higher (increased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) the sample or the subject from which the sample was derived as a pancreatic cancer patient, e.g., an early stage pancreatic cancer patient, and / or if the level is lower (decreased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) the sample or the subject from which the sample was derived as a pancreatic cancer patient, e.g., a late stage pancreatic cancer patient; - if the level of TNF, its encoding gene, or a combination thereof in said blood sample is higher (increased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) said sample or the subject from whom said sample was derived as a pancreatic cancer patient, for example, a patient with early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer regardless of stage (early stage pancreatic cancer and / or late stage pancreatic cancer); - if the level of CLEC7A, its encoding gene, or a combination thereof in the blood sample is lower (decreased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) the sample or the subject from which the sample was derived as a pancreatic cancer patient, e.g., an early stage pancreatic cancer patient, and / or if the level of CLEC7A, its encoding gene, or a combination thereof in the blood sample is higher (increased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) the sample or the subject from which the sample was derived as a pancreatic cancer patient, e.g., a late stage pancreatic cancer patient; - if the level of CXCL8, its encoding gene, or a combination thereof in said blood sample is higher (increased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) said sample or the subject from whom said sample was derived as a pancreatic cancer patient, for example, a patient with early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer regardless of stage (early stage pancreatic cancer and / or late stage pancreatic cancer); - if the level of FOXP3, its encoding gene, or a combination thereof in the blood sample is higher (increased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) the sample or the subject from which the sample was derived as a pancreatic cancer patient, e.g., an early stage pancreatic cancer patient, and / or if the level is lower (decreased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) the sample or the subject from which the sample was derived as a pancreatic cancer patient, e.g., a late stage pancreatic cancer patient; - if the level of VEGFA, its encoding gene, or a combination thereof in said blood sample is higher (increased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) said sample or the subject from whom said sample was derived as a pancreatic cancer patient, for example, a patient with early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer regardless of stage (early stage pancreatic cancer and / or late stage pancreatic cancer); - if the level of CCL2, its encoding gene, or a combination thereof in said blood sample is higher (increased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) said sample or the subject from whom said sample was derived as a pancreatic cancer patient, for example, a patient with early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer regardless of stage (early stage pancreatic cancer and / or late stage pancreatic cancer); - if the level of CCL5, its encoding gene, or a combination thereof in said blood sample is lower (decreased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) said sample or the subject from whom said sample was derived as a pancreatic cancer patient, for example, a patient with early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer regardless of stage (early stage pancreatic cancer and / or late stage pancreatic cancer); - if the level of CCR5, its encoding gene, or a combination thereof in the blood sample is higher (increased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) the sample or the subject from which the sample was derived as a pancreatic cancer patient, e.g., an early stage pancreatic cancer patient, and / or if the level is lower (decreased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) the sample or the subject from which the sample was derived as a pancreatic cancer patient, e.g., a late stage pancreatic cancer patient; - if the level of CXCR4, its encoding gene, or a combination thereof in said blood sample is higher (increased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) said sample or the subject from whom said sample was derived as a pancreatic cancer patient, for example, a patient with early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer regardless of stage (early stage pancreatic cancer and / or late stage pancreatic cancer); - if the level of ARG1, its encoding gene, or a combination thereof in said blood sample is higher (increased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) said sample or the subject from whom said sample was derived as a pancreatic cancer patient, for example, a patient with early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer regardless of stage (early stage pancreatic cancer and / or late stage pancreatic cancer); - if the level of CXCR2, its encoding gene, or a combination thereof in the blood sample is lower (decreased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) the sample or the subject from which the sample was derived as a pancreatic cancer patient, e.g., an early stage pancreatic cancer patient, and / or if the level of CXCR2, its encoding gene, or a combination thereof in the blood sample is higher (increased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) the sample or the subject from which the sample was derived as a pancreatic cancer patient, e.g., a late stage pancreatic cancer patient; - if the level of PTGS2, its encoding gene, or a combination thereof in said blood sample is higher (increased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) said sample or the subject from whom said sample was derived as a pancreatic cancer patient, for example, a patient with early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer regardless of stage (early stage pancreatic cancer and / or late stage pancreatic cancer); - if the level of PTGES2, its encoding gene, or a combination thereof in said blood sample is lower (decreased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) said sample or the subject from whom said sample was derived as a pancreatic cancer patient, for example, a patient with early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer regardless of stage (early stage pancreatic cancer and / or late stage pancreatic cancer); - if the level of SLC27A2, its encoding gene, or a combination thereof in said blood sample is higher (increased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) said sample or the subject from whom said sample was derived as a pancreatic cancer patient, for example, a patient with early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer regardless of stage (early stage pancreatic cancer and / or late stage pancreatic cancer); - if the level of PTGES, its encoding gene, or a combination thereof in said blood sample is higher (increased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) said sample or the subject from whom said sample was derived as a pancreatic cancer patient, for example, a patient with early stage pancreatic cancer, late stage pancreatic cancer, or all pancreatic cancer regardless of stage (early stage pancreatic cancer and / or late stage pancreatic cancer); - diagnosing (or confirming or determining) the sample or the subject from whom the sample was derived as a pancreatic cancer patient if the level of IFNB1, its encoding gene, or a combination thereof in the blood sample is lower (decreased) than in a comparison sample (e.g., a sample with a similar disease); and - If the level of IFNA1, its encoding gene, or a combination thereof in the blood sample is lower (decreased) than in a comparison sample (e.g., a sample with a similar disease), diagnosing (or confirming or determining) the sample or the subject from which the sample was derived as a pancreatic cancer patient. More specifically, the method may be a method for diagnosing early stage pancreatic cancer or a method for providing information on early stage pancreatic cancer diagnosis, comprising the steps of: (a) detecting, from a blood sample isolated from a subject, one or more genes selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20) selected from the group consisting of: IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES); their encoding genes; or a combination thereof.

[0079] More specifically, the method for diagnosing or providing information on early stage pancreatic cancer diagnosis may comprise detecting a marker selected from the following: (1-1) One or more selected from the group consisting of SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2, and PTGS2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13) selected from the group) (e.g., one or more (1, 2, 3, 4, 5, 6, 7, 8, or 9) selected from the group consisting of ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF, and FOXP3), a coding gene thereof, or a combination thereof; (1-2) one or more selected from the group consisting of IFNG, SLC27A2, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4, and IFNB1 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13) selected from the group), their encoding genes, or combinations thereof; (1-3) one or more selected from the group consisting of SLC27A2, IFNG, CCL2, TNF, PTGES, FOXP3, PTGES2, CXCR4, and CXCR2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), their encoding genes, or combinations thereof; (1-4) one or more selected from the group consisting of IFNL1, IFNG, CXCL11, CCL2, PTGES2, SLC27A2, and PTGES (e.g., any one or more (e.g., 2, 3, 4, 5, 6, or 7) selected from the group), their encoding genes, or combinations thereof; (1-5) one or more selected from the group consisting of ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF, and FOXP3 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), their encoding genes, or combinations thereof; (1-6) one or more selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20) selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA), a coding gene thereof, or a combination thereof; (1-7) one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12) selected from the group), their encoding genes, or combinations thereof; (1-8) one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15) selected from the group), their encoding genes, or combinations thereof; and (1-9) One or more selected from the group consisting of CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, or 8) selected from the group), genes encoding the same, or combinations thereof.

[0080] The method for diagnosing early stage pancreatic cancer or the method for providing information on early stage pancreatic cancer diagnosis may further comprise the steps of: (b) in the blood sample, - diagnosing (or confirming or determining) the sample or the subject from which the sample was derived as a pancreatic cancer patient, more particularly an early stage pancreatic cancer patient, if the level of one or more selected from the group consisting of IFNL1, CXCL11, TNF, CXCL8, FOXP3, VEGFA, CCL2, CCR5, CXCR4, ARG1, PTGS2, SLC27A2, and PTGES (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, or 11) selected from the group consisting of IFNL1, CXCL11, TNF, CXCL8, FOXP3, VEGFA, CCL2, CCR5, CXCR4, ARG1, PTGS2, SLC27A2, and PTGES), their encoding genes, or a combination thereof, is higher (increased) than that of a comparison sample (e.g., a normal sample); and / or - If the levels of one or more (e.g., one, two, three, four, or five) selected from the group consisting of IFNG, CLEC7A, CCL5, CXCR2, and PTGES2, their encoding genes, or a combination thereof, are lower (decreased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) the sample or the subject from which the sample was derived as a pancreatic cancer patient, more specifically, an early stage pancreatic cancer patient.

[0081] In another embodiment, the method may be a method for diagnosing or providing information on the diagnosis of late stage pancreatic cancer, comprising the steps of: (a) detecting, from a blood sample isolated from a subject, one or more genes selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, or 18) selected from the group consisting of: IFNL1, IFNG, CXCL11, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES); their encoding genes; or a combination thereof.

[0082] More specifically, the method for diagnosing or providing information on the diagnosis of late stage pancreatic cancer may comprise detecting a marker selected from the following: (2-1) one or more selected from the group consisting of VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2, and CXCL8 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, or 11) selected from the group) (e.g., one or more (1, 2, 3, 4, 5, 6, 7, 8, or 9) selected from the group consisting of CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF, and VEGFA), a gene encoding the same, or a combination thereof; (2-2) one or more selected from the group consisting of PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, IFNL1, and SLC27A2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15) selected from the group), genes encoding same, or combinations thereof; (2-3) one or more selected from the group consisting of VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCR2, FOXP3, PTGS2, and CXCL8 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group), their encoding genes, or combinations thereof; or (2-4) one or more selected from the group consisting of IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, and PTGES2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14) selected from the group), their encoding genes, or combinations thereof; (2-5) one or more selected from the group consisting of CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF, and VEGFA (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), their encoding genes, or combinations thereof; (2-6) one or more selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20) selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA), a coding gene thereof, or a combination thereof; (2-7) one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12) selected from the group), their encoding genes, or combinations thereof; (2-8) one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15) selected from the group), their encoding genes, or combinations thereof; or (2-9) One or more selected from the group consisting of CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, or 8) selected from the group), genes encoding the same, or combinations thereof.

[0083] The method for diagnosing late-stage pancreatic cancer or the method for providing information on the diagnosis of late-stage pancreatic cancer may further comprise the steps of: (b) in the blood sample, - diagnosing (or confirming or determining) the sample or the subject from which the sample was derived as a pancreatic cancer patient, more specifically a late-stage pancreatic cancer patient, if the level of one or more selected from the group consisting of IFNL1, TNF, CLEC7A, CXCL8, VEGFA, CCL2, CXCR4, ARG1, CXCR2, PTGS2, SLC27A2, and PTGES (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12) selected from the group consisting of IFNL1, TNF, CLEC7A, CXCL8, VEGFA, CCL2, CXCR4, ARG1, CXCR2, PTGS2, SLC27A2, and PTGES), their encoding genes, or a combination thereof, is higher (increased) than that of a comparison sample (e.g., a normal sample); and / or - If the level of one or more genes selected from the group consisting of IFNG, CXCL11, FOXP3, CCL5, CCR5, and PTGES2 (e.g., any one or more (e.g., 2, 3, 4, 5, or 6) selected from the group), their encoding genes, or a combination thereof, is lower (decreased) than that of a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) the sample or the subject from which the sample was derived as a pancreatic cancer patient, more specifically, a late-stage pancreatic cancer patient.

[0084] In another embodiment, the method may be a method for diagnosing or providing information on the diagnosis of all pancreatic cancers (early stage pancreatic cancer and / or late stage pancreatic cancer) comprising the steps of: (a) detecting, from a blood sample isolated from a subject, one or more genes selected from the group consisting of IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20) selected from the group consisting of: IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES); their encoding genes; or a combination thereof.

[0085] More specifically, the method for diagnosing or providing information on the diagnosis of all pancreatic cancer (early stage pancreatic cancer and / or late stage pancreatic cancer) may comprise detecting a marker selected from the following: (3-1) one or more selected from the group consisting of SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A, and ARG1 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12) selected from the group), a coding gene thereof, or a combination thereof; (3-2) one or more selected from the group consisting of IFNG, PTGES2, CCL5, SLC27A2, VEGFA, CCL2, TNF, FOXP3, CXCR4, IFNA1, IFNL1, PTGES, CCR5, CLEC7A, IFNB1, CXCR2, and PTGS2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17) selected from the group), a coding gene thereof, or a combination thereof; (3-3) one or more selected from the group consisting of SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, and CLEC7A (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group), their encoding genes, or combinations thereof; or (3-4) one or more selected from the group consisting of IFNG, CCL2, and PTGES2 (e.g., one, two, or three selected from the group), their encoding genes, or a combination thereof; (3-5) one or more selected from the group consisting of ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4, and CCL5 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), their encoding genes, or combinations thereof; (3-6) one or more selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20) selected from the group consisting of ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA), a coding gene thereof, or a combination thereof; (3-7) one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12) selected from the group), their encoding genes, or combinations thereof; (3-8) one or more selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11 (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15) selected from the group), their encoding genes, or combinations thereof; or (3-9) One or more selected from the group consisting of CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF (e.g., any one or more (e.g., 2, 3, 4, 5, 6, 7, or 8) selected from the group), genes encoding the same, or combinations thereof.

[0086] The method for diagnosing or providing information on the diagnosis of all pancreatic cancers (early stage pancreatic cancer and / or late stage pancreatic cancer) may further comprise the steps of: (b) if the levels of one or more (e.g., one, two, or three) selected from the group consisting of IFNG, CCL5, and PTGES2, their encoding genes, or a combination thereof, in the blood sample are lower (decreased) than in a comparison sample (e.g., a normal sample), or the levels of one or more (e.g., one, two, three, four, five, six, seven, eight, nine, or ten) selected from the group consisting of IFNL1, TNF, CXCL8, VEGFACCL2, CXCR4, ARG1, PTGS2, SLC27A2, and PTGES, their encoding genes, or a combination thereof, are higher (increased) than in a comparison sample (e.g., a normal sample), diagnosing (or confirming or determining) the sample or the subject from which the sample was derived as a patient with pancreatic cancer (early stage pancreatic cancer, late stage pancreatic cancer, or all of these).

[0087] In another embodiment, the method may be a method for diagnosing pancreatic cancer (early stage pancreatic cancer and / or late stage pancreatic cancer), a method for providing information on the diagnosis of all pancreatic cancers (early stage pancreatic cancer and / or late stage pancreatic cancer), comprising the steps of: (a) detecting one or more (one or two) selected from the group consisting of IFNB1 and IFNA1, their encoding genes, or a combination thereof, from a blood sample isolated from a subject; and (b) if the level of one or more (one or two) selected from the group consisting of IFNB1 and IFNA1, their encoding genes, or a combination thereof, in the blood sample is lower (decreased) than that in a comparison sample (e.g., a sample with a similar disease), diagnosing (or confirming or determining) the sample or the subject from which the sample was derived as a patient with pancreatic cancer (early stage pancreatic cancer, late stage pancreatic cancer, or all of these). This method allows patients with pancreatic cancer (early stage pancreatic cancer, late stage pancreatic cancer, or all of these) to be distinguished from patients with the similar disease.

[0088] The method of using the above-mentioned IFNB1 and / or IFNA1 as a marker may be one for distinguishing pancreatic cancer (early stage pancreatic cancer, late stage pancreatic cancer, or all of these) from similar diseases, such as positive pancreatic diseases (pancreatitis (chronic pancreatitis and / or acute pancreatitis), pancreatic positive tumors, intraductal papillary mucinous neoplasms (IPMN), other pancreatic diseases (pancreatic diseases excluding pancreatic cancer (pancreatic malignant tumors)) such as autoimmune pancreatitis (AIP), biliary tract cancer, etc.). The method further comprises: (a) measuring the level of one or more of the biomarkers described above from a blood sample isolated from the subject; and (b)(i) comparing the level of biomarkers measured in the blood sample with the level of biomarkers in a comparison sample (e.g., a normal sample, a sample with a similar disease, etc.); (ii) diagnosing (or confirming or determining) the sample or the subject from which the sample was derived as having pancreatic cancer (early stage pancreatic cancer, late stage pancreatic cancer, or all of these) if the level of the biomarker measured in the sample is higher or lower than that in the comparison sample; or (iii) all of steps (i) and (ii) Optionally, the method may further comprise, prior to step (b) (steps (i) and / or (ii)), measuring the level of the biomarker in a comparison sample.

[0089] Measuring the level of the biomarker can be performed by measuring the concentration of the biomarker (protein, gene (full length DNA, cDNA, mRNA, etc.), or all of these) and / or the number of cells expressing the biomarker. The method for measuring the concentration of the biomarker and / or the number of cells expressing the biomarker is not particularly limited and can be appropriately selected from the group consisting of all methods commonly used for quantitative analysis of proteins, genes, and / or cells, such as immunochromatography, immunohistochemical staining, enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (RIA), enzyme immunoassay (EIA), fluorescence immunoassay (FIA), luminescence immunoassay (LIA), Western blotting, microarray analysis, flow cytometry, polymerase chain reaction (PCR; e.g., qPCR, real-time PCR, real-time qPCR, etc.), and fluorescent in situ hybridization (FISH), but is not limited thereto. In one example, the step of measuring the level of the biomarker may further include, but is not limited to, a statistical analysis method that can be used for biomarker analysis (e.g., a regression analysis method such as stepwise logistic regression analysis). For more details on "measuring the level of the biomarker," please refer to the explanation in the "Detection of the biomarker" section above.

[0090] As used herein, "high level of a biomarker" can mean that the level of a biomarker in a sample (e.g., the concentration (level) of the biomarker (protein and / or gene) (e.g., in the case of a gene, the Ct value, ΔCt value, and / or ΔΔCt value measured by mPCR), the number of cells expressing the biomarker, etc.) is about 1% or more, about 2% or more, about 3% or more, about 4% or more, about 5% or more, about 7% or more, about 8% or more, about 9% or more, about 10% or more, about 12% or more, about 15% or more, about 18% or more, about 20% or more, about 22% or more, about 25% or more, about 28% or more, or about 30% or more higher than that of a comparison sample.

[0091] As used herein, "low level of a biomarker" can mean that the level of a biomarker in a sample (e.g., the concentration (level) of the biomarker (protein and / or gene) (e.g., in the case of a gene, the Ct value, ΔCt value, and / or ΔΔCt value measured by PCR, etc.), the number of cells expressing the biomarker, etc.) is lower or less than that of a comparative sample by about 1% or more, about 2% or more, about 3% or more, about 4% or more, about 5% or more, about 7% or more, about 8% or more, about 9% or more, about 10% or more, about 12% or more, about 15% or more, about 18% or more, about 20% or more, about 22% or more, about 25% or more, about 28% or more, or about 30% or more.

[0092] In another example, the method may be a method for diagnosing or providing information on early stage pancreatic cancer diagnosis, comprising the steps of: (a-1) Measuring the level of one or more proteins selected from the group consisting of TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13) selected from the group), their encoding genes, or a combination thereof, from a blood sample isolated from the subject.

[0093] In one example, the step of measuring the level of the biomarker is the same as that described above. For example, the step of measuring the level of the biomarker can be performed by quantifying the biomarker (for example, by measuring Ct value, ΔCt value, and / or ΔΔCt value in the case of PCR) and optionally by regression analysis (for example, stepwise logistic regression analysis), and can further perform appropriate statistical analysis as needed.

[0094] The method for diagnosing early stage pancreatic cancer or the method for providing information for diagnosing early stage pancreatic cancer may further include, after step (a-1), the following steps: (b-1) Calculating using the following formula [Formula 1]logit(p)=B0+B1×TNF+B2×IFNG+B3×IFNL1+B4×CXCL11+B5×CLEC7A+B6×VEGFA+B7×CCL2+B8×CXCR4+B9×CXCR2+B10×ARG1+B11×SLC27A2+B12×PTGES2+B13×PTGES (In Equation 1, B0: Rational numbers (up to four decimal places) between 30 and 50, 30 and 47.5, 30 and 45, 32.5 and 50, 32.5 and 47.5, 32.5 and 45, 35 and 50, 35 and 47.5, or 35 and 45, for example, 35.8476 or 44.4033; TNF: expression level of biomarker TNF; B1: coefficient for the expression level of the biomarker TNF, a rational number between -3 and -2 or between -2.9 and -2.5 (valid up to four decimal places, e.g., -2.5794 or -2.8042) or 0; IFNG: expression level of biomarker IFNG; B2: coefficient for the expression level of the biomarker IFNG, a rational number between 3 and 4 or 3.3 and 3.8 (valid up to four decimal places, e.g., 3.3956 or 3.7082) or 0; IFNL1: expression level of biomarker IFNL1; B3: coefficient for the expression level of the biomarker IFNL1, a rational number between 0.1 and 0.5 or 0.2 and 0.3 (valid up to four decimal places, e.g., 0.2358) or 0; CXCL11: expression level of biomarker CXCL11; B4: coefficient for the expression level of the biomarker CXCL11, a rational number between 0.1 and 0.2 (valid up to four decimal places, e.g., 0.1568) or 0; CLEC7A: expression level of biomarker CLEC7A; B5: coefficient for the expression level of the biomarker CLEC7A, a rational number between 0.8 and 1.3 or 1 and 1.1 (valid up to four decimal places, e.g., 1.0951) or 0; VEGFA: expression level of biomarker VEGFA; B6: Coefficient for the expression level of the biomarker VEGFA, a rational number between -1.5 and -0.2 or -1 and -0.7 (valid up to four decimal places, e.g., -0.8407) or 0; CCL2: expression level of biomarker CCL2; B7: coefficient for the expression level of biomarker CCL2, a rational number between -1 and -0.1 or between -0.7 and -0.5 (valid up to four decimal places, e.g., -0.5380 or -0.6622) or 0; CXCR4: expression level of biomarker CXCR4; B8: Coefficient for the expression level of the biomarker CXCR4, a rational number between -1.5 and -0.5 or between -1.1 and -0.7 (valid up to four decimal places, e.g., -0.9422) or 0; CXCR2: expression level of biomarker CXCR2; B9: coefficient for the expression level of the biomarker CXCR2, a rational number between 0.7 and 1.7 or between 0.9 and 1.5 (valid up to four decimal places, e.g., 1.4027 or 1.0804) or 0; ARG1: expression level of biomarker ARG1; B10: Coefficient for the expression level of the biomarker ARG1, a rational number between -1.7 and -0.7 or between -1.4 and -1 (valid up to four decimal places, e.g., -1.143 or -1.2971) or 0; SLC27A2: expression level of biomarker SLC27A2; B11: Coefficient for the expression level of the biomarker SLC27A2, a rational number between -5 and -4 or between -4.8 and -4.3 (valid up to four decimal places, e.g., -4.3771 or -4.7971) or 0; PTGES2: expression level of biomarker PTGES2; B12: coefficient for the expression level of the biomarker PTGES2, a rational number between 2.7 and 3.5 or 3 and 3.3 (valid up to four decimal places, e.g., 3.1076 or 3.1934) or 0; PTGES: expression level of biomarker PTGES; B13: Coefficient for the expression level of the biomarker PTGES, a rational number between -1 and -0.2 or between -0.8 and -0.6 (valid up to four decimal places, e.g., -0.6396 or -0.7064) or 0; However, one or more selected items from B1 to B13 are not 0.

[0095] The expression level of each biomarker applied to [Equation 1] may be a value measured and quantified by ΔCt derived by performing real-time PCR (e.g., real-time qPCR; see Example 2).

[0096] The method for diagnosing early stage pancreatic cancer or the method for providing information for diagnosing early stage pancreatic cancer may further include, after step (b-1), the following step: (c-1) A step of comparing the value obtained in the step (b-1) with a cut-off value.

[0097] In this case, the cut-off value for diagnosing early stage pancreatic cancer may be a rational number between −2.5 and −1.5 or −2 and −1.8 (valid up to 5 or 6 decimal places), for example, −1.855994 or −1.90875.

[0098] If the value obtained in step (b-1) exceeds the cut-off value, the test subject can be predicted (judged, determined) to be a patient with early stage pancreatic cancer or to be at high risk of developing early stage pancreatic cancer. In this case, whether the value obtained in step (b-1) exceeds the cut-off value can be determined based on the comparison result in step (c-1). In another example, if the value obtained in step (b-1) is equal to or less than the cut-off value, the test subject can be predicted (judged, determined) to be normal and / or at low risk of developing pancreatic cancer (early stage pancreatic cancer).

[0099] Therefore, the method for diagnosing early stage pancreatic cancer or the method for providing information for diagnosing early stage pancreatic cancer may further comprise the following steps after or simultaneously with step (c-1): (d-1) A step of predicting (judging, determining) that the subject is an early stage pancreatic cancer patient or a patient at high risk of developing early stage pancreatic cancer if the value obtained in step (b-1) exceeds the cut-off value.

[0100] In another example, the method may be a method for diagnosing or providing information on early stage pancreatic cancer diagnosis, comprising the steps of: (a-2) Measuring the level of one or more proteins selected from the group consisting of CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF (e.g., any one or more (2, 3, 4, 5, 6, 7, or 8) selected from the group), their encoding genes, or a combination thereof, from a blood sample isolated from the subject.

[0101] In one example, the step of measuring the level of the biomarker is the same as that described above. For example, the step of measuring the level of the biomarker can be performed by quantifying the biomarker (for example, by measuring Ct value, ΔCt value, and / or ΔΔCt value in the case of PCR) and optionally by regression analysis (for example, stepwise logistic regression analysis), and can further perform appropriate statistical analysis as needed.

[0102] The method for diagnosing early stage pancreatic cancer or the method for providing information on early stage pancreatic cancer diagnosis may further include, after step (a-2), the following step: (b-2) Calculating using the following formula [Formula 2]logit(p)=B0+B1×IFNG+B2×SLC27A2+B3×CCL5+B4×PTGES2+B5×TNF+B6×IFNL1+B7×CCL2+B8×CXCR2 (In Equation 2, B0: Rational numbers (up to six decimal places) in the range -5 to -0.1, -5 to -0.5, -5 to -1, -5 to -1.5, -2.5 to -0.1, -2.5 to -0.5, -2.5 to -1, or -2.5 to -1.5, e.g., -1.957576; IFNG: expression level of biomarker IFNG; B1: coefficient for the expression level of the biomarker IFNG, a rational number between 1 and 3 or 1.7 and 2.3 (valid up to six decimal places, e.g., 1.942999) or 0; SLC27A2: expression level of biomarker SLC27A2; B2: coefficient for the expression level of the biomarker SLC27A2, a rational number between -3 and -1.5 or between -2.5 and -2 (valid up to six decimal places, e.g., -2.370157) or 0; CCL5: expression level of biomarker CCL5; B3: coefficient for the expression level of the biomarker CCL5, a rational number between 0.1 and 0.5 or 0.2 and 0.3 (valid up to six decimal places, e.g., 0.236554) or 0; PTGES2: expression level of biomarker PTGES2; B4: coefficient for the expression level of the biomarker PTGES2, a rational number between 1 and 2.5 or 1.5 and 2 (valid up to six decimal places, e.g., 1.781672) or 0; TNF: expression level of biomarker TNF; B5: Coefficient for the expression level of the biomarker TNF, a rational number between -2 and -0.5 or between -1.5 and -1 (valid up to six decimal places, e.g., -1.328085) or 0; IFNL1: expression level of biomarker IFNL1; B6: Coefficient for the expression level of the biomarker IFNL1, a rational number between -0.5 and -0.1 or between -0.3 and -0.1 (valid up to six decimal places, e.g., -0.170127) or 0; CCL2: expression level of biomarker CCL2; B7: Coefficient for the expression level of the biomarker CCL2, a rational number between -1 and -0.1 or between -0.7 and -0.3 (valid up to six decimal places, e.g., -0.495828) or 0; CXCR2: expression level of biomarker CXCR2; B8: Coefficient for the expression level of the biomarker CXCR2, a rational number between 0.1 and 1 or between 0.5 and 0.8 (valid up to six decimal places, e.g., 0.611586) or 0; However, one or more selected items from B1 to B8 are not 0.

[0103] The expression level of each biomarker applied to [Equation 2] may be a value measured and quantified by ΔCt derived by performing real-time PCR (e.g., real-time qPCR; see Example 2). In one specific example, to improve the accuracy of prediction, the ΔCt value can be statistically processed using a predetermined statistical analysis method and then applied to Equation 2. Examples of usable statistical analysis methods include Robust Scaler. For example, when Robust Scaler is applied, the value (x') obtained by applying the ΔCt value to the following Equation 5 can be applied to Equation 2: x' = [x - median(x)] / IQR [Formula 5] (x: ΔCt value for each marker in the diagnostic subject; median(x): median of ΔCt values ​​for each marker in an arbitrary population including the diagnostic subject; IQR (interquartile range): range between the third quartile (Q3) and the first quartile (Q1) (Q3-Q1)).

[0104] The method for diagnosing early stage pancreatic cancer or the method for providing information on early stage pancreatic cancer diagnosis may further include, after step (b-2), the following step: (c-2) A step of comparing the value obtained in the step (b-2) with a cut-off value. In this case, the cut-off value for diagnosing early stage pancreatic cancer is a rational number between 0.1 and 0.5 or between 0.2 and 0.3 (valid up to three decimal places), for example, 0.282.

[0105] If the value obtained in step (b-2) exceeds the cut-off value, the test subject can be predicted (judged, determined) to be an early stage pancreatic cancer patient or have a high risk of developing early stage pancreatic cancer. In this case, whether the value obtained in step (b-2) exceeds the cut-off value can be determined based on the comparison result in step (c-2). In another example, if the value obtained in step (b-1) is equal to or less than the cut-off value, the test subject can be predicted (judged, determined) to be normal and / or have a low risk of developing pancreatic cancer (early stage pancreatic cancer).

[0106] Therefore, the method for diagnosing early stage pancreatic cancer or the method for providing information for diagnosing early stage pancreatic cancer may further comprise the following step after or simultaneously with step (c-2): (d-2) A step of predicting (judging, determining) that the subject is an early stage pancreatic cancer patient or a patient at high risk of developing early stage pancreatic cancer if the value obtained in step (b-2) exceeds the cut-off value.

[0107] In another example, the method may be a method for diagnosing or providing information on overall pancreatic cancer diagnosis (early stage pancreatic cancer and / or late stage pancreatic cancer) comprising the steps of: (a-3) Measuring the level of one or more proteins selected from the group consisting of TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, SLC27A2, and PTGES2 (e.g., any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, or 11) selected from the group), their encoding genes, or a combination thereof, from a blood sample isolated from the subject.

[0108] In one example, the step of measuring the level of the biomarker is the same as that described above. For example, the step of measuring the level of the biomarker can be performed by quantifying the biomarker (for example, by measuring Ct value, ΔCt value, and / or ΔΔCt value in the case of PCR) and optionally by regression analysis (for example, stepwise logistic regression analysis), and can further perform appropriate statistical analysis as needed.

[0109] In one embodiment, the method for diagnosing pancreatic cancer or the method for providing information for diagnosing pancreatic cancer may further include the following steps after step (a-3): (b-3) Calculating using the following formula [Formula 3]logit(p)=B0+B1×TNF+B2×IFNG+B3×CXCL11+B4×VEGFA+B5×CCL2+B6×CCL5+B7×CXCR4+B8×CXCR2+B9×PTGS2+B10×SLC27A2+B11×PTGES2 (In Equation 3, B0: Rational numbers (up to four decimal places) between 30 and 40, 30 and 38, 30 and 37, 32.5 and 40, 32.5 and 38, 32.5 and 37, for example, 36.9898 or 36.6273; TNF: expression level of biomarker TNF; B1: coefficient for the expression level of the biomarker TNF, a rational number between -2.5 and -2 or between -2.3 and -2.2 (valid up to four decimal places, e.g., -2.2200 or -2.2286) or 0; IFNG: expression level of biomarker IFNG; B2: coefficient for the expression level of the biomarker IFNG, a rational number between 0.5 and 1.5 or 0.9 and 1.1 (valid up to four decimal places, e.g., 0.9955 or 1.0041) or 0; CXCL11: expression level of biomarker CXCL11; B3: coefficient for the expression level of the biomarker CXCL11, a rational number between 0.1 and 0.5 or 0.3 and 0.4 (valid up to four decimal places, e.g., 0.3413 or 0.3704) or 0; VEGFA: expression level of biomarker VEGFA; B4: coefficient for the expression level of the biomarker VEGFA, a rational number between −3.2 and −2.5 or −2.9 and −2.7 (valid up to four decimal places, e.g., −2.7990 or −2.7473) or 0; CCL2: expression level of biomarker CCL2; B5: coefficient for the expression level of biomarker CCL2, a rational number between −0.3 and −0.01 or −0.25 and −0.15 (valid up to four decimal places, e.g., −0.1913 or −0.2240) or 0; CCL5: expression level of biomarker CCL5; B6: coefficient for the expression level of biomarker CCL5, a rational number between 1 and 1.5 or 1.3 and 1.4 (valid up to four decimal places, e.g., 1.3628 or 1.3874) or 0; CXCR4: expression level of biomarker CXCR4; B7: coefficient for the expression level of the biomarker CXCR4, a rational number between -2.5 and -1.5 or between -2.2 and -2 (valid up to four decimal places, e.g., -2.0521 or -2.0986) or 0; CXCR2: expression level of biomarker CXCR2; B8: coefficient for the expression level of the biomarker CXCR2, a rational number between 0.2 and 1.2 or between 0.6 and 0.8 (valid up to four decimal places, e.g., 0.7037 or 0.6388) or 0; PTGS2: expression level of biomarker PTGS2; B9: Coefficient for the expression level of the biomarker PTGS2, a rational number between -0.01 and -0.1 (valid up to four decimal places, e.g., -0.0640) or 0; SLC27A2: expression level of biomarker SLC27A2; B10: Coefficient for the expression level of the biomarker SLC27A2, a rational number between -3.5 and -3 or between -3.3 and -3.1 (valid up to four decimal places, e.g., -3.1754 or -3.1990) or 0; PTGES2: expression level of biomarker PTGES2; B11: Coefficient for the expression level of the biomarker PTGES2, a rational number between 4 and 5 or 4.4 and 4.6 (valid up to four decimal places, e.g., 4.4765) or 0; However, one or more selected values ​​from B1 to B11 are not 0.

[0110] The expression level of each biomarker applied to [Equation 3] may be a value measured and quantified by ΔCt derived by performing real-time PCR (e.g., real-time qPCR; see Example 2).

[0111] The method for diagnosing pancreatic cancer overall or the method for providing information on diagnosing pancreatic cancer overall regardless of the stage of progression may further include the following steps after step (b-3): (c-3) A step of comparing the value obtained in the step (b-3) with a cut-off value.

[0112] In this case, the cut-off value for diagnosing pancreatic cancer is a rational number (valid up to five decimal places) between −3.5 and −2 or −3 and −2.5, for example, −0.25109 or −0.29033.

[0113] If the value obtained in step (c-3) exceeds the cut-off value, the test subject can be predicted (judged, determined) to be a pancreatic cancer patient or have a high risk of developing pancreatic cancer. In this case, whether the value obtained in step (b-3) exceeds the cut-off value can be determined based on the comparison result in step (c-3). In another example, if the value obtained in step (b-3) is equal to or less than the cut-off value, the test subject can be predicted (judged, determined) to be normal and / or have a low risk of developing pancreatic cancer (total pancreatic cancer).

[0114] Therefore, the method for diagnosing pancreatic cancer or the method for providing information for diagnosing pancreatic cancer may further include the following steps after step (c-3): (d-3) A step of predicting (judging, determining) that the subject is a pancreatic cancer patient or a patient at high risk of developing pancreatic cancer if the value obtained in step (c-3) exceeds the cut-off value.

[0115] In another example, the method may be a method for diagnosing or providing information on overall pancreatic cancer diagnosis (early stage pancreatic cancer and / or late stage pancreatic cancer) comprising the steps of: (a-4) Measuring the level of one or more proteins selected from the group consisting of CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF (e.g., any one or more (2, 3, 4, 5, 6, 7, or 8) selected from the group), their encoding genes, or a combination thereof, from a blood sample isolated from the subject.

[0116] In one example, the step of measuring the level of the biomarker is the same as that described above. For example, the step of measuring the level of the biomarker can be performed by quantifying the biomarker (for example, by measuring Ct value, ΔCt value, and / or ΔΔCt value in the case of PCR) and optionally by regression analysis (for example, stepwise logistic regression analysis), and can further perform appropriate statistical analysis as needed.

[0117] The method for diagnosing pancreatic cancer or the method for providing information for diagnosing pancreatic cancer may further include the following steps after step (a-4): (b-4) Calculating using the following formula [Formula 4]logit(p)=B0+B1×IFNG+B2×SLC27A2+B3×CCL5+B4×PTGES2+B5×TNF+B6×IFNL1+B7×CCL2+B8×CXCR2 (In Equation 4, B0: Rational numbers between 0.1 and 1, 0.1 and 0.8, 0.5 and 1, and 0.5 and 0.8 (up to 6 decimal places), for example, 0.654363; IFNG: expression level of biomarker IFNG; B1: coefficient for the expression level of the biomarker IFNG, a rational number between 0.5 and 2 or 1.2 and 1.6 (valid up to six decimal places, e.g., 1.397767) or 0; SLC27A2: expression level of biomarker SLC27A2; B2: coefficient for the expression level of the biomarker SLC27A2, a rational number between -2.5 and -1 or between -2 and -1.6 (valid up to six decimal places, e.g., -1.874652) or 0; CCL5: expression level of biomarker CCL5; B3: coefficient for the expression level of the biomarker CCL5, a rational number between 0.1 and 1.2 or 0.6 and 1 (valid up to six decimal places, e.g., 0.855608) or 0; PTGES2: expression level of biomarker PTGES2; B4: coefficient for the expression level of the biomarker PTGES2, a rational number between 1 and 2.5 or 1.5 and 2 (valid up to six decimal places, e.g., 1.782533) or 0; TNF: expression level of biomarker TNF; B5: Coefficient for the expression level of the biomarker TNF, a rational number between -3 and -1.5 or between -2.5 and -2.1 (valid up to six decimal places, e.g., -2.378006) or 0; IFNL1: expression level of biomarker IFNL1; B6: Coefficient for the expression level of the biomarker IFNL1, a rational number between -0.0002 and -0.0001 (valid up to six decimal places, e.g., -0.000140) or 0; CCL2: expression level of biomarker CCL2; B7: Coefficient for the expression level of the biomarker CCL2, a rational number between -1 and -0.1 or between -0.7 and -0.3 (valid up to six decimal places, e.g., -0.535484) or 0; CXCR2: expression level of biomarker CXCR2; B9: Coefficient for the expression level of the biomarker CXCR2, a rational number between 0.1 and 0.7 or 0.2 and 0.4 (valid up to six decimal places, e.g., 0.300359) or 0; However, one or more selected items from B1 to B8 are not 0.

