KR20190082187A - Biomarkers for the diagnosis of ovarian cancer, indicating differences in expression levels - Google Patents

Abstract

The present invention relates to biomarkers for the diagnosis of ovarian cancer and uses thereof. Compositions, kits, and methods according to one aspect allow not only the diagnosis of ovarian cancer, but also the prediction of prognosis based on the gene expression of ovarian cancer tissue after surgery or treatment, thereby enabling patients with ovarian cancer to receive appropriate prognostic measures. In addition, by securing gene profiling data of Asian, especially Korean ovarian cancer patients and analyzing the data, it is possible to overcome problems in predicting the prognosis of ovarian cancer patients based on the conventional data of Western people.

Description

[0002] Biomarkers for the diagnosis of ovarian cancer, indicating differences in expression levels,

Biomarkers for the diagnosis of ovarian cancer and their use.

Seventy percent of patients with high-grade serous ovarian cancer die from cancer. Standard therapy is the chemotherapy that is given after surgery. Since cancer recurs in about 25% of patients within 6 months after chemotherapy and only 31% is likely to survive for more than 5 years, new treatments other than standard therapies are needed. The Cancer Genome Atlas (TCGA) researcher consortium produces and analyzes exome data, mRNA expression data, and epigenetics data for approximately 300 ovarian cancer patients for the development of new therapies Patients were identified. However, the above study has the problem that most of the patients are Europeans and that data analysis does not find a cluster of patients or gene expression markers that show a large difference in prognosis.

The present inventors have accomplished the present invention by acquiring and analyzing data of Korean ovarian cancer patients in various stages and selecting a new expression gene list in ovarian cancer.

IL2, IL6, IRF8, LAG3, IL2, IL4, CD27, CD27, CD40, CD68, CD8A, CSF2RB, CSF3R, CTLA4, CXCR3, EVI2B, FOXL2, GZMA, GZMB, HAVCR1, IDO1, IL1R2, The present invention provides a composition for diagnosing ovarian cancer comprising an agent for measuring mRNA or protein expression levels of LTB, MNDA, PDCD1, PDCD1LG2, PRF1, RASGRP1, SELL, SLAMF1, SOD2, TAP1, TIGIT, TNFRSF6B or TNFSF15.

Another aspect is to provide an ovarian cancer diagnostic kit comprising the above composition.

Another aspect is that the biological sample isolated from an individual is selected from the group consisting of AIM2, CD2, CD244, CD27, CD274, CD40, CD68, CD8A, CSF2RB, CSF3R, CTLA4, CXCR3, EVI2B, FOXL2, GZMA, GZMB, HAVCR1, IDO1, IL1R2, IL2RA, Measuring mRNA or protein expression levels of IL32, IL6, IRF8, LAG3, LTB, MNDA, PDCD1, PDCD1LG2, PRF1, RASGRP1, SELL, SLAMF1, SOD2, TAP1, TIGIT, TNFRSF6B or TNFSF15; And comparing the measured expression level to an expression level of a normal control; And to provide an information providing method for diagnosing ovarian cancer.

IL2, IL6, IRF8, LAG3, IL2, IL4, CD27, CD27, CD40, CD68, CD8A, CSF2RB, CSF3R, CTLA4, CXCR3, EVI2B, FOXL2, GZMA, GZMB, HAVCR1, IDO1, IL1R2, The present invention provides an ovarian cancer diagnostic composition comprising an agent for measuring mRNA or protein expression levels of LTB, MNDA, PDCD1, PDCD1LG2, PRF1, RASGRP1, SELL, SLAMF1, SOD2, TAP1, TIGIT, TNFRSF6B or TNFSF15.

As used herein, the term "diagnosis" means identifying the presence or characteristic of pathophysiology. Diagnosis in one aspect is to confirm the presence and / or degree of ovarian cancer, i.e., progress, and includes the prognosis after treatment or post-operative, i. E., The likelihood of recurrence.

As used herein, the term "marker" refers to a substance which can be distinguished from a normal group and an individual having ovarian cancer. The term " marker " Nucleic acid, gene lipid, glycolipid, glycoprotein, sugar, and the like. In particular, it may be a protein or a gene that changes in a tissue isolated from an individual having ovarian cancer of the present invention.

As used herein, the term "agent that measures the level of expression of mRNA or protein" refers to a marker that increases or decreases in ovarian cancer patients, such as AIM2, CD2, CD244, CD27, CD274, CD40, CD68, CD8A, CSF2RB, CSF3R, CTLA4 , CXCR3, EVI2B, FOXL2, GZMA, GZMB, HAVCR1, IDO1, IL1R2, IL2RA, IL32, IL6, IRF8, LAG3, LTB, MNDA, PDCD1, PDCD1LG2, PRF1, RASGRP1, SELL, SLAMF1, SOD2, TAP1, TIGIT, TNFRSF6B Or a molecule that can be used in the detection and / or quantification of a marker by identifying the level of TNFSF15 mRNA or protein expression. Specifically, the agent for measuring the mRNA expression level of the gene may be, for example, a pair of primers, a probe, or an antisense nucleotide that specifically binds to the gene. Since the nucleic acid information of the genes is known by Genebank et al., A person skilled in the art can design a primer or a probe that specifically amplifies a specific region of these genes based on the sequence.

As used herein, the term "primer pair" is a primer pair that contains all combinations of primer pairs consisting of forward and reverse primers that recognize the target gene sequence, and specifically provides analysis results with specificity and sensitivity. The nucleic acid sequence of the primer is inconsistent with the non-target sequence present in the sample and can be given high specificity when it is a primer that amplifies only the target gene sequence containing a complementary primer binding site and does not induce nonspecific amplification .

As used herein, the term "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 the sample through the binding do. The probe molecule may be a peptide nucleic acid (PNA), a peptide nucleic acid (LNA), a peptide, a polypeptide, a protein, an RNA or a DNA, although it is not limited as a substance commonly used in the art. More specifically, the probe may be a biomolecule derived from or derived from an organism, or prