Composition for diagnosing pancreatic cancer

Abstract

Provided are a biomarker for diagnosing pancreatic cancer, a composition containing an agent capable of detecting the biomarker for diagnosing pancreatic cancer, and a method for diagnosing pancreatic cancer using the same.

Description

Technical Field

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority and the benefit of priority to Korean Patent Application No. 10-2022-0123808, filed on September 28, 2022, the disclosure of which is incorporated herein by reference in its entirety.

[0003] The present disclosure relates to a biomarker for diagnosing pancreatic cancer; a composition for diagnosing pancreatic cancer, comprising an agent capable of detecting the biomarker; and a method of diagnosing pancreatic cancer using the same. Background Art

[0004] Biomarkers refer to indicators that can identify changes caused in a living organism due to external influences and are actively studied for diagnosing various diseases (such as cancer and neurological diseases) or predicting the efficacy of specific therapeutic agents.

[0005] The pancreas is an organ about 20 cm long located behind the stomach, secreting digestive enzymes and hormones. Generally, pancreatic cancer may refer to pancreatic ductal adenocarcinoma. With the widespread adoption of Western-type eating habits, the incidence of pancreatic cancer has increased, and it is known that men are more frequently diagnosed with the disease, with a high mortality rate.

[0006] Pancreatic cancer is associated with various risk factors, including smoking, coffee drinking, alcohol consumption, a meat-rich diet, diabetes, a history of chronic pancreatitis and non-polyposis colorectal cancer syndrome. In addition, exposure to substances such as beta-naphthylamine and benzidine has been implicated as a potential cause.

[0007] In its early stages, pancreatic cancer often has no obvious symptoms. Symptoms such as pain and weight loss usually only appear after the cancer has metastasized throughout the body, contributing to its high mortality rate.

[0008] In order to be able to treat pancreatic cancer more effectively, it is necessary to develop technologies for early diagnosis, determination of disease progression, and differentiation from other similar diseases. Summary of the invention

[0009] Technical issues

[0010] One embodiment provides a biomarker for diagnosing pancreatic cancer, comprising at least one 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 its encoding gene. The biomarker can be used for the detection or analysis of the buffy coat of blood.

[0011] Another embodiment provides a composition for diagnosing pancreatic cancer or a kit for diagnosing pancreatic cancer, comprising a reagent capable of detecting at least one of 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 its encoding gene. The composition or kit for diagnosing pancreatic cancer can be used for the white blood cell layer of blood.

[0012] Another embodiment provides a method for diagnosing pancreatic cancer or a method for providing information for diagnosing pancreatic cancer, the method comprising the step of detecting at least one of 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 genes encoding the same in a blood sample separated from a subject. The blood sample may include a buffy coat of blood. The detection step may include determining the presence or absence and / or measuring the level of at least one of 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 in a blood sample.

[0013] Another embodiment provides a method for detecting at least one of 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 its encoding gene in diagnosing pancreatic cancer and / or in manufacturing a composition for diagnosing pancreatic cancer or a kit for diagnosing pancreatic cancer. Pancreatic cancer diagnosis can be performed using a blood buffy coat, or a composition or kit for diagnosing pancreatic cancer can be used for a blood buffy coat.

[0014] Pancreatic cancer can include early-stage pancreatic cancer, advanced-stage pancreatic cancer, or both.

[0015] Technical Solution

[0016] Hereinafter, a detailed description of the present disclosure will be given:

[0017] Diagnosis of Pancreatic Cancer

[0018] As used herein, the term "pancreatic cancer" refers collectively to tumors arising in the pancreas, which may include benign tumors, such as cystic tumors, such as serous cystic tumors, mucinous cystic tumors, intraductal papillary mucinous tumors, solid pseudopapillary tumors, lymphoepithelial cysts, and cystic teratomas, as well as malignant tumors, such as pancreatic ductal adenocarcinoma, acinar cell carcinoma, and neuroendocrine tumors. The pancreatic cancer that can be diagnosed using the biomarkers provided in the present disclosure can be selected from the above-mentioned pancreatic cancers, and for example, can be selected from malignant tumors, but is not limited thereto.

[0019] In addition, the term "pancreatic cancer" as used herein can be classified based on its stage of progression and can refer to early pancreatic cancer (e.g., resectable pancreatic cancer) and / or advanced pancreatic cancer (e.g., borderline resectable pancreatic cancer, locally advanced pancreatic cancer, or metastatic pancreatic cancer), etc., or can include all of them.

[0020] As used herein, the term "diagnosis" may include, but is not limited to, determining a subject's susceptibility to a particular disease or condition, determining whether a subject currently has a particular disease or condition, assessing the risk of developing a particular disease or condition, prognostic determination for a subject with a particular disease or condition (e.g., identifying a pre-metastatic or metastatic cancer state, determining the stage of a cancer, assessing the response of a cancer to treatment, etc.), and / or treatment measurement, such as monitoring a subject's status to provide information about the effectiveness of a treatment.

[0021] The term "diagnosis of pancreatic cancer" herein may refer to identifying the presence, likelihood (risk) of onset and / or progression of pancreatic cancer (e.g., early pancreatic cancer, advanced pancreatic cancer, or both) in a subject, and / or distinguishing pancreatic cancer from normal conditions or other similar diseases (e.g., benign pancreatic diseases (pancreatitis (chronic and / or acute pancreatitis), benign pancreatic tumors, intraductal papillary mucinous neoplasms (IPMN), autoimmune pancreatitis (AIP), other pancreatic disorders (excluding pancreatic malignancies), etc., and biliary tract cancer).

[0022] Biomarkers for diagnosing pancreatic cancer

[0023] In the present disclosure, at least one, for example, one or more (for example, a combination of two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen or twenty) are provided as biomarkers for diagnosing pancreatic cancer. The biomarkers described in the present disclosure may refer to at least one of the above proteins and / or their encoding genes.

[0024] In a specific embodiment, the biomarker for diagnosing pancreatic cancer can be IFNL1, its encoding gene or its combination. Biomarker can be characterized as, compared with a reference sample (e.g., a normal sample), the expression level and / or concentration in a pancreatic cancer sample (e.g., a sample of early pancreatic cancer, late pancreatic cancer or all pancreatic cancers, and has nothing to do with the cancer stage (early pancreatic cancer and late pancreatic cancer)) is high (increased). Biomarker can be used for diagnosing pancreatic cancer, including early pancreatic cancer, late pancreatic cancer or all pancreatic cancers, and has nothing to do with the cancer stage (early pancreatic cancer and late pancreatic cancer).

[0025] In another specific embodiment, the biomarker for diagnosing pancreatic cancer can be IFNG, its encoding gene or a combination thereof. The biomarker can be characterized as, compared with a reference sample (e.g., a normal sample), the expression level and / or concentration in a pancreatic cancer sample (e.g., an example of early pancreatic cancer, advanced pancreatic cancer or all pancreatic cancers, regardless of the cancer stage (early pancreatic cancer and advanced pancreatic cancer)) is low (reduced). The biomarker can be used to diagnose pancreatic cancer, including early pancreatic cancer, advanced pancreatic cancer or all pancreatic cancers, regardless of the cancer stage (early pancreatic cancer and advanced pancreatic cancer).

[0026] In another specific embodiment, the biomarker for diagnosing pancreatic cancer can be CXCL11, its encoding gene or a combination thereof. The biomarker can be characterized as, compared with a reference sample (e.g., a normal sample), the expression level and / or concentration in the early pancreatic cancer sample is high (increased), and / or the expression level and / or concentration in the late pancreatic cancer sample is low (reduced). The biomarker can be used to diagnose pancreatic cancer, including, for example, early pancreatic cancer and / or late pancreatic cancer.

[0027] In another specific embodiment, the biomarker for diagnosing pancreatic cancer can be TNF, its encoding gene or a combination thereof. The biomarker can be characterized as, compared with a reference sample (e.g., a normal sample), the expression level and / or concentration in a pancreatic cancer sample (e.g., an example of early pancreatic cancer, advanced pancreatic cancer or all pancreatic cancers, regardless of the cancer stage) is high (increased). The biomarker can be used to diagnose pancreatic cancer, including early pancreatic cancer, advanced pancreatic cancer or all pancreatic cancers, regardless of the cancer stage (early pancreatic cancer and advanced pancreatic cancer).

[0028] In another specific embodiment, the biomarker for diagnosing pancreatic cancer can be CLEC7A, its encoding gene or a combination thereof. The biomarker can be characterized as, compared with a reference sample (e.g., a normal sample), the expression level and / or concentration in the advanced pancreatic cancer sample is high (increased), and / or the expression level and / or concentration in the early pancreatic cancer sample is low (decreased). The biomarker can be used to diagnose pancreatic cancer, such as advanced pancreatic cancer and / or early pancreatic cancer.

[0029] In another specific embodiment, the biomarker for diagnosing pancreatic cancer can be CXCL8, its encoding gene or a combination thereof. The biomarker can be characterized as, compared with a reference sample (e.g., a normal sample), the expression level and / or concentration in a pancreatic cancer sample (e.g., early pancreatic cancer, advanced pancreatic cancer or all pancreatic cancers, regardless of the cancer stage) is high (increased). The biomarker can be used to diagnose pancreatic cancer, including early pancreatic cancer, advanced pancreatic cancer or all pancreatic cancers, regardless of the cancer stage (early pancreatic cancer and advanced pancreatic cancer).

[0030] In another specific embodiment, the biomarker for diagnosing pancreatic cancer can be FOXP3, its encoding gene or a combination thereof. The biomarker can be characterized as, compared with a reference sample (e.g., a normal sample), the expression level and / or concentration in the advanced pancreatic cancer sample is low (decreased), and / or the expression level and / or concentration in the early pancreatic cancer sample is high (increased). The biomarker can be used to diagnose pancreatic cancer, such as early pancreatic cancer and / or advanced pancreatic cancer.

[0031] In another specific embodiment, the biomarker for diagnosing pancreatic cancer can be VEGFA, its encoding gene or a combination thereof. The biomarker can be characterized as, compared with a reference sample (e.g., a normal sample), the expression level and / or concentration in a pancreatic cancer sample (e.g., a sample of early pancreatic cancer, late pancreatic cancer or all pancreatic cancers, and has nothing to do with the cancer stage (early pancreatic cancer and late pancreatic cancer)) is high (increased). The biomarker can be used to diagnose pancreatic cancer, such as early pancreatic cancer, late pancreatic cancer or all pancreatic cancers, and has nothing to do with the cancer stage (early pancreatic cancer and late pancreatic cancer).

[0032] In another specific embodiment, the biomarker for diagnosing pancreatic cancer can be CCL2, its encoding gene or a combination thereof. The biomarker can be characterized as, compared to a reference sample (e.g., a normal sample), the expression level and / or concentration in a pancreatic cancer sample (e.g., an example of early pancreatic cancer, advanced pancreatic cancer or all pancreatic cancers, regardless of the cancer stage (early pancreatic cancer and advanced pancreatic cancer)) is high (increased). The biomarker can be used to diagnose pancreatic cancer, such as early pancreatic cancer, advanced pancreatic cancer or all pancreatic cancers, regardless of the cancer stage (early pancreatic cancer and advanced pancreatic cancer).

[0033] In another specific embodiment, the biomarker for diagnosing pancreatic cancer can be CCL5, its encoding gene or a combination thereof. The biomarker can be characterized as a low (lower) expression level and / or concentration in a pancreatic cancer sample (e.g., a sample of early pancreatic cancer, advanced pancreatic cancer or all pancreatic cancers, regardless of the cancer stage (early pancreatic cancer and advanced pancreatic cancer)) compared to a reference sample (e.g., a normal sample). The biomarker can be used to diagnose pancreatic cancer, such as early pancreatic cancer, advanced pancreatic cancer or all pancreatic cancers, regardless of the cancer stage (early pancreatic cancer and advanced pancreatic cancer).

[0034] In another specific embodiment, the biomarker for diagnosing pancreatic cancer can be CCR5, its encoding gene or a combination thereof. The biomarker can be characterized as, compared with a reference sample (e.g., a normal sample), the expression level and / or concentration in the advanced pancreatic cancer sample is low (reduced), and / or the expression level and / or concentration in the early pancreatic cancer sample is high (increased). The biomarker can be used to diagnose pancreatic cancer, such as early pancreatic cancer and / or advanced pancreatic cancer.

[0035] In another specific embodiment, the biomarker for diagnosing pancreatic cancer can be CXCR4, its encoding gene or a combination thereof. The biomarker can be characterized as, compared with a reference sample (e.g., a normal sample), the expression level and / or concentration in a pancreatic cancer sample (e.g., a sample of early pancreatic cancer, late pancreatic cancer or all pancreatic cancers, and has nothing to do with the cancer stage (early pancreatic cancer and late pancreatic cancer)) is high (increased). The biomarker can be used to diagnose pancreatic cancer, such as early pancreatic cancer, late pancreatic cancer or all pancreatic cancers, and has nothing to do with the cancer stage (early pancreatic cancer and late pancreatic cancer).

[0036] In another specific embodiment, the biomarker for diagnosing pancreatic cancer can be ARG1, its encoding gene or a combination thereof. The biomarker can be characterized as a high (increased) expression level and / or concentration in a pancreatic cancer sample (e.g., a sample of early pancreatic cancer, advanced pancreatic cancer or all pancreatic cancers, regardless of the cancer stage (early pancreatic cancer and advanced pancreatic cancer)) compared to a reference sample (e.g., a normal sample). The biomarker can be used to diagnose pancreatic cancer, such as early pancreatic cancer, advanced pancreatic cancer or all pancreatic cancers, regardless of the cancer stage (early pancreatic cancer and advanced pancreatic cancer).

[0037] In another specific embodiment, the biomarker for diagnosing pancreatic cancer can be CXCR2, its encoding gene or a combination thereof. The biomarker can be characterized as, compared with a reference sample (e.g., a normal sample), the expression level and / or concentration in the advanced pancreatic cancer sample is high (increased), and / or the expression level and / or concentration in the early pancreatic cancer sample is low (reduced). The biomarker can be used to diagnose pancreatic cancer, such as early pancreatic cancer and / or advanced pancreatic cancer.

[0038] In another specific embodiment, the biomarker for diagnosing pancreatic cancer can be PTGS2, its encoding gene or a combination thereof. The biomarker can be characterized as, compared with a reference sample (e.g., a normal sample), the expression level and / or concentration in a pancreatic cancer sample (e.g., a sample of early pancreatic cancer, advanced pancreatic cancer or all pancreatic cancers, regardless of the cancer stage (early pancreatic cancer and advanced pancreatic cancer)) is high (increased). The biomarker can be used to diagnose pancreatic cancer, such as early pancreatic cancer, advanced pancreatic cancer or all pancreatic cancers, regardless of the cancer stage (early pancreatic cancer and advanced pancreatic cancer).

[0039] In another specific embodiment, the biomarker for diagnosing pancreatic cancer can be PTGES2, its encoding gene or its combination. Biomarker can be characterized as, compared with a reference sample (e.g., a normal sample), the expression level and / or concentration in a pancreatic cancer sample (e.g., a sample of early pancreatic cancer, late pancreatic cancer or all pancreatic cancers, and has nothing to do with the cancer stage (early pancreatic cancer and late pancreatic cancer)) is low (reduced). Biomarker can be used for diagnosing pancreatic cancer, such as early pancreatic cancer, late pancreatic cancer or all pancreatic cancers, and has nothing to do with the cancer stage (early pancreatic cancer and late pancreatic cancer).

[0040] In another specific embodiment, the biomarker for diagnosing pancreatic cancer can be SLC27A2, its encoding gene or a combination thereof. The biomarker can be characterized as a high (increased) expression level and / or concentration in a pancreatic cancer sample (e.g., a sample of early pancreatic cancer, advanced pancreatic cancer, or all pancreatic cancers, regardless of the cancer stage (early pancreatic cancer and advanced pancreatic cancer)) compared to a reference sample (e.g., a normal sample). The biomarker can be used to diagnose pancreatic cancer, such as early pancreatic cancer, advanced pancreatic cancer, or all pancreatic cancers, regardless of the cancer stage (early pancreatic cancer and advanced pancreatic cancer).

[0041] In another specific embodiment, the biomarker for diagnosing pancreatic cancer can be PTGES, its encoding gene or its combination. Biomarker can be characterized as, compared with a reference sample (e.g., a normal sample), the expression level and / or concentration in a pancreatic cancer sample (e.g., a sample of early pancreatic cancer, late pancreatic cancer or all pancreatic cancers, and has nothing to do with the cancer stage (early pancreatic cancer and late pancreatic cancer)) is high (increased). Biomarker can be used for diagnosing pancreatic cancer, such as early pancreatic cancer, late pancreatic cancer or all pancreatic cancers, and has nothing to do with the cancer stage (early pancreatic cancer and late pancreatic cancer).

[0042] In another specific embodiment, the biomarker for diagnosing pancreatic cancer can be at least one (one or two) selected from the group consisting of IFNB1 and IFNA1, its encoding gene or a combination thereof. The biomarker can be characterized as a low (reduced) expression level and / or concentration in a pancreatic cancer sample compared to samples from similar diseases (e.g., benign pancreatic diseases (pancreatitis (chronic and / or acute pancreatitis), benign pancreatic tumors, intraductal papillary mucinous neoplasms (IPMN), autoimmune pancreatitis (AIP), other pancreatic disorders (excluding pancreatic malignancies), etc.). The biomarker can be used to diagnose pancreatic cancer, especially early pancreatic cancer, and / or to distinguish pancreatic cancer from benign pancreatic diseases (e.g., pancreatitis (chronic pancreatitis and / or acute pancreatitis), benign pancreatic tumors, intraductal papillary mucinous neoplasms (IPMN), autoimmune pancreatitis (AIP) and other pancreatic diseases (excluding pancreatic cancer (pancreatic malignancies) and / or bile duct cancer).

[0043] The 20 types of biomarkers may be derived from mammals, such as primates (including humans, monkeys, etc.) and rodents (such as mice, rats, etc.), but are not limited thereto.

[0044] Details of the biomarkers are given in Table 1 below.

[0045] Table 1

[0046]

[0047]

[0048] Reagents capable of detecting biomarkers

[0049] As used herein, the term "detection of a biomarker" may refer to determining the presence or absence of a biomarker in a sample and / or measuring the level (concentration) of a biomarker in a sample.

[0050] Herein, the reagent capable of detecting at least one biomarker and its encoding gene 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 one or more selected from the group (for example, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 or 20)) can be selected from small molecule compounds, proteins and nucleic acid molecules that can bind to the biomarkers.

[0051] In one embodiment, when the biomarker is at least one protein 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, the reagent capable of detecting the biomarker can be selected from the group consisting of: proteins (e.g., antibodies, antigen-binding fragments of antibodies, antibody mimetics containing antigen-binding fragments, receptors, etc.), peptides, nucleic acid molecules (e.g., polynucleotides, oligonucleotides, etc.) and small molecule compounds (chemicals, small molecules), all of which bind to the biomarker, but are not limited to this.

[0052] In another embodiment, when the biomarker is at least one gene selected from the group consisting of genes encoding IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CCL25, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2 and PTGES (for example, one or more (for example, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 or 20) genes (full-length DNA, cDNA or mRNA) selected from the group), the reagent capable of detecting the biomarker can be selected from the group consisting of nucleic acid molecules (for example, oligonucleotides, polynucleotides, primers, probes, nucleic acid aptamers, antisense oligonucleotides, etc.), small molecule compounds, proteins and peptides, all of which can bind to (or hybridize with) the biomarker genes, but are not limited thereto.

[0053] The detectable agent of the biomarker may be labeled with a conventional labeling substance or may be unlabeled, such as a fluorescent substance, a chromogenic substance, a luminescent substance, a radioactive isotope or a heavy metal.