[0118] The expression level of each biomarker applied to [Equation 4] may be a value measured and quantified as ΔCt derived by performing real-time PCR (e.g., real-time qPCR; see Example 2). In one specific example, to improve the accuracy of prediction, the ΔCt value can be statistically processed using a predetermined statistical analysis method and then applied to Equation 4. Examples of usable statistical analysis methods include Robust Scaler. For example, when Robust Scaler is applied, the value (x') obtained by applying the ΔCt value to the following Equation 5 can be applied to Equation 4: x' = [x - median(x)] / IQR [Formula 5] (x: ΔCt value for each marker in the diagnostic subject; median(x): median value for each marker in an arbitrary population including the diagnostic subject; IQR (interquartile range): range between the third quartile (Q3) and the first quartile (Q1) (Q3-Q1)). The method for diagnosing pancreatic cancer or the method for providing information for diagnosing pancreatic cancer may further include the following steps after step (b-4): (c-4) A step of comparing the value obtained in the step (b-4) with a cut-off value. In this case, the cut-off value for diagnosing pancreatic cancer is a rational number (valid up to three decimal places) between 0.3 and 1.2 or 0.5 and 0.9, for example, 0.732.

[0119] If the value obtained in step (b-4) exceeds the cut-off value, the test subject can be predicted (judged, determined) to be a pancreatic cancer (total pancreatic cancer) patient or at high risk of developing pancreatic cancer (total pancreatic cancer). In this case, whether the value obtained in step (b-4) exceeds the cut-off value can be determined based on the comparison result in step (c-4). In another example, if the value obtained in step (b-4) is equal to or less than the cut-off value, the test subject can be predicted (judged, determined) to be normal and / or at low risk of developing pancreatic cancer (total pancreatic cancer).

[0120] Therefore, the method for diagnosing pancreatic cancer or the method for providing information for diagnosing pancreatic cancer may further include the following steps after or simultaneously with step (c-4): (d-4) A step of predicting (judging, determining) the subject as a pancreatic cancer patient or a patient at high risk of developing pancreatic cancer if the value obtained in step (b-4) exceeds the cut-off value.

[0121] The methods for diagnosing pancreatic cancer or for providing information on pancreatic cancer diagnosis provided herein include, after the detecting step, comparing step, or diagnosing (predicting, judging, or determining) step: A step of treating a subject diagnosed with pancreatic cancer (early stage pancreatic cancer, late stage pancreatic cancer, or both) It may further include:

[0122] The pancreatic cancer treatment may refer to chemotherapy such as administration of a pancreatic cancer therapeutic agent (e.g., anticancer agent: 5-fluorouracil, gemcitabine, Tarceva (erlotinib), antibody, etc.), radiation therapy, surgery, or a combination of two or more of these.

[0123] The treatment for pancreatic cancer can be applied differently depending on the stage and progression of the pancreatic cancer. Early-stage pancreatic cancer (e.g., resectable pancreatic cancer) is pancreatic cancer that can be treated by surgery, and treatment for early-stage pancreatic cancer can be performed by surgery alone or by surgery followed by adjuvant anti-cancer therapy. Adjuvant anti-cancer therapy refers to anti-cancer therapy other than surgery, and may refer to chemotherapy such as administration of a pancreatic cancer therapeutic agent (e.g., one or more anti-cancer agents selected from the group consisting of 5-fluorouracil, gemcitabine, Tarceva (erlotinib), leucovorin, irinotecan, oxaliplatin, folfirinox, abraxane, onivyde, TS-1, capecitabine, antibodies, etc.), anti-cancer radiation therapy, or a combination thereof.

[0124] Treatment for late-stage pancreatic cancer (e.g., borderline resectable pancreatic cancer, locally advanced pancreatic cancer, metastatic pancreatic cancer, etc.) can be applied differently depending on the stage of progression of each pancreatic cancer.

[0125] For example, in the case of borderline resectable pancreatic cancer among late-stage pancreatic cancers, after prior adjuvant treatment (e.g., administration of one or more anticancer agents selected from the group consisting of 5-fluorouracil, leucovorin, irinotecan, oxaliplatin, etc. (e.g., FOLFIRINOX, which is a treatment (administration) of a combination of the above four anticancer agents)), depending on the course of treatment, i) if surgery is possible, post-operative anticancer treatment can be performed, or ii) if surgery is not possible, anticancer treatment can be performed. The anti-cancer treatment may refer to chemotherapy such as administration of a pancreatic cancer therapeutic agent (e.g., one or more anti-cancer agents selected from the group consisting of 5-fluorouracil, gemcitabine, tarceva (erlotinib), leucovorin, irinotecan, oxaliplatin, antibodies, etc.), anti-cancer radiation therapy, or a combination thereof.

[0126] In the case of locally advanced pancreatic cancer, among late-stage pancreatic cancers, first-line adjuvant treatment (e.g., administration of one or more anticancer drugs selected from the group consisting of 5-fluorouracil, leucovorin, irinotecan, oxaliplatin, etc. (e.g., FOLFIRINOX, which is a treatment (administration) of a combination of the above four anticancer drugs)) can be performed, and then, depending on the progression of the disease, the above-described first-line adjuvant treatment can be continued or second-line treatment (e.g., administration of a combination of nanoparticle albumin-paclitaxel (nab-paclitaxel) and gemcitabine), anticancer radiation therapy, or a combination of two or more of these can be performed.

[0127] In the case of metastatic pancreatic cancer among late-stage pancreatic cancer, adjuvant treatment (e.g., administration of one or more anticancer drugs selected from the group consisting of 5-fluorouracil, leucovorin, irinotecan, oxaliplatin, etc. (e.g., FOLFIRINOX, which is a treatment using a combination of the above four anticancer drugs)), anticancer treatment (e.g., nanoparticle albumin-paclitaxel conjugate (nab-paclitaxel)), After the initial treatment (e.g., a combination of 5-fluorouracil and gemcitabine, or gemcitabine alone), or a combination thereof, a second-line treatment can be administered depending on the patient's progress. The second-line treatment can refer to chemotherapy, such as a combination of nanoparticle albumin-paclitaxel (nab-paclitaxel) and gemcitabine, a combination of 5-fluorouracil and liposomal irinotecan, or a combination of 5-fluorouracil and liposomal oxaliplatin.

[0128] blood sample The diagnostic subject sample or blood sample to which the pancreatic cancer diagnostic compositions, kits, and methods provided herein are applicable may include a liquid biopsy obtained (or isolated or derived) from a diagnostic subject, such as blood, serum, plasma, and / or cells isolated therefrom; in one example, the sample may include a buffy coat isolated from a diagnostic subject.

[0129] As used herein, the term "buffy coat" refers to the entire white blood cell layer formed between the upper plasma layer and the lower red blood cell layer when blood is centrifuged. It is a mixture of blood components (e.g., monocytes, granulocytes, lymphocytes, etc.) excluding plasma and red blood cells, and is used to clearly distinguish it from peripheral blood mononuclear cells (PBMCs) (see FIG. 3). The blood sample used herein may be a blood-derived buffy coat, but it does not necessarily have to be a sample consisting only of peripheral blood mononuclear cells. In one example, the buffy coat may be obtained from the middle buffy coat layer among the plasma layer (top), buffy coat layer (middle), and red blood cell layer (bottom) obtained sequentially from the top by centrifuging blood under one or more (1, 2, or 3) conditions selected from the following conditions (1) to (3): (1) Temperature: 2~30℃, 2~28℃, 2~25℃, 2~23℃, 2~20℃, 2~18℃, 2~15℃, 2~13℃, 2~10℃, 2~8℃, 2~6℃, 2~5℃, 2~4℃, 3~30℃, 3~28℃, 3~25℃, 3~23℃, 3~20℃, 3~18℃, 3~15℃, 3~13℃, 3~10℃, 3~8℃, 3~6℃, 3~5℃, 3~4℃, 4~30℃, 4~28℃, 4~25℃, 4~23℃, 4~20℃, 4~18℃, 4~15℃, 4~13℃, 4~10℃, 4-8°C, 4-6°C, 4-5°C, 5-30°C, 5-28°C, 5-25°C, 5-23°C, 5-20°C, 5-18°C, 5-15°C, 5-13°C, 5-10°C, 5-8°C, 5-6°C, 10-30°C, 10-28°C, 10-25°C, 10-23°C, 10-20°C, 10-18°C, 10-15°C, 10-13°C, 15-30°C, 15-28°C, 15-25°C, 15-23°C, 15-20°C, 15-18°C, 20-30°C, 20-28°C, 20-25°C, or 20-23°C; (2) Speed: 300g~2000g, 300g~1800g, 300g~1500g, 300g~1300g, 300g~1000g, 500g~2000g, 500g~1800g, 500g~1500g, 500g~1300g, 500g~1000g, 600g~1000g, 700g~1000g, 800g~1000g, 500g~900g, 600g~900g, 700g~900g, 800g~900g, 500g~800g, 600g~800g, or 700g~800g; and (3) Duration: 5-20 minutes, 7-20 minutes, 9-20 minutes, 5-15 minutes, 7-15 minutes, 9-15 minutes, 5-12 minutes, 7-12 minutes, or 9-12 minutes.

[0130] In this specification, the subject (individual) to be diagnosed can be selected from mammals including humans, primates including monkeys, and rodents including mice and rats, and can be an individual in need of pancreatic cancer diagnosis.

[0131] In this specification, the comparison sample refers to a sample obtained (or isolated or derived) from a normal individual (e.g., a sample not suffering from pancreatic cancer (early stage pancreatic cancer, late stage pancreatic cancer, or all of these)) or an individual with a similar disease (a positive pancreatic disease (such as pancreatitis (chronic pancreatitis and / or acute pancreatitis), a positive pancreatic tumor, intraductal papillary mucinous neoplasia (IPMN)), autoimmune pancreatitis (AIP), other pancreatic diseases (pancreatic diseases excluding pancreatic cancer (malignant pancreatic tumor)) and / or biliary tract cancer), and for example, the normal individual is selected from mammals including humans, primates including monkeys, and rodents including mice and rats, and may be an individual of the same species as the subject to be diagnosed, and the comparison sample may contain blood, serum, plasma, and / or cells isolated therefrom obtained (or isolated or derived) from the comparison subject, and specifically, may contain buffy coat.

[0132] Screening of pancreatic cancer therapeutic agents In another embodiment, a method is provided for screening candidate drugs for treating pancreatic cancer by measuring the levels of the biomarkers upon treatment with the candidate compound.

[0133] More specifically, the screening method comprises: contacting the biological sample with a candidate compound; measuring in said biological sample the level of one or more biomarkers selected from the group consisting of the biomarkers described above and their encoding genes; and comparing the level of the biomarker in the biological sample contacted with the candidate compound with the level of the ubiquitin degrading enzyme and / or the gene encoding the same in the biological sample not contacted with the candidate substance; may include:

[0134] The comparing step can be carried out by measuring the biomarker levels before and after contact (treatment) of the same biological sample with a candidate compound and comparing them, or by contacting only a portion of the biological sample with the candidate compound and measuring the biomarker levels in the portion that has been contacted with the candidate compound and the portion that has not been contacted with the candidate compound and comparing them.

[0135] If the level of the biomarker in the biological sample contacted with the candidate compound is reduced compared to the level of the biomarker in the biological sample not contacted with the candidate substance, i.e., if the candidate compound reduces the level of the biomarker in the biological sample or inhibits its expression, the candidate compound can be determined to be a candidate substance for the prevention and / or treatment of pancreatic cancer.

[0136] The biological sample may include blood, serum, plasma, and / or cells isolated therefrom obtained (or isolated or derived) from a living body, for example, a pancreatic cancer patient, and specifically may include a buffy coat.

[0137] The candidate compound may be selected from the group consisting of various compounds, such as small molecule compounds, proteins, polypeptides, oligopeptides, polynucleotides, oligonucleotides, plant or animal extracts, and the like.

[0138] The level of the biomarker in the biological sample can be measured by a conventional gene or protein quantitative detection method and / or by evaluating the measurement results, and the specific measurement method is the same as that described above.

[0139] All numerical values ​​provided herein are to be construed as including a normal error range as long as the desired functions and / or effects of the present application are achieved, for example, but not limited to, a range of -10% (or -9%, -8%, -7%, -6%, -5%, -4%, -3%, -2%, or -1%) to +10% (or +9%, +8%, +7%, +6%, +5%, +4%, +3%, +2%, or +1%). [Effects of the Invention]

[0140] Through this application, pancreatic cancer can be diagnosed non-invasively, simply, and with high accuracy using only patient-derived blood, and the progression stage of pancreatic cancer can be more accurately diagnosed and distinguished from other similar diseases, which can be useful in establishing more effective treatment strategies for pancreatic cancer. [Brief explanation of the drawings]

[0141] [Figure 1] FIG. 1 is a schematic diagram illustrating an exemplary buffy coat sample preparation process in comparison with a PBMC sample. [Figure 2] 1 is a graph showing the results (ΔΔCt values) of real-time qPCR obtained for IFNL1 in a normal control group, an early stage pancreatic cancer patient group (Early PC), and a late stage pancreatic cancer patient group (Late PC). [Figure 3] 1 is a graph showing the real-time qPCR results (ΔΔCt values) obtained for IFNG in a normal control group, an early stage pancreatic cancer patient group, and a late stage pancreatic cancer patient group. [Figure 4]1 is a graph showing the results of real-time qPCR (ΔΔCt values) obtained for CXCL11 in a normal control group, an early stage pancreatic cancer patient group, and a late stage pancreatic cancer patient group. [Figure 5] 1 is a graph showing the real-time qPCR results (ΔΔCt values) obtained for TNF in a normal control group, an early stage pancreatic cancer patient group, and a late stage pancreatic cancer patient group. [Figure 6] 1 is a graph showing the results of real-time qPCR (ΔΔCt values) obtained for CLEC7A in a normal control group, an early stage pancreatic cancer patient group, and a late stage pancreatic cancer patient group. [Figure 7] 1 is a graph showing the results of real-time qPCR (ΔΔCt values) obtained for CXCL8 in a normal control group, an early stage pancreatic cancer patient group, and a late stage pancreatic cancer patient group. [Figure 8] 1 is a graph showing the real-time qPCR results (ΔΔCt values) obtained for FOXP3 in a normal control group, an early stage pancreatic cancer patient group, and a late stage pancreatic cancer patient group. [Figure 9] 1 is a graph showing the real-time qPCR results (ΔΔCt values) obtained for VEGFA in a normal control group, an early stage pancreatic cancer patient group, and a late stage pancreatic cancer patient group. [Figure 10] 1 is a graph showing the results of real-time qPCR (ΔΔCt values) obtained for CCL2 in a normal control group, an early stage pancreatic cancer patient group, and a late stage pancreatic cancer patient group. [Figure 11] 1 is a graph showing the results of real-time qPCR (ΔΔCt values) obtained for CCL5 in a normal control group, an early stage pancreatic cancer patient group, and a late stage pancreatic cancer patient group. [Figure 12] 1 is a graph showing the real-time qPCR results (ΔΔCt values) obtained for CCR5 in a normal control group, an early stage pancreatic cancer patient group, and a late stage pancreatic cancer patient group. [Figure 13] 1 is a graph showing the results of real-time qPCR (ΔΔCt values) obtained for CXCR4 in a normal control group, an early stage pancreatic cancer patient group, and a late stage pancreatic cancer patient group. [Figure 14]1 is a graph showing the results (ΔΔCt values) of real-time qPCR obtained for ARG1 in a normal control group, an early stage pancreatic cancer patient group, and a late stage pancreatic cancer patient group. [Figure 15] 1 is a graph showing the results of real-time qPCR (ΔΔCt values) obtained for CXCR2 in a normal control group, an early stage pancreatic cancer patient group, and a late stage pancreatic cancer patient group. [Figure 16] 1 is a graph showing the results of real-time qPCR (ΔΔCt values) obtained for PTGS2 in a normal control group, an early stage pancreatic cancer patient group, and a late stage pancreatic cancer patient group. [Figure 17] 1 is a graph showing the real-time qPCR results (ΔΔCt values) obtained for PTGES2 in a normal control group, an early stage pancreatic cancer patient group, and a late stage pancreatic cancer patient group. [Figure 18] 1 is a graph showing the results of real-time qPCR (ΔΔCt values) obtained for SLC27A2 in a normal control group, an early stage pancreatic cancer patient group, and a late stage pancreatic cancer patient group. [Figure 19] 1 is a graph showing the real-time qPCR results (ΔΔCt values) obtained for PTGES in a normal control group, an early stage pancreatic cancer patient group, and a late stage pancreatic cancer patient group. [Figure 20] 1 is a graph showing the real-time qPCR results (ΔΔCt values) obtained for IFNB1 in a group of patients with pancreatic cancer and a group of patients with positive pancreatic disease. [Figure 21] 1 is a graph showing the results of real-time qPCR (ΔΔCt values) obtained for IFNB1 in a group of patients with pancreatic cancer and a group of patients with biliary tract cancer. [Figure 22] 1 is a graph showing real-time qPCR results (ΔΔCt values) obtained for IFNA1 in a group of patients with pancreatic cancer and a group of patients with positive pancreatic disease. [Figure 23] 1 shows the results of ROC curve analysis obtained using a combination of nine markers (ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF, and FOXP3) in a normal control group and a group of patients with early stage pancreatic cancer. [Figure 24] The ROC curve analysis results obtained using a combination of nine markers (CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF, and VEGFA) in a normal control group and a group of patients with late-stage pancreatic cancer are shown. [Figure 25] 1 shows the ROC curve analysis results obtained using a combination of nine markers (ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4, and CCL5) in normal control groups and all pancreatic cancer patient groups. [Figure 26A] The ROC curve analysis results obtained using all 20 markers in the normal control group and the early stage pancreatic cancer patient group are shown. [Figure 26B] The ROC curve analysis results obtained using all 20 markers in the normal control group and the late-stage pancreatic cancer patient group are shown. [Figure 26C] The ROC curve analysis results obtained using all 20 markers in the normal control group and all pancreatic cancer patient groups are shown. [Figure 27A] The ROC curve analysis results obtained using 12 markers (CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3) in a normal control group and a group of patients with early stage pancreatic cancer are shown. [Figure 27B] The ROC curve analysis results obtained using 12 markers (CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3) in a normal control group and a group of patients with late-stage pancreatic cancer are shown. [Figure 27C] The ROC curve analysis results obtained using 12 markers (CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3) in the normal control group and all pancreatic cancer patient groups are shown. [Figure 28A]The ROC curve analysis results obtained using 15 markers (CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11) in normal control and early stage pancreatic cancer patient groups are shown. [Figure 28B] The ROC curve analysis results obtained using 15 markers (CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11) in normal control and late-stage pancreatic cancer patient groups are shown. [Figure 28C] ROC curve analysis results obtained using 15 markers (CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11) in normal control and all pancreatic cancer patient groups are shown. [Figure 29A] The results of ROC curve analysis obtained using eight markers (CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF) in a group of normal controls and patients with early stage pancreatic cancer are shown. [Figure 29B] The results of ROC curve analysis obtained using eight markers (CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF) in a group of normal controls and patients with late-stage pancreatic cancer are shown. [Figure 29C] The ROC curve analysis results obtained using eight markers (CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF) in the normal control group and all pancreatic cancer patient groups are shown. [Figure 30] 29 is a table summarizing the results of FIGS. 23 to 29C. DETAILED DESCRIPTION OF THE INVENTION

[0142] The present invention will be described in more detail below through examples and test examples. However, these examples and test examples are for illustrative purposes only and should not be construed as limiting the present invention.

[0143] Example 1: Sample preparation To confirm the expression of pancreatic cancer biomarkers in pancreatic cancer, we measured the mRNA expression levels of various markers in buffy coats derived from blood samples from patients with pancreatic cancer, patients with pancreatic diseases (3 with pancreatitis (chronic and acute pancreatitis), 12 with pancreatic tumors, 1 with intraductal papillary mucinous neoplasm (IPMN), 2 with autoimmune pancreatitis (AIP), and other pancreatic diseases; a total of 20 patients), and 40 patients with biliary tract cancer. For comparison, we also performed similar tests on buffy coats derived from blood samples from healthy controls without pancreatic cancer.

[0144] First, 8 ml of blood was collected from 105 pancreatic cancer patients (36 with early-stage pancreatic cancer and 69 with late-stage pancreatic cancer) and 183 healthy individuals, and collected in EDTA tubes. Within two hours of collection, the EDTA tubes were centrifuged at 1800 g for 10 minutes at 24°C. The upper layer was separated into plasma, buffy coat, and red blood cells. The upper layer of plasma was removed from the blood, and 250 μl of buffy coat was separated into a storage tube and stored in a -80°C deep freezer.

[0145] The pancreatic cancer patients were classified into early stage pancreatic cancer patients and late stage pancreatic cancer patients according to the criteria in Table 2 below: [Table 2]

[0146] Example 2. Real-time qPCR Gene expression in the samples prepared in Example 1 was measured by real-time qPCR, which was performed by probe-based multiplex PCR.

[0147] First, total RNA was extracted from 250 μl of the frozen buffy coat from Example 1 using the NucleoSpin® NA Blood kit (MACHEREY-NAAGEL) according to the manufacturer's recommended protocol. cDNA was synthesized using 1 μg of RNA per sample. cDNA synthesis was performed using the GoScript™ Reverse Transcription system kit (Promega).

[0148] For multiplex PCR, the probes for each marker were labeled with FAM dye, and the internal reference gene, GAPDH, was labeled with HEX dye. Primers and probes were purchased from IDT (Integrated DNA Technologies, Inc.).

[0149] To confirm gene expression in samples, GoTaq® Probe qPCR Master Mix (Promega) was prepared to a final volume of 20 μl according to the protocol. Gene expression testing was performed using a QuantStudio 3.5 Real-Time PCR System (Applied Biosystems) under the standard cycling conditions provided by the system's software. From the real-time qPCR results, Ct values ​​representing the mRNA expression levels of each marker and Ct values ​​for GAPDH mRNA expression were extracted from the samples. ΔCt values ​​were calculated by calculating the difference between the mRNA expression levels of each marker and GAPDH mRNA expression levels in the samples. To compare the mRNA expression levels of each marker between healthy subjects and pancreatic cancer patients, or between pancreatic cancer and positive pancreatic disease and biliary tract cancer groups, ΔΔCt values ​​were calculated using the formula: ΔCt (each sample from pancreatic cancer or positive pancreatic disease and biliary tract cancer group) - ΔCt (average of healthy subjects). To show the increase or decrease in marker mRNA expression levels from the pancreatic cancer group relative to healthy subjects, or the pancreatic cancer group relative to the positive pancreatic disease group, -ΔΔCtThe values ​​obtained by converting the ΔCt to ΔCt were used for ANOVA analysis. All other statistical analyses used ΔCt. A higher ΔΔCt value indicates higher (increased) gene expression, and a lower ΔΔCt value indicates lower (decreased) gene expression. Meanwhile, a decrease in ΔCt value indicates an actual increase in gene expression, and an increase in ΔCt value indicates an actual decrease in gene expression.

[0150] The markers used are shown in Table 3, and the nucleic acid sequences (5' to 3') of the primers and probes for each marker are shown in Table 4 below: [Table 3] [Table 4-1] [Table 4-2] (In Table 4 above, the probe is a structure including a 5' FAM dye, an internal ZEN Quencher, and a 3' Iowa Black® Fluorescent Quencher (IBFQ).)

[0151] Data from qPCR experiments with GAPDH Ct values ​​of 26.5 or higher were excluded. All data used for statistical analysis were analyzed using ΔCt values, except for ANOVA analysis, which used ΔΔCt values. Kruskal-Wallis tests (statistical software: Graphad PRISM9) were used to confirm significant differences between pancreatic cancer patients and healthy controls for each marker. Logistic regression and ROC curve analysis (statistical software: MedCalc) were used to analyze the AUC, sensitivity, and specificity of marker combinations.

[0152] Example 3: Diagnosis of pancreatic cancer using each marker Buffy coat samples obtained from 105 pancreatic cancer patients (36 early stage pancreatic cancer patients, 69 late stage pancreatic cancer patients) and 183 healthy individuals were analyzed by the method described in Example 1. The results of real-time qPCR (ΔΔCt values) for each of the markers in Table 3 were obtained by the method described in Example 2. The results are shown in Figures 2 to 19 and summarized in Table 5 below. (ANOVA analysis; NC: normal control (normal patient group), PC: pancreatic cancer patient group, Early PC (E.PC): early stage pancreatic cancer patient group, Late PC (L.PC): late stage pancreatic cancer patient group): [Table 5]

[0153] As can be seen in Table 5, all of the tested markers showed expression patterns (increase and / or decrease) in the pancreatic cancer patient groups (early stage pancreatic cancer patient group and late stage pancreatic cancer patient group) that distinguished them from the normal group, and in particular, showed statistically significant differences in expression patterns compared to the normal group in at least one of the early stage pancreatic cancer patient group and late stage pancreatic cancer patient group.

[0154] Example 4: Distinguishing pancreatic cancer from similar diseases using the markers IFNA1 and IFNB1 Using the method described in Example 1, buffy coat samples were obtained from 105 pancreatic cancer patients, 17 patients with positive pancreatic diseases (1 patient with pancreatitis, 11 patients with pancreatic tumors (benign pancreatic disease), 1 patient with IPMN (intraductal papillary mucinous neoplasm), 2 patients with AIP (autoimmune pancreatitis), and 2 patients with other pancreatic diseases), and 40 patients with biliary tract cancer. The real-time qPCR results (ΔΔCt values) for the IFNA1 and IFNB1 markers were obtained using the method described in Example 2. The results are shown in Figures 20, 21 (all for IFNB1), and 22 (IFNA1) (*p<0.05, p value: Non-parametric t-test analysis).

[0155] As shown in Figures 20 to 22, the IFNA1 and IFNB1 markers showed a statistically significant decrease in expression in pancreatic cancer patients (including early-stage pancreatic cancer patients and late-stage pancreatic cancer patients) compared to patients with similar diseases such as positive pancreatic disease and / or biliary tract cancer.

[0156] From the results of Examples 3 and 4, it can be confirmed that each of the 20 markers listed in Table 3 can distinguish pancreatic cancer patients (early stage pancreatic cancer patients and / or late stage pancreatic cancer patients) from healthy individuals or patients with similar diseases (positive pancreatic disease and / or biliary tract cancer).

[0157] Example 5: Marker relative importance analysis Based on the previously measured ΔCt values, the relative importance of the 20 pancreatic cancer markers listed in Table 3 was confirmed through significance verification using logistic regression analysis and feature selection analysis.

[0158] 5.1.logistic regression analysis When two or more markers were combined and analyzed, the effect of each marker on changes in diagnostic performance within the comparison group was confirmed. Logistic regression (MedCalc software Ltd) analysis was performed to confirm the Wald values ​​of each marker derived when combining markers. After analyzing 20 markers in combination, markers with Wald values ​​of 1 or greater were selected in each comparison group (normal group vs. early stage pancreatic cancer patient group, normal group vs. late stage pancreatic cancer patient group, normal group vs. all pancreatic cancer patient group). The results obtained from the above analysis are shown in Tables 6 to 8.

[0159] [Table 6]

[0160] [Table 7]

[0161] [Table 8]

[0162] As shown in Tables 6 to 8, the larger the Wald value of the selected marker, the greater the influence of the marker on diagnostic performance.

[0163] 5.2.Feature selection analysis (Feature selection was performed to confirm the importance of markers from the 20 markers and select the main markers in comparisons between the normal group and the early (initial) pancreatic cancer patient group, the normal group and the late pancreatic cancer patient group, and the normal group and the overall pancreatic cancer patient group. The analysis was performed using the R program Boruta package (Miron B. Kursa, Witold R. Rudnicki (2010). Feature Selection with the Boruta Package. Journal of Statistical Software, 36 (11), pp. 1-13.). Each marker was considered a feature (variable), and features (variables) with importance values ​​lower than the maximum importance of the shadow feature, which is the criterion for importance, were removed.

[0164] The results obtained from the above analysis are shown in Tables 9 to 11.

[0165] [Table 9]

[0166] [Table 10]

[0167] [Table 11]

[0168] As shown in Tables 9 to 11, meanlmp is a numerical representation of the importance of each marker in the comparison group. Selected markers having a value higher than the maximum importance value of the Shadow feature are listed in the table, and the higher the value, the greater the influence of the marker.

[0169] Example 6: Diagnosis of pancreatic cancer using a combination of markers Among the markers listed in Table 3, a ROC curve analysis was performed using the expression levels of two or more combinations selected from the analysis results in Example 5.1 that were shown to be significantly high.

[0170] Using the method described in Example 1, buffy coat samples were obtained from pancreatic cancer patients (patients with early stage pancreatic cancer and patients with late stage pancreatic cancer) and healthy individuals. For the markers that were shown to be significantly higher in Tables 6 to 8, real-time qPCR (ΔCt values) was obtained using the method described in Example 2, and these resulting values ​​were combined for statistical analysis.

[0171] Logistic regression was applied as a classifier, and the results of statistical analysis of the obtained real-time qPCR results were shown as receiver operating characteristic curves (ROC curves) (Figures 23 to 30). The ROC curves enable confirmation of the optimal sensitivity and specificity of the classifier (Logistic Regression) and the cut-off value for diagnosing pancreatic cancer. Sensitivity (%) = (TP / TP+FN) x 100 Specificity (%)=(TN / TN+FP)×100 Youden's index(J)=max(sensitivity+specificity-1) AUC:area under the ROC curve [TP (True Positive): number of patients whose results were shown to be positive among those who were actually positive (pancreatic cancer); FN (False Negative): The number of patients whose results were negative when they were actually positive (pancreatic cancer); TN (True Negative): The number of patients whose results were actually negative; FP (False Positive): The number of patients whose results were positive when in fact they were negative.

[0172] First, the results of ROC curve analysis obtained using a combination of nine markers (9 Huvet markers (Early PC); ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF, and FOXP3) that were confirmed to have excellent ability to distinguish between normal and early pancreatic cancer in Table 6 are shown in Figure 23 and Table 12 (177 normal patients, 35 early pancreatic cancer patients): [Table 12]

[0173] As shown in Figure 23 and Table 12, when the combination of the nine markers (ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF, and FOXP3) was used, the AUC value for the early stage pancreatic cancer patient group (compared to the normal group) was close to 1 (0.979), and both the sensitivity and specificity were above 90%, confirming that the combination of the nine markers can accurately and effectively distinguish between the normal group and early stage pancreatic cancer patients.

[0174] In addition, the results of ROC curve analysis obtained using a combination of nine markers (9 Huvet markers (Late PC); CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF, and VEGFA) that were confirmed to have excellent ability to distinguish between normal and late-stage pancreatic cancer in Table 7 are shown in Figure 24 and Table 13 (177 normal patients, 67 late-stage pancreatic cancer patients): [Table 13]

[0175] As shown in Figure 24 and Table 13, when the combination of the nine markers (CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF, and VEGFA) was used, the AUC value for the late-stage pancreatic cancer patient group (compared to the normal group) was close to 1 (0.951), and the sensitivity and specificity were both approximately 90%, confirming that the combination of the nine markers can accurately and effectively distinguish between the normal group and late-stage pancreatic cancer patients.

[0176] In addition, the results of ROC curve analysis obtained using a combination of nine markers (9 Huvet markers (All PC); ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4, and CCL5) that were confirmed to have excellent ability to distinguish between normal and all pancreatic cancers in Table 8 are shown in Figure 25 and Table 14 (177 normal patients, 102 pancreatic cancer patients (35 early-stage pancreatic cancer patients, 67 late-stage pancreatic cancer patients)): [Table 14]

[0177] As shown in Figure 25 and Table 14, when the combination of the nine markers (ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4, and CCL5) was used, the AUC value for all pancreatic cancer (all stage) patient groups (compared to normal groups) was close to 1 (0.942), with a sensitivity of approximately 95% and a specificity of approximately 81%, confirming that the combination of the nine markers can accurately and effectively distinguish pancreatic cancer patients from normal groups.

[0178] In addition, using all combinations of the 20 markers listed in Table 3 (All Huvet markers; ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA), samples from normal subjects (177 patients) and pancreatic cancer patients (101 patients; 34 patients with early-stage pancreatic cancer and 67 patients with late-stage pancreatic cancer) were analyzed by logistic regression. The ROC curve analysis results are shown in Figures 26A (normal vs. early-stage pancreatic cancer), 26B (normal vs. late-stage pancreatic cancer), and 26C (normal vs. all pancreatic cancers).

[0179] As shown in Figures 26A to 26C, when a combination of the 20 markers (ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA) was used, the AUC values ​​in the early stage pancreatic cancer, late stage pancreatic cancer, and all stage pancreatic cancer patient groups relative to the normal group were close to 1 (0.95 or higher), with a sensitivity of approximately 92% or higher and a specificity of approximately 85% or higher, confirming that the combination of the 20 markers can accurately and effectively distinguish between the normal group and pancreatic cancer (early stage pancreatic cancer and / or late stage pancreatic cancer) patients.

[0180] In addition, of the markers listed in Table 3, 12 markers (Marker Set 1: CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3) were selected by combining the nine normal vs. early stage pancreatic cancer markers in Table 12 and the nine normal vs. all pancreatic cancer markers in Table 14 (six of these markers overlap). Samples from a normal group (177 patients) and pancreatic cancer patients (102 patients; 35 early stage pancreatic cancer patients and 67 late stage pancreatic cancer patients) were analyzed by logistic regression using ROC curve analysis results, which are shown in Figures 27A (normal vs. early stage pancreatic cancer), 27B (normal vs. late stage pancreatic cancer), and 27C (normal vs. all pancreatic cancer).

[0181] As shown in Figures 27A to 27C, when the combination of the 12 markers (CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3) was used, the AUC values ​​for early stage pancreatic cancer, late stage pancreatic cancer, and all stage pancreatic cancer patient groups relative to the normal group were close to 1 (0.94 or higher), the sensitivity was approximately 91% or higher, and the specificity was approximately 75% or higher, confirming that the combination of the 12 markers can accurately and effectively distinguish between normal groups and pancreatic cancer (early stage pancreatic cancer and / or late stage pancreatic cancer) patients.

[0182] In addition, 15 markers (Marker Set 2: CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11) selected from the markers listed in Table 3 were combined with the nine normal vs. early stage pancreatic cancer markers in Table 12 and the nine normal vs. late stage pancreatic cancer markers in Table 13 (three of these markers overlap). Samples from normals (177 patients) and pancreatic cancer patients (102 patients; 35 early stage pancreatic cancer patients and 67 late stage pancreatic cancer patients) were analyzed by logistic regression using ROC curve analysis results, which are shown in Figures 28A (normal vs. early stage pancreatic cancer), 28B (normal vs. late stage pancreatic cancer), and 28C (normal vs. all pancreatic cancers).

[0183] As shown in Figures 28A to 28C, when a combination of the 15 markers (CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11) was used, the AUC values ​​in the early stage pancreatic cancer, late stage pancreatic cancer, and all stage pancreatic cancer patient groups relative to the normal group were close to 1 (0.95 or higher), the sensitivity was approximately 89% or higher, and the specificity was approximately 85% or higher, confirming that the combination of the 15 markers can accurately and effectively distinguish between the normal group and pancreatic cancer (early stage pancreatic cancer and / or late stage pancreatic cancer) patients.

[0184] In addition, eight markers selected from those listed in Table 3 (Marker Set 3: CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF) were used to analyze samples from a normal group (177 patients) and pancreatic cancer patients (102 patients; 35 patients with early-stage pancreatic cancer and 67 patients with late-stage pancreatic cancer) using logistic regression. The ROC curve analysis results are shown in Figures 29A (normal vs. early-stage pancreatic cancer), 29B (normal vs. late-stage pancreatic cancer), and 29C (normal vs. all pancreatic cancers).

[0185] As shown in Figures 29A to 29C, when the combination of the eight markers (CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF) was used, the AUC values ​​in the early stage pancreatic cancer, late stage pancreatic cancer, and all stage pancreatic cancer patient groups relative to the normal group were close to 1 (0.9 or higher), the sensitivity was approximately 88% or higher, and the specificity was approximately 80% or higher, confirming that the combination of the eight markers can accurately and effectively distinguish between the normal group and pancreatic cancer (early stage pancreatic cancer and / or late stage pancreatic cancer) patients.

[0186] The results of Figures 23 to 29C are summarized in Figure 30.

[0187] Example 7. Model development for pancreatic cancer diagnosis prediction To estimate the predictive model, stepwise logistic regression was performed to select variables (markers), and statistical analysis was performed using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA). To balance underfitting and overfitting of the predictive model, 10-fold cross validation was used for validation and evaluation. The split ratios of the test set and training set were 90:10, 80:20, 75:25, and 70:30. Diagnostic accuracy evaluation indices were calculated for each iteration, and the performance of the model was evaluated by checking the point where the Youden index was maximized from the ROC curve analysis results.

[0188] Odds indicates how many times higher the probability of having pancreatic cancer is compared to the probability of not having pancreatic cancer. If you set it to 1 for pancreatic cancer and 0 for not having pancreatic cancer, you can derive the odds value by applying it to the following formula:

number

[0189] The optimal prediction model was analyzed to determine the optimal marker combinations b0, b1, b2, . . ., b k The regression coefficients can be estimated. By taking the logarithm of both sides of the odds equation, the prediction model can be expressed as follows: X1, X2, X3, ... X k indicates the value of each marker actually measured from the sample (ΔCt value measured by real-time qPCR using the method described in Example 2).

[0190] A comparison of healthy individuals (183 individuals) with early-stage pancreatic cancer (36 individuals) yielded optimal model equations for diagnosing early-stage pancreatic cancer using a combination of 8 markers (Model_R1) and a combination of 13 markers (Model_R2). A comparison of healthy individuals (183 individuals) with overall pancreatic cancer (106 individuals) yielded optimal model equations for diagnosing overall pancreatic cancer using a combination of 11 markers (Model_A1) and a combination of 10 markers (Model_A2) (Table 15). Sample analysis allows for the identification of pancreatic cancer cases by substituting the expression measurements of each marker (ΔCt values ​​measured by real-time qPCR using the method described in Example 2) into the model equation.

[0191] [Table 15-1]

[0192] [Table 15-2]

[0193] Below are the results of analyzing actual patient samples using the Model_R1 logit(p)=35.8476+(-2.5794)×TNF+(3.3956)×IFNG+(-0.5380)×CCL2+(1.4027)×CXCR2+(-1.143)×ARG1+(-4.3771)×SLC27A2+(3.1076)×PTGES2+(-0.6396)×PTGES model equation.

[0194] The analytical value of the sample HV18 patient was 35.8476 + (-2.5794) x 6.503 + (3.3956) x 6.88 + (-0.5380) x 10.72 + (1.4027) x 0.535 + (-1.143) x 7.035 + (-4.3771) x 10.654 + (3.1076) x 5.68 + (-0.6396) x 10.994 = -6.637, which is lower than the cutoff value of -1.855994. Therefore, the HV18 patient can be predicted to be within the normal range, indicating a low likelihood of developing pancreatic cancer. The HV18 patient is actually a sample belonging to the healthy control group.

[0195] The analytical value for the HV119 patient sample was 35.8476 + (-2.5794) x 6.304 + (3.3956) x 9.499 + (-0.5380) x 10.502 + (1.4027) x 1.496 + (-1.143) x 4.878 + (-4.3771) x 9.708 + (3.1076) x 4.963 + (-0.6396) x 11.822 = 8.083, which is higher than the cutoff standard of -1.855994. Therefore, the HV119 patient can be predicted to have a high probability of developing pancreatic cancer. The HV119 patient is indeed a sample belonging to the early-stage pancreatic cancer group.

[0196] The following are the results of analyzing actual patient samples using the Model_R2 logit(p)=44.4033+(-2.8042)×TNF+(3.7082)×IFNG+(0.2358)×IFNL1+(0.1568)×CXCL11+(1.0951)×CLEC7A+(-0.8407)×VEGFA+(-0.6622)×CCL2+(-0.9422)×CXCR4+(1.0804)×CXCR2+(-1.2971)×ARG1+(-4.7971)×SLC27A2+(3.1934)×PTGES2+(-0.7064)×PTGES model equation.

[0197] The analytical value of the sample HV18 patient was: 44.4033 + (-2.8042) × 6.5032 + (3.7082) × 6.8802 + (0.2358) × 9.4032 + (0.1568) × 10.5360 + (1.0951) × 1.4825 + (-0.8407) × 7.7399 + (-0.6622) × 10.7275 + (-0.9422) × 2.9629 + (1.0 The result is "(3.1934) x 0.5352 + (-1.2971) x 7.0352 + (-4.7971) x 10.6540 + (3.1934) x 5.6802 + (-0.7064) x 10.9943 = -8.512", which is lower than the cut-off standard of -1.908747, so HV18 patients can be predicted to be within the normal range with a low probability of developing pancreatic cancer. HV18 patients are actually samples belonging to the healthy control group.

[0198] The analytical value of the sample HV119 patient was: 44.4033 + (-2.8042) x 6.3042 + (3.7082) x 9.4998 + (0.2358) x 7.8130 + (0.1568) x 10.3085 + (1.0951) x 1.1619 + (-0.8407) x 7.0730 + (-0.6622) x 10.5027 + (-0.9422) x 0.0542 + (1.0804) × 1.4966 + (-1.2971) × 4.8782 + (-4.7971) × 9.7083 + (3.1934) × 4.9634 + (-0.7064) × 11.8220 = 9.948, which is higher than the cut-off standard of -1.908747. Therefore, HV119 patients can be predicted to have a high probability of developing pancreatic cancer. HV119 patients are a sample belonging to the actual early-stage pancreatic cancer group.

[0199] Below are the results of analyzing actual patient samples using the Model_A1 logit(p)=36.9898+(-2.220)×TNF+(0.9955)×IFNG+(0.3413)×CXCL11+(-2.799)×VEGFA+(-0.1913)×CCL2+(1.3628)×CCL5+(-2.0521)×CXCR4+(0.7037)×CXCR2+(-0.064)×PTGS2+(-3.1754)×SLC27A2+(4.4765)×PTGES2 model equation.

[0200] The analytical value of the sample HV18 patient was: 36.9898 + (-2.220) x 6.5032 - + (0.9955) x 6.8802 + (0.3413) x 10.5360 + (-2.799) x 7.7399 + (-0.1913) x 10.7275 + (1.3628) x 1.0155 + (-2.0521) x 2.9629 + (0.70 37) × 0.5352 + (-0.064) × 3.9349 + (-3.1754) × 10.6540 + (4.4765) × 5.6802 = -3.693, which is lower than the cut-off standard of -0.251091, so HV18 patients can be predicted to be within the normal range with a low probability of developing pancreatic cancer. HV18 patients are actually samples belonging to the healthy control group.

[0201] The analytical value of the sample HV119 patient was "36.9898 + (-2.220) x 6.3042 + (0.9955) x 9.4998 + (0.3413) x 10.3085 + (-2.799) x 7.0730 + (-0.1913) x 10.5027 + (1.3628) x 0.5032 + (-2.0521) x 0.542 + (0.7037) x 1.4966 + (-0.064) x 5.5966 + (-3.1754) x 9.7083 + (4.4765) x 4.9634 = 6.824", which is higher than the cut-off criterion of -0.251091, and therefore it can be predicted that the HV119 patient has a high possibility of developing pancreatic cancer. The HV119 patient is indeed a sample belonging to the early stage pancreatic cancer group.

[0202] The analytical value for the sample HV131 patient was "36.9898 + (-2.220) x 6.5761 + (0.9955) x 8.7846 + (0.3413) x 10.7145 + (-2.799) x 7.3347 + (-0.1913) x 8.8499 + (1.3628) x 1.5673 + (-2.0521) x 3.4826 + (0.7037) x 2.0970 + (-0.064) x 4.7682 + (-3.1754) x 11.1328 + (4.4765) x 6.3557 = 1.830", which is higher than the cut-off criterion of -0.251091, and therefore it can be predicted that the HV131 patient has a high possibility of developing pancreatic cancer. The HV131 patient is actually a sample belonging to the pancreatic cancer (LAPC; locally advanced pancreatic cancer) group.

[0203] Below are the results of analyzing actual patient samples using the Model_A2 logit(p)=36.6273+(1.0041)×IFNG+(-2.7473)×VEGFA+(-3.199)×SLC27A2+(4.4958)×PTGES2+(-2.2286)×TNF+(-2.0986)×CXCR4+(0.6388)×CXCR2+(1.3874)×CCL5+(-0.224)×CCL2+(0.3704)×CXCL11 model equation.

[0204] The analytical value of the sample HV18 patient was 36.6273 + (1.0041) × 6.8802 + (-2.7473) × 7.7399 + (-3.199) × 10.6540 + (4.4958) × 5.6802 + (-2.2286) × 6.5032 + (-2.0986) × 2.9629 + (0.6388) × 0.5352 + (1.3874) × 1.0155 + (-0.224) × 10.7275 + (0.3704) × 10.5360 = -3.734, which is lower than the cutoff value of -0.290325. Therefore, the HV18 patient can be predicted to be within the normal range, indicating a low probability of developing pancreatic cancer. The HV18 patient is actually a sample belonging to the healthy control group. 15

[0205] The analytical value for the HV119 patient sample was 36.6273 + (1.0041) × 9.4998 + (-2.7473) × 7.0730 + (-3.199) × 9.7083 + (4.4958) × 4.9634 + (-2.2286) × 6.3042 + (-2.0986) × 0.0542 + (0.6388) × 1.4966 + (1.3874) × 0.5032 + (-0.224) × 10.5027 + (0.3704) × 10.3085 = 6.948, which is higher than the cutoff value of -0.290325. Therefore, the HV119 patient can be predicted to have a high probability of developing pancreatic cancer. The HV119 patient is indeed a sample belonging to the early-stage pancreatic cancer group.

[0206] The analytical value for the sample HV131 patient was "36.6273 + (1.0041) × 8.7846 + (-2.7473) × 7.3347 + (-3.199) × 11.1328 + (4.4958) × 6.3557 + (-2.2286) × 6.5761 + (-2.0986) × 3.4826 + (0.6388) × 2.0970 + (1.3874) × 1.5673 + (-0.224) × 8.8499 + (0.3704) × 10.7145 = 1.794", which is higher than the cut-off criterion of -0.290325, and therefore it can be predicted that the HV131 patient has a high possibility of developing pancreatic cancer. The HV131 patient is actually a sample belonging to the pancreatic cancer (LAPC; locally advanced pancreatic cancer) group.

[0207] The results of performance verification of the four models (Model_R1, Model_R2, Model_A1, and Model_A2) are summarized in Table 16 below.

[0208] [Table 16]

[0209] As can be seen in Table 16, all of the pancreatic cancer diagnostic model formulas were confirmed to have high accuracy in diagnosing pancreatic cancer, with sensitivity (86% to 100%) and specificity (86% to 94%).

[0210] A comparison of healthy individuals (183 individuals) with early-stage pancreatic cancer (36 individuals) yielded an optimal model equation (Model_R3) for diagnosing early-stage pancreatic cancer using a combination of eight markers (the same as Marker Set 3). A comparison of healthy individuals (183 individuals) with overall pancreatic cancer (106 individuals) yielded an optimal model equation (Model_A3) for diagnosing overall pancreatic cancer using a combination of eight markers (the same as Marker Set 3) (Table 18). Through sample analysis, the expression measurements of each marker (ΔCt values ​​measured by real-time qPCR using the method described in Example 2) were substituted into the model equation to identify pancreatic cancer cases. The ΔCt values ​​were preprocessed and converted using the Robust Scaler method (using a Python program) and then substituted into the model equation. The preprocessing was performed using the following Equation 5: x' = [x - median(x)] / IQR [Formula 5] (x: ΔCt value for each marker in the diagnostic subject; median(x): median value for each marker in an arbitrary population including the diagnostic subject; IQR (interquartile range): range between the third quartile (Q3) and the first quartile (Q1) (Q3-Q1)).

[0211] [Table 17]

[0212] [Table 18]

[0213] Below are the results of analyzing actual patient samples using the Model_R3 model: logit(p)=-1.9575757578511082+(1.942999)×IFNG+(-2.370157)×SLC27A2+(0.236554)×CCL5+(1.781672)×PTGES2+(-1.328085)×TNF+(-0.170127)×IFNL1+(-0.495828)×CCL2+(0.611586)×CXCR2.

[0214] The analytical value of the sample HV18 patient was "-1.9575757578511082 + (1.942999) × (-1.2370) + (-2.370157) × (-0.1331) + (0.236554) × (-0.4664) + (1.781672) × 0.3444 + (-1.328085) × (-0.5977) + (-0.170127) × (-0.2057) + (-0.495828) × (0.0298) + (0.611586) × (-0.4166) = -2.953", which is lower than the cut-off criterion of 0.282, and therefore it can be predicted that the HV18 patient is within the normal range with a low probability of developing pancreatic cancer. HV18 patients actually belong to the healthy control group.

[0215] The analytical value of the sample HV119 patient was "-1.95757578511082 + (1.942999) × 1.7197 + (-2.370157) × (-1.4376) + (0.236554) × (-1.3830) + (1.781672) × (-1.0756) + (-1.328085) × (-0.8764) + (-0.170127) × (-0.8646) + (-0.495828) × (-0.1705) + (0.611586) × (0.5392) = 4.273", which is higher than the cutoff standard of 0.282, and therefore it can be predicted that the HV119 patient has a high possibility of developing pancreatic cancer. HV119 patients indeed belong to the early stage pancreatic cancer group.

[0216] Below are the results of analyzing actual patient samples using the Model_A3 logit(p) == 0.6543628925241534 + (1.397767) × IFNG + (-1.874652) × SLC27A2 + (0.855608) × CCL5 + (1.782533) × PTGES2 + (-2.378006) × TNF + (-0.000140) × IFNL1 + (-0.535484) × CCL2 + (0.300359) × CXCR2 model equation.

[0217] The analytical value of the sample HV18 patient was "0.6543628925241534 + (1.397767) × (-1.1890) + (-1.874652) × (-0.1430) + (0.855608) × (-0.5804) + (1.782533) × 0.2535 + (-2.378006) × (-0.4540) + (-0.000140) × (-0.1177) + (-0.535484) × 0.1412 + (0.300359) × (-0.2964) = 0.131", which is lower than the cutoff standard of 0.732, so it can be predicted that the HV18 patient is within the normal range with a low probability of developing pancreatic cancer. HV18 patients actually belong to the healthy control group.

[0218] The analytical value of the sample HV119 patient was "0.6543628925241534 + (1.397767) × 1.5295 + (-1.874652) × (-1.5209) + (0.855608) × (-1.4431) + (1.782533) × (-1.2116) + (-2.378006) × (-0.7036) + (-0.000140) × (-0.7524) + (-0.535484) × 0.0158 + (0.300359) × 0.5844 = 4.089", which is higher than the cutoff standard of 0.732, so it can be predicted that the HV119 patient has a high possibility of developing pancreatic cancer. HV119 patients indeed belong to the early stage pancreatic cancer group.

[0219] The analytical value of the sample HV131 patient was "0.6543628925241534 + (1.397767) × 0.78734 + (-1.874652) × 0.55463 + (0.855608) × 0.34889 + (1.782533) × 1.6339 + (-2.378006) × (-0.36270) + (-0.000140) × 0.73377 + (-0.535484) × (-0.90540) + (0.300359) × 1.13440 = 5.614", which is higher than the cutoff standard of 0.732, and therefore it can be predicted that the HV131 patient has a high possibility of developing pancreatic cancer. HV131 patients actually belong to the locally advanced pancreatic cancer (LAPC) group.

Claims

1. a detectable formulation of a biomarker for diagnosing pancreatic cancer, The biomarker for diagnosing pancreatic cancer is one or more selected from the group consisting of SLC27A2, CXCL11, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, PTGES, IFNG, IFNL1, TNF, IFNB1, and IFNA1, or a gene encoding the biomarker, or a combination thereof.

2. The biomarker for diagnosing pancreatic cancer is (1) one or more selected from the group consisting of SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2, and PTGS2; one or more selected from the group consisting of SLC27A2, IFNG, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4, and IFNB1; one or more selected from the group consisting of SLC27A2, IFNL1, IFNG, CXCL11, CCL2, PTGES2, and PTGES; one or more selected from the group consisting of SLC27A2, CCL5, CXCR4, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11; one or more selected from the group consisting of SLC27A2, CCL2, CCL5, CXCR2, IFNL1, IFNG, PTGES2, and TNF; one or more selected from the group consisting of SLC27A2, TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, PTGES2, and PTGES; one or more selected from the group consisting of SLC27A2, TNF, IFNG, CCL2, CXCR2, ARG1, PTGES2, and PTGES; one or more selected from the group consisting of SLC27A2, VEGFA, CXCR4, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2, and CXCL8; one or more selected from the group consisting of SLC27A2, PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, and IFNL1; one or more selected from the group consisting of IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, and PTGES2; one or more selected from the group consisting of SLC27A2, CCL5, PTGS2, CXCR2, CXCR4, CXCL11, PTGES2, TNF, and VEGFA; one or more selected from the group consisting of SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A, and ARG1; one or more selected from the group consisting of SLC27A2, FNG, PTGES2, CCL5, VEGFA, CCL2, TNF, FOXP3, CXCR4, IFNA1, IFNL1, PTGES, CCR5, CLEC7A, IFNB1, CXCR2, and PTGS2; one or more selected from the group consisting of SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, and CLEC7A; one or more selected from the group consisting of SLC27A2, ARG1, CCL2, IFNG, PTGES2, TNF, VEGFA, CXCR4, and CCL5; one or more selected from the group consisting of SLC27A2, TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, and PTGES2; or one or more selected from the group consisting of SLC27A2, IFNG, VEGFA, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2, and CXCL11; (2) the coding gene of (1); or (3) A combination of (1) and (2) above The composition for diagnosing pancreatic cancer according to claim 1,

3. The biomarker for diagnosing pancreatic cancer is (1) one or more selected from the group consisting of SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2, and PTGS2; one or more selected from the group consisting of SLC27A2, IFNG, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4, and IFNB1; one or more selected from the group consisting of SLC27A2, IFNL1, IFNG, CXCL11, CCL2, PTGES2, and PTGES; one or more selected from the group consisting of SLC27A2, CCL5, CXCR4, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11; one or more selected from the group consisting of SLC27A2, CCL2, CCL5, CXCR2, IFNL1, IFNG, PTGES2, and TNF; one or more selected from the group consisting of SLC27A2, TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, PTGES2, and PTGES; or one or more selected from the group consisting of SLC27A2, TNF, IFNG, CCL2, CXCR2, ARG1, PTGES2, and PTGES; (2) the coding gene of (1); or (3) A combination of (1) and (2) above The diagnostic composition for pancreatic cancer according to claim 1, which is for use in diagnosing early-stage pancreatic cancer.

4. The biomarker for diagnosing pancreatic cancer is (1) SLC27A2, ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA; SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2, and PTGS2; SLC27A2, IFNG, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4, and IFNB1; SLC27A2, IFNG, CCL2, TNF, PTGES, FOXP3, PTGES2, CXCR4, and CXCR2; SLC27A2, IFNL1, IFNG, CXCL11, CCL2, PTGES2, and PTGES; SLC27A2, ARG1, CCL2, CLEC7A, IFNG, PTGES, PTGES2, TNF, and FOXP3; SLC27A2, CCL5, CXCR4, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3; SLC27A2, CCL5, CXCR4, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11; SLC27A2, CCL2, CCL5, CXCR2, IFNL1, IFNG, PTGES2, and TNF; SLC27A2, TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, PTGES2, and PTGES; or SLC27A2, TNF, IFNG, CCL2, CXCR2, ARG1, PTGES2, and PTGES; (2) the coding gene of (1); or (3) A combination of (1) and (2) above The diagnostic composition for pancreatic cancer according to claim 1, which is for use in diagnosing early-stage pancreatic cancer.

5. The biomarker for diagnosing pancreatic cancer is (1) one or more selected from the group consisting of SLC27A2, VEGFA, CXCR4, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2, and CXCL8; one or more selected from the group consisting of SLC27A2, PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, and IFNL1; one or more selected from the group consisting of IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, and PTGES2; one or more selected from the group consisting of SLC27A2, CCL5, PTGS2, CXCR2, CXCR4, CXCL11, PTGES2, TNF, and VEGFA; one or more selected from the group consisting of SLC27A2, CCL5, CXCR4, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11; or one or more selected from the group consisting of SLC27A2, CCL2, CCL5, CXCR2, IFNL1, IFNG, PTGES2, and TNF; (2) the coding gene of (2); or (3) A combination of (1) and (2) above The diagnostic composition for pancreatic cancer according to claim 1, which is for use in diagnosing late-stage pancreatic cancer.

6. The biomarker for diagnosing pancreatic cancer is (1) SLC27A2, ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA; SLC27A2, VEGFA, CXCR4, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2, and CXCL8; SLC27A2, PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, and IFNL1; SLC27A2, VEGFA, CXCR4, TNF, PTGES2, CCL5, CXCR2, FOXP3, PTGS2, and CXCL8; IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, and PTGES2; SLC27A2, CCL5, PTGS2, CXCR2, CXCR4, CXCL11, PTGES2, TNF, and VEGFA; SLC27A2, CCL5, CXCR4, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3; SLC27A2, CCL5, CXCR4, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11; or SLC27A2, CCL2, CCL5, CXCR2, IFNL1, IFNG, PTGES2, and TNF; (2) the coding gene of (1); or (3) A combination of (1) and (2) above The diagnostic composition for pancreatic cancer according to claim 1, which is for use in diagnosing late-stage pancreatic cancer.

7. The biomarker for diagnosing pancreatic cancer is (1) one or more selected from the group consisting of SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A, and ARG1; one or more selected from the group consisting of SLC27A2, IFNG, PTGES2, CCL5, VEGFA, CCL2, TNF, FOXP3, CXCR4, IFNA1, IFNL1, PTGES, CCR5, CLEC7A, IFNB1, CXCR2, and PTGS2; one or more selected from the group consisting of SLC27A2, ARG1, CCL2, IFNG, PTGES2, TNF, VEGFA, CXCR4, and CCL5; one or more selected from the group consisting of SLC27A2, CCL5, CXCR4, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11; one or more selected from the group consisting of SLC27A2, CCL2, CCL5, CXCR2, IFNL1, IFNG, PTGES2, and TNF; one or more selected from the group consisting of SLC27A2, TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, and PTGES2; or one or more selected from the group consisting of SLC27A2, IFNG, VEGFA, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2, and CXCL11; (2) a coding gene for the above 1; or (3) A combination of 1 and 2 above The diagnostic composition for pancreatic cancer according to claim 1, which is for use in diagnosing early stage pancreatic cancer, late stage pancreatic cancer, or all of these.

8. The biomarker for diagnosing pancreatic cancer is (1) SLC27A2, ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA; SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A, and ARG1; SLC27A2, IFNG, PTGES2, CCL5, VEGFA, CCL2, TNF, FOXP3, CXCR4, IFNA1, IFNL1, PTGES, CCR5, CLEC7A, IFNB1, CXCR2, and PTGS2; SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, and CLEC7A; IFNG, CCL2, and PTGES2; SLC27A2, ARG1, CCL2, IFNG, PTGES2, TNF, VEGFA, CXCR4, and CCL5; SLC27A2, CCL5, CXCR4, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3; SLC27A2, CCL5, CXCR4, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11; SLC27A2, CCL2, CCL5, CXCR2, IFNL1, IFNG, PTGES2, and TNF; SLC27A2, TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, and PTGES2; or SLC27A2, IFNG, VEGFA, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2, and CXCL11; (2) the coding gene of (1); or (3) A combination of (1) and (2) above The diagnostic composition for pancreatic cancer according to claim 1, which is for use in diagnosing early stage pancreatic cancer, late stage pancreatic cancer, or all of these.

9. the biomarker for diagnosing pancreatic cancer is one or more selected from the group consisting of IFNB1 and IFNA1, a gene encoding the one or more, or a combination thereof; The composition for diagnosing pancreatic cancer according to claim 1, which distinguishes early stage pancreatic cancer, late stage pancreatic cancer, or all of these from pancreatic diseases other than pancreatic cancer.

10. The biomarker for diagnosing pancreatic cancer is a biomarker set selected from the following, its encoding genes, or a combination thereof: The pancreatic cancer diagnostic composition according to claim 1, for use in diagnosing early stage pancreatic cancer, late stage pancreatic cancer, or all of these: SLC27A2, ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF, and VEGFA; SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2, and PTGS2; SLC27A2, IFNG, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4, and IFNB1; SLC27A2, IFNG, CCL2, TNF, PTGES, FOXP3, PTGES2, CXCR4, and CXCR2; SLC27A2, IFNL1, IFNG, CXCL11, CCL2, PTGES2, and PTGES; SLC27A2, ARG1, CCL2, CLEC7A, IFNG, PTGES, PTGES2, TNF, and FOXP3; SLC27A2, CCL5, CXCR4, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3; SLC27A2, CCL5, CXCR4, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11; SLC27A2, CCL2, CCL5, CXCR2, IFNL1, IFNG, PTGES2, and TNF; SLC27A2, TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, PTGES2, and PTGES; SLC27A2, TNF, IFNG, CCL2, CXCR2, ARG1, PTGES2, and PTGES; SLC27A2, VEGFA, CXCR4, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2, and CXCL8; SLC27A2, PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, and IFNL1; SLC27A2, VEGFA, CXCR4, TNF, PTGES2, CCL5, CXCR2, FOXP3, PTGS2, and CXCL8; IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, and PTGES2; SLC27A2, CCL5, PTGS2, CXCR2, CXCR4, CXCL11, PTGES2, TNF, and VEGFA; SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A, and ARG1; SLC27A2, IFNG, PTGES2, CCL5, VEGFA, CCL2, TNF, FOXP3, CXCR4, IFNA1, IFNL1, PTGES, CCR5, CLEC7A, IFNB1, CXCR2, and PTGS2; SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, and CLEC7A; IFNG, CCL2, and PTGES2; SLC27A2, ARG1, CCL2, IFNG, PTGES2, TNF, VEGFA, CXCR4, and CCL5; SLC27A2, TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, and PTGES2; and SLC27A2, IFNG, VEGFA, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2, and CXCL11.

11. The composition for diagnosing pancreatic cancer according to any one of claims 1 to 10, which is for use on a blood-derived buffy coat.

12. The buffy coat is a total white blood cell layer formed between an upper plasma layer and a lower red blood cell layer when blood is centrifuged, and is obtained from the middle buffy coat layer among a plasma layer (upper), a buffy coat layer (middle), and a red blood cell layer (lower) obtained sequentially from the top by centrifuging blood under one or more conditions selected from the following conditions (1) to (3): (1) Temperature: 2-30℃; (2) Speed: 300g to 2000g; and (3) Time: 5 to 20 minutes.

13. The pancreatic cancer diagnostic composition according to claim 11, wherein the buffy coat is obtained from the middle buffy coat layer among a plasma layer (top), a buffy coat layer (middle), and a red blood cell layer (bottom) obtained in this order from the top when blood is centrifuged under one or more conditions selected from the following conditions (1) to (3): (1) Temperature: 4-25℃; (2) Speed: 500g to 1800g; and (3) Time: 7 to 20 minutes.

14. The composition for diagnosing pancreatic cancer according to any one of claims 1 to 10, wherein the detectable agent is one or more selected from the group consisting of small molecule compounds, proteins, peptides, and nucleic acid molecules that bind to the biomarker for diagnosing pancreatic cancer.

15. A kit for diagnosing pancreatic cancer, comprising the composition for diagnosing pancreatic cancer according to any one of claims 1 to 10.

16. The kit for diagnosing pancreatic cancer according to claim 15, which is for use with blood-derived buffy coat.

17. detecting a biomarker for diagnosing pancreatic cancer from a blood sample isolated from the subject; A method for providing information for diagnosing pancreatic cancer, wherein the biomarker for diagnosing pancreatic cancer is one or more selected from the group consisting of SLC27A2, IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, and PTGES, or their encoding genes, or a combination thereof.

18. 18. The method of providing information on pancreatic cancer diagnosis of claim 17, wherein the blood sample is a blood-derived buffy coat.

19. The buffy coat is a total white blood cell layer formed between an upper plasma layer and a lower red blood cell layer when blood is centrifuged, and is obtained from the middle buffy coat layer among a plasma layer (upper), a buffy coat layer (middle), and a red blood cell layer (lower) obtained sequentially from the top by centrifuging blood under one or more conditions selected from the following conditions (1) to (3): (1) Temperature: 2-30℃; (2) Speed: 300g to 2000g; and (3) Time: 5 to 20 minutes.

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