KR102348291B1 - Method for predicting the treatment response of a cancer patient - Google Patents

Abstract

The present invention relates to a method for predicting the treatment responsiveness of a cancer patient, and more particularly, to a method for selecting an appropriate treatment method for each patient by predicting the response efficiency according to treatment and the prognosis of the patient after treatment in cancer patients. it's about

Description

Method for predicting the treatment response of a cancer patient

The present invention relates to a method for predicting the treatment responsiveness of a cancer patient, and more particularly, to a method for selecting an appropriate treatment method for each patient by predicting the response efficiency according to treatment and the prognosis after treatment in cancer patients .

Cells, the smallest unit constituting the human body, divide and grow, die and disappear due to intracellular regulatory functions when normal, maintaining cell number balance. If a cell is damaged for some reason, it recovers through treatment and functions as a normal cell, but if there is no recovery, it dies on its own. However, for various reasons, abnormal cells whose proliferation and inhibition are not controlled not only proliferate excessively, but also invade surrounding tissues and organs, resulting in mass formation and destruction of normal tissues, which is defined as cancer. Cancer is the proliferation of cells that cannot be suppressed, and it destroys the structure and function of normal cells and organs, so the diagnosis and treatment are very important.

On the other hand, gastric cancer is the second most common cause of death in 700,349 deaths in 2000, and is the fourth most commonly diagnosed cancer in the world. It is considered a single heterogeneous disease with several epidemiological and histopathological features. Gastric cancer treatment is primarily based on clinical parameters such as tumor, node, metastasis (TNM) staging that determines whether a patient should be treated with surgery alone or with surgery and chemotherapy. Unlike breast cancer and colorectal cancer, gastric cancer clearly differs from stage 1 to stage 4 according to the TNM staging system. That is, in the case of stage 1, the 5-year survival rate is more than 90%, and in case of stage 4, it shows a big difference of 20% or less. Therefore, it can be seen that the prognostic predictive power of the TNM staging system is very good [Reference, 7th edition of the AJCC cancer staging Manual: stomach. AnnSurgOncol 2010;17:3077-3079]. Based on the staging system, gastric cancer is often divided into Early Gastric Cancer, Locally Advanced Gastric Cancer, Locally Advanced Invasive Gastric Cancer, and Metastatic Gastric Cancer. .

Cancer treatment can be broadly divided into surgery, radiation therapy, and chemotherapy. For gastric cancer, surgery is possible, so surgery is commonly used. However, even after surgery, if the cancer is advanced, the recurrence rate is very high. Therefore, in order to prevent recurrence and improve the prognosis of gastric cancer patients, multidisciplinary treatment including chemotherapy or chemo-radiation after surgery has been introduced. However, although these treatment methods improve the general clinical outcome in patients, the clinicopathological heterogeneity of the tumor and the different outcomes of patients in the same stage have limitations in predicting the task of adjuvant chemotherapy. access is lacking.

Despite recent advances, challenges in cancer therapy remain to target specific treatment regimens to pathologically distinct tumor types and ultimately to personalize tumor therapy to maximize outcome. Therefore, there is a need for trials that simultaneously provide predictive information on patient response to various treatment options.

One object of the present invention relates to a method for predicting the treatment responsiveness of a cancer patient.

Another object of the present invention relates to a composition for predicting therapeutic responsiveness in cancer patients.

Another object of the present invention relates to a kit comprising a composition for predicting therapeutic responsiveness of cancer patients.

However, the technical problem to be achieved by the present invention is not limited to the above-mentioned problems, and other problems not mentioned will be clearly understood by those of ordinary skill in the art from the following description.

The inventors of the present invention found that, among cancer patients, especially gastric cancer patients, when microsatellites instability (MSI) is high, the prognosis is good, but the reactivity to standard anticancer therapy is predicted to be low. and found that a specific biomarker was characteristically low in some recurrent patients, leading to the present invention.

According to an embodiment of the present invention, (a) measuring microsatellite instability (MSI) in a sample isolated from a cancer patient; and (b) GZMA (granzyme A), GZMB (granzyme B), CXCL9 (CXC motif chemokine ligand 9), and CXCL10 (CXC motif chemokine ligand) from samples isolated from cancer patients when the microsatellite instability is evaluated to be high. 10) and IL32 (interleukin 32), it relates to a method for predicting treatment responsiveness of a cancer patient, comprising measuring the mRNA expression level of one or more proteins selected from the group consisting of or a gene encoding the same.

In the present invention, the type of cancer to be evaluated for treatment responsiveness is not particularly limited, and for example, gastric cancer, brain cancer, lung cancer, non-small cell lung cancer, colon cancer, bone cancer, pancreatic cancer, skin cancer, head or neck cancer, Skin or intraocular melanoma, uterine cancer, ovarian cancer, rectal cancer, perianal cancer, colon cancer, breast cancer, fallopian tube carcinoma, endometrial carcinoma, cervical carcinoma, vaginal carcinoma, vulvar carcinoma, Hodgkin's disease, esophageal cancer, small intestine Cancer, endocrine adenocarcinoma, thyroid cancer, parathyroid cancer, adrenal cancer, soft tissue sarcoma, urethral cancer, penile cancer, prostate cancer, chronic or acute leukemia, lymphocytic lymphoma, bladder cancer, kidney or ureter cancer, renal cell carcinoma, renal pelvic carcinoma, central nervous system (CNS; central nervous system) tumor, it may be selected from the group consisting of primary CNS lymphoma, spinal cord tumor, and pituitary adenoma, preferably gastric cancer.

In the present invention, the term "microsatellites" refers to short repeating nucleotide sequences in the form of mono-, di-, tri- and tetranucleotides distributed throughout the gene of eukaryotes. In general, such a repeating sequence exists in the form of 10 to 40 simple repetitions (tandem repeat) in the chromosome. Also, in the present invention, the term "Microsatellites instability (MSI)" refers to mutations caused by short base deletions or insertions in the microsatellite gene, and is mainly caused by defects in the DNA mismatch repair system. refers to the genetic instability of the body. "Genomic instability" refers to the transformation of normal cells into tumor cells due to the accumulation of DNA damage, changes and mutations. BAT26, D5S346, BAT25, D17S250, and D2S123 were presented as five microsatellite markers recommended by the National Cancer Institute of the United States. If two or more of these markers show instability, it is defined as "high degree of microsatellite instability (MSI-H)", and if only one marker shows instability, " It is defined as a case of low degree of microsatellite instability (MSI-L), and if it does not show instability in all five markers, it is defined as a case of “microsatellite stable (MSS)”. However, in some cases, when mated tumor and normal tissue cannot be obtained, five mononucleotide markers, BAT25, BAT26, NR21, NR22 (or NR27) and NR24, can be used as microsatellite markers in tumor tissue. If there are three or more markers showing instability, it is defined as MSI-H with high microsatellite instability, and when there is instability in one or two markers, it is defined as MSI-L with low microsatellite instability, and five markers. If there was no instability in all cases, the microsatellite was defined as a stable MSS.

In the present invention, the method for analyzing microsatellite instability is not particularly limited, but, for example, the five microsatellite markers (BAT26, D5S346, BAT25, D17S250, D2S123) or After measuring the microsatellite markers of BAT25, BAT26, NR21, NR22 (or NR27) and NR24 through a polymerase chain reaction using a fluorescently labeled primer, the initial denaturation process was carried out at 95°C for 15 minutes, and at 94°C for 1 minute. Min, after a total of 30 cycles of 1 minute at 58°C and 1 minute at 72°C, the final amplification process may be performed at 72°C for 5 minutes, but is not limited thereto, and the measurement temperature and time can be appropriately adjusted . After that, 10 L of GeneScan 500 ROX size standard (Applied Biosystems, Foster, CA, USA) and Hi-Di Formamide (Applied Biosystems, Foster, CA, USA) were mixed with the reaction sample, and reacted at 95°C for 5 minutes, then ice After cooling, the sample above may be subjected to fragment analysis in 3100 Genetic Analyzer (Applied Biosystems, Foster, CA, USA), but is not limited thereto. However, the sequence of the primer used in the experiment is not particularly limited, and the primer for the microsatellite generally used in the art may be used, and the original Bethesda panel may be used as a non-limiting example.

In the present invention, the "sample" includes, but is not limited to, samples such as whole blood, plasma, blood, saliva, urine, sputum, lymph and intercellular fluid isolated from a cancer patient individual.

In the present invention, as a result of analyzing microsatellite instability on samples collected from cancer patients, preferably gastric cancer patients, as described above, when the microsatellite instability is evaluated to be high, surgical excision therapy; At least one of chemotherapy and radiation therapy, and more preferably, it is highly responsive to surgical excision therapy, so it can be predicted that the likelihood of recurrence after treatment is low and the prognosis is good.

However, in the present invention, as a result of analyzing microsatellite instability as described above, the microsatellite instability was evaluated to be high, but when the expression level of the following biomarkers is low, the reactivity to standard anticancer therapy is low and the possibility of recurrence thereafter This can be expected to be very high.

Specifically, in the present invention, one or more proteins selected from the group consisting of GZMA, GZMB, CXCL9, CXCL10 and IL32 from a sample isolated from a cancer patient evaluated as having high microsatellite instability as a result of the microsatellite instability analysis as described above. Alternatively, the mRNA expression level of a gene encoding it may be measured.

In the present invention, the biomarkers GZMA, GZMB, CXCL9, CXCL10 and IL32 expression level measurement or comparative analysis methods include protein chip analysis, immunoassay, ligand binding assay, MALDI-TOF (Matrix Assisted Laser Desorption/Ionization Time) of Flight Mass Spectrometry) analysis, SELDI-TOF (Sulface Enhanced Laser Desorption/Ionization Time of Flight Mass Spectrometry) analysis, radioimmunoassay, radioimmunodiffusion method, octeroni immunodiffusion method, rocket immunoelectrophoresis, tissue immunostaining, complement Stationary methods, two-dimensional electrophoresis analysis, liquid chromatography-Mass Spectrometry (LC-MS), liquid chromatography-Mass Spectrometry/Mass Spectrometry (LC-MS/MS), Western blotting and ELISA (enzyme linked immunosorbent assay), but is not limited thereto.

In the present invention, the expression level of the biomarkers GZMA, GZMB, CXCL9, CXCL10 and IL32 is an antibody, oligopeptide, ligand, PNA (peptide nucleic acid) that specifically binds to the GZMA, GZMB, CXCL9, CXCL10 or IL32. And it can be measured using one or more selected from the group consisting of aptamer (aptamer). In the present invention, the sequence information of GZMA, GZMB, CXCL9, CXCL10 and IL32 is the same as SEQ ID NOs: 1 to 5, respectively, so those skilled in the art can easily find antibodies, oligopeptides, ligands, PNAs or aptamers specific to the protein based on this. will be able to design

In the present invention, the "antibody" refers to a substance that specifically binds to an antigen and causes an antigen-antibody reaction. For the purposes of the present invention, an antibody refers to an antibody that specifically binds to GZMA, GZMB, CXCL9, CXCL10 or IL32. Antibodies of the present invention include polyclonal antibodies, monoclonal antibodies and recombinant antibodies. The antibody can be readily prepared using techniques well known in the art. For example, the polyclonal antibody is prepared by injecting the antigen of GZMA, GZMB, CXCL9, CXCL10 or IL32 into an animal and collecting blood from the animal to obtain a serum containing the antibody by a method well known in the art. can be produced Such polyclonal antibodies can be prepared from any animal such as goat, rabbit, sheep, monkey, horse, pig, cow, dog, and the like. In addition, monoclonal antibodies can be prepared using the hybridoma method well known in the art (see Kohler and Milstein (1976) European Journal of Immunology 6:511-519), or the phage antibody library technology (Clackson et al, Nature, 352). :624-628, 1991; Marks et al, J. Mol. Biol., 222:58, 1-597, 1991). The antibody prepared by the above method may be separated and purified using methods such as gel electrophoresis, dialysis, salt precipitation, ion exchange chromatography, and affinity chromatography. In addition, the antibodies of the present invention include functional fragments of antibody molecules as well as complete forms having two full-length light chains and two full-length heavy chains. A functional fragment of an antibody molecule means a fragment having at least an antigen-binding function, and includes Fab, F(ab'), F(ab')2 and Fv.

In the present invention, the "PNA (Peptide Nucleic Acid)" refers to an artificially synthesized polymer similar to DNA or RNA, and was first introduced by Professors Nielsen, Egholm, Berg and Buchardt of the University of Copenhagen, Denmark in 1991. Whereas DNA has a phosphate-ribose sugar backbone, PNA has a repeated N-(2-aminoethyl)-glycine backbone linked by peptide bonds, which greatly increases binding strength and stability to DNA or RNA, resulting in molecular biology , diagnostic assays and antisense therapy. PNA is described in Nielsen PE, Egholm M, Berg RH, Buchardt O (December 1991). "Sequence-selective recognition of DNA by strand displacement with a thymine-substituted polyamide". Science 254 (5037): 1497-1500.