[0054] In one embodiment, when the biomarker is at least one protein 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., 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) proteins selected from the group), conventional protein detection (or measurement or analysis) methods such as enzymatic reaction, fluorescence, luminescence and / or radiation detection can be used for detection of the biomarker. Specifically, detection can be performed using a method selected from the group consisting of immunochromatography, immunohistochemical staining, enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (RIA), enzyme immunoassay (EIA), fluorescent immunoassay (FIA), luminescent immunoassay (LIA), Western blotting, microarray and flow cytometry, but is not limited thereto.

[0055] In another embodiment, when the biomarker is at least one gene (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., 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) genes selected from the group), conventional gene detection (or measurement or analysis) methods can be used for the detection of biomarkers. For example, conventional gene analysis methods using primers, probes, aptamers or antisense oligonucleotides that can hybridize with genes can be used. Specifically, polymerase chain reaction (PCR) (e.g., qPCR, real-time PCR, real-time qPCR, fluorescence in situ hybridization (FISH), Southern blotting and microarray methods can be used for detection, but are not limited thereto. In a specific embodiment, the primers can detect a continuous 5-1000 bp sequence within a gene (full-length DNA, cDNA or mRNA), such as 10-500 bp, 20-200 bp or 50-200 bp. The primer pair can include sequences that can hybridize (e.g., be complementary) to continuous 5' and 3' terminal sequences of 5-100 bp (e.g., 5-50 bp, 5-30 bp or 10-25 bp) within the gene fragment.

[0056] Probe, aptamer or antisense oligonucleotide can have the total length of 5-1000bp, 5-500bp, 5-200bp, 5-100bp, 5-50bp, 5-30bp or 5-25bp. These molecules can have complementary sequences, which can be combined with or hybridized to the continuous 5-1000bp, 5-500bp, 5-200bp, 5-100bp, 5-50bp, 5-30bp or 5-25bp sequence in the marker gene (full-length DNA, cDNA or mRNA). The term "can be combined" can refer to the ability to combine all or part of the gene by chemical and / or physical interactions (such as covalent bonding). The term "can hybridize" can refer to the ability to form a complementary combination with at least 80% sequence complementarity, such as 90% or more, 95% or more, 98% or more, 99% or more or 100%.

[0057] Biomarker detection

[0058] Herein, as mentioned above, the term "detection of a biomarker" may refer to determining the presence or absence and / or measuring the level (concentration) of a biomarker.

[0059] When the biomarker is a protein, its detection can be carried out by conventional protein detection methods, for example, a method selected from the group consisting of: immunochromatography, immunohistochemical staining, enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (RIA), enzyme immunoassay (EIA), fluorescent immunoassay (FIA), luminescent immunoassay (LIA), Western blotting, microarray and flow cytometry, but not limited thereto.

[0060] When the biomarker is a gene, its detection can be performed by conventional gene detection methods, for example, a method selected from the group consisting of: polymerase chain reaction (PCR) (e.g., qPCR, real-time PCR, real-time qPCR, etc.), fluorescence in situ hybridization (FISH), Southern blotting, microarray technology, but not limited thereto.

[0061] In the present disclosure, "measurement of biomarker levels" can be performed by qualitative and / or quantitative analysis of the results obtained from the above-mentioned biomarker detection methods (for proteins and / or genes).

[0062] In one embodiment, when a labeled detection agent is used, the level of the biomarker can be measured by qualitative analysis of signal intensity by conventional methods (e.g., comparing the intensity or area of ​​fluorescence and / or luminescence, or the thickness and / or darkness of a gel electrophoresis band relative to a control sample), or by quantitative analysis by conventional methods (e.g., by numerically evaluating the intensity or area of ​​fluorescence and / or luminescence, or the thickness and / or darkness of a gel electrophoresis band), but is not limited thereto.

[0063] In another embodiment, when conventional polymerase chain reaction (PCR; such as qPCR, real-time PCR, real-time qPCR, etc.) is used, conventional quantitative PCR methods can be used to measure the level of biomarkers, for example, by measuring Ct (cycle threshold) values, ΔCt values ​​(ΔCt = Ct (gene) - Ct (control gene)) and / or ΔΔCt values ​​(ΔΔCt = ΔCt (target gene) - ΔCt (reference gene)), but are not limited thereto.

[0064] In yet another embodiment, the measurement of biomarker levels may also include an additional step of performing conventional statistical analysis on the quantified biomarker levels (e.g., in the case of PCR, Ct, ΔCt and / or ΔΔCt values). Here, statistical analysis is intended to cover all conventional statistical analysis tools, including various machine learning models and / or algorithms. Examples of such statistical analysis include, but are not limited to, regression analysis (e.g., logistic regression, stepwise logistic regression, etc.), integration, decision trees, random forests, gradient boosting, XGBoost, Light GBM (light gradient boosting machine), Gaussian naive Bayes, SVM (support vector machine), Bagging (guided aggregation), Boosting, etc. For example, regression analysis (e.g., logistic regression, stepwise logistic regression, etc.) and other appropriate statistical analysis (e.g., one or more of the aforementioned methods) may be used as needed for statistical analysis.

[0065] Compositions and kits for diagnosing pancreatic cancer

[0066] The compositions provided herein for diagnosing pancreatic cancer may include reagents capable of detecting the above-mentioned biomarkers.

[0067] The kits for diagnosing pancreatic cancer provided herein (also referred to as biosensors) can include reagents capable of detecting biomarkers or compositions for diagnosing pancreatic cancer containing such reagents. In one embodiment, the kit for diagnosing pancreatic cancer can include reagents (reagents capable of detecting biomarkers) or compositions for diagnosing pancreatic cancer in conventional formats (e.g., microarrays or panels).

[0068] The kit for diagnosing pancreatic cancer may also include a detection means. The detection means may be a tool capable of qualitatively and / or quantitatively analyzing the presence and / or level of a biomarker detected by a reagent capable of detecting a biomarker. In one embodiment, the detection means may be selected from the aforementioned protein and / or gene detection methods.

[0069] In one embodiment, the kit may be an RT-PCR kit, a DNA chip kit, an ELISA kit, a protein chip kit, a rapid diagnosis kit, or a multiple reaction monitoring (MRM) kit, but is not limited thereto.

[0070] In a specific embodiment, the composition and / or kit for diagnosing pancreatic cancer may include a reagent capable of detecting at least one biomarker 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., 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); genes encoding them, or a combination thereof. The pancreatic cancer that can be diagnosed using the composition or kit may be early pancreatic cancer, advanced pancreatic cancer, or both.

[0071] In another embodiment, the composition and / or kit for diagnosing pancreatic cancer may comprise an agent capable of detecting at least one 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., 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 , 15, 16, 17, 18, 19 or 20)), or at least one 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., 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); genes encoding them; or a combination thereof. In this regard, the pancreatic cancer that can be diagnosed using the composition or kit can be early pancreatic cancer, advanced pancreatic cancer, or both.

[0072] In one embodiment, the composition and / or kit for diagnosing pancreatic cancer may comprise at least one reagent capable of detecting at least one biomarker selected from the following group:

[0073] At least one 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., 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), genes encoding them or a combination thereof;

[0074] At least one selected from the group consisting of: SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2 and PTGS2 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13) selected from the group), genes encoding them or a combination thereof;

[0075] At least one selected from the group consisting of IFNG, SLC27A2, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4 and IFNB1 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13) selected from the group), genes encoding them or a combination thereof;

[0076] At least one selected from the group consisting of: SLC27A2, IFNG, CCL2, TNF, PTGES, FOXP3, PTGES2, CXCR4 and CXCR2 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8 or 9) selected from the group), genes encoding them or a combination thereof;

[0077] At least one selected from the group consisting of IFNL1, IFNG, CXCL11, CCL2, PTGES2, SLC27A2 and PTGES (e.g., one or more (e.g., 2, 3, 4, 5, 6 or 7) selected from the group), genes encoding them or a combination thereof;

[0078] At least one selected from the group consisting of ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF and FOXP3 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8 or 9) selected from the group), genes encoding them or a combination thereof;

[0079] At least one selected from the group consisting of: CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES and FOXP3 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12) selected from the group), genes encoding them or a combination thereof;

[0080] At least one selected from the group consisting of: CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2 and CXCL11 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15) selected from the group), genes encoding them or a combination thereof;

[0081] At least one selected from the group consisting of: CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2 and TNF (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7 or 8) selected from the group), genes encoding them or a combination thereof;

[0082] At least one selected from the group consisting of: TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, SLC27A2, PTGES2 and PTGES (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13) selected from the group), genes encoding them or a combination thereof;

[0083] At least one selected from the group consisting of: TNF, IFNG, CCL2, CXCR2, ARG1, SLC27A2, PTGES2 and PTGES (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7 or 8) selected from the group), genes encoding them or a combination thereof;

[0084] At least one selected from the group consisting of: VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2 and CXCL8 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10 or 11) selected from the group), genes encoding them or a combination thereof;

[0085] At least one selected from the group consisting of: PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, IFNL1 and SLC27A2 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15) selected from the group), genes encoding them or a combination thereof;

[0086] At least one selected from the group consisting of: VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCR2, FOXP3, PTGS2 and CXCL8 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9 or 10) selected from the group), genes encoding them or a combination thereof;

[0087] At least one selected from the group consisting of IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2 and PTGES2 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13 or 14) selected from the group), genes encoding them or a combination thereof;

[0088] At least one selected from the group consisting of: CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF and VEGFA (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8 or 9) selected from the group), genes encoding them or a combination thereof;

[0089] At least one selected from the group consisting of: SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A and ARG1 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12) selected from the group), genes encoding them or a combination thereof;

[0090] At least one 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., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16 or 17) selected from the group), genes encoding them or a combination thereof;

[0091] At least one selected from the group consisting of: SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, and CLEC7A (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group), genes encoding them, or a combination thereof;

[0092] At least one selected from the group consisting of: IFNG, CCL2 and PTGES2 (eg, one, two or three selected from the group), genes encoding the same or a combination thereof;

[0093] At least one selected from the group consisting of ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4 and CCL5 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8 or 9) selected from the group), genes encoding them or a combination thereof;

[0094] At least one selected from the group consisting of: TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, SLC27A2 and PTGES2 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10 or 11) selected from the group), genes encoding them or a combination thereof; and

[0095] At least one selected from the group consisting of: IFNG, VEGFA, SLC27A2, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2 and CXCL11 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9 or 10) selected from the group), their encoding genes or a combination thereof.

[0096] For example, a composition and / or kit for diagnosing pancreatic cancer may include reagents capable of detecting a biomarker panel, genes encoding the biomarkers, or a combination thereof selected from the following groups:

[0097] ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF and VEGFA;

[0098] SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2 and PTGS2;

[0099] IFNG, SLC27A2, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4 and IFNB1;

[0100] SLC27A2, IFNG, CCL2, TNF, PTGES, FOXP3, PTGES2, CXCR4 and CXCR2;

[0101] IFNL1, IFNG, CXCL11, CCL2, PTGES2, SLC27A2, and PTGES;

[0102] ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF, and FOXP3;

[0103] CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES and FOXP3;

[0104] CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2 and CXCL11;

[0105] CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF;

[0106] TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, SLC27A2, PTGES2 and PTGES;

[0107] TNF, IFNG, CCL2, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES;

[0108] VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2, and CXCL8;

[0109] PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, IFNL1, and SLC27A2;

[0110] VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCR2, FOXP3, PTGS2, and CXCL8;

[0111] IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, and PTGES2;

[0112] CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF, and VEGFA;

[0113] SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A, and ARG1;

[0114] IFNG, PTGES2, CCL5, SLC27A2, VEGFA, CCL2, TNF, FOXP3, CXCR4, IFNA1, IFNL1, PTGES, CCR5, CLEC7A, IFNB1, CXCR2 and PTGS2;

[0115] SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, and CLEC7A;

[0116] IFNG, CCL2, and PTGES2;

[0117] ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4, and CCL5;

[0118] TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, SLC27A2, and PTGES2; and

[0119] IFNG, VEGFA, SLC27A2, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2, and CXCL11.

[0120] More specifically, the composition and / or kit for diagnosing pancreatic cancer may include an agent capable of detecting at least one 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., 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, or 20)); genes encoding them; or a combination thereof. In this regard, the pancreatic cancer that can be detected using the composition or kit may be early pancreatic cancer.

[0121] In one embodiment, the composition or kit for diagnosing pancreatic cancer is used to diagnose early pancreatic cancer, and may include at least one selected from the group consisting of:

[0122] (1-1) an agent capable of detecting at least one selected from the group consisting of SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2, and PTGS2 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13) selected from the group), genes encoding the genes, or a combination thereof;

[0123] (1-2) an agent capable of detecting at least one selected from the group consisting of IFNG, SLC27A2, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4 and IFNB1 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13) selected from the group), genes encoding them or a combination thereof;

[0124] (1-3) an agent capable of detecting at least one selected from the group consisting of SLC27A2, IFNG, CCL2, TNF, PTGES, FOXP3, PTGES2, CXCR4 and CXCR2 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8 or 9) selected from the group), genes encoding the genes or a combination thereof;

[0125] (1-4) an agent capable of detecting at least one selected from the group consisting of IFNL1, IFNG, CXCL11, CCL2, PTGES2, SLC27A2 and PTGES (e.g., one or more (e.g., 2, 3, 4, 5, 6 or 7) selected from the group), genes encoding the genes or a combination thereof;

[0126] (1-5) an agent capable of detecting at least one selected from the group consisting of ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF, and FOXP3 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), genes encoding the genes, or a combination thereof;

[0127] (1-6) an agent capable of detecting at least one 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., 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, or 20)), genes encoding them, or a combination thereof;

[0128] (1-7) an agent capable of detecting at least one selected from the group consisting of: CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3 (e.g., one or more selected from the group (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12)); genes encoding them or a combination thereof;

[0129] (1-8) an agent capable of detecting at least one selected from the group consisting of: CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11 (e.g., one or more selected from the group (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15)), genes encoding them, or a combination thereof;

[0130] (1-9) an agent capable of detecting at least one selected from the group consisting of: CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, or 8) selected from the group), genes encoding the genes, or a combination thereof;

[0131] (1-10) an agent capable of detecting at least one selected from the group consisting of TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13) selected from the group), genes encoding them, or a combination thereof; and

[0132] (1-11) An agent capable of detecting at least one agent selected from the group consisting of: TNF, IFNG, CCL2, CXCR2, ARG1, SLC27A2, PTGES2 and PTGES (for example, one or more (for example, 2, 3, 4, 5, 6, 7 or 8) selected from the group), their encoding genes or a combination thereof.

[0133] For example, a composition and / or kit for diagnosing pancreatic cancer may include a reagent capable of detecting a biomarker group selected from the following groups; a gene encoding the biomarker group; or a combination thereof. In this regard, the pancreatic cancer that can be diagnosed using the composition and / or kit may be early pancreatic cancer:

[0134] ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF and VEGFA;

[0135] SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2 and PTGS2;

[0136] IFNG, SLC27A2, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4 and IFNB1;

[0137] SLC27A2, IFNG, CCL2, TNF, PTGES, FOXP3, PTGES2, CXCR4 and CXCR2;

[0138] IFNL1, IFNG, CXCL11, CCL2, PTGES2, SLC27A2, and PTGES;

[0139] ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF, and FOXP3;

[0140] CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES and FOXP3;

[0141] CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2 and CXCL11;

[0142] CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF;

[0143] TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES; and

[0144] TNF, IFNG, CCL2, CXCR2, ARG1, SLC27A2, PTGES2 and PTGES.

[0145] In another embodiment, the composition and / or kit for diagnosing pancreatic cancer may include an agent capable of detecting at least one of the following: IFNL1, IFNG, CXCL11, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2 and PTGES (e.g., 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); genes encoding them; or a combination thereof. In this regard, the pancreatic cancer that can be diagnosed using the composition and / or kit may be advanced pancreatic cancer.

[0146] In one embodiment, the composition and / or kit for diagnosing pancreatic cancer is used to diagnose advanced pancreatic cancer and may include at least one reagent capable of detecting:

[0147] (2-1) at least one selected from the group consisting of: VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2, and CXCL8 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, or 11) selected from the group), genes encoding the genes, or a combination thereof;

[0148] (2-2) at least one selected from the group consisting of: PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, IFNL1, and SLC27A2 (e.g., one or more selected from the group (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15)); genes encoding the genes or a combination thereof;

[0149] (2-3) at least one selected from the group consisting of: VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCR2, FOXP3, PTGS2, and CXCL8 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group); genes encoding the genes or a combination thereof;

[0150] (2-4) at least one selected from the group consisting of IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, and PTGES2 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, or 14) selected from the group); genes encoding the genes or a combination thereof;

[0151] (2-5) at least one selected from the group consisting of: CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF, and VEGFA (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), genes encoding them, or a combination thereof;

[0152] (2-6) at least one 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., 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 or 20)), genes encoding them or a combination thereof;

[0153] (2-7) at least one selected from the group consisting of: CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES and FOXP3 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12) selected from the group), genes encoding them or a combination thereof;

[0154] (2-8) at least one selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15) selected from the group), genes encoding them, or a combination thereof; and

[0155] (2-9) At least one selected from the group consisting of: CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2 and TNF (for example, one or more selected from the group (for example, 2, 3, 4, 5, 6, 7 or 8)), their encoding genes or a combination thereof.

[0156] For example, a composition and / or kit for diagnosing pancreatic cancer may include a reagent capable of detecting a biomarker group selected from the following groups; a gene encoding the biomarker group; or a combination thereof. In this regard, the pancreatic cancer that can be diagnosed using the composition and / or kit may be advanced pancreatic cancer:

[0157] ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF and VEGFA;

[0158] VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2, and CXCL8;

[0159] PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, IFNL1, and SLC27A2;

[0160] VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCR2, FOXP3, PTGS2, and CXCL8;

[0161] IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, and PTGES2;

[0162] CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF, and VEGFA;

[0163] CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES and FOXP3;

[0164] CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11; and

[0165] CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2 and TNF.

[0166] In another embodiment, the composition and / or kit for diagnosing pancreatic cancer may include an agent capable of detecting at least one of IFNL1, IFNG, CXCL11, TNF, IFNB1, IFNA1, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, PTGES2, SLC27A2, and PTGES (e.g., 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); genes encoding them; or a combination thereof. In this regard, the pancreatic cancer that can be detected using the composition or kit may be pancreatic cancer at any stage, regardless of progression, such as early pancreatic cancer, advanced pancreatic cancer, or both.

[0167] In one embodiment, the composition and / or kit for diagnosing pancreatic cancer is used to diagnose all stages of pancreatic cancer and may include at least one detectable agent selected from the group consisting of:

[0168] (3-1) an agent capable of detecting at least one selected from the group consisting of SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A and ARG1 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12) selected from the group), genes encoding the genes or a combination thereof;

[0169] (3-2) an agent capable of detecting at least one 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., one or more selected from the group (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, or 17)), genes encoding them, or a combination thereof;

[0170] (3-3) an agent capable of detecting at least one selected from the group consisting of SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, and CLEC7A (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group), genes encoding the genes, or a combination thereof;

[0171] (3-4) an agent capable of detecting at least one selected from the group consisting of: IFNG, CCL2, and PTGES2 (for example, one, two, or three selected from the group), genes encoding the same, or a combination thereof;

[0172] (3-5) an agent capable of detecting at least one selected from the group consisting of ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4 and CCL5 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8 or 9) selected from the group), genes encoding them or a combination thereof;

[0173] (3-6) an agent capable of detecting at least one 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., 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, or 20)), genes encoding them, or a combination thereof;

[0174] (3-7) an agent capable of detecting at least one selected from the group consisting of: CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES and FOXP3 (e.g., one or more selected from the group (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12)), genes encoding them or a combination thereof;

[0175] (3-8) an agent capable of detecting at least one selected from the group consisting of: CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11 (e.g., one or more selected from the group (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15)), genes encoding them, or a combination thereof;

[0176] (3-9) an agent capable of detecting at least one selected from the group consisting of: CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, or 8) selected from the group), genes encoding the genes, or a combination thereof;

[0177] (3-10) an agent capable of detecting at least one selected from the group consisting of TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, SLC27A2, and PTGES2 (e.g., one or more selected from the group (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, or 11)), genes encoding them, or a combination thereof; or

[0178] (3-11) An agent capable of detecting at least one selected from the group consisting of IFNG, VEGFA, SLC27A2, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2, and CXCL11 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group), a gene encoding the gene, or a combination thereof. In this regard, the pancreatic cancer that can be detected using the composition or kit can be pancreatic cancer at any stage, regardless of progression, such as early pancreatic cancer, advanced pancreatic cancer, or both.