In the present invention, the "aptamer" is an oligonucleic acid or peptide molecule, and the general information of the aptamer is described in Bock LC et al., Nature 355(6360):5646(1992); Hoppe-Seyler F, Butz K "Peptide aptamers: powerful new tools for molecular medicine". J Mol Med. 78(8):42630(2000); Cohen BA, Colas P, Brent R. "An artificial cell-cycle inhibitor isolated from a combinatorial library". Proc Natl Acad Sci USA. 95(24): 142727 (1998).

In the present invention, as a method for measuring the mRNA expression level of the gene encoding GZMA, GZMB, CXCL9, CXCL10 or IL32, reverse transcription polymerase reaction (RT-PCR), competitive reverse transcription polymerase reaction (Competitive RT-PCR) ), real-time reverse transcription polymerase reaction (Real-time RT-PCR), RNase protection assay (RPA), Northern blotting, DNA chip, etc., but are not limited thereto.

In the present invention, the mRNA expression level of the genes encoding the biomarkers GZMA, GZMB, CXCL9, CXCL10 and IL32 is a gene encoding one or more proteins selected from the group consisting of GZMA, GZMB, CXCL9, CXCL10 and IL32. It can be measured using one or more selected from the group consisting of primers, probes, and antisense nucleotides that specifically bind to mRNA. In the present invention, the sequence information of GZMA, GZMB, CXCL9, CXCL10 and IL32 is the same as SEQ ID NOs: 1 to 5, respectively, so those skilled in the art can easily prepare primers, probes or antisense nucleotides specific for the gene encoding the protein based on this. you will be able to design

In the present invention, the "primer" is a fragment recognizing a target gene sequence, including a pair of forward and reverse primers, but preferably, a primer pair that provides analysis results having specificity and sensitivity. High specificity can be conferred when the primer's nucleic acid sequence is a sequence that is inconsistent with a non-target sequence present in the sample, thus amplifying only the target gene sequence containing the complementary primer binding site and not causing non-specific amplification. .

In the present invention, the "probe" refers to a substance capable of specifically binding to a target substance to be detected in a sample, and refers to a substance capable of specifically confirming the presence of a target substance in a sample through the binding. The type of probe is not limited as a material commonly used in the art, but preferably PNA (peptide nucleic acid), LNA (locked nucleic acid), peptide, polypeptide, protein, RNA or DNA, and most preferably For example, it may be PNA. More specifically, the probe is a biomaterial derived from or similar thereto, or manufactured in vitro, and includes, for example, enzymes, proteins, antibodies, microorganisms, animal and plant cells and organs, neurons, DNA, and It may be RNA, and DNA includes cDNA, genomic DNA, and oligonucleotides, RNA includes genomic RNA, mRNA, and oligonucleotides, and examples of proteins include antibodies, antigens, enzymes, peptides, and the like.

In the present invention, the "antisense" means that the antisense oligomer is hybridized with a target sequence in RNA by Watson-Crick base pairing, and typically mRNA and RNA in the target sequence: A sequence of nucleotide bases allowing the formation of an oligomeric heteroduplex and oligomers having an inter-subunit backbone. An oligomer may have exact sequence complementarity or approximate complementarity to a target sequence.

In the present invention, when the expression level of one or more proteins selected from the group consisting of GZMA, GZMB, CXCL9, CXCL10 and IL32 or the mRNA encoding them is lower than that of the control group through the process as described above, the treatment responsiveness to standard anticancer therapy is Low, high recurrence rate, and poor prognosis can be predicted.

In an embodiment of the present invention, the control group may be a median value (average value of the cancer patients) of the population of cancer patients.

In another embodiment of the present invention, the control group may be a sample obtained from a patient with no recurrence among the cancer patients, that is, from a patient who has been cured after treatment among the cancer patients.

In the present invention, “cure” refers to a state in which a cancer patient is completely cured without recurrence after undergoing surgical excision therapy, chemical therapy, or radiation therapy.

In the present invention, as described above, it is clinically evaluated that microsatellite instability is high among gastric cancer patients, and mRNA expression of one or more proteins selected from the group consisting of GZMA, GZMB, CXCL9, CXCL10 and IL32 or a gene encoding the same Reduced levels compared to controls may inform the decision to perform immunotherapy rather than surgical excision therapy and chemotherapy, which are predicted to be less responsive to treatment.

According to another embodiment of the present invention, GZMA, GZMB, CXCL9, CXCL10, and relates to a composition for predicting treatment responsiveness of a cancer patient comprising an agent for measuring the expression level of one or more proteins selected from the group consisting of IL32.

In the present invention, the agent for measuring the expression level of the GZMA, GZMB, CXCL9, CXCL10 and IL32 protein is an antibody, oligopeptide, ligand, PNA (peptide nucleic acid) and an aptamer that specifically binds to the protein. It may include one or more selected from the group consisting of.

In the present invention, the GZMA, GZMB, CXCL9, CXCL10 and IL32 proteins, antibodies, oligopeptides, ligands, PNAs and aptamers specific thereto, and the description of cancer patients overlap with the description of the method and are described below. omit

The composition of the present invention is for measuring the degree of microsatellite instability, and may further include primers specific for each of the BAT26, D5S346, BAT25, D17S250 and D2S123 genes. Since information on the BAT26, D5S346, BAT25, D17S250 and D2S123 genes according to the present invention is known, those skilled in the art will be able to easily design a primer that specifically binds to the gene based on this.

In addition, the composition of the present invention is for measuring the degree of microsatellite instability, BAT25, BAT26, NR21, NR22 (or NR27) and NR24 It may further comprise a specific primer for each gene. Since the information on the BAT25, BAT26, NR21, NR22 (or NR27) and NR24 genes according to the present invention is known, those skilled in the art will be able to easily design a primer that specifically binds to the gene based on this.

According to another embodiment of the present invention, GZMA, GZMB, CXCL9, CXCL10, and comprising an agent for measuring the mRNA expression level of a gene encoding one or more proteins selected from the group consisting of IL32, Therapeutic responsiveness of a cancer patient It relates to a composition for prediction.

In the present invention, the agent for measuring the expression level of the mRNA may include one or more selected from the group consisting of a primer, a probe, and an antisense nucleotide that specifically binds to the mRNA.

In the present invention, the mRNA of the gene encoding the GZMA, GZMB, CXCL9, CXCL10 and IL32 proteins, primers, probes, and antisense nucleotides specific thereto, and the description of the cancer patient overlap with the description of the method. omit the description.

The composition of the present invention is for measuring the degree of microsatellite instability, and may further include primers specific for each of the BAT26, D5S346, BAT25, D17S250 and D2S123 genes. Since information on the BAT26, D5S346, BAT25, D17S250 and D2S123 genes according to the present invention is known, those skilled in the art will be able to easily design a primer that specifically binds to the gene based on this.

In addition, the composition of the present invention is for measuring the degree of microsatellite instability, BAT25, BAT26, NR21, NR22 (or NR27) and NR24 It may further comprise a specific primer for each gene. Since the information on the BAT25, BAT26, NR21, NR22 (or NR27) and NR24 genes according to the present invention is known, those skilled in the art will be able to easily design a primer that specifically binds to the gene based on this.

In the present invention, the degree of microsatellite instability and the mRNA expression level of the GZMA, GZMB, CXCL9, CXCL10 or IL32 protein or the gene encoding the same in the sample measured from the cancer patient using the composition were measured and then compared with the control group. By preparing for it, it is possible to predict whether recurrence occurs with the treatment responsiveness and prognosis to standard chemotherapy.

More specifically, a sample measured from a cancer patient is measured to have high microsatellite instability, and the expression level of one or more proteins selected from the group consisting of GZMA, GZMB, CXCL9, CXCL10 and IL32 or mRNA encoding the same is higher than that of the control group. If it is low, it can be predicted that the treatment responsiveness to standard anticancer therapy is low and the likelihood of recurrence is high.

In an embodiment of the present invention, the control group may be a median value (average value of the cancer patients) of the population of cancer patients.

In another embodiment of the present invention, the control group may be a sample obtained from a patient with no recurrence among the cancer patients, that is, from a patient who has been cured after treatment among the cancer patients.

A sample measured from a cancer patient using the composition of the present invention is measured to have high microsatellite instability, and expression level of one or more proteins selected from the group consisting of GZMA, GZMB, CXCL9, CXCL10 and IL32 or mRNA encoding the same If it is low compared to this control, the patient may be informed to decide to undergo immunotherapy rather than surgical excision therapy and chemotherapy, which are predicted to have low therapeutic responsiveness.

According to another embodiment of the present invention, it relates to a kit for predicting treatment responsiveness of a cancer patient comprising the composition according to the present invention.

As such, the present invention can increase the survival probability or survival period by precisely predicting the reactivity of a cancer patient to standard anticancer therapy, and reduce cost and relieve pain to the patient by not performing unnecessary therapy.

The present invention can predict relapse probability and treatment responsiveness with high accuracy by measuring the expression levels of biomarkers of microsatellite instability and GZMA, GZMB, CXCL9, CXCL10 and/or IL32 from a sample taken from a cancer patient. In the future, appropriate treatment can be planned, which can further raise the level of public health.

1 is a heatmap showing the difference in gene expression level between a group in which gastric cancer recurred and a group in which gastric cancer did not recur among 65 MSI-H gastric cancer patients in Example 2 of the present invention.

Hereinafter, the present invention will be described in detail with reference to the following examples. However, the following examples are only illustrative of the present invention, and the content of the present invention is not limited by the following examples.

Example

[Example 1] Confirmation of microsatellite instability (MSI)

DNA for PCR was extracted from gastric cancer tissue samples taken from 300 gastric cancer patients. To confirm MSI, the five mononucleotide repeat markers BAT25, BAT26, NR21, NR22 and NR24 recommended by the National Cancer Institute (NCI) to define microsatellite instability were used as microsatellite instability markers. was used as 2 μl of 10× buffer (Roche, Mannheim, Germany), MgCl ₂ 50 ng DNA in 20 μl of a reaction solution containing 1.7-2.5 mmol/L, 0.3 μM of the primer pair of Table 1, 250 μM of deoxynucleotide triphosphate, and 2.5 units of DNA polymerase (Roche) was amplified. In the amplification, the initial denaturation process was performed at 94°C for 5 minutes, then repeated 30 times for 1 minute at 94°C, 1 minute at 55°C, and 1 minute at 72°C, and final extension reaction at 72°C for 10 minutes. was performed.

Then, 0.7 µL of the amplified sample was combined with 0.3 µL of GeneScan 500 Size Standard and 9 µL of HiDi formamide in ABI Prism 3100 Genetic Analyzer for separation of each fragment. When the temperature of the Genetic Analyzer oven reached 60°C, 15 kV was applied and electrophoresis was started. POP-4 was used as the separation solvent. After converting the fluorescence intensity into digital information, the data was acquired in real time by processing with ABI Prism 3100 Data Collection software.

In analyzing the MSI results, if a shift of microsatellite is observed in three or more of the five markers, BAT25, BAT26, NR21, NR22, and NR24, it indicates that microsatellite instability is high (microsatellite instability- high, MSI-H), microsatellite instability-low (MSI-L) when observed only in one or two of the five markers, and shift in all five markers If this was not observed, the microsatellite was evaluated as stable.

As a result, microsatellite shift was observed in three or more markers among BAT25, BAT26, NR21, NR22, and NR24 in 65 patients out of a total of 300 gastric cancer patients, which was confirmed as 'high microsatellite instability'. , and in the remaining 235 patients, microsatellite migration was observed only at two or less of BAT25, BAT26, NR21, NR22 and NR24 markers or none of the 5 markers.

microsatellite gene GenBank numbers repeat
(Repeat) primer sequence Average PCR product size BAT26 hMSH2 U04045 26 A intron 5 tgactacttttgacttcagcc
aaccattcaacatttttaaccc 120bp BAT25 c-kit X06182 25 T intron 16 tcgcctccaagaatgtaagt
tctgcattttaactatggctc 124bp NR24 Zinc finger 2 X60152 24T 3'UTR ccattgctgaattttacctc
attgtgccattgcattccaa 132bp NR21 SLC7A8 XM_033393 21T 5'UTR taaatgtatgtctcccctgg
attcctactccgcattcaca 103bp NR22 Transmembrane precursor protein B5 L38961 22T 3'UTR gaggcttgtcaaggacataa
aattcggatgccatccagtt 142bp

[ Example 2] Relapse-related of biomarkers Confirm

The raw data (raw data, Affymetrix Human Genome U133 PLUS 2.0 Array) of the gene expression data of 65 gastric cancer patients judged to have high microsatellite instability in Example 1 was normalized and After log2 substitution, match with Entrez Gene ID using nsFiltering function. In case of overlapping Gene ID, genes with large variance are selected, and Affymetrix quality control probe sets are filtered with small variance among all. After that, the final analysis was performed. Among 65 gastric cancer patients with high microsatellite instability, after surgical resection, gastric cancer recurred and non-recurred groups were classified, and then the gene information (different expression gene, DEG) that differed in the gene expression level between the two groups was included in the Limma package. When the corrected p-value is less than 0.05, obtain a gene list with a difference in gene expression between the relapsed group and the non-relapsed group (Table 2), and use the list to calculate gene expression as a heatmap shown as (FIG. 1).

gene logFC mean expression level t P.Value adj.P.Val B Expression level comparison C2 -1.33339 5.003988 -4.41236 3.81E-05 0.03457 2.053465 low GZMB -2.19639 8.689186 -4.39416 4.07E-05 0.03457 1.996245 low ADAMDEC1 -1.82127 9.144099 -4.33932 4.95E-05 0.03457 1.824524 low ZNF616 -0.8335 5.713146 -4.30408 5.60E-05 0.03457 1.714782 low TNFRSF11A -1.70815 6.438942 -4.27129 6.29E-05 0.03457 1.613081 low CXCL9 -2.07572 10.32948 -4.17757 8.73E-05 0.03457 1.324748 low HLA-DPB1 -1.19257 12.36055 -4.1356 0.000101 0.03457 1.196736 low HLA-DRB6 -1.20956 8.547579 -4.13283 0.000102 0.03457 1.188304 low NFE2L3 -1.1931 8.465625 -4.12409 0.000105 0.03457 1.161758 low CXCL10 -1.91347 10.15331 -4.06324 0.00013 0.03538 0.977749 low IL2RB -1.35432 7.68727 -4.05827 0.000132 0.03538 0.962782 low IL7 -1.53258 7.49292 -4.00717 0.000157 0.038783 0.809569 low GZMA -1.81444 9.005174 -3.98166 0.000171 0.040052 0.733514 low FBXO6 -0.96418 8.915836 -3.96902 0.000179 0.040052 0.695934 low IL32 -1.46458 7.015645 -3.93369 0.000202 0.040052 0.591248 low SORD -1.59889 6.013597 -3.92289 0.000209 0.040052 0.559358 low CXCL13 -2.32393 9.158827 -3.92108 0.00021 0.040052 0.554033 low CXCR6 -1.13127 6.310303 -3.91621 0.000214 0.040052 0.539676 low ETV7 -1.45842 6.306728 -3.90989 0.000218 0.040052 0.521033 low CD74 -1.25827 11.58224 -3.90443 0.000222 0.040052 0.504974 low LYSMD2 -0.6948 10.46475 -3.89925 0.000226 0.040052 0.489742 low AGPAT5 -0.8099 6.73317 -3.88969 0.000234 0.040052 0.461671 low CD2 -1.31146 7.41472 -3.87946 0.000242 0.040052 0.431646 low HLA-DMA -1.32384 10.38903 -3.78399 0.000332 0.047052 0.153933 low MAP1B 1.32083 6.476908 5.248086 1.71E-06 0.017424 4.794845 high RTN4 0.787528 2.896637 4.988526 4.59E-06 0.02339 3.922003 high STOX2 1.84847 4.25125 4.59826 1.95E-05 0.03457 2.644728 high DDX17 0.882581 4.3106 4.561716 2.23E-05 0.03457 2.527564 high CTSF 1.053357 5.544487 4.455103 3.27E-05 0.03457 2.188348 high MEG3 0.887927 3.040368 4.433155 3.54E-05 0.03457 2.119009 high MCAM 0.94202 8.29461 4.373785 4.38E-05 0.03457 1.932316 high GUCY1A2 1.121474 3.758308 4.350695 4.75E-05 0.03457 1.860059 high AMOTL1 1.292375 6.355113 4.283264 6.03E-05 0.03457 1.650176 high TRPC1 1.164857 3.262306 4.280468 6.09E-05 0.03457 1.641513 high UQCRC2 0.481829 2.621685 4.263569 6.46E-05 0.03457 1.589205 high EMCN 1.111293 5.0009568 4.250447 6.77E-05 0.03457 1.548663 high SRSF3 1.195185 3.680651 4.239522 7.03E-05 0.03457 1.514958 high AKAP12 2.228955 5.747579 4.224573 7.41E-05 0.03457 1.468919 high DCHS1 1.045352 5.834223 4.20017 8.07E-05 0.03457 1.39395 high TAGLN 1.3823 8.543915 4.187304 8.44E-05 0.03457 1.354519 high SHANK3 0.544167 2.594592 4.177207 8.74E-05 0.03457 1.323622 high GJC1 1.107278 6.745062 4.153577 9.49E-05 0.03457 1.251473 high MPDZ 1.082336 4.862436 4.152209 9.54E-05 0.03457 1.247302 high ACTA2 1.092545 11.34651 4.151083 9.57E-05 0.03457 1.24387 high PPP1R14A 1.212908 4.053492 4.150816 9.58E-05 0.03457 1.243057 high TCEAL7 1.168425 3.844495 4.149665 9.62E-05 0.03457 1.239549 high ZNF667-AS1 0.833364 3.83938 4.097777 0.000115 0.03538 1.082001 high FGFR1 0.952603 5.087338 4.096866 0.000115 0.03538 1.079244 high HEYL 0.952202 4.149992 4.074818 0.000125 0.03538 1.012646 high BRE-AS1 0.930276 2.772523 4.066037 0.000128 0.03538 0.986178 high FAM127A 1.126816 6.798237 4.059924 0.000131 0.03538 0.967771 high DIP2C 0.848527 7.181012 4.021007 0.00015 0.038217 0.850961 high ZSCAN18 1.422034 5.156526 4.020742 0.00015 0.038217 0.850168 high ARHGEF10 1.153034 6.125647 4.00212 0.00016 0.038783 0.794504 high SLIT2 0.979751 3.13523 3.967252 0.00018 0.040052 0.690683 high LDOC1 0.915701 2.995853 3.958168 0.000185 0.040052 0.663722 high TGFB1I1 1.069464 7.265525 3.944105 0.000195 0.040052 0.622055 high AOC3 1.170695 6.861094 3.936624 0.0002 0.040052 0.599924 high FAM127B 1.374918 4.469837 3.912136 0.000217 0.040052 0.52766 high KLF7 0.99774 5.575596 3.896077 0.000229 0.040052 0.480417 high CRYZL1 0.549643 4.684211 3.891841 0.000232 0.040052 0.467974 high LRRC17 1.338749 4.095627 3.882228 0.00024 0.040052 0.439766 high CC2D2A 0.735234 3.655715 3.869297 0.00025 0.040052 0.401891 high VIM 0.991129 4.46647 3.865823 0.000253 0.040052 0.391725 high ENPEP 1.226377 5.504886 3.865309 0.000254 0.040052 0.390223 high CHD1L 0.809365 3.333888 3.863191 0.000255 0.040052 0.384029 high MYL9 1.21751 5.314801 3.851383 0.000266 0.041012 0.349544 high PTPRM 0.797899 7.524321 3.847024 0.00027 0.041012 0.336827 high ARMCX2 1.362951 6.383315 3.838564 0.000277 0.041565 0.312173 high CNPY4 0.514118 5.29828 3.825412 0.00029 0.042796 0.273914 high RAI14 0.851579 9.429513 3.818331 0.000297 0.043189 0.253347 high FERMT2 1.102402 5.269186 3.787591 0.000328 0.047052 0.164335 high

The portion indicated in red in the second row in FIG. 1 corresponds to a patient with recurrence of gastric cancer. In the case of a patient who recurred after gastric cancer resection, the expression of GZMA, GZMB, CXCL9, CXCL10 and IL32 compared to a patient who did not relapse and was cured. It can be seen that the level was significantly decreased and displayed in dark blue.

In Table 2, logFC is a value obtained by quantifying the expression level of each gene in log2 compared to the expression level of each gene in a patient who has not recovered from gastric cancer after gastric cancer resection. Also in Table 1 above, it can be seen that the expression levels of GZMA, GZMB, CXCL9, CXCL10 and IL32 were significantly reduced in patients who did not relapse after gastric cancer resection and recovered compared to patients who had relapsed.

In the present invention, the microsatellite instability is evaluated to be high in cancer patients, and the expression levels of the biomarkers of GZMA, GZMB, CXCL9, CXCL10 and IL32 are the average value of the cancer patients, or patients with no recurrence among the cancer patients. If the expression level is lower than the expression level of , it can be predicted that the treatment responsiveness to standard anticancer therapy is low and the recurrence rate is high, and furthermore, for these patients, a treatment plan with immunotherapy rather than standard anticancer therapy can be designed.

As described above in detail a specific part of the present invention, for those of ordinary skill in the art, this specific description is only a preferred embodiment, and it is clear that the scope of the present invention is not limited thereto. Accordingly, the substantial scope of the present invention will be defined by the appended claims and their equivalents.