[0179] For example, a composition and / or kit for diagnosing pancreatic cancer may include a reagent capable of detecting a biomarker group selected from the following groups; a gene encoding the biomarker group; or a combination thereof. In this regard, the pancreatic cancer that can be diagnosed using the composition and / or kit may be early pancreatic cancer, late-early pancreatic cancer, or both:

[0180] ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF and VEGFA;

[0181] SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A, and ARG1;

[0182] IFNG, PTGES2, CCL5, SLC27A2, VEGFA, CCL2, TNF, FOXP3, CXCR4, IFNA1, IFNL1, PTGES, CCR5, CLEC7A, IFNB1, CXCR2 and PTGS2;

[0183] SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, and CLEC7A;

[0184] IFNG, CCL2, and PTGES2;

[0185] ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4, and CCL5;

[0186] CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES and FOXP3;

[0187] CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2 and CXCL11;

[0188] CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF;

[0189] TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, SLC27A2, and PTGES2; and

[0190] IFNG, VEGFA, SLC27A2, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2, and CXCL11.

[0191] In another embodiment, the composition and / or kit for diagnosing pancreatic cancer may include an agent capable of detecting at least one biomarker (one or two) selected from the group consisting of IFNB1 and IFNA1, its encoding gene or a combination thereof. In this regard, the diagnostic composition and / or kit may be designed to distinguish pancreatic cancer (e.g., early pancreatic cancer and / or advanced pancreatic cancer) from similar diseases (e.g., benign pancreatic diseases (pancreatitis (chronic pancreatitis and / or acute pancreatitis), benign pancreatic tumors, intraductal papillary mucinous neoplasms (IPMN), autoimmune pancreatitis (AIP) and other pancreatic diseases (excluding pancreatic cancer (malignant pancreatic tumors)), etc.) and bile duct cancer).

[0192] The composition and / or kit for diagnosing pancreatic cancer may include at least one of the biomarkers IFNB1 and IFNA1, genes encoding them, or a combination thereof to effectively distinguish pancreatic cancer from benign pancreatic diseases and other similar conditions.

[0193] Methods for diagnosing pancreatic cancer

[0194] The present disclosure provides a composition and method for diagnosing pancreatic cancer (or a method for providing diagnostic information). The method may include the step of detecting the above-mentioned biomarkers in a blood sample isolated from a subject, that is, at least one biomarker 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., 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 or 20)), and its encoding gene.

[0195] In one embodiment, the biomarker may include at least one selected from the group consisting of:

[0196] At least one 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., 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), genes encoding them or a combination thereof;

[0197] At least one selected from the group consisting of: SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2 and PTGS2 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13) selected from the group), genes encoding them or a combination thereof;

[0198] At least one selected from the group consisting of IFNG, SLC27A2, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4 and IFNB1 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13) selected from the group), genes encoding them or a combination thereof;

[0199] At least one selected from the group consisting of: SLC27A2, IFNG, CCL2, TNF, PTGES, FOXP3, PTGES2, CXCR4 and CXCR2 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8 or 9) selected from the group), genes encoding them or a combination thereof;

[0200] At least one selected from the group consisting of IFNL1, IFNG, CXCL11, CCL2, PTGES2, SLC27A2 and PTGES (e.g., one or more (e.g., 2, 3, 4, 5, 6 or 7) selected from the group), genes encoding them or a combination thereof;

[0201] At least one selected from the group consisting of ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF and FOXP3 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8 or 9) selected from the group), genes encoding them or a combination thereof;

[0202] At least one selected from the group consisting of: CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES and FOXP3 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12) selected from the group), genes encoding them or a combination thereof;

[0203] At least one selected from the group consisting of: CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2 and CXCL11 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15) selected from the group), genes encoding them or a combination thereof;

[0204] At least one selected from the group consisting of: CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2 and TNF (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7 or 8) selected from the group), genes encoding them or a combination thereof;

[0205] At least one selected from the group consisting of: TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, SLC27A2, PTGES2 and PTGES (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13) selected from the group), genes encoding them or a combination thereof;

[0206] At least one selected from the group consisting of: TNF, IFNG, CCL2, CXCR2, ARG1, SLC27A2, PTGES2 and PTGES (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7 or 8) selected from the group), genes encoding them or a combination thereof;

[0207] At least one selected from the group consisting of: VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2 and CXCL8 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10 or 11) selected from the group), genes encoding them or a combination thereof;

[0208] At least one selected from the group consisting of: PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, IFNL1 and SLC27A2 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15) selected from the group), genes encoding them or a combination thereof;

[0209] At least one selected from the group consisting of: VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCR2, FOXP3, PTGS2 and CXCL8 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9 or 10) selected from the group), genes encoding them or a combination thereof;

[0210] At least one selected from the group consisting of IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2 and PTGES2 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13 or 14) selected from the group), genes encoding them or a combination thereof;

[0211] At least one selected from the group consisting of: CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF and VEGFA (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8 or 9) selected from the group), genes encoding them or a combination thereof;

[0212] At least one selected from the group consisting of: SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A and ARG1 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12) selected from the group), genes encoding them or a combination thereof;

[0213] At least one 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., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16 or 17) selected from the group), genes encoding them or a combination thereof;

[0214] At least one selected from the group consisting of: SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, and CLEC7A (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group), genes encoding them, or a combination thereof;

[0215] At least one selected from the group consisting of: IFNG, CCL2 and PTGES2 (eg, one, two or three selected from the group), genes encoding the same or a combination thereof;

[0216] At least one selected from the group consisting of: ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4 and CCL5 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8 or 9) selected from the group); genes encoding them or a combination thereof;

[0217] At least one selected from the group consisting of: TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, SLC27A2 and PTGES2 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10 or 11) selected from the group); genes encoding them or a combination thereof; and

[0218] At least one selected from the group consisting of: IFNG, VEGFA, SLC27A2, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2 and CXCL11 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9 or 10) selected from the group); their encoding genes or a combination thereof.

[0219] For example, the biomarker can be a panel of biomarkers selected from the following group; genes encoding them or a combination thereof:

[0220] ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF and VEGFA;

[0221] SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2 and PTGS2;

[0222] IFNG, SLC27A2, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4 and IFNB1;

[0223] SLC27A2, IFNG, CCL2, TNF, PTGES, FOXP3, PTGES2, CXCR4 and CXCR2;

[0224] IFNL1, IFNG, CXCL11, CCL2, PTGES2, SLC27A2, and PTGES;

[0225] ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF, and FOXP3;

[0226] CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES and FOXP3;

[0227] CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2 and CXCL11;

[0228] CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF;

[0229] TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, SLC27A2, PTGES2 and PTGES;

[0230] TNF, IFNG, CCL2, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES;

[0231] VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2, and CXCL8;

[0232] PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, IFNL1, and SLC27A2;

[0233] VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCR2, FOXP3, PTGS2, and CXCL8;

[0234] IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, and PTGES2;

[0235] CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF, and VEGFA;

[0236] SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A, and ARG1;

[0237] IFNG, PTGES2, CCL5, SLC27A2, VEGFA, CCL2, TNF, FOXP3, CXCR4, IFNA1, IFNL1, PTGES, CCR5, CLEC7A, IFNB1, CXCR2 and PTGS2;

[0238] SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, and CLEC7A;

[0239] IFNG, CCL2, and PTGES2;

[0240] ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4, and CCL5;

[0241] TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, SLC27A2, and PTGES2; and

[0242] IFNG, VEGFA, SLC27A2, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2, and CXCL11.

[0243] More specifically, the biomarker may include at least one selected from the following group, wherein the pancreatic cancer that can be diagnosed therewith is early pancreatic cancer:

[0244] At least one 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., 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), genes encoding them or a combination thereof;

[0245] At least one selected from the group consisting of: SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2 and PTGS2 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13) selected from the group), genes encoding them or a combination thereof;

[0246] At least one selected from the group consisting of IFNG, SLC27A2, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4 and IFNB1 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13) selected from the group); genes encoding them or a combination thereof;

[0247] At least one selected from the group consisting of: SLC27A2, IFNG, CCL2, TNF, PTGES, FOXP3, PTGES2, CXCR4 and CXCR2 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8 or 9) selected from the group); genes encoding them or a combination thereof;

[0248] At least one selected from the group consisting of: IFNL1, IFNG, CXCL11, CCL2, PTGES2, SLC27A2 and PTGES (e.g., one or more (e.g., 2, 3, 4, 5, 6 or 7) selected from the group); genes encoding them or a combination thereof;

[0249] At least one selected from the group consisting of: ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF and FOXP3 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8 or 9) selected from the group); genes encoding them or a combination thereof;

[0250] At least one selected from the group consisting of: CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES and FOXP3 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12) selected from the group); genes encoding them or a combination thereof;

[0251] At least one selected from the group consisting of: CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2 and CXCL11 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15) selected from the group); genes encoding them or a combination thereof;

[0252] At least one selected from the group consisting of: CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2 and TNF (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7 or 8) selected from the group); genes encoding them or a combination thereof;

[0253] At least one selected from the group consisting of: TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, SLC27A2, PTGES2 and PTGES (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13) selected from the group); genes encoding them or a combination thereof; and

[0254] At least one selected from the group consisting of: TNF, IFNG, CCL2, CXCR2, ARG1, SLC27A2, PTGES2 and PTGES (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7 or 8) selected from the group); genes encoding them or a combination thereof.

[0255] More specifically, for example, the biomarker can be a biomarker panel selected from the following group; a gene encoding the biomarker; or a combination thereof, wherein the pancreatic cancer that can be diagnosed using the biomarker is an early stage pancreatic cancer:

[0256] ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF and VEGFA;

[0257] SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2 and PTGS2;

[0258] IFNG, SLC27A2, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4 and IFNB1;

[0259] SLC27A2, IFNG, CCL2, TNF, PTGES, FOXP3, PTGES2, CXCR4 and CXCR2;

[0260] IFNL1, IFNG, CXCL11, CCL2, PTGES2, SLC27A2, and PTGES;

[0261] ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF, and FOXP3;

[0262] CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES and FOXP3;

[0263] CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2 and CXCL11;

[0264] CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF;

[0265] TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, SLC27A2, PTGES2, and PTGES; and

[0266] TNF, IFNG, CCL2, CXCR2, ARG1, SLC27A2, PTGES2 and PTGES.

[0267] In another embodiment, the biomarker may include at least one selected from the following group, and the pancreatic cancer diagnosed therefrom is advanced pancreatic cancer:

[0268] At least one 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., 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), genes encoding them or a combination thereof;

[0269] At least one selected from the group consisting of: VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2 and CXCL8 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10 or 11) selected from the group); genes encoding them or a combination thereof;

[0270] At least one selected from the group consisting of: PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, IFNL1 and SLC27A2 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15) selected from the group); genes encoding them or a combination thereof;

[0271] At least one selected from the group consisting of: VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCR2, FOXP3, PTGS2 and CXCL8 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9 or 10) selected from the group); genes encoding them or a combination thereof;

[0272] At least one selected from the group consisting of IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2 and PTGES2 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13 or 14) selected from the group); genes encoding them or a combination thereof;

[0273] At least one selected from the group consisting of: CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF and VEGFA (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8 or 9) selected from the group); genes encoding them or a combination thereof;

[0274] At least one selected from the group consisting of: CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES and FOXP3 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12) selected from the group); genes encoding them or a combination thereof;

[0275] At least one selected from the group consisting of: CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15) selected from the group); genes encoding them or a combination thereof; and

[0276] At least one selected from the group consisting of: CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2 and TNF (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7 or 8) selected from the group); genes encoding them or a combination thereof.

[0277] For example, the biomarker can be a biomarker panel selected from the group consisting of: encoding genes; or a combination thereof, and the pancreatic cancer diagnosed by it is advanced pancreatic cancer:

[0278] ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF and VEGFA;

[0279] VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2, and CXCL8;

[0280] PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, IFNL1, and SLC27A2;

[0281] VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCR2, FOXP3, PTGS2, and CXCL8;

[0282] IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2, and PTGES2;

[0283] CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF, and VEGFA;

[0284] CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES and FOXP3;

[0285] CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11; and

[0286] CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2 and TNF.

[0287] In another embodiment, the biomarker may include at least one selected from the following, and the pancreatic cancer that can be diagnosed is pancreatic cancer of any stage, regardless of progression, such as early pancreatic cancer, advanced pancreatic cancer, or both:

[0288] At least one 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., 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), genes encoding them or a combination thereof;

[0289] At least one selected from the group consisting of: SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A and ARG1 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12) selected from the group); genes encoding them or a combination thereof;

[0290] At least one 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., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16 or 17) selected from the group); genes encoding them or a combination thereof;

[0291] At least one selected from the group consisting of: SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, and CLEC7A (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group); genes encoding them or a combination thereof;

[0292] At least one selected from the group consisting of: IFNG, CCL2 and PTGES2 (eg, one, two or three selected from the group), genes encoding the same or a combination thereof;

[0293] At least one selected from the group consisting of ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4 and CCL5 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8 or 9) selected from the group), genes encoding them or a combination thereof;

[0294] At least one selected from the group consisting of: CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES and FOXP3 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12) selected from the group), genes encoding them or a combination thereof;

[0295] At least one selected from the group consisting of: CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2 and CXCL11 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15) selected from the group), genes encoding them or a combination thereof;

[0296] At least one selected from the group consisting of: CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2 and TNF (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7 or 8) selected from the group); genes encoding them or a combination thereof;

[0297] At least one selected from the group consisting of: TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, SLC27A2 and PTGES2 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10 or 11) selected from the group); genes encoding them or a combination thereof; and

[0298] At least one selected from the group consisting of: IFNG, VEGFA, SLC27A2, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2 and CXCL11 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9 or 10) selected from the group); their encoding genes or a combination thereof.

[0299] For example, the biomarker can be a biomarker panel selected from the group consisting of: encoding genes; or a combination thereof, and the pancreatic cancer that can be diagnosed with it is pancreatic cancer at any stage, regardless of progression, such as early pancreatic cancer, advanced pancreatic cancer, or both:

[0300] ARG1, CCL2, CCL5, CCR5, PTGS2, CXCR2, CXCR4, CLEC7A, SLC27A2, FOXP3, CXCL11, IFNG, IFNA1, IFNB1, IFNL1, CXCL8, PTGES, PTGES2, TNF and VEGFA;

[0301] SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A, and ARG1;

[0302] IFNG, PTGES2, CCL5, SLC27A2, VEGFA, CCL2, TNF, FOXP3, CXCR4, IFNA1, IFNL1, PTGES, CCR5, CLEC7A, IFNB1, CXCR2 and PTGS2;

[0303] SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, and CLEC7A;

[0304] IFNG, CCL2, and PTGES2;

[0305] ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4, and CCL5;

[0306] CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES and FOXP3;

[0307] CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2 and CXCL11;

[0308] CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF;

[0309] TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, SLC27A2, and PTGES2; and

[0310] IFNG, VEGFA, SLC27A2, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2, and CXCL11.

[0311] In this method, the step of detecting biomarkers can include determining the presence or absence of biomarkers in the sample, measuring the level (concentration) of biomarkers, or performing both. In this method, when the biomarkers in the sample are present at a higher and / or lower level than a reference sample (e.g., a normal sample or a sample from a subject suffering from a similar disease), the sample or the subject of the sample source can be diagnosed (or identified or determined) as a pancreatic cancer patient. The diagnosis of pancreatic cancer patients can include confirming or determining that the subject suffers from pancreatic cancer and / or distinguishing pancreatic cancer patients from subjects suffering from similar diseases. Pancreatic cancer can refer to early pancreatic cancer, advanced pancreatic cancer, or both. Normal subjects can refer to subjects who do not suffer from pancreatic cancer (including early pancreatic cancer, advanced pancreatic cancer, or both). Similar diseases can refer to benign pancreatic diseases (including pancreatitis (chronic pancreatitis and / or acute pancreatitis), benign pancreatic tumors, intraductal papillary mucinous tumors (IPMN), autoimmune pancreatitis (AIP) or other pancreatic diseases (excluding pancreatic cancer (malignant pancreatic tumors)) and / or bile duct cancer.

[0312] In one embodiment, the method for diagnosing pancreatic cancer or the method for providing information for diagnosing pancreatic cancer provided in the present disclosure may include:

[0313] (a) detecting at least one of the above biomarkers in a blood sample isolated from a subject; and

[0314] (b) when the biomarkers in the blood sample are present at higher and / or lower levels compared to a reference sample (e.g., a normal sample or a sample from a subject with a similar disease), diagnosing (or identifying or determining) that the sample or the subject from which the sample is derived is a pancreatic cancer patient (including early pancreatic cancer, advanced pancreatic cancer, or both).

[0315] In the method, step (b) may 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) of the following steps:

[0316] - when IFNL1, its encoding gene or a combination thereof in a blood sample is present at a higher (increased) level compared to a reference sample (e.g., a normal sample), diagnosing (or identifying or determining) that the sample or the subject from which the sample is derived is a pancreatic cancer patient, for example, a patient with early pancreatic cancer, advanced pancreatic cancer, or pancreatic cancer at any stage regardless of progression (including early pancreatic cancer and / or advanced pancreatic cancer);

[0317] - when IFNG, its encoding gene or a combination thereof in a blood sample is present at a lower (decreased) level compared to a reference sample (e.g., a normal sample), diagnosing (or identifying or determining) that the sample or the subject from which the sample is derived is a pancreatic cancer patient, for example, a patient with early pancreatic cancer, advanced pancreatic cancer, or pancreatic cancer at any stage regardless of progression (including early pancreatic cancer and / or advanced pancreatic cancer);

[0318] - When CXCL11, its encoding gene or a combination thereof in a blood sample is present at a higher (increased) level compared to a reference sample (e.g., a normal sample), diagnosing (or identifying or determining) that the sample or the subject from which the sample is derived is a patient with early-stage pancreatic cancer, and / or when CXCL11, its encoding gene or a combination thereof in a blood sample is present at a lower (decreased) level, diagnosing that the sample or the subject from which the sample is derived is a patient with advanced-stage pancreatic cancer;

[0319] - when TNF, its encoding gene or a combination thereof in a blood sample is present at a higher (increased) level compared to a reference sample (e.g., a normal sample), diagnosing (or identifying or determining) that the sample or the subject from which the sample is derived is a pancreatic cancer patient, for example, a patient with early pancreatic cancer, advanced pancreatic cancer, or pancreatic cancer at any stage regardless of progression (including early pancreatic cancer and / or advanced pancreatic cancer);

[0320] - When CLEC7A, its encoding gene or a combination thereof in a blood sample is present at a lower (decreased) level compared to a reference sample (e.g., a normal sample), diagnosing (or identifying or determining) that the sample or the subject from which the sample is derived is a patient with early-stage pancreatic cancer, and / or when CLEC7A, its encoding gene or a combination thereof in a blood sample is present at a higher (increased) level, diagnosing that the sample is a patient with advanced-stage pancreatic cancer;

[0321] - when CXCL8, a gene encoding it, or a combination thereof in a blood sample is present at a higher (increased) level compared to a reference sample (e.g., a normal sample), diagnosing (or identifying or determining) that the sample or the subject from which the sample is derived is a pancreatic cancer patient, for example, a patient with early pancreatic cancer, advanced pancreatic cancer, or pancreatic cancer at any stage regardless of progression (including early pancreatic cancer and / or advanced pancreatic cancer);

[0322] - When FOXP3, its encoding gene or a combination thereof in a blood sample is present at a higher (increased) level compared to a reference sample (e.g., a normal sample), diagnosing (or identifying or determining) that the sample or the subject from which the sample is derived is a patient with early-stage pancreatic cancer, and / or when FOXP3, its encoding gene or a combination thereof in a blood sample is present at a lower (decreased) level, diagnosing that the sample or the subject from which the sample is derived is a patient with advanced-stage pancreatic cancer;

[0323] - when VEGFA, its encoding gene, or a combination thereof in a blood sample is present at a higher (increased) level compared to a reference sample (e.g., a normal sample), diagnosing (or identifying or determining) that the sample or the subject from which the sample is derived is a pancreatic cancer patient, for example, a patient with early pancreatic cancer, advanced pancreatic cancer, or pancreatic cancer at any stage regardless of progression (including early pancreatic cancer and / or advanced pancreatic cancer);

[0324] - when CCL2, a gene encoding it, or a combination thereof in a blood sample is present at a higher (increased) level compared to a reference sample (e.g., a normal sample), diagnosing (or identifying or determining) that the sample or the subject from which the sample is derived is a pancreatic cancer patient, for example, a patient with early pancreatic cancer, advanced pancreatic cancer, or pancreatic cancer at any stage regardless of progression (including early pancreatic cancer and / or advanced pancreatic cancer);

[0325] - when CCL5, a gene encoding it, or a combination thereof in a blood sample is present at a lower (decreased) level compared to a reference sample (e.g., a normal sample), diagnosing (or identifying or determining) that the sample or the subject from which the sample is derived is a pancreatic cancer patient, for example, a patient with early pancreatic cancer, advanced pancreatic cancer, or pancreatic cancer at any stage regardless of progression (including early pancreatic cancer and / or advanced pancreatic cancer);

[0326] - When CCR5, its encoding gene or a combination thereof in a blood sample is present at a higher (increased) level compared to a reference sample (e.g., a normal sample), diagnosing (or identifying or determining) that the sample or the subject from which the sample is derived is a patient with early-stage pancreatic cancer, and / or when CCR5, its encoding gene or a combination thereof in a blood sample is present at a lower (decreased) level, diagnosing that the sample is a patient with advanced-stage pancreatic cancer;

[0327] - when CXCR4, a gene encoding it, or a combination thereof in a blood sample is present at a higher (increased) level compared to a reference sample (e.g., a normal sample), diagnosing (or identifying or determining) that the sample or the subject from which the sample is derived is a pancreatic cancer patient, for example, a patient with early pancreatic cancer, advanced pancreatic cancer, or pancreatic cancer at any stage regardless of progression (including early pancreatic cancer and / or advanced pancreatic cancer);

[0328] - when ARG1, a gene encoding it, or a combination thereof in a blood sample is present at a higher (increased) level compared to a reference sample (e.g., a normal sample), diagnosing (or identifying or determining) that the sample or the subject from which the sample is derived is a pancreatic cancer patient, for example, a patient with early pancreatic cancer, advanced pancreatic cancer, or pancreatic cancer at any stage regardless of progression (including early pancreatic cancer and / or advanced pancreatic cancer);

[0329] - When CXCR2, its encoding gene or a combination thereof in a blood sample is present at a lower (decreased) level compared to a reference sample (e.g., a normal sample), diagnosing (or identifying or determining) that the sample or the subject from which the sample is derived is a patient with early-stage pancreatic cancer, and / or when CXCR2, its encoding gene or a combination thereof in a blood sample is present at a higher (increased) level, diagnosing that the sample is a patient with advanced-stage pancreatic cancer;

[0330] - when PTGS2, a gene encoding it, or a combination thereof in a blood sample is present at a higher (increased) level compared to a reference sample (e.g., a normal sample), diagnosing (or identifying or determining) that the sample or the subject from which the sample is derived is a pancreatic cancer patient, for example, a patient with early pancreatic cancer, advanced pancreatic cancer, or pancreatic cancer at any stage regardless of progression (including early pancreatic cancer and / or advanced pancreatic cancer);

[0331] - when PTGES2, a gene encoding it, or a combination thereof in a blood sample is present at a lower (decreased) level compared to a reference sample (e.g., a normal sample), diagnosing (or identifying or determining) that the sample or the subject from which the sample is derived is a pancreatic cancer patient, for example, a patient with early pancreatic cancer, advanced pancreatic cancer, or pancreatic cancer at any stage regardless of progression (including early pancreatic cancer and / or advanced pancreatic cancer);

[0332] - when SLC27A2, a gene encoding it, or a combination thereof in a blood sample is present at a higher (increased) level compared to a reference sample (e.g., a normal sample), diagnosing (or identifying or determining) that the sample or the subject from which the sample is derived is a pancreatic cancer patient, for example, a patient with early pancreatic cancer, advanced pancreatic cancer, or pancreatic cancer at any stage regardless of progression (including early pancreatic cancer and / or advanced pancreatic cancer);

[0333] -When PTGES, its encoding gene, or a combination thereof in a blood sample is present at a higher (increased) level compared to a reference sample (e.g., a normal sample), the sample or the subject from which the sample is derived is diagnosed (or identified or determined) as a pancreatic cancer patient, for example, a patient with early pancreatic cancer, advanced pancreatic cancer, or pancreatic cancer at any stage regardless of progression (including early pancreatic cancer and / or advanced pancreatic cancer).

[0334] - when IFNB1, its encoding gene, or a combination thereof in a blood sample is present at a lower (decreased) level compared to a reference sample (e.g., a similar disease sample), diagnosing (or identifying or determining) that the sample or the subject from which the sample is derived is a pancreatic cancer patient; and

[0335] - When IFNA1, its encoding gene or a combination thereof is present at a lower (decreased) level in a blood sample compared to a reference sample (eg, a similar disease sample), diagnosing (or identifying or determining) that the sample or the subject from which the sample is derived is a pancreatic cancer patient.

[0336] More specifically, the method may be a method for diagnosing early pancreatic cancer, or a method for providing information for diagnosing early pancreatic cancer, comprising the following steps:

[0337] (a) detecting: at least one of the following 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., 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)) in a blood sample isolated from a subject; genes encoding them; or a combination thereof.

[0338] More specifically, the method for diagnosing early pancreatic cancer, or the method for providing information for early pancreatic cancer diagnosis may include the step of detecting one or more of the following markers:

[0339] (1-1) at least one selected from the group consisting of SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2 and PTGS2 (e.g., one or more selected from the group (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13)) (e.g., at least one selected from the group consisting of ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF and FOXP3 (1, 2, 3, 4, 5, 6, 7, 8 or 9)); genes encoding them; or a combination thereof;

[0340] (1-2) at least one selected from the group consisting of IFNG, SLC27A2, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4 and IFNB1 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13) selected from the group), genes encoding them or a combination thereof;

[0341] (1-3) at least one selected from the group consisting of SLC27A2, IFNG, CCL2, TNF, PTGES, FOXP3, PTGES2, CXCR4 and CXCR2 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8 or 9) selected from the group), genes encoding them or a combination thereof;

[0342] (1-4) at least one selected from the group consisting of IFNL1, IFNG, CXCL11, CCL2, PTGES2, SLC27A2 and PTGES (e.g., one or more (e.g., 2, 3, 4, 5, 6 or 7) selected from the group), genes encoding them or a combination thereof;

[0343] (1-5) at least one selected from the group consisting of ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF, and FOXP3 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), genes encoding them, or a combination thereof;

[0344] (1-6) at least one 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., 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), genes encoding them or a combination thereof;

[0345] (1-7) at least one selected from the group consisting of: CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES and FOXP3 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12) selected from the group), genes encoding them or a combination thereof;

[0346] (1-8) at least one selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, or 8) selected from the group), genes encoding them, or a combination thereof; and

[0347] (1-9) at least one selected from the group consisting of: CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2 and TNF (for example, one or more (for example, 2, 3, 4, 5, 6, 7 or 8) selected from the group); their encoding genes or a combination thereof.

[0348] The method for diagnosing early pancreatic cancer or the method for providing early pancreatic cancer diagnosis information may further comprise the following steps:

[0349] (b) in blood samples,

[0350] - when at least one selected from the group consisting of IFNL1, CXCL11, TNF, CXCL8, FOXP3, VEGFA, CCL2, CCR5, CXCR4, ARG1, PTGS2, SLC27A2 and PTGES (e.g., 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), the genes encoding them or a combination thereof are present at a higher (increased) level compared to a reference sample (e.g., a normal sample), diagnosing (or confirming or determining) that the blood sample or the subject from which the blood sample is derived is a pancreatic cancer patient, more specifically, an early pancreatic cancer patient; and / or

[0351] - When at least one (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 present at a lower (decreased) level compared to a reference sample (e.g., a normal sample), the blood sample or the subject from which the blood sample is derived is diagnosed (or confirmed or determined) as a pancreatic cancer patient, more specifically, an early pancreatic cancer patient.

[0352] In another embodiment, the method may be a method for diagnosing advanced pancreatic cancer or providing information for diagnosing advanced pancreatic cancer, comprising the steps of:

[0353] (a) detecting at least one of 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., 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), genes encoding them or a combination thereof in a blood sample isolated from a subject.

[0354] More specifically, the method for diagnosing advanced pancreatic cancer or providing information for diagnosing advanced pancreatic cancer may include the step of detecting a marker selected from the following group:

[0355] (2-1) at least one selected from the group consisting of: VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2 and CXCL8 (e.g., 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); genes encoding them; or a combination thereof;

[0356] (2-2) at least one selected from the group consisting of PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES, IFNL1 and SLC27A2 (e.g., one or more selected from the group (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15)), genes encoding them or a combination thereof;

[0357] (2-3) at least one selected from the group consisting of: VEGFA, CXCR4, SLC27A2, TNF, PTGES2, CCL5, CXCR2, FOXP3, PTGS2, and CXCL8 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group), genes encoding the genes, or a combination thereof;

[0358] (2-4) at least one selected from the group consisting of IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2 and PTGES2 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13 or 14) selected from the group), genes encoding them or a combination thereof;

[0359] (2-5) at least one selected from the group consisting of: CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF, and VEGFA (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, or 9) selected from the group), genes encoding them, or a combination thereof;

[0360] (2-6) at least one 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., 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 or 20)), genes encoding them or a combination thereof;

[0361] (2-7) at least one selected from the group consisting of: CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES and FOXP3 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12) selected from the group), genes encoding them or a combination thereof;

[0362] (2-8) at least one selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11 (e.g., one or more selected from the group (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15)), genes encoding them, or a combination thereof; or

[0363] (2-9) At least one selected from the group consisting of: CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2 and TNF (for example, one or more selected from the group (for example, 2, 3, 4, 5, 6, 7 or 8)), their encoding genes or a combination thereof.

[0364] The method for diagnosing advanced pancreatic cancer or the method for providing advanced pancreatic cancer diagnosis information may further comprise the following steps:

[0365] (b) in blood samples,

[0366] - when at least one selected from the group consisting of IFNL1, TNF, CLEC7A, CXCL8, VEGFA, CCL2, CXCR4, ARG1, CXCR2, PTGS2, SLC27A2 and PTGES (e.g., 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), the genes encoding them or a combination thereof are present at a higher (increased) level compared to a reference sample (e.g., a normal sample), diagnosing (or identifying or determining) that the blood sample or the subject from which the blood sample is derived is a pancreatic cancer patient, more specifically, a patient with advanced pancreatic cancer; and / or

[0367] - When at least one selected from the group consisting of IFNG, CXCL11, FOXP3, CCL5, CCR5 and PTGES2 (for example, one or more (for example, 2, 3, 4, 5 or 6) selected from the group), the encoding genes or a combination thereof are present at a lower (decreased) level compared to a reference sample (for example, a normal sample), the blood sample or the subject from which the blood sample is derived is diagnosed (or identified or determined) as a pancreatic cancer patient, more specifically, a patient with advanced pancreatic cancer.

[0368] In another embodiment, the method may be a method for diagnosing all pancreatic cancers (early pancreatic cancer and / or advanced pancreatic cancer) or a method for providing diagnostic information of all pancreatic cancers (early pancreatic cancer and / or advanced pancreatic cancer), comprising the following steps:

[0369] (a) detecting: at least one of the following 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, 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); its encoding gene; or a combination thereof in a blood sample isolated from a subject.

[0370] More specifically, a method for diagnosing all pancreatic cancers (early pancreatic cancer and / or advanced pancreatic cancer) or a method for providing diagnostic information for all pancreatic cancers (early pancreatic cancer and / or advanced pancreatic cancer) may comprise detecting markers from the following groups:

[0371] (3-1) at least one selected from the group consisting of SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A and ARG1 (for example, one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12) selected from the group), genes encoding them or a combination thereof;

[0372] (3-2) at least one selected from the group consisting of IFNG, PTGES2, CCL5, SLC27A2, VEGFA, CCL2, TNF, FOXP3, CXCR4, IFNA1, IFNL1, PTGES, CCR5, CLEC7A, IFNB1, CXCR2 and PTGS2 (for example, 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 them or a combination thereof;

[0373] (3-3) at least one selected from the group consisting of SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, and CLEC7A (for example, one or more (2, 3, 4, 5, 6, 7, 8, 9, or 10) selected from the group);

[0374] (3-4) at least one selected from the group consisting of IFNG, CCL2 and PTGES2 (for example, one or more (one, two or three) selected from the group), genes encoding them or a combination thereof;

[0375] (3-5) at least one selected from the group consisting of ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4 and CCL5 (for example, one or more (2, 3, 4, 5, 6, 7, 8 or 9) selected from the group), genes encoding them or a combination thereof;

[0376] (3-6) at least one 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., 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), genes encoding them, or a combination thereof;

[0377] (3-7) at least one selected from the group consisting of: CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES and FOXP3 (e.g., one or more (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 or 12) selected from the group), genes encoding them or a combination thereof;

[0378] (3-8) at least one selected from the group consisting of CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11 (e.g., one or more selected from the group (e.g., 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, or 15)), genes encoding them, or a combination thereof; or

[0379] (3-9) At least one selected from the group consisting of: CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2 and TNF (for example, one or more selected from the group (for example, 2, 3, 4, 5, 6, 7 or 8)), their encoding genes or a combination thereof.

[0380] The method for diagnosing all pancreatic cancers (early stage pancreatic cancer and / or advanced stage pancreatic cancer) or the method for providing diagnostic information of all pancreatic cancers (early stage pancreatic cancer and / or advanced stage pancreatic cancer) may further comprise the following steps:

[0381] (b) when at least one (e.g., one, two or three) selected from the group consisting of FNG, CCL5 and PTGES2, the genes encoding them or a combination thereof are present in the blood sample at a lower (decreased) level compared to a reference sample (e.g., a normal sample), or when at least one (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9 or 10) selected from the group consisting of IFNL1, TNF, CXCL8, VEGFA, CCL2, CXCR4, ARG1, PTGS2, SLC27A2 and PTGES, the genes encoding them or a combination thereof are present at a higher (increased) level compared to a reference sample (e.g., a normal sample), the blood sample or the subject from which the blood sample is derived is diagnosed (or confirmed or determined) as a pancreatic cancer patient (a patient with early pancreatic cancer, advanced pancreatic cancer or both).

[0382] In another embodiment, the method may be a method for diagnosing pancreatic cancer (early stage pancreatic cancer and / or advanced stage pancreatic cancer) or a method for providing diagnostic information of all pancreatic cancers (early stage pancreatic cancer and / or advanced stage pancreatic cancer), comprising the following steps:

[0383] (a) detecting at least one (one or two) selected from the group consisting of IFNB1 and IFNA1, genes encoding them, or a combination thereof in a blood sample isolated from a subject; and

[0384] (b) when at least one (1 or 2) selected from the group consisting of IFNB1 and IFNA1, its encoding gene or a combination thereof is present in a blood sample at a lower (reduced) level compared to a reference sample (e.g., a sample from a subject with a similar disease), the blood sample or the subject from which the blood sample is derived is diagnosed (or confirmed or determined) as a pancreatic cancer patient (early pancreatic cancer, advanced pancreatic cancer or both). The method allows for differentiation of pancreatic cancer patients (early pancreatic cancer, advanced pancreatic cancer or both) from patients with similar diseases.

[0385] The method using IFNB1 and / or IFNA1 as a marker can be used to distinguish pancreatic cancer (early pancreatic cancer, advanced pancreatic cancer, or both) from similar diseases, such as benign pancreatic diseases (pancreatitis (chronic pancreatitis and / or acute pancreatitis), benign pancreatic tumors, intraductal papillary mucinous neoplasms (IPMN), autoimmune pancreatitis (AIP), and other pancreatic diseases (excluding pancreatic cancer (malignant pancreatic tumors)) and bile duct cancer.

[0386] In addition, the method may further include the following steps:

[0387] (a) measuring the level of at least one of the above biomarkers in a blood sample isolated from a subject; and

[0388] (b)(i) comparing the level of the biomarker measured in the blood sample with the level of the biomarker in a reference sample (e.g., a normal sample or a sample from a subject with a similar disease);

[0389] (ii) diagnosing (or confirming or determining) that the sample or the subject from which the sample is derived is a pancreatic cancer patient (early-stage pancreatic cancer, advanced-stage pancreatic cancer, or both) when the level of the biomarker measured in the sample is higher or lower than the level of the biomarker in the reference sample; or

[0390] (iii) both steps (i) and (ii). Optionally, the method may further comprise, prior to step (b) (steps (i) and / or (ii)), an additional step of measuring the level of the biomarker in a reference sample.

[0391] The step of 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 both) and / or the number of cells expressing the biomarker. The method of measuring the concentration of the biomarker and / or the number of cells expressing the biomarker is not particularly limited, and the method can be any commonly used method for quantitative analysis of proteins, genes and / or cells, and is appropriately selected from the group consisting of immunochromatography, immunohistochemistry, enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (RIA), enzyme immunoassay (EIA), fluorescent immunoassay (FIA), luminescent immunoassay (LIA), protein blotting, microarray analysis, flow cytometry, polymerase chain reaction (PCR, such as qPCR, real-time PCR, real-time qPCR) and fluorescence in situ hybridization (FISH), but not limited thereto. In one embodiment, the step of measuring the level of the biomarker can also include applying a statistical analysis method suitable for biomarker analysis, such as regression analysis (e.g., stepwise logistic regression analysis), but not limited thereto. For further details on "biomarker level measurement", please refer to the "biomarker detection" section described previously.

[0392] As used herein, the phrase "increased biomarker level" refers to a situation where the biomarker level in a sample (e.g., the concentration (level) of a biomarker (protein and / or gene) (e.g., for a gene, a Ct value, a ΔCt value and / or a ΔΔCt value measured by PCR, or the number of cells expressing the biomarker) is about 1% or more, 2% or more, 3% or more, 4% or more, 5% or more, 7% or more, 8% or more, 9% or more, 10% or more, 12% or more, 15% or more, 18% or more, 20% or more, 22% or more, 25% or more, 28% or more, or 30% or more higher than the biomarker level in a reference sample.

[0393] As used herein, the phrase "reduced biomarker level" refers to a situation where the biomarker level in a sample (e.g., the concentration (level) of a biomarker (protein and / or gene) (e.g., for a gene, a Ct value, a ΔCt value and / or a ΔΔCt value measured by PCR, or the number of cells expressing the biomarker) is approximately 1% or more, 2% or more, 3% or more, 4% or more, 5% or more, 7% or more, 8% or more, 9% or more, 10% or more, 12% or more, 15% or more, 18% or more, 20% or more, 22% or more, 25% or more, 28% or more, or 30% or more lower than the biomarker level in a reference sample.

[0394] In another embodiment, the method may be a method for diagnosing early pancreatic cancer or a method for providing early pancreatic cancer diagnosis information, comprising the following steps:

[0395] (a-1) measuring the level of at least one biomarker selected from the group consisting of TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, SLC27A2, PTGES2 and PTGES (selected from one or more (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 or 13) of the group), their encoding genes or a combination thereof in a blood sample isolated from a subject.

[0396] In one embodiment, the step of measuring the biomarker level is as described above. For example, the biomarker level can be measured by quantitative analysis (e.g., in the case of PCR, measuring Ct values, ΔCt values ​​and / or ΔΔCt values) and optionally performing regression analysis (e.g., stepwise logistic regression analysis). Additional statistical analysis can also be performed as needed.

[0397] The method for diagnosing early pancreatic cancer or the method for providing early pancreatic cancer diagnosis information may further comprise the following steps after step (a-1):

[0398] (b-1) is calculated using the following formula:

[0399] [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

[0400] (in,

[0401] B0: a rational number in the range of 30 to 50, 30 to 47.5, 30 to 45, 32.5 to 50, 32.5 to 47.5, 32.5 to 45, 35 to 50, 35 to 47.5, or 35 to 45 (up to four decimal places), for example, 35.8476 or 44.4033;

[0402] TNF: expression level of TNF biomarker;

[0403] B1: coefficient of TNF expression level, a rational number in the range of -3 to -2 or -2.9 to -2.5 (up to four decimal places, such as -2.5794 or -2.8042), or 0;

[0404] IFNG: expression level of IFNG biomarker;

[0405] B2: coefficient of IFNG expression level, a rational number in the range of 3 to 4 or 3.3 to 3.8 (up to four decimal places, such as 3.3956 or 3.7082), or 0;

[0406] IFNL1: expression level of IFNL1 biomarker;

[0407] B3: coefficient of IFNL1 expression level, a rational number in the range of 0.1 to 0.5 or 0.2 to 0.3 (up to four decimal places, e.g., 0.2358), or 0;

[0408] CXCL11: expression level of CXCL11 biomarker;

[0409] B4: coefficient of CXCL11 expression level, a rational number ranging from 0.1 to 0.2 (up to four decimal places, e.g., 0.1568), or 0;

[0410] CLEC7A: expression level of CLEC7A biomarker;

[0411] B5: coefficient of CLEC7A expression level, a rational number in the range of 0.8 to 1.3 or 1 to 1.1 (up to four decimal places, e.g., 1.0951), or 0;

[0412] VEGFA: expression level of VEGFA biomarker;

[0413] B6: coefficient of VEGFA expression level, a rational number in the range of -1.5 to -0.2 or -1 to -0.7 (up to four decimal places, e.g. -0.8407), or 0;

[0414] CCL2: expression level of CCL2 biomarker;

[0415] B7: coefficient of CCL2 expression level, a rational number in the range of -1 to -0.1 or -0.7 to -0.5 (up to four decimal places, such as -0.5380 or -0.6622), or 0;

[0416] CXCR4: expression level of CXCR4 biomarker;

[0417] B8: coefficient of CXCR4 expression level, a rational number in the range of -1.5 to -0.5 or -1.1 to -0.7 (up to four decimal places, e.g. -0.9422), or 0;

[0418] CXCR2: expression level of CXCR2 biomarker;

[0419] B9: coefficient of CXCR2 expression level, a rational number in the range of 0.7 to 1.7 or 0.9 to 1.5 (up to four decimal places, such as 1.4027 or 1.0804), or 0;

[0420] ARG1: expression level of ARG1 biomarker;

[0421] B10: coefficient of ARG1 expression level, a rational number in the range of -1.7 to -0.7 or -1.4 to -1 (up to four decimal places, e.g. -1.143 or -1.2971), or 0;

[0422] SLC27A2: expression level of SLC27A2 biomarker;

[0423] B11: coefficient of SLC27A2 expression level, a rational number in the range of -5 to -4 or -4.8 to -4.3 (up to four decimal places, for example, -4.3771 or -4.7971), or 0;

[0424] PTGES2: expression level of PTGES2 biomarker;

[0425] B12: coefficient of PTGES2 expression level, a rational number in the range of 2.7 to 3.5 or 3 to 3.3 (up to four decimal places, for example, 3.1076 or 3.1934), or 0;

[0426] PTGES: expression level of PTGES biomarker;

[0427] B13: coefficient of PTGES expression level, a rational number in the range of -1 to -0.2 or -0.8 to -0.6 (up to four decimal places, e.g., -0.6396 or -0.7064), or 0;

[0428] The condition is that at least one of B1 to B13 is not 0).

[0429] The expression level of each biomarker used in [Formula 1] may be a value measured and quantified using a ΔCt value obtained using real-time PCR (eg, real-time qPCR; see Example 2).

[0430] The method for diagnosing early pancreatic cancer or the method for providing early pancreatic cancer diagnosis information may further comprise the following steps after step (b-1):

[0431] (c-1) Compare the value obtained in step (b-1) with the cutoff value.

[0432] In this regard, the cutoff value for diagnosing early pancreatic cancer may be a rational number (significant to five or six decimal places) in the range of -2.5 to -1.5 or -2 to -1.8, such as -1.855994 or -1.90875.

[0433] If the value obtained in step (b-1) exceeds the cutoff value, it can be predicted (determined or identified) that the subject is an early pancreatic cancer patient or is at high risk of developing early pancreatic cancer. It can be determined based on the comparison result in step (c-1) whether the value obtained in step (b-1) exceeds the cutoff value. In another implementation, if the value obtained in step (b-1) is equal to or lower than the cutoff value, it can be predicted (determined or identified) that the subject is normal and / or has a low risk of pancreatic cancer (early pancreatic cancer).

[0434] Therefore, the method for diagnosing early pancreatic cancer or the method for providing early pancreatic cancer diagnosis information may further include the following steps after step (c-1) or simultaneously with step (c-1):

[0435] (d-1) When the value obtained in step (b-1) exceeds the cutoff value, predicting (determining or identifying) the subject as an early pancreatic cancer patient or an individual at high risk of early pancreatic cancer.

[0436] In another embodiment, a method for diagnosing early pancreatic cancer or a method for providing early pancreatic cancer diagnosis information may include the following steps:

[0437] (a-2) measuring the expression level of at least one (for example, one or more (2, 3, 4, 5, 6, 7 or 8) selected from the group consisting of CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2 and TNF), the encoding genes thereof or a combination thereof in a blood sample isolated from the subject.

[0438] In one embodiment, the step of measuring the level of a biomarker is as described above. For example, the biomarker level can be quantified (e.g., by measuring Ct values, ΔCt values ​​and / or ΔΔCt values ​​by PCR), and optionally, by regression analysis (e.g., stepwise logistic regression analysis). Additional statistical analysis can be performed as needed.

[0439] The method for diagnosing early pancreatic cancer or the method for providing early pancreatic cancer diagnosis information may further comprise the following steps after step (a-2):

[0440] (b-2) Calculate using the following formula

[0441] [Formula 2] logit(p) = B0 + B1 × IFNG + B2 × SLC27A2 + B3 × CCL5 + B4 × PTGES2 + B5 × TNF + B6 × IFNL1 + B7 × CCL2 + B8 × CXCR2

[0442] (in:

[0443] B0: a rational number in the range of -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 (valid to six decimal places), for example, -1.957576;

[0444] IFNG: expression level of IFNG biomarker;

[0445] B1: coefficient of IFNG biomarker expression, a rational number in the range of 1 to 3 or 1.7 to 2.3 (valid to six decimal places, e.g., 1.942999), or 0;

[0446] SLC27A2: expression level of SLC27A2 biomarker;

[0447] B2: coefficient of SLC27A2 biomarker expression, a rational number in the range of -3 to -1.5 or -2.5 to -2 (valid to six decimal places, e.g., -2.370157), or 0;

[0448] CCL5: expression level of CCL5 biomarker;

[0449] B3: coefficient of CCL5 biomarker expression, a rational number in the range of 0.1 to 0.5 or 0.2 to 0.3 (valid to six decimal places, e.g., 0.236554), or 0;

[0450] PTGES2: expression level of PTGES2 biomarker;

[0451] B4: coefficient of PTGES2 biomarker expression, a rational number in the range of 1 to 2.5 or 1.5 to 2 (valid to six decimal places, e.g., 1.781672), or 0;

[0452] TNF: expression level of TNF biomarker;

[0453] B5: coefficient of TNF biomarker expression, a rational number in the range of -2 to -0.5 or -1.5 to -1 (valid to six decimal places, e.g., -1.328085), or 0;

[0454] IFNL1: expression level of IFNL1 biomarker;

[0455] B6: coefficient of IFNL1 biomarker expression, a rational number in the range of -0.5 to -0.1 or -0.3 to -0.1 (valid to six decimal places, e.g. -0.170127), or 0;

[0456] CCL2: expression level of CCL2 biomarker;

[0457] B7: coefficient of CCL2 biomarker expression, a rational number in the range of -1 to -0.1 or -0.7 to -0.3 (valid to six decimal places, e.g., -0.495828), or 0;

[0458] CXCR2: expression level of CXCR2 biomarker;

[0459] B8: coefficient of CXCR2 biomarker expression, a rational number in the range of 0.1 to 1 or 0.5 to 0.8 (valid to six decimal places, e.g., 0.611586), or 0,

[0460] The condition is that at least one of B1 to B8 is not 0. )

[0461] The expression level of each biomarker applied in [Formula 2] can be a value measured and quantified based on the ΔCt obtained using real-time PCR (e.g., real-time qPCR; see Example 2). In one embodiment, in order to improve the prediction accuracy, the ΔCt value can be statistically processed using a predetermined statistical analysis method before being applied to [Formula 2]. Examples of applicable statistical analysis methods include Robust Scaler, etc. For example, when Robust Scaler is applied, the ΔCt value can be processed using [Formula 5] to obtain a transformed value (x'), which is then applied to [Formula 2]:

[0462] x'=[x-median(x)] / IQR[Formula 5]

[0463] (x: ΔCt value of each biomarker in diagnosed subjects; Median (x): median of ΔCt values ​​of corresponding biomarkers in a given population including diagnosed subjects; and IQR (interquartile range): range between the third quartile (Q3) and the first quartile (Q1), calculated as Q3-Q1).

[0464] The method for diagnosing early pancreatic cancer or the method for providing early pancreatic cancer diagnosis information may further comprise the following steps after step (b-2):

[0465] (c-2) Compare the value obtained in step (b-2) with the cutoff value.

[0466] In this regard, the cutoff value for diagnosing early pancreatic cancer may be a rational number (significant to three decimal places) in the range of 0.1 to 0.5 or 0.2 to 0.3, for example 0.282.

[0467] When the value obtained in step (b-2) exceeds the cutoff value, it can be predicted (determined, inferred) that the test subject is an early pancreatic cancer patient or is at a high risk of suffering from early pancreatic cancer. In this case, it can be determined based on the comparison result in step (c-2) whether the value obtained in step (b-2) exceeds the cutoff value. In another embodiment, when the numerical value obtained in step (b-2) is equal to or lower than the cutoff value, it can be predicted (determined, inferred) that the test subject is normal and / or has a low risk of suffering from pancreatic cancer (early pancreatic cancer).

[0468] Therefore, the method for diagnosing early pancreatic cancer or the method for providing early pancreatic cancer diagnosis information may further include the following steps after step (c-2) or simultaneously with step (c-2):

[0469] (d-2) When the value obtained in step (b-2) exceeds the cutoff value, predicting (determining, inferring) that the test subject is an early pancreatic cancer patient or a patient at high risk of having early pancreatic cancer.

[0470] In another embodiment, the method may be a method for diagnosing all pancreatic cancers (early-stage pancreatic cancers and / or advanced-stage pancreatic cancers) or a method for providing diagnostic information for all pancreatic cancers, comprising the following steps:

[0471] (a-3) measuring the level of at least one of the group consisting of TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2, SLC27A2 and PTGES2 (for example, any one or more (2, 3, 4, 5, 6, 7, 8, 9, 10 or 11) selected from the group), the genes encoding them or a combination thereof in a blood sample isolated from the subject.

[0472] In one embodiment, the step of measuring the level of a biomarker is as described above. For example, the step of measuring the level of a biomarker may include quantification of the biomarker (e.g., measuring Ct values, ΔCt values, and / or ΔΔCt values ​​by PCR) and optionally regression analysis (e.g., stepwise logistic regression analysis). In addition, appropriate statistical analysis may also be performed as needed.

[0473] In one embodiment, the method for diagnosing all pancreatic cancers or the method for providing diagnostic information for all pancreatic cancers may further include the following steps after step (a-3):

[0474] (b-3) Calculate using the following formula

[0475] [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

[0476] (in,

[0477] B0: a rational number (valid to four decimal places) selected from the range of 30 to 40, 30 to 38, 30 to 37, 32.5 to 40, 32.5 to 38, 32.5 to 37, 36 to 40, 36 to 38 or 36 to 37, for example, 36.9898 or 36.6273;

[0478] TNF: expression level of TNF biomarker;

[0479] B1: coefficient of TNF biomarker, selected from a rational number from -2.5 to -2 or -2.3 to -2.2 (valid to four decimal places, such as -2.2200 or -2.2286), or 0;

[0480] IFNG: expression level of IFNG biomarker;

[0481] B2: coefficient of the IFNG biomarker, selected from a rational number between 0.5 and 1.5 or between 0.9 and 1.1 (valid to four decimal places, such as 0.9955 or 1.0041), or 0;

[0482] CXCL11: expression level of CXCL11 biomarker;

[0483] B3: a coefficient of the CXCL11 biomarker, selected from a rational number of 0.1 to 0.5 or 0.3 to 0.4 (valid to four decimal places, such as 0.3413 or 0.3704), or 0;

[0484] VEGFA: expression level of VEGFA biomarker;

[0485] B4: coefficient of the VEGFA biomarker, selected from a rational number from -3.2 to -2.5 or -2.9 to -2.7 (valid to four decimal places, such as -2.7990 or -2.7473), or 0;

[0486] CCL2: expression level of CCL2 biomarker;

[0487] B5: a coefficient of the CCL2 biomarker, selected from a rational number from -0.3 to -0.01 or -0.25 to -0.15 (valid to four decimal places, such as -0.1913 or -0.2240), or 0;

[0488] CCL5: expression level of CCL5 biomarker;

[0489] B6: a coefficient of the CCL5 biomarker, selected from a rational number of 1 to 1.5 or 1.3 to 1.4 (valid to four decimal places, such as 1.3628 or 1.3874), or 0;

[0490] CXCR4: expression level of CXCR4 biomarker;

[0491] B7: coefficient of the CXCR4 biomarker, selected from a rational number from -2.5 to -1.5 or -2.2 to -2 (valid to four decimal places, such as -2.0521 or -2.0986), or 0;

[0492] CXCR2: expression level of CXCR2 biomarker;

[0493] B8: a coefficient of the CXCR2 biomarker, selected from a rational number of 0.2 to 1.2 or 0.6 to 0.8 (valid to four decimal places, such as 0.7037 or 0.6388), or 0;

[0494] PTGS2: expression level of PTGS2 biomarker;

[0495] B9: coefficient of the PTGS2 biomarker, selected from a rational number between -0.01 and -0.1 (valid to four decimal places, e.g., -0.0640), or 0;

[0496] SLC27A2: expression level of SLC27A2 biomarker;

[0497] B10: a coefficient of the SLC27A2 biomarker, selected from a rational number between -3.5 and -3 or between -3.3 and -3.1 (valid to four decimal places, such as -3.1754 or -3.1990), or 0;

[0498] PTGES2: expression level of PTGES2 biomarker;

[0499] B11: coefficient of the PTGES2 biomarker, selected from a rational number between 4 and 5 or between 4.4 and 4.6 (valid to four decimal places, for example, 4.4765) or 0;

[0500] The condition is that at least one of B1 to B11 is not 0. )

[0501] The expression level of each biomarker applied in Formula 3 may be a value measured and quantified based on a ΔCt value obtained by real-time PCR (eg, real-time qPCR; see Example 2).

[0502] Regardless of the stage of disease progression, the method for diagnosing all pancreatic cancers or providing diagnostic information for any pancreatic cancer may further comprise the following steps after step (b-3):

[0503] (c-3) Compare the value obtained in step (b-3) with the cutoff value.

[0504] In this regard, the cutoff value for diagnosing all pancreatic cancers can be a rational number (significant to five decimal places) in the range of -3.5 to -2 or -3 to -2.5, such as -0.25109 or -0.29033.

[0505] When the value obtained in step (b-3) exceeds the cutoff value, it can be predicted (determined, determined) that the test subject is a pancreatic cancer patient or has a high risk of developing pancreatic cancer. In this case, it can be determined based on the comparison result in step (c-3) whether the value obtained in step (b-3) exceeds the cutoff value. In another embodiment, when the numerical value obtained in step (b-3) is equal to or lower than the cutoff value, it can be predicted (determined, determined) that the test subject is normal and / or has a low risk of developing pancreatic cancer.

[0506] Therefore, the method for diagnosing all pancreatic cancers or providing diagnostic information for all pancreatic cancers may include the following steps after step (c-3) or simultaneously with step (c-3):

[0507] (d-3) When the value obtained in step (c-3) exceeds the cutoff value, predicting (determining, deciding) that the test subject is a pancreatic cancer patient or a patient with a high risk of developing pancreatic cancer.

[0508] In another embodiment, the method may be a method for diagnosing all pancreatic cancers (early-stage pancreatic cancers and / or advanced-stage pancreatic cancers) or a method for providing diagnostic information for all pancreatic cancers, comprising the following steps:

[0509] (a-4) measuring the level of at least one of the group consisting of CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2 and TNF (for example, any one or more (2, 3, 4, 5, 6, 7 or 8) selected from the group), the genes encoding them or a combination thereof in a blood sample isolated from the subject.

[0510] In one embodiment, the step of measuring the level of a biomarker is as described above. For example, the step of measuring the level of a biomarker can be performed by quantifying the biomarker (e.g., in the case of PCR, measuring Ct values, ΔCt values ​​and / or ΔΔCt values) and optionally performing a regression analysis (e.g., a stepwise logistic regression analysis). In addition, appropriate statistical analysis can be performed as needed.

[0511] The method for diagnosing all pancreatic cancers or providing diagnostic information of all pancreatic cancers may further include the following steps after step (a-4):

[0512] (b-4) Calculate using the following formula:

[0513] [Formula 4] logit(p) = B0 + B1 × IFNG + B2 × SLC27A2 + B3 × CCL5 + B4 × PTGES2 + B5 × TNF + B6 × IFNL1 + B7 × CCL2 + B8 × CXCR2

[0514] (in,

[0515] B0: a rational number in the range of 0.1 to 1, 0.1 to 0.8, 0.5 to 1, or 0.5 to 0.8 (valid to six decimal places), for example, 0.654363;

[0516] IFNG: expression level of biomarker IFNG;

[0517] B1: coefficient of the expression level of the biomarker IFNG, a rational number in the range of 0.5 to 2 or 1.2 to 1.6 (valid to six decimal places, e.g., 1.397767) or 0;

[0518] SLC27A2: expression level of biomarker SLC27A2;

[0519] B2: coefficient of the biomarker SLC27A2 expression level, a rational number in the range of -2.5 to -1 or -2 to -1.6 (valid to six decimal places, e.g., -1.874652) or 0;

[0520] CCL5: expression level of biomarker CCL5;

[0521] B3: coefficient of the expression level of the biomarker CCL5, a rational number in the range of 0.1 to 1.2 or 0.6 to 1 (valid to six decimal places, for example, 0.855608) or 0;

[0522] PTGES2: expression level of biomarker PTGES2;

[0523] B4: coefficient of the expression level of the biomarker PTGES2, a rational number in the range of 1 to 2.5 or 1.5 to 2 (valid to six decimal places, for example, 1.782533) or 0;

[0524] TNF: expression level of biomarker TNF;

[0525] B5: coefficient of the biomarker TNF expression level, a rational number in the range of -3 to -1.5 or -2.5 to -2.1 (valid to six decimal places, e.g. -2.378006) or 0;

[0526] IFNL1: expression level of biomarker IFNL1;

[0527] B6: coefficient of the biomarker IFNL1 expression level, a rational number in the range of -0.0002 to -0.0001 (valid to six decimal places, e.g., -0.000140) or 0;

[0528] CCL2: expression level of biomarker CCL2;

[0529] B7: coefficient of the expression level of the biomarker CCL2, a rational number in the range of -1 to -0.1 or -0.7 to -0.3 (valid to six decimal places, for example -0.535484) or 0;

[0530] CXCR2: expression level of biomarker CXCR2;

[0531] B8: coefficient of the biomarker CXCR2 expression level, a rational number in the range of 0.1 to 0.7 or 0.2 to 0.4 (valid to six decimal places, for example, 0.300359) or 0,

[0532] The condition is that at least one of B1 to B8 is not 0. )

[0533] The expression level of each biomarker applied in [Formula 4] can be a value measured and quantified by a ΔCt value obtained by real-time PCR (e.g., real-time qPCR; see Example 2). In a specific embodiment, in order to improve the prediction accuracy, the ΔCt value can be statistically processed using a predetermined statistical analysis method before being applied to Formula 4. An example of an available statistical analysis method is Robust Scaler. For example, when Robust Scaler is applied, the ΔCt value can be processed using the following formula [Formula 5], and the resulting value (x') can be applied to Formula 4:

[0534] x'=[x-median(x)] / IQR[Formula 5]

[0535] (x: ΔCt value of each marker of diagnosed subjects; Median (x): median of ΔCt value of each marker in an arbitrary group including diagnosed subjects; IQR (interquartile range): range (Q3-Q1) between the third quartile (Q3) and the first quartile (Q1)).