<110> Industry-Academic Cooperation Foundation, Yonsei University <120> Method for predicting the treatment response of a cancer patient <130> DPB167334 <160> 5 <170> KoPatentIn 3.0 <210> 1 <211> 262 <212> PRT <213> Homo sapiens <400> 1 Met Arg Asn Ser Tyr Arg Phe Leu Ala Ser Ser Leu Ser Val Val Val 1 5 10 15 Ser Leu Leu Leu Ile Pro Glu Asp Val Cys Glu Lys Ile Ile Gly Gly 20 25 30 Asn Glu Val Thr Pro His Ser Arg Pro Tyr Met Val Leu Leu Ser Leu 35 40 45 Asp Arg Lys Thr Ile Cys Ala Gly Ala Leu Ile Ala Lys Asp Trp Val 50 55 60 Leu Thr Ala Ala His Cys Asn Leu Asn Lys Arg Ser Gln Val Ile Leu 65 70 75 80 Gly Ala His Ser Ile Thr Arg Glu Glu Pro Thr Lys Gln Ile Met Leu 85 90 95 Val Lys Lys Glu Phe Pro Tyr Pro Cys Tyr Asp Pro Ala Thr Arg Glu 100 105 110 Gly Asp Leu Lys Leu Leu Gln Leu Thr Glu Lys Ala Lys Ile Asn Lys 115 120 125 Tyr Val Thr Ile Leu His Leu Pro Lys Lys Gly Asp Asp Val Lys Pro 130 135 140 Gly Thr Met Cys Gln Val Ala Gly Trp Gly Arg Thr His Asn Ser Ala 145 150 155 160 Ser Trp Ser Asp Thr Leu Arg Glu Val Asn Ile Thr Ile Ile Asp Arg 165 170 175 Lys Val Cys Asn Asp Arg Asn His Tyr Asn Phe Asn Pro Val Ile Gly 180 185 190 Met Asn Met Val Cys Ala Gly Ser Leu Arg Gly Gly Arg Asp Ser Cys 195 200 205 Asn Gly Asp Ser Gly Ser Pro Leu Leu Cys Glu Gly Val Phe Arg Gly 210 215 220 Val Thr Ser Phe Gly Leu Glu Asn Lys Cys Gly Asp Pro Arg Gly Pro 225 230 235 240 Gly Val Tyr Ile Leu Leu Ser Lys Lys His Leu Asn Trp Ile Ile Met 245 250 255 Thr Ile Lys Gly Ala Val 260 <210> 2 <211> 247 <212> PRT <213> Homo sapiens <400> 2 Met Gln Pro Ile Leu Leu Leu Leu Ala Phe Leu Leu Leu Pro Arg Ala 1 5 10 15 Asp Ala Gly Glu Ile Ile Gly Gly His Glu Ala Lys Pro His Ser Arg 20 25 30 Pro Tyr Met Ala Tyr Leu Met Ile Trp Asp Gln Lys Ser Leu Lys Arg 35 40 45 Cys Gly Gly Phe Leu Ile Gln Asp Asp Phe Val Leu Thr Ala Ala His 50 55 60 Cys Trp Gly Ser Ser Ile Asn Val Thr Leu Gly Ala His Asn Ile Lys 65 70 75 80 Glu Gln Glu Pro Thr Gln Gln Phe Ile Pro Val Lys Arg Pro Ile Pro 85 90 95 His Pro Ala Tyr Asn Pro Lys Asn Phe Ser Asn Asp Ile Met Leu Leu 100 105 110 Gln Leu Glu Arg Lys Ala Lys Arg Thr Arg Ala Val Gln Pro Leu Arg 115 120 125 Leu Pro Ser Asn Lys Ala Gln Val Lys Pro Gly Gln Thr Cys Ser Val 130 135 140 Ala Gly Trp Gly Gln Thr Ala Pro Leu Gly Lys His Ser His Thr Leu 145 150 155 160 Gln Glu Val Lys Met Thr Val Gln Glu Asp Arg Lys Cys Glu Ser Asp 165 170 175 Leu Arg His Tyr Tyr Asp Ser Thr Ile Glu Leu Cys Val Gly Asp Pro 180 185 190 Glu Ile Lys Lys Thr Ser Phe Lys Gly Asp Ser Gly Gly Pro Leu Val 195 200 205 Cys Asn Lys Val Ala Gln Gly Ile Val Ser Tyr Gly Arg Asn Asn Gly 210 215 220 Met Pro Pro Arg Ala Cys Thr Lys Val Ser Ser Phe Val His Trp Ile 225 230 235 240 Lys Lys Thr Met Lys Arg His 245 <210> 3 <211> 125 <212> PRT <213> Homo sapiens <400> 3 Met Lys Lys Ser Gly Val Leu Phe Leu Leu Leu Gly Ile Ile Leu Leu Val 1 5 10 15 Leu Ile Gly Val Gln Gly Thr Pro Val Val Arg Lys Gly Arg Cys Ser 20 25 30 Cys Ile Ser Thr Asn Gln Gly Thr Ile His Leu Gln Ser Leu Lys Asp 35 40 45 Leu Lys Gln Phe Ala Pro Ser Pro Ser Cys Glu Lys Ile Glu Ile Ile 50 55 60 Ala Thr Leu Lys Asn Gly Val Gln Thr Cys Leu Asn Pro Asp Ser Ala 65 70 75 80 Asp Val Lys Glu Leu Ile Lys Lys Trp Glu Lys Gln Val Ser Gln Lys 85 90 95 Lys Lys Gln Lys Asn Gly Lys Lys His Gln Lys Lys Lys Val Leu Lys 100 105 110 Val Arg Lys Ser Gln Arg Ser Arg Gln Lys Lys Thr Thr 115 120 125 <210> 4 <211> 98 <212> PRT <213> Homo sapiens <400> 4 Met Asn Gln Thr Ala Ile Leu Ile Cys Cys Leu Ile Phe Leu Thr Leu 1 5 10 15 Ser Gly Ile Gln Gly Val Pro Leu Ser Arg Thr Val Arg Cys Thr Cys 20 25 30 Ile Ser Ile Ser Asn Gln Pro Val Asn Pro Arg Ser Leu Glu Lys Leu 35 40 45 Glu Ile Ile Pro Ala Ser Gln Phe Cys Pro Arg Val Glu Ile Ile Ala 50 55 60 Thr Met Lys Lys Lys Gly Glu Lys Arg Cys Leu Asn Pro Glu Ser Lys 65 70 75 80 Ala Ile Lys Asn Leu Leu Lys Ala Val Ser Lys Glu Arg Ser Lys Arg 85 90 95 Ser Pro <210> 5 <211> 234 <212> PRT <213> Homo sapiens <400> 5 Met Cys Phe Pro Lys Val Leu Ser Asp Asp Met Lys Lys Leu Lys Ala 1 5 10 15 Arg Met Val Met Leu Leu Pro Thr Ser Ala Gln Gly Leu Gly Ala Trp 20 25 30 Val Ser Ala Cys Asp Thr Glu Asp Thr Val Gly His Leu Gly Pro Trp 35 40 45 Arg Asp Lys Asp Pro Ala Leu Trp Cys Gln Leu Cys Leu Ser Ser Gln 50 55 60 His Gln Ala Ile Glu Arg Phe Tyr Asp Lys Met Gln Asn Ala Glu Ser 65 70 75 80 Gly Arg Gly Gln Val Met Ser Ser Leu Ala Glu Leu Glu Asp Asp Phe 85 90 95 Lys Glu Gly Tyr Leu Glu Thr Val Ala Ala Tyr Tyr Glu Glu Gln His 100 105 110 Pro Glu Leu Thr Pro Leu Leu Glu Lys Glu Arg Asp Gly Leu Arg Cys 115 120 125 Arg Gly Asn Arg Ser Pro Val Pro Asp Val Glu Asp Pro Ala Thr Glu 130 135 140 Glu Pro Gly Glu Ser Phe Cys Asp Lys Val Met Arg Trp Phe Gln Ala 145 150 155 160 Met Leu Gln Arg Leu Gln Thr Trp Trp His Gly Val Leu Ala Trp Val 165 170 175 Lys Glu Lys Val Val Ala Leu Val His Ala Val Gln Ala Leu Trp Lys 180 185 190 Gln Phe Gln Ser Phe Cys Cys Ser Leu Ser Glu Leu Phe Met Ser Ser 195 200 205 Phe Gln Ser Tyr Gly Ala Pro Arg Gly Asp Lys Glu Glu Leu Thr Pro 210 215 220 Gln Lys Cys Ser Glu Pro Gln Ser Ser Lys 225 230

Claims (20)