[0536] The method for diagnosing all pancreatic cancers or providing diagnostic information of all pancreatic cancers may further comprise the following steps after step (b-4):

[0537] (c-4) Compare the value obtained in step (b-4) with the cutoff value.

[0538] In this regard, the cutoff value for diagnosing all pancreatic cancers may be a rational number (significant to three decimal places) in the range of 0.3 to 1.2 or 0.5 to 0.9, such as 0.732.

[0539] When the value obtained in step (b-4) exceeds the cutoff value, it can be predicted (determined, determined) that the test subject is a pancreatic cancer patient (all pancreatic cancers) or has a high risk of suffering from pancreatic cancer (all pancreatic cancers). In this case, it can be determined based on the comparison result in step (c-4) whether the value obtained in step (b-4) exceeds the cutoff value. In another embodiment, when the numerical value obtained in step (b-4) is equal to or lower than the cutoff value, it can be predicted (determined, determined) that the test subject is normal and / or has a low risk of suffering from pancreatic cancer (all pancreatic cancers).

[0540] Therefore, the method for diagnosing all pancreatic cancers or providing diagnostic information for all pancreatic cancers may include the following steps after step (c-4) or simultaneously with step (c-4):

[0541] (d-4) When the value obtained in step (b-4) exceeds the cutoff value, predicting (determining, deciding) that the subject is a patient who will develop all pancreatic cancers or a patient who has a high risk of developing all pancreatic cancers.

[0542] The method for diagnosing pancreatic cancer or providing diagnostic information of pancreatic cancer provided in the present disclosure may also include, after the detection step, the comparison step or the diagnosis (prediction, determination or decision) step, the step of treating pancreatic cancer in a subject diagnosed as having pancreatic cancer (early pancreatic cancer, advanced pancreatic cancer or both).

[0543] Pancreatic cancer treatment may refer to chemotherapy, such as administration of pancreatic cancer therapeutic agents (eg, anticancer agents: 5-fluorouracil (5-FU), gemcitabine, Tarceva (erlotinib), antibodies, etc.), radiation therapy, surgery, or a combination of two or more thereof.

[0544] According to the stage and progress of pancreatic cancer, pancreatic cancer treatment can be applied differently. Early pancreatic cancer (e.g., resectable pancreatic cancer) is a pancreatic cancer stage that can be treated by surgery. The treatment of early pancreatic cancer can only involve surgery or adjuvant chemotherapy after surgical resection. Adjuvant chemotherapy refers to anticancer therapy beyond surgery, and can include chemotherapy, such as administration of pancreatic cancer therapeutic agent (e.g., selected from one or more anticancer agents in the group consisting of 5-fluorouracil (5-FU), gemcitabine, tarceva (erlotinib), leucovorin, irinotecan, oxaliplatin, oxaliplatin three-drug chemotherapy (Folfirinox), albumin-bound paclitaxel (Abraxane), irinotecan liposome (Onivyde), TS-1, capecitabine, antibodies, etc.), chemoradiotherapy or its combination.

[0545] Treatment of advanced pancreatic cancer (eg, borderline resectable pancreatic cancer, locally advanced pancreatic cancer, metastatic pancreatic cancer) may be applied differently depending on the stage of progression of each type of pancreatic cancer.

[0546] For example, for pancreatic cancer with borderline resectable disease in advanced pancreatic cancer, neoadjuvant therapy (e.g., administration of one or more anticancer agents selected from the group consisting of 5-fluorouracil (5-FU), leucovorin, irinotecan, oxaliplatin, etc. (e.g., oxaliplatin triple chemotherapy (FOLFIRINOX), which involves combined administration of four anticancer agents)) can be performed. Thereafter, depending on the treatment results, (i) if surgical resection is possible, adjuvant chemotherapy can be performed after surgery, and (ii) if surgical resection is not possible, chemotherapy can be performed.

[0547] For locally advanced pancreatic cancer in advanced pancreatic cancer, neoadjuvant therapy (e.g., administration of one or more anticancer agents selected from the group consisting of 5-fluorouracil (5-FU), leucovorin, irinotecan, oxaliplatin, etc. (e.g., oxaliplatin triple chemotherapy, which involves combined administration of four anticancer agents)) can be performed. Thereafter, depending on the progression results, neoadjuvant therapy or secondary therapy (e.g., combination therapy of nanoparticle albumin-bound paclitaxel (nab-paclitaxel) and gemcitabine), chemoradiotherapy, or a combination of two or more thereof can be continued.

[0548] For metastatic pancreatic cancer in advanced pancreatic cancer, neoadjuvant therapy (e.g., administration of one or more anticancer agents selected from the group consisting of 5-fluorouracil (5-FU), leucovorin, irinotecan, oxaliplatin, etc. (e.g., oxaliplatin triple chemotherapy, which involves the combined administration of four anticancer agents)), chemotherapy (e.g., combination therapy of nanoparticle albumin-bound paclitaxel (nab-paclitaxel) and gemcitabine, or administration of gemcitabine alone), or a combination thereof may be performed. Thereafter, secondary treatment may be performed depending on the patient's condition. Secondary treatment may refer to chemotherapy, including, for example, combination therapy of nanoparticle albumin-bound paclitaxel (nab-paclitaxel) and gemcitabine, combination therapy of 5-fluorouracil (5-FU) and liposomal irinotecan, or combination therapy of 5-fluorouracil (5-FU) and liposomal oxaliplatin.

[0549] Blood samples

[0550] Diagnostic target samples or blood samples suitable for the compositions, kits and methods for diagnosing pancreatic cancer provided in the present disclosure may include liquid biopsy samples obtained (or separated or derived) from the diagnosis subject, such as blood, serum, plasma and / or cells separated therefrom. In one embodiment, the sample may include a buffy coat separated from the diagnosis subject.

[0551] 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 during centrifugation of blood. It is a mixture of blood components other than plasma and red blood cells (e.g., monocytes, granulocytes, lymphocytes, etc.) and is clearly different from peripheral blood mononuclear cells (PBMCs) (see Figure 3). The blood sample used in the present disclosure may be a blood-derived buffy coat, and may not be a sample consisting only of peripheral blood mononuclear cells. In one embodiment, after centrifuging the blood under one or more (1, 2, or 3) conditions selected from the following conditions (1) to (3), a buffy coat may be obtained from the middle buffy coat among the sequentially separated plasma layer (top), buffy coat (middle), and red blood cell layer (bottom):

[0552] (1) Temperature: 2 to 30°C, 2 to 28°C, 2 to 25°C, 2 to 23°C, 2 to 20°C, 2 to 18°C, 2 to 15°C, 2 to 13°C, 2 to 10°C, 2 to 8°C, 2 to 6°C, 2 to 5°C, 2 to 4°C, 3 to 30°C, 3 to 28°C, 3 to 25°C, 3 to 23°C, 3 to 20°C, 3 to 18°C, 3 to 15°C, 3 to 13°C, 3 to 10°C, 3 to 8°C, 3 to 6°C, 3 to 5°C, 3 to 4°C, 4 to 30°C, 4 to 28°C, 4 to 25°C, 4 to 23°C, 4 to 20°C, 4 to 18°C, 4 to 15°C, 4 to 13°C, 4 to 10℃, 4 to 8℃, 4 to 6℃, 4 to 5℃, 5 to 30℃, 5 to 28℃, 5 to 25℃, 5 to 23℃, 5 to 20℃, 5 to 18℃, 5 to 15℃, 5 to 13℃, 5 to 10℃, 5 to 8℃, 5 to 6℃, 10 to 30℃, 10 to 28℃, 10 to 25℃, 10 to 23℃, 10 to 20℃, 10 to 18℃, 10 to 15℃, 10 to 13℃, 15 to 30℃, 15 to 28℃, 15 to 25℃, 15 to 23℃, 15 to 20℃, 15 to 18℃, 20 to 30℃, 20 to 28℃, 20 to 25℃, or 20 to 23℃;

[0553] (2) Speed: 300 g to 2000 g, 300 g to 1800 g, 300 g to 1500 g, 300 g to 1300 g, 300 g to 1000 g, 500 g to 2000 g, 500 g to 1800 g, 500 g to 1500 g, 500 g to 1300 g, 500 g to 1000 g, 600 g to 1000 g, 700 g to 1000 g, 800 g to 1000 g, 500 g to 900 g, 600 g to 900 g, 700 g to 900 g, 800 g to 900 g, 500 g to 800 g, 600 g to 800 g, or 700 g to 800 g; and

[0554] (3) Duration: The duration is 5 to 20 minutes, 7 to 20 minutes, 9 to 20 minutes, 5 to 15 minutes, 7 to 15 minutes, 9 to 15 minutes, 5 to 12 minutes, 7 to 12 minutes or 9 to 12 minutes.

[0555] In the present disclosure, the diagnostic subject (individual) may be selected from mammals, including primates such as humans and monkeys, rodents such as mice and rats, and other species in need of pancreatic cancer diagnosis.

[0556] In the present disclosure, the control sample may be a sample obtained from (or separated from or derived from) a normal individual (e.g., an individual who does not suffer from pancreatic cancer (early pancreatic cancer, advanced pancreatic cancer, or both)) or an individual suffering from a similar disease (benign pancreatic disease, such as pancreatitis (chronic pancreatitis and / or acute pancreatitis), benign pancreatic tumors, intraductal papillary mucinous neoplasms (IPMN), autoimmune pancreatitis (AIP) and other pancreatic diseases (excluding pancreatic cancer (malignant pancreatic tumors)) and / or bile duct cancer). For example, the normal individual may be selected from mammals, including primates such as humans and monkeys, rodents such as mice and rats, and may be an individual of the same species as the diagnosed subject. The comparison sample may include blood, serum, plasma, and / or cells separated therefrom obtained (or separated or derived) from the comparison subject. Specifically, the comparison sample may include a buffy coat.

[0557] Screening of therapeutic agents for pancreatic cancer

[0558] Another embodiment provides a method of screening candidate compounds for pancreatic cancer therapeutics by measuring the levels of biomarkers after treatment with the candidate compounds.

[0559] More specifically, the screening method may include the following steps:

[0560] contacting the biological sample with a candidate compound;

[0561] Measuring the level of at least one biomarker selected from the aforementioned biomarkers and genes encoding them in a biological sample; and

[0562] The level of the biomarker in a biological sample treated with the candidate compound is compared to the level of the biomarker or its encoding gene in a biological sample not treated with the candidate compound.

[0563] The comparing step can be performed by measuring and comparing the levels of the biomarker in the same biological sample before and after treatment with the candidate compound, or by contacting only a portion of the biological sample with the candidate compound, measuring the levels of the biomarker in the treated and uncontacted portions, and comparing those levels.

[0564] When the level of the biomarker in a biological sample treated with the candidate compound is lower than the level of the biomarker in an untreated biological sample, that is, when the candidate compound reduces the level of the biomarker or inhibits the expression of the biomarker, the candidate compound can be determined to be a potential agent for preventing and / or treating pancreatic cancer.

[0565] The biological sample may include blood, serum, plasma and / or cells derived from (isolated or derived from) an organism (eg, a pancreatic cancer patient). More specifically, the biological sample may include a buffy coat.

[0566] The candidate compound can be selected from various types of compounds, including small molecules, proteins, polypeptides, oligopeptides, polynucleotides, oligonucleotides or extracts derived from plants or animals.

[0567] The measurement of the biomarker level in the biological sample can be performed using conventional gene or protein quantitative methods and / or by evaluating the measurement results. The specific measurement method can be as described above.

[0568] All numerical values ​​provided herein should be interpreted as including conventional error ranges, as long as the desired functions and / or effects of the present application can be achieved. For example, these values ​​can be interpreted as including -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%), but are not limited thereto.

[0569] Beneficial Effects

[0570] Through this application, pancreatic cancer can be diagnosed with high accuracy in a non-invasive and simple manner using only patient-derived blood. In addition, the progression stage of pancreatic cancer can be diagnosed more accurately, and differentiation from other similar diseases can be achieved, thereby enabling the development of more effective pancreatic cancer treatment strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0571] Figure 1 is a schematic diagram exemplifying the buffy coat sample preparation process compared to PBMC samples.

[0572] Figure 2 It is a graph showing the real-time qPCR results (ΔΔCt value) of IFNL1 in the normal control group, the early pancreatic cancer patient group (early PC), and the late pancreatic cancer patient group (late PC).

[0573] Figure 3 It is a graph showing the real-time qPCR results (ΔΔCt value) of IFNG in the normal control group, the early pancreatic cancer patient group, and the advanced pancreatic cancer patient group.

[0574] Figure 4 It is a graph showing the real-time qPCR results (ΔΔCt value) of CXCL11 in the normal control group, the early pancreatic cancer patient group, and the advanced pancreatic cancer patient group.

[0575] Figure 5It is a graph showing the real-time qPCR results (ΔΔCt value) of TNF in the normal control group, the early pancreatic cancer patient group, and the advanced pancreatic cancer patient group.

[0576] Figure 6 It is a graph showing the real-time qPCR results (ΔΔCt value) of CLEC7A in the normal control group, the early pancreatic cancer patient group, and the advanced pancreatic cancer patient group.

[0577] Figure 7 It is a graph showing the real-time qPCR results (ΔΔCt value) of CXCL8 in the normal control group, the early pancreatic cancer patient group, and the advanced pancreatic cancer patient group.

[0578] Figure 8 It is a graph showing the real-time qPCR results (ΔΔCt value) of FOXP3 in the normal control group, the early pancreatic cancer patient group, and the advanced pancreatic cancer patient group.

[0579] Fig. 9 It is a graph showing the real-time qPCR results (ΔΔCt value) of VEGFA in the normal control group, the early pancreatic cancer patient group, and the advanced pancreatic cancer patient group.

[0580] Fig.10 It is a graph showing the real-time qPCR results (ΔΔCt value) of CCL2 in the normal control group, the early pancreatic cancer patient group, and the advanced pancreatic cancer patient group.

[0581] Fig.11 It is a graph showing the real-time qPCR results (ΔΔCt value) of CCL5 in the normal control group, the early pancreatic cancer patient group, and the advanced pancreatic cancer patient group.

[0582] Fig.12 It is a graph showing the real-time qPCR results (ΔΔCt value) of CCR5 in the normal control group, the early pancreatic cancer patient group, and the advanced pancreatic cancer patient group.

[0583] Fig.13 It is a graph showing the real-time qPCR results (ΔΔCt value) of CXCR4 in the normal control group, the early pancreatic cancer patient group, and the advanced pancreatic cancer patient group.

[0584] Fig.14 It is a graph showing the real-time qPCR results (ΔΔCt value) of ARG1 in the normal control group, the early pancreatic cancer patient group, and the advanced pancreatic cancer patient group.

[0585] Fig.15 It is a graph showing the real-time qPCR results (ΔΔCt value) of CXCR2 in the normal control group, the early pancreatic cancer patient group, and the advanced pancreatic cancer patient group.

[0586] Fig.16It is a graph showing the real-time qPCR results (ΔΔCt value) of PTGS2 in the normal control group, the early pancreatic cancer patient group, and the advanced pancreatic cancer patient group.

[0587] Fig.17 It is a graph showing the real-time qPCR results (ΔΔCt value) of PTGES2 in the normal control group, the early pancreatic cancer patient group, and the advanced pancreatic cancer patient group.

[0588] Fig.18 It is a graph showing the real-time qPCR results (ΔΔCt value) of SLC27A2 in the normal control group, the early pancreatic cancer patient group, and the advanced pancreatic cancer patient group.

[0589] Fig.19 It is a graph showing the real-time qPCR results (ΔΔCt value) of PTGES in the normal control group, the early pancreatic cancer patient group, and the advanced pancreatic cancer patient group.

[0590] Fig. 20 It is a graph showing the real-time qPCR results (ΔΔCt value) of IFNB1 in the pancreatic cancer patient group and the benign pancreatic disease patient group.

[0591] Fig.21 It is a graph showing the real-time qPCR results (ΔΔCt value) of IFNB1 in the pancreatic cancer patient group and the bile duct cancer patient group.

[0592] Fig. 22 It is a graph showing the real-time qPCR results (ΔΔCt value) of IFNA1 in the pancreatic cancer patient group and the benign pancreatic disease patient group.

[0593] Fig.23 Shown is a ROC curve analysis using a combination of 9 markers (ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF, and FOXP3) in normal controls and early pancreatic cancer patients.

[0594] Fig.24 Shown is a ROC curve analysis using a combination of 9 markers (CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF, and VEGFA) in normal controls and advanced pancreatic cancer patients.

[0595] Fig.25 Shown is a ROC curve analysis using a combination of 9 markers (ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4, and CCL5) in normal controls and all pancreatic cancer patients.

[0596] Fig.26aShown is the ROC curve analysis using all 20 markers in normal controls and early pancreatic cancer patients.

[0597] Figure 26b ROC curve analysis using all 20 markers in normal controls and advanced pancreatic cancer patients is shown.

[0598] Fig.26c ROC curve analysis using all 20 markers in normal controls and all pancreatic cancer patients is shown.

[0599] Fig.27a ROC curve analysis using 12 markers (CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3) in normal controls and early pancreatic cancer patients is shown.

[0600] Figure 27b ROC curve analysis using 12 markers (CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3) in normal controls and advanced pancreatic cancer patients is shown.

[0601] Fig.27c ROC curve analysis using 12 markers (CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3) in normal controls and all pancreatic cancer patients is shown.

[0602] Fig.28a ROC curve analysis using 15 markers (CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11) in normal controls and early pancreatic cancer patients is shown.

[0603] Fig.28b ROC curve analysis using 15 markers (CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11) in normal controls and advanced pancreatic cancer patients is shown.

[0604] Fig.28cROC curve analysis using 15 markers (CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11) in normal controls and all pancreatic cancer patients is shown.

[0605] Fig.29a ROC curve analysis using eight markers (CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF) in normal controls and early pancreatic cancer patients is shown.

[0606] Fig.29b ROC curve analysis using eight markers (CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF) in normal controls and advanced pancreatic cancer patients is shown.

[0607] Fig.29c ROC curve analysis using eight markers (CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF) in normal controls and all pancreatic cancer patients is shown.

[0608] Fig.30 It is a summary Figure 23 to Figure 29c The table of results. DETAILED DESCRIPTION

[0609] The following description is intended to illustrate the scope of the present invention, but should not be construed as limiting the scope of the present invention.

[0610] Example 1: Sample preparation

[0611] To investigate the expression patterns of pancreatic cancer biomarkers in pancreatic cancer, buffy coat samples from the blood of pancreatic cancer patients, benign pancreatic disease patients (including 3 cases of pancreatitis (chronic and acute pancreatitis), 12 cases of benign pancreatic tumors, 1 case of intraductal papillary mucinous neoplasm (IPMN), 2 cases of autoimmune pancreatitis (AIP), and other pancreatic diseases; 20 cases in total) and cholangiocarcinoma patients (40 cases) were used to measure the mRNA expression levels of various markers. In addition, for comparison, the same experiment was performed using buffy coat samples from the blood of healthy individuals without pancreatic cancer (normal control group).

[0612] First, blood samples (8 mL each) were collected from 105 patients with pancreatic cancer (36 early pancreatic cancer and 69 advanced pancreatic cancer) and 183 healthy individuals. The collected blood samples were placed in EDTA tubes and centrifuged at 1,800 g for 10 minutes at 24 ° C within 2 hours of collection. The upper layer of the centrifuged blood (which is separated into plasma, white blood cell layer and red blood cells in turn) was processed by removing the plasma layer. Then, 250 μL of the white blood cell layer was separated into a storage tube and stored in a refrigerator at -80 ° C.

[0613] Pancreatic cancer patients were classified into early-stage and late-stage groups according to the criteria shown in Table 2 below:

[0614] Table 2

[0615]

[0616]

[0617] Example 2: Real-time qPCR

[0618] Real-time qPCR was used to measure gene expression in the samples prepared in Example 1, and real-time qPCR was performed using a probe-based multiplex PCR method.

[0619] First, follow the manufacturer's recommended regimen using Total RNA was extracted from 250 μL of frozen buffy coat sample (prepared in Example 1) using RNA Blood Kit (MACHEREY-NAGEL). TM cDNA synthesis was performed using the Reverse Transcription System Kit (Promega), and 1 μg of RNA from each sample was used for cDNA synthesis.

[0620] For multiplex PCR, each marker probe was labeled with FAM dye, while GAPDH as an internal reference gene was labeled with HEX dye. Primers and probes were purchased from IDT (Integrated DNA Technologies, Inc.).

[0621] To evaluate the expression of each gene in a sample, Probe qPCR Master Mix (Promega) protocol was used to prepare the reactions in a final volume of 20 μL. Gene expression assays were performed using QuantStudio 3 and 5 Real-Time PCR Systems (Applied Biosystems) under standard cycling conditions provided by the instrument software. In the real-time qPCR results, the Ct value of the mRNA expression level of each marker and the Ct value of the GAPDH mRNA expression level were extracted. The difference between the mRNA expression level of each marker and the GAPDH mRNA expression level was calculated to obtain the ΔCt value. In order to compare the mRNA expression level of each marker between healthy individuals and pancreatic cancer patients or between pancreatic cancer and benign pancreatic disease / cholangiocarcinoma groups, the ΔΔCt value was calculated using the following formula: ΔΔCt = ΔCt (pancreatic cancer or benign pancreatic disease / cholangiocarcinoma samples) - ΔCt (average value of healthy individuals). In order to visualize the increase or decrease in the mRNA expression level of each marker in pancreatic cancer patients compared with healthy individuals or patients with benign pancreatic diseases, 2 -ΔΔCt Formula conversion numerical value and use ANOVA analysis.All other statistical analyses are carried out using ΔCt values.Higher ΔΔCt values ​​indicate that gene expression increases, while lower ΔΔCt values ​​indicate that gene expression decreases.On the contrary, the decrease in ΔCt values ​​indicates that actual gene expression is upregulated, while the increase in ΔCt values ​​indicates that actual gene expression is downregulated.

[0622] The markers used in the experiment are listed in Table 3, and the nucleotide sequences (5'→3') of the primers and probes for each marker are provided in Table 4 below:

[0623] Table 3

[0624] serial number Gene name Reference sequence (NCBI) IDT test name 1 IL29(IFNL1) NM_172140 Hs.PT.56a.21113836.g 2 IFNG NM_000619 Hs.PT.58.3781960 3 CXCL11(I-TAC) NM_005409 Hs.PT.58.26723814 4 TNF NM_000594 Hs.PT.58.45380900 5 IFNB1 NM_002176 Hs.PT.58.39481063 6 IFNA1 NM_024013 Hs.PT.58.46311748.g 7 DECTIN-1(CLEC7A) NM_022570(5) Hs.PT.58.40018774 8 IL-8 (CXCL8) NM_000584 Hs.PT.58.38869678.G 9 FOXP3 NM_014009 Hs.PT.58.3671186 10 VEGFA NM_003376 Hs.PT.58.1149801 11 CCL2 NM_002982 Hs.PT.58.45467977 12 CCL5 NM_002985 Hs.PT.58.1724551 13 CCR5 NM_000579 Hs.PT.58.2249633 14 CXCR4 NM_003467 Hs.PT.58.22298491 15 ARG1 NM_001244438 Hs.PT.56a.20779559 16 CXCR2 NM_001557 Hs.PT.58.40527202 17 SLC27A2 (FATP2) NM_003645 Hs.PT.58.38450787 18 PTGS2 (COX2) NM_000963 Hs.PT.58.77266 19 PTGES2 NM_198938 Hs.PT.58.40424722 20 PTGES (PTGES1) NM_004878 Hs.PT.58.39853040

[0625] Table 4

[0626]

[0627]

[0628]

[0629] (In Table 4, the probe structure includes 5'FAM dye, internal ZEN quencher and *3'Iowa Fluorescence quencher (IBFQ).

[0630] For qPCR analysis, data from samples with GAPDH Ct values ​​above 26.5 were excluded. All statistical analyses were performed using ΔCt values, except for ANOVA using ΔΔCt values. To evaluate the statistical significance of each marker between pancreatic cancer patients and healthy individuals, the Kruskal-Wallis test was performed using GraphPad PRISM9 statistical software. For AUC, sensitivity, and specificity analysis based on marker combinations, logistic regression and ROC curve analysis were performed using MedCalc statistical software.

[0631] Example 3: Diagnosis of pancreatic cancer using individual markers

[0632] For 105 pancreatic cancer patients (36 early pancreatic cancer patients and 69 advanced pancreatic cancer patients) and 183 healthy individuals, buffy coat samples were obtained using the method described in Example 1. Real-time qPCR was performed for each marker listed in Table 3 using the method described in Example 2, and the results (ΔΔCt values) are shown in Table 3. Figures 2 to 19 As shown, and summarized in the following Table 5. (ANOVA analysis; NC: normal control (healthy group), PC: pancreatic cancer patient group, early PC (E.PC): early pancreatic cancer patient group, late PC (L.PC): late pancreatic cancer patient group):

[0633] Table 5

[0634]

[0635]

[0636] As demonstrated in Table 5, all tested markers showed differential expression patterns (increased and / or decreased) in pancreatic cancer patients (both early and late stages) compared to the normal group. It is noteworthy that at least one of the early or late stage pancreatic cancer groups showed statistically significant differences in expression patterns compared to the normal group.

[0637] Example 4: Use of markers IFNA1 and IFNB1 to differentiate pancreatic cancer from similar diseases

[0638] Bleucosphere samples were obtained from 105 pancreatic cancer patients, 17 benign pancreatic disease patients (1 pancreatitis patient, 11 benign pancreatic tumor patients, 1 intraductal papillary mucinous neoplasm (IPMN) patient, 2 autoimmune pancreatitis (AIP) patients, 2 other pancreatic disease patients) and 40 cholangiocarcinoma patients using the method described in Example 1. Real-time qPCR was performed for IFNA1 and IFNB1 markers using the method described in Example 2, and the results (ΔΔCt values) were as follows: Fig. 20 and Fig.21 (IFNB1) and Fig. 22 (IFNA1) (*p<0.05, p value: non-parametric t-test analysis).

[0639] like Figure 20 to Figure 22 As shown, IFNA1 and IFNB1 markers exhibited a statistically significant decrease in expression in pancreatic cancer patients (early and advanced stages) compared to patients with benign pancreatic disease and / or cholangiocarcinoma (which are similar diseases).

[0640] Based on the results of Examples 3 and 4, it was confirmed that each of the 20 markers listed in Table 3 can distinguish pancreatic cancer patients (early and / or advanced) from healthy individuals or patients with similar diseases (benign pancreatic diseases and / or bile duct cancer).

[0641] Example 5: Relative importance analysis of markers

[0642] Based on the previously measured ΔCt values, the relative importance of the 20 pancreatic cancer markers listed in Table 3 was validated by logistic regression analysis and feature selection analysis to assess statistical significance.

[0643] 5.1 Logistic regression analysis

[0644] When two or more markers are combined for analysis, the impact of each marker on the diagnostic performance within the comparison group is assessed. Logistic regression analysis (MedCalc software Ltd) is performed to determine the Wald value of each marker when the markers are used in combination. The combination of 20 markers is analyzed in various comparison groups (healthy group vs. early pancreatic cancer patients, healthy group vs. late pancreatic cancer patients, healthy group vs. all pancreatic cancer patients), and markers with a Wald value of ≥1 are selected in each comparison group.

[0645] The results obtained from this analysis are shown in Tables 6 to 8.

[0646] Table 6

[0647]

[0648] Table 7

[0649]

[0650]

[0651] Table 8

[0652]

[0653] As shown in Tables 6 to 8, the larger the Wald value, the greater the impact of the marker on the diagnostic performance.

[0654] 5.2 Feature Selection Analysis

[0655] Feature selection was performed to determine the importance of each of the 20 markers in different comparison groups (healthy group vs. early pancreatic cancer patients, healthy group vs. late pancreatic cancer patients, and healthy group vs. all pancreatic cancer patients). The Boruta package in R software (Miron B. Kursa, Witold R. Rudnicki (2010). Feature Selection with the Boruta Package. Journal of Statistical Software, 36 (11), p. 1-13.) was used for analysis. In the case where each marker is considered as a single feature (variable), the maximum importance value of the shadow feature is used as a threshold. Features (markers) whose importance is lower than the maximum importance of the shadow feature are removed.

[0656] The results obtained from this analysis are shown in Tables 9 to 11.

[0657] Table 9

[0658]

[0659] Table 10

[0660]

[0661] Table 11

[0662]

[0663] As shown in Tables 9 to 11, the meanImp value quantifies the importance of each marker in different comparison groups. Markers with importance values ​​higher than the maximum shadow feature importance are selected. The higher the value, the greater the impact of the marker on pancreatic cancer diagnosis.

[0664] Example 6: Diagnosis of pancreatic cancer using a combination of markers

[0665] From the markers listed in Table 3, marker combinations with high statistical significance as determined in Example 5.1 were selected for ROC curve analysis.

[0666] Using the method in Example 2, real-time qPCR (ΔCt values) was performed on the highly significant markers (listed in Tables 6 to 8) obtained from the buffy coat samples obtained from pancreatic cancer patients (early stage pancreatic patients and advanced stage pancreatic patients) and healthy individuals described in Example 1. The combined results were statistically analyzed.

[0667] With logistic regression as the classifier, the analysis results are presented as receiver operating characteristic (ROC) curves ( Figures 23 to 30 ). The optimal sensitivity, specificity, and cutoff values ​​for pancreatic cancer diagnosis were determined from the ROC curve.

[0668] Sensitivity (%) = (TP / (TP+FN))*100

[0669] Specificity (%) = (TN / (TN+FP))*100

[0670] Youden index (J) = max (sensitivity + specificity - 1)

[0671] AUC (area under the ROC curve)

[0672] [TP (True Positive): The number of pancreatic cancer patients who were correctly diagnosed as positive

[0673] FN (false negative): the number of pancreatic cancer patients who were incorrectly diagnosed as negative

[0674] TN (True Negative): The number of healthy individuals correctly diagnosed as negative

[0675] FP (False Positive): The number of healthy individuals who were mistakenly diagnosed as negative

[0676] The ROC curve analysis results of the 9 biomarker combinations (9 Huvet markers (early PC): ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF and FOXP3) that showed excellent discrimination ability between normal and early pancreatic cancer as identified in Table 6 are shown in Table 6. Fig.23 As shown in Table 12 (normal group: 177 subjects; early pancreatic cancer group: 35 subjects).

[0677] Table 12

[0678]

[0679] like Fig.23 As shown in Table 12, when a nine-biomarker combination (ARG1, CCL2, CLEC7A, SLC27A2, IFNG, PTGES, PTGES2, TNF, and FOXP3) was used, the AUC value of early pancreatic cancer (compared with the normal group) was close to 1 (0.979). In addition, both the sensitivity and specificity exceeded 90%, confirming that the biomarker combination can accurately and effectively distinguish normal subjects from early pancreatic cancer patients.

[0680] In addition, the ROC curve analysis results of the 9 biomarker combinations (9 Huvet markers (advanced PC): CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF and VEGFA) that showed excellent discrimination ability between normal and advanced pancreatic cancer as identified in Table 7 are as follows Fig.24 As shown in Table 13 (normal group: 177 subjects; advanced pancreatic cancer group: 67 subjects).

[0681] Table 13

[0682]

[0683] like Fig.24 As shown in Table 13, when the nine biomarker combinations (CCL5, PTGS2, CXCR2, CXCR4, SLC27A2, CXCL11, PTGES2, TNF and VEGFA) were used, the AUC value of advanced pancreatic cancer (compared with the normal group) was close to 1 (0.951). In addition, the sensitivity and specificity were both about 90%, confirming that the biomarker combination can accurately and effectively distinguish normal subjects from advanced pancreatic cancer patients.

[0684] In addition, the ROC curve analysis results of the 9 biomarker combinations (9 Huvet markers (all PCs): ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4 and CCL5) that showed excellent discrimination ability between normal and all pancreatic cancers as identified in Table 8 are as follows Fig.25 As shown in Table 14 (normal group: 177 subjects; pancreatic cancer group: 102 subjects, including 35 early pancreatic cancer patients and 67 advanced pancreatic cancer patients).

[0685] Table 14

[0686]

[0687] Fig.25 The results shown in Table 14 show that when the nine-marker combination (ARG1, CCL2, SLC27A2, IFNG, PTGES2, TNF, VEGFA, CXCR4 and CCL5) is used, the AUC value of all stages of pancreatic cancer (compared with the normal group) is close to 1 (0.942). The sensitivity is about 95% and the specificity is about 81%, confirming that the nine-marker combination can accurately and effectively distinguish pancreatic cancer patients from normal individuals.

[0688] In addition, logistic regression analysis was performed on samples from normal individuals (177) and pancreatic cancer patients (101; early stage: 34, late stage: 67) using a combination of all 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). The results of ROC curve analysis are shown in Fig.26a (Comparison between normal and early pancreatic cancer), Figure 26b (normal vs advanced pancreatic cancer) and Fig.26c (Normal vs. all pancreatic cancers) are shown.

[0689] like Figures 26a to 26c As shown, when a combination of 20 biomarkers (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 ​​of all patient groups (including early pancreatic cancer, advanced pancreatic cancer, and pancreatic cancer of all stages) were close to 1 (0.95 or higher) compared with the normal group. In addition, the sensitivity exceeded 92% and the specificity exceeded 85%, confirming that the 20 biomarker combination can accurately and effectively distinguish normal individuals from pancreatic cancer patients (early pancreatic cancer and / or advanced pancreatic cancer).

[0690] In addition, among the biomarkers listed in Table 3, a 12-biomarker subgroup (marker group 1) was selected with 6 overlapping markers by integrating 9 biomarkers from Table 12 (normal vs. early pancreatic cancer) and 9 biomarkers from Table 14 (normal vs. all pancreatic cancer). The selected biomarkers (CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3) were used for logistic regression analysis of samples from 177 normal subjects and 102 pancreatic cancer patients (35 early pancreatic cancer patients and 67 advanced pancreatic cancer patients), and the resulting ROC curve analysis was performed in Fig.27a (Comparison between normal and early pancreatic cancer), Figure 27b (normal vs advanced pancreatic cancer) and Fig.27c (Normal vs. all pancreatic cancers) are shown.

[0691] like Figures 27a to 27cAs shown, when a combination of 12 biomarkers (CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, and FOXP3) was used, the AUC values ​​of all patient groups (including early pancreatic cancer, advanced pancreatic cancer, and pancreatic cancer of all stages) were all over 0.94 compared with the normal group. In addition, the sensitivity was over 91% and the specificity was over 75%, confirming that the 12 biomarker combination can accurately and effectively distinguish normal individuals from pancreatic cancer patients (early and / or advanced pancreatic cancer).

[0692] In addition, among the biomarkers listed in Table 3, a 15-biomarker subgroup (marker group 2) was selected with three overlapping markers by integrating 9 biomarkers from Table 12 (normal vs. early pancreatic cancer comparison) and 9 biomarkers from Table 13 (normal vs. advanced pancreatic cancer comparison). The selected biomarkers (CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11) were used for logistic regression analysis of samples from 177 normal subjects and 102 pancreatic cancer patients (35 early pancreatic cancer patients and 67 advanced pancreatic cancer patients), and the resulting ROC curve analysis was performed in Fig.28a (Comparison between normal and early pancreatic cancer), Fig.28b (normal vs advanced pancreatic cancer) and Fig.28c (Comparison of normal and total pancreatic cancer) is shown.

[0693] like Figures 28a to 28c As shown, when a combination of 15 biomarkers (CCL5, CXCR4, SLC27A2, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2, and CXCL11) was used, the AUC values ​​of all patient groups (including early pancreatic cancer, advanced pancreatic cancer, and pancreatic cancer of all stages) were all over 0.95 compared with the normal group. In addition, the sensitivity was over 89% and the specificity was over 85%, confirming that the 15 biomarker combination can accurately and effectively distinguish normal individuals from pancreatic cancer patients (early and / or advanced pancreatic cancer).

[0694] In addition, among the biomarkers listed in Table 3, a subgroup of eight biomarkers was selected (marker group 3: CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2, and TNF). Using these biomarkers, logistic regression analysis was performed on samples from 177 normal subjects and 102 pancreatic cancer patients (35 early pancreatic cancer patients and 67 advanced pancreatic cancer patients), and the results of ROC curve analysis were shown in Table 3. Fig.29a (Comparison between normal and early pancreatic cancer), Fig.29b (normal vs advanced pancreatic cancer) and Fig.29c (Comparison of normal and total pancreatic cancer) is shown.

[0695] like Figures 29a to 29c As shown, when using a combination of 8 biomarkers (CCL2, CCL5, CXCR2, SLC27A2, IFNL1, IFNG, PTGES2 and TNF), the AUC values ​​of all patient groups (including early pancreatic cancer, advanced pancreatic cancer and all stages of pancreatic cancer) were all over 0.9 compared with the normal group. In addition, the sensitivity was over 88% and the specificity was over 80%, confirming that the combination of 8 biomarkers can accurately and effectively distinguish normal individuals from pancreatic cancer patients (early and / or advanced pancreatic cancer).

[0696] Figure 23 to Figure 29c The results are summarized in Fig.30 middle.

[0697] Example 7: Development of a predictive model for pancreatic cancer diagnosis

[0698] In order to estimate the prediction model, stepwise logistic regression was performed on the variable (marker) selection, and statistical analysis was performed using SAS ver9.4 (SAS Institute Inc., NC, Cary, USA). In order to balance underfitting and overfitting, model validation and evaluation were performed using 10 times of cross validation. The split ratio of the test group and the training group was set to 90:10, 80:20, 75:25 and 70:30. For each iteration, the diagnostic accuracy index was calculated, and the maximum Youden index in the ROC curve analysis was used to identify the best performance point to evaluate the model.