(a) measuring microsatellite instability (MSI) in a sample isolated from a cancer patient;
(b) GZMA (granzyme A), GZMB (granzyme B), CXCL9 (CXC motif chemokine ligand 9), CXCL10 (CXC motif chemokine ligand 10) from samples isolated from cancer patients when the microsatellite instability is evaluated to be high ) and IL32 (interleukin 32) measuring the mRNA expression level of one or more proteins selected from the group consisting of or a gene encoding the same; and
When the mRNA expression level of one or more proteins selected from the group consisting of GZMA, GZMB, CXCL9, CXCL10 and IL32 measured in (b) or a gene encoding them is lower than that of the control group, the cancer patient is treated after surgical resection Including the step of predicting that the recurrence rate will be high,
The cancer patient is a gastric cancer patient,
When the microsatellite instability is evaluated as high (1) DNA damage, change or mutation of two or more microsatellite markers among BAT26, D5S346, BAT25, D17S250 and D2S123 is confirmed in a sample isolated from a cancer patient ; or (2) BAT25 in a sample isolated from a cancer patient; BAT26; NR21; NR22 or NR27; and DNA damage, change or mutation of three or more microsatellite markers among NR24 microsatellite markers. A method for predicting treatment responsiveness in cancer patients. delete delete delete delete According to claim 1,
The GZMA is represented by SEQ ID NO: 1, the GZMB is represented by SEQ ID NO: 2, the CXCL9 is represented by SEQ ID NO: 3, the CXCL10 is represented by SEQ ID NO: 4, and the IL32 is represented by SEQ ID NO: 5 Phosphorus, a method for predicting treatment responsiveness in cancer patients. delete delete According to claim 1,
The control group is the mRNA expression level of one or more proteins selected from the group consisting of GZMA, GZMB, CXCL9, CXCL10 and IL32, or a gene encoding the same, measured from a sample obtained from a patient with no recurrence among the cancer patients. , a method for predicting treatment responsiveness in cancer patients. According to claim 1,
When the mRNA expression level of one or more proteins selected from the group consisting of GZMA, GZMB, CXCL9, CXCL10 and IL32 measured in (b) or a gene encoding them is lower than that of the control group, the treatment responsiveness to standard anticancer therapy is A method of predicting treatment responsiveness in a cancer patient, comprising predicting to be low. Measuring the expression level of one or more proteins selected from the group consisting of GZMA (granzyme A), GZMB (granzyme B), CXCL9 (CXC motif chemokine ligand 9), CXCL10 (CXC motif chemokine ligand 10) and IL32 (interleukin 32) A composition for predicting therapeutic responsiveness in cancer patients, comprising the agent,
The cancer is gastric cancer with high microsatellite instability,
The cancer with high microsatellite instability is (1) when DNA damage, change or mutation of two or more microsatellite markers among BAT26, D5S346, BAT25, D17S250 and D2S123 is confirmed in a sample isolated from a cancer patient; or (2) BAT25 in a sample isolated from a cancer patient; BAT26; NR21; NR22 or NR27; and DNA damage, change or mutation of three or more microsatellite markers among the NR24 microsatellite markers,
When the expression level of one or more proteins selected from the group consisting of GZMA, GZMB, CXCL9, CXCL10 and IL32 measured in the cancer patient is lower than that of the control group, the cancer patient is predicted to have a high recurrence rate after surgical resection, composition . 12. The method of claim 11,
The agent for measuring the expression level of the protein comprises at least one selected from the group consisting of an antibody, oligopeptide, ligand, PNA (peptide nucleic acid) and aptamer that specifically binds to the protein, cancer A composition for predicting a patient's therapeutic responsiveness. 12. The method of claim 11,
The composition further comprises a primer specific for each of BAT26, D5S346, BAT25, D17S250 and D2S123 genes, the composition for predicting treatment responsiveness of cancer patients. 12. The method of claim 11,
The composition comprises BAT25; BAT26; NR21; NR22 or NR27; And further comprising a primer specific for each of the NR24 gene, a composition for predicting treatment responsiveness of cancer patients. 15. A kit for predicting therapeutic responsiveness of a cancer patient comprising the composition of any one of claims 11 to 14,
The cancer is gastric cancer with high microsatellite instability,
The cancer with high microsatellite instability is (1) when DNA damage, change or mutation of two or more microsatellite markers among BAT26, D5S346, BAT25, D17S250 and D2S123 is confirmed in a sample isolated from a cancer patient; or (2) BAT25 in a sample isolated from a cancer patient; BAT26; NR21; NR22 or NR27; and DNA damage, change or mutation of three or more microsatellite markers among the NR24 microsatellite markers,
When the expression level of one or more proteins selected from the group consisting of GZMA, GZMB, CXCL9, CXCL10 and IL32 measured in the cancer patient is lower than that in the control group, the cancer patient is predicted to have a high recurrence rate after surgical resection, kit . mRNA of a gene encoding one or more proteins selected from the group consisting of GZMA (granzyme A), GZMB (granzyme B), CXCL9 (CXC motif chemokine ligand 9), CXCL10 (CXC motif chemokine ligand 10), and IL32 (interleukin 32) A composition for predicting treatment responsiveness of cancer patients, comprising an agent for measuring the expression level of
The cancer is gastric cancer with high microsatellite instability,
The cancer with high microsatellite instability is (1) when DNA damage, change or mutation of two or more microsatellite markers among BAT26, D5S346, BAT25, D17S250 and D2S123 is confirmed in a sample isolated from a cancer patient; or (2) BAT25 in a sample isolated from a cancer patient; BAT26; NR21; NR22 or NR27; and DNA damage, change or mutation of three or more microsatellite markers among the NR24 microsatellite markers,
When the mRNA expression level of a gene encoding one or more proteins selected from the group consisting of GZMA, GZMB, CXCL9, CXCL10 and IL32 measured in the cancer patient is lower than that of the control group, the cancer patient has a lower recurrence rate after surgical resection The composition, which is expected to be high. 17. The method of claim 16,
The agent for measuring the expression level of the mRNA comprises at least one selected from the group consisting of primers, probes and antisense nucleotides that specifically bind to the mRNA, a composition for predicting treatment responsiveness of cancer patients. 17. The method of claim 16,
The composition further comprises a primer specific for each of BAT26, D5S346, BAT25, D17S250 and D2S123 genes, the composition for predicting treatment responsiveness of cancer patients. 17. The method of claim 16,
The composition comprises BAT25; BAT26; NR21; NR22 or NR27; And further comprising a primer specific for each of the NR24 gene, a composition for predicting treatment responsiveness of cancer patients. A kit for predicting therapeutic responsiveness of a cancer patient comprising the composition of any one of claims 16 to 19,
The cancer is gastric cancer with high microsatellite instability,
The cancer with high microsatellite instability is (1) when DNA damage, change or mutation of two or more microsatellite markers among BAT26, D5S346, BAT25, D17S250 and D2S123 is confirmed in a sample isolated from a cancer patient; or (2) BAT25 in a sample isolated from a cancer patient; BAT26; NR21; NR22 or NR27; and DNA damage, change or mutation of three or more microsatellite markers among the NR24 microsatellite markers,
When the mRNA expression level of a gene encoding one or more proteins selected from the group consisting of GZMA, GZMB, CXCL9, CXCL10 and IL32 measured in the cancer patient is lower than that of the control group, the cancer patient has a lower recurrence rate after surgical resection Expected to be high, the kit.

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