[0699] The odds ratio represents the ratio of the likelihood of having pancreatic cancer to the likelihood of not having pancreatic cancer. Pancreatic cancer cases are assigned 1 and non-cancer cases are assigned 0. The odds ratio is calculated using the following formula:

[0700]

[0701] logit(p)=b0+b1X1+b2X2+b3X3+...+b k Xk

[0702] Through the best prediction model analysis, the regression coefficients b0, b1, b2, ..., b k . Taking the logarithm of both sides of the comparison value formula, the final prediction model formula is derived as the above formula: wherein X1, X2, X3, ..., Xk represent the actual measured value (ΔCt value) of each marker obtained from the sample using real-time qPCR, as described in Example 2.

[0703] In the comparison between 183 normal individuals and 36 early pancreatic cancer patients, 8 biomarker combinations (model_R1) and 13 biomarker combinations (model_R2) were used to obtain the best diagnostic model for early pancreatic cancer. In addition, in the comparison between 183 normal individuals and 106 total pancreatic cancer patients (including both early and late pancreatic cancer patients), 11 biomarker combinations (model_A1) and 10 biomarker combinations (model_A2) were used to obtain the best diagnostic model for total pancreatic cancer (Table 15). By analyzing the biomarker expression levels in the sample, the diagnosis prediction of pancreatic cancer can be carried out by inputting ΔCt values ​​(using real-time qPCR measurement, as described in Example 2) into the model formula.

[0704] Table 15

[0705]

[0706]

[0707]

[0708] By applying the model formula 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 of model_R1 to actual patient samples, the analysis results obtained are as follows:

[0709] For sample HV18, the calculated value is '35.8476+(-2.5794)×6.503+(3.3956)×6.88+(-0.5380)×10.72+(1.4027)×0.535+(-1.143)×7.035+(-4.3771)×10.654+(3.1076)×5.68+(-0.6396)×10.994=-6.637'. Since this value is lower than the cutoff value of -1.855994, sample HV18 is predicted to have a low risk of pancreatic cancer and is classified as normal. The actual sample HV18 belongs to the normal group.

[0710] For sample HV119, the calculated value is '35.8476+(-2.5794)×6.304+(3.3956)×9.499+(-0.5380)×10.502+(1.4027)×1.496+(-1.143)×4.878+(-4.3771)×9.708+(3.1076)×4.963+(-0.6396)×11.822=8.083'. Since this value is higher than the cutoff value of -1.855994, sample HV119 is predicted to have a high risk of pancreatic cancer. The actual sample HV119 belongs to the early pancreatic cancer group.

[0711] By applying the model_R2 formula: 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 to actual patient samples, the analysis results obtained are as follows:

[0712] For sample HV18, the calculated value is '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+(1.0804)×0.5352+(-1.2971)×7.0352+(-4.7971)×10.6540+(3.1934)×5.6802+(-0.7064)×10.9943=-8.512'. Since this value is lower than the cutoff value of -1.908747, sample HV18 is predicted to have a low risk of pancreatic cancer and is classified as normal. The actual sample HV18 belongs to the normal group.

[0713] For sample HV119, the calculated value is '44.4033+(-2.8042)×6.3042+(3.7082)×9.4998+(0.2358)×7.8130+(0.1568)×10.3085+(1.0951)×1.1619+(-0.8407)×7.0730+(-0.6622)×10.5027+(-0.9422)×0.0542+(1.0804)×1.4966+(-1.2971)×4.8782+(-4.7971)×9.7083+(3.1934)×4.9634+(-0.7064)×11.8220=9.948'. Since this value is higher than the cutoff value of -1.908747, the sample HV119 is predicted to have a high risk of pancreatic cancer. The actual sample HV119 belongs to the early pancreatic cancer group.

[0714] By applying the model_A1 formula 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 to actual patient samples, the analysis results obtained are as follows:

[0715] For sample HV18, the calculated value is '36.9898+(-2.220)×6.5032-+(0.9955)×6.8802+(0.3413)×10.5360+(-2.799)×7.7399+(-0.1913)×10.7275+(1.3628)×1.0155+(-2.0521)×2.9629+(0.7037)×0.5352+(-0.064)×3.9349+(-3.1754)×10.6540+(4.4765)×5.6802=-3.693'. Since this value is lower than the cutoff value of -0.251091, sample HV18 is predicted to have a low risk of pancreatic cancer and is classified as normal. The actual sample HV18 belongs to the normal group.

[0716] For sample HV119, the calculated value is '36.9898+(-2.220)×6.3042+(0.9955)×9.4998+(0.3413)×10.3085+(-2.799)×7.0730+(-0.1913)×10.5027+(1.3628)×0.5032+(-2.0521)×0.542+(0.7037)×1.4966+(-0.064)×5.5966+(-3.1754)×9.7083+(4.4765)×4.9634=6.824'. Since this value is higher than the cutoff value of -0.251091, sample HV119 is predicted to have a high risk of pancreatic cancer. The actual sample HV119 belongs to the early pancreatic cancer group.

[0717] For sample HV131, the calculated value is '36.9898+(-2.220)×6.5761+(0.9955)×8.7846+(0.3413)×10.7145+(-2.799)×7.3347+(-0.1913)×8.8499+(1.3628)×1.5673+(-2.0521)×3.4826+(0.7037)×2.0970+(-0.064)×4.7682+(-3.1754)×11.1328+(4.4765)×6.3557=1.830'. Since this value is lower than the cutoff value of -0.251091, sample HV131 is predicted to have a high risk of pancreatic cancer. The actual sample HV131 belongs to the pancreatic cancer group (LAPC; locally advanced pancreatic cancer).

[0718] By applying the model_A2 formula 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 to actual patient samples, the analysis results obtained are as follows:

[0719] For sample HV18, the calculated value is '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. Since this value is lower than the cutoff value of -0.290325, sample HV18 is predicted to have a low risk of pancreatic cancer and is classified as normal. The actual sample HV18 belongs to the normal group.

[0720] For sample HV119, the calculated value is '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'. Since this value is higher than the cutoff value of -0.290325, sample HV119 is predicted to have a high risk of pancreatic cancer. The actual sample HV119 belongs to the early pancreatic cancer group.

[0721] For sample HV131, the calculated value is '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'. Since this value is higher than the cutoff value of -0.290325, sample HV131 is predicted to have a high risk of pancreatic cancer. The actual sample HV131 belongs to the pancreatic cancer group (LAPC; locally advanced pancreatic cancer).

[0722] The results of the performance verification of the four models (Model_R1, Model_R2, Model_A1, and Model_A2) are summarized in Table 16.

[0723] Table 16

[0724]

[0725] As demonstrated in Table 16, all pancreatic cancer diagnostic models showed high diagnostic accuracy, with sensitivities ranging from 86% to 100% and specificities ranging from 86% to 94%.

[0726] From the comparison between normal individuals (183 samples) and early pancreatic cancer patients (36 samples), the best model formula (model_R3) for early pancreatic cancer diagnosis using 8 kinds of marker combinations (same as marker group 3) is obtained. From the comparison between normal individuals (183 samples) and all pancreatic cancer patients (106 samples), the best model formula (model_A3) for diagnosing all pancreatic cancers (table 18) using 8 kinds of marker combinations (same as marker group 3) is obtained. The expression value of each marker obtained from sample analysis by real-time qPCR (ΔCt value) as described in Example 2 can be input into the model formula for pancreatic cancer diagnosis prediction. Before being applied to the model formula, the ΔCt value is pre-processed using the Robust Scaler method (implemented in Python). This pre-processing is carried out using the following formula 5:

[0727] x'=[x-median(x)] / IQR[Formula 5]

[0728] (x: ΔCt value of each marker in the diagnosed subjects, Median (x): median of ΔCt value of each marker in any group including diagnosed subjects, IQR (interquartile range): difference (Q3-Q1) between the third quartile (Q3) and the first quartile (Q1))

[0729] Table 17

[0730] Model-R3 median IQR Model-A3 median IQR IFNG 7.9761 0.8860 IFNG 8.0259 0.9636 SLC27A2 10.7505 0.7249 SLC27A2 10.7522 0.6863 CC.5 1.2762 0.5589 CCL5 1.3601 0.5938 PTGES2 5.5063 0.5048 PTGES2 5.5562 0.4893 TNF 6.9300 0.7141 TNF 6.8653 0.7976 IFNL1 9.8998 2.4137 IFNL1 9.6981 2.5056 CCL2 10.7752 1.5991 CCL2 10.4742 1.7941 CXCR2 0.9542 1.0059 CXCR2 0.8587 1.0916

[0731] Table 18

[0732]

[0733] By applying the model_R3 formula logit(p)=-1.95757578511082+(1.942999)×IFNG+(-2.370157)×SLC27A2+(0.236554)×CCL5+(1.781672)×PTGES2+(-1.328085)×TNF+(-0.170127)×IFNL1+(-0.495828)×CCL2+(0.611586)×CXCR2 to actual patient samples, the analysis results obtained are as follows:

[0734] For sample HV18, the calculated value is '-1.95757578511082+(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'. Since this value is lower than the cutoff value of 0.282, sample HV18 is predicted to have a low risk of pancreatic cancer and is classified as normal. The actual sample HV18 belongs to the normal group.

[0735] For sample HV119, the calculated value is '-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'. Since this value is higher than the cutoff value of 0.282, sample HV119 is predicted to have a high risk of pancreatic cancer. The actual sample HV119 belongs to the early pancreatic cancer group.

[0736] By applying the model_A3 formula 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 to actual patient samples, the analysis results obtained are as follows:

[0737] For sample HV18, the calculated value is '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'. Since this value is lower than the cutoff value of 0.732, sample HV18 is predicted to have a low risk of pancreatic cancer and is classified as normal. The actual sample HV18 belongs to the normal group.

[0738] For sample HV119, the calculated value is '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'. Since this value is higher than the cutoff value of 0.732, sample HV119 is predicted to have a high risk of pancreatic cancer. The actual sample HV119 belongs to the early pancreatic cancer group.

[0739] For sample HV131, the calculated value is '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'. Since this value is higher than the cutoff value of 0.732, sample HV131 is predicted to have a high risk of pancreatic cancer. Indeed, sample HV131 belongs to the pancreatic cancer group (LAPC; locally advanced pancreatic cancer).

Claims

1. A composition for diagnosing pancreatic cancer, comprising a reagent capable of detecting a biomarker for diagnosing pancreatic cancer, in, The biomarker for diagnosing pancreatic cancer is at least one 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, their encoding genes or a combination thereof.

2. The composition according to claim 1, in, The biomarkers for diagnosing pancreatic cancer are selected from: (1) at least one selected from the group consisting of SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2 and PTGS2; At least one selected from the group consisting of SLC27A2, IFNG, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4 and IFNB1; At least one selected from the group consisting of SLC27A2, IFNL1, IFNG, CXCL11, CCL2, PTGES2 and PTGES; At least one selected from the group consisting of SLC27A2, CCL5, CXCR4, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2 and CXCL11; At least one selected from the group consisting of SLC27A2, CCL2, CCL5, CXCR2, IFNL1, IFNG, PTGES2 and TNF; At least one selected from the group consisting of SLC27A2, TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, PTGES2 and PTGES; At least one selected from the group consisting of SLC27A2, TNF, IFNG, CCL2, CXCR2, ARG1, PTGES2 and PTGES; At least one selected from the group consisting of SLC27A2, VEGFA, CXCR4, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2 and CXCL8; At least one selected from the group consisting of SLC27A2, PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES and IFNL1; At least one selected from the group consisting of IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2 and PTGES2; At least one selected from the group consisting of SLC27A2, CCL5, PTGS2, CXCR2, CXCR4, CXCL11, PTGES2, TNF and VEGFA; At least one selected from the group consisting of SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A and ARG1; At least one selected from the group consisting of SLC27A2, IFNG, PTGES2, CCL5, VEGFA, CCL2, TNF, FOXP3, CXCR4, IFNA1, IFNL1, PTGES, CCR5, CLEC7A, IFNB1, CXCR2 and PTGS2; At least one selected from the group consisting of SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2 and CLEC7A; At least one selected from the group consisting of SLC27A2, ARG1, CCL2, IFNG, PTGES2, TNF, VEGFA, CXCR4 and CCL5; At least one selected from the group consisting of SLC27A2, TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2 and PTGES2; or At least one selected from the group consisting of SLC27A2, IFNG, VEGFA, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2 and CXCL11; (2) the gene encoding the above (1); or (3) A combination of the above (1) and (2).

3. The composition according to claim 1, wherein The biomarkers used to diagnose pancreatic cancer include: (1) at least one selected from the group consisting of SLC27A2, IFNG, CCL2, TNF, PTGES, CLEC7A, ARG1, PTGES2, FOXP3, CXCR4, VEGFA, CXCR2 and PTGS2; At least one selected from the group consisting of SLC27A2, IFNG, CCL5, FOXP3, PTGES2, TNF, IFNA1, IFNL1, CCL2, CXCR2, PTGES, CXCR4 and IFNB1; At least one selected from the group consisting of SLC27A2, IFNL1, IFNG, CXCL11, CCL2, PTGES2 and PTGES; At least one selected from the group consisting of SLC27A2, CCL5, CXCR4, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2 and CXCL11; At least one selected from the group consisting of SLC27A2, CCL2, CCL5, CXCR2, IFNL1, IFNG, PTGES2 and TNF; At least one selected from the group consisting of SLC27A2, TNF, IFNG, IFNL1, CXCL11, CLEC7A, VEGFA, CCL2, CXCR4, CXCR2, ARG1, PTGES2 and PTGES; or At least one selected from the group consisting of SLC27A2, TNF, IFNG, CCL2, CXCR2, ARG1, PTGES2 and PTGES; (2) the gene encoding the above (1); or (3) A combination of (1) and (2) above, and The composition is used for diagnosing early pancreatic cancer.

4. The composition according to claim 1, wherein The biomarkers used to diagnose pancreatic cancer include: (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 gene encoding the above (1); or (3) A combination of (1) and (2) above, and The composition is used for diagnosing early pancreatic cancer.

5. The composition according to claim 1, wherein The biomarkers used to diagnose pancreatic cancer include: (1) at least one selected from the group consisting of SLC27A2, VEGFA, CXCR4, TNF, PTGES2, CCL5, CXCL11, CXCR2, FOXP3, PTGS2 and CXCL8; At least one selected from the group consisting of SLC27A2, PTGES2, IFNG, CCL5, VEGFA, PTGS2, CLEC7A, CXCR4, TNF, FOXP3, CCL2, CXCR2, CXCL8, PTGES and IFNL1; At least one selected from the group consisting of IFNG, TNF, CLEC7A, CXCL8, FOXP3, VEGFA, CCL2, CCL5, CCR5, CXCR4, ARG1, CXCR2, PTGS2 and PTGES2; At least one selected from the group consisting of SLC27A2, CCL5, PTGS2, CXCR2, CXCR4, CXCL11, PTGES2, TNF and VEGFA; At least one selected from the group consisting of SLC27A2, CCL5, CXCR4, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2 and CXCL11; or At least one selected from the group consisting of SLC27A2, CCL2, CCL5, CXCR2, IFNL1, IFNG, PTGES2 and TNF; (2) the gene encoding the above (1); or (3) A combination of (1) and (2) above, and The composition is used for diagnosing advanced pancreatic cancer.

6. The composition according to claim 1, wherein The biomarkers used to diagnose pancreatic cancer include: (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 gene encoding the above (1); or (3) A combination of (1) and (2) above, and The composition is used for diagnosing advanced pancreatic cancer.

7. The composition according to claim 1, wherein The biomarkers used to diagnose pancreatic cancer include: At least one selected from the group consisting of SLC27A2, PTGES2, VEGFA, TNF, CXCR4, IFNG, CCL5, CXCR2, CCL2, CXCL11, CLEC7A and ARG1; At least one selected from the group consisting of SLC27A2, IFNG, PTGES2, CCL5, VEGFA, CCL2, TNF, FOXP3, CXCR4, IFNA1, IFNL1, PTGES, CCR5, CLEC7A, IFNB1, CXCR2 and PTGS2; At least one selected from the group consisting of SLC27A2, ARG1, CCL2, IFNG, PTGES2, TNF, VEGFA, CXCR4 and CCL5; At least one selected from the group consisting of SLC27A2, CCL5, CXCR4, PTGES2, TNF, VEGFA, ARG1, CCL2, CLEC7A, IFNG, PTGES, FOXP3, PTGS2, CXCR2 and CXCL11; At least one selected from the group consisting of SLC27A2, CCL2, CCL5, CXCR2, IFNL1, IFNG, PTGES2 and TNF; At least one selected from the group consisting of SLC27A2, TNF, IFNG, CXCL11, VEGFA, CCL2, CCL5, CXCR4, CXCR2, PTGS2 and PTGES2; or At least one selected from the group consisting of SLC27A2, IFNG, VEGFA, PTGES2, TNF, CXCR4, CXCR2, CCL5, CCL2 and CXCL11; (2) the gene encoding the above (1); or (2) A combination of (1) and (2) above, and The composition is used for diagnosing one or both of early-stage pancreatic cancer and advanced-stage pancreatic cancer.

8. The composition according to claim 1, wherein The biomarkers used to diagnose pancreatic cancer include: (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 gene encoding the above (1); or (3) A combination of (1) and (2) above, and The composition is used for diagnosing one or both of early-stage pancreatic cancer and advanced-stage pancreatic cancer.

9. The composition according to claim 1, wherein The biomarker for diagnosing pancreatic cancer comprises at least one selected from the group consisting of IFNB1 and IFNA1, genes encoding the same, or a combination thereof, and The composition distinguishes one or both of early pancreatic cancer and advanced pancreatic cancer from pancreatic diseases other than pancreatic cancer.

10. The composition according to claim 1, The composition is used for diagnosing one or both of early pancreatic cancer and advanced pancreatic cancer, and Wherein, the biomarker for diagnosing pancreatic cancer comprises one selected from the following biomarker groups, their encoding genes or a combination thereof: 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 according to any one of claims 1 to 10, wherein The composition is applied to the blood-derived buffy coat.

12. The composition according to claim 11, wherein The buffy coat is a whole white blood cell layer formed between the top plasma layer and the bottom red blood cell layer after centrifugation of blood, and is obtained from the middle white blood cell layer among the plasma layer (top), the buffy coat (middle), and the red blood cell layer (bottom) separated in sequence after centrifugation of blood under one or more conditions selected from the following conditions (1) to (3): (1) Temperature: 2°C to 30°C; (2) Speed: 300g to 2000g; and (3) Duration: 5 to 20 minutes.

13. The composition according to claim 11, wherein After centrifuging blood under one or more conditions selected from the following conditions (1) to (3), the intermediate white blood cell layer is obtained from the plasma layer (top), the white blood cell layer (middle), and the red blood cell layer (bottom) separated in sequence: (1) Temperature: 4°C to 25°C; (2) Speed: 500g to 1800g; and (3) Duration: 7 to 20 minutes.

14. The composition according to any one of claims 1 to 10, wherein The reagent capable of detecting a biomarker is at least one selected from the group consisting of small molecule compounds, proteins, peptides and nucleic acids, and the reagent is combined with the biomarker for diagnosing pancreatic cancer.

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

16. The kit according to claim 15, wherein The kit is applied to blood-derived buffy coat.

17. A method for providing diagnostic information of pancreatic cancer, the method comprising the steps of detecting a biomarker for diagnosing pancreatic cancer in a blood sample isolated from a subject, in, The biomarker for diagnosing pancreatic cancer is at least one 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, their encoding genes or a combination thereof.

18. The method according to claim 17, wherein: The blood sample is a blood-derived buffy coat.

19. The method according to claim 18, wherein: The white blood cell layer is obtained from the intermediate white blood cell layer among the plasma layer (top), the white blood cell layer (middle) and the red blood cell layer (bottom) separated in sequence after centrifuging the blood under one or more conditions selected from the following conditions (1) to (3): (1) Temperature: 2°C to 30°C; (2) Speed: 300g to 2000g; and (3) Duration: 5 to 20 minutes.

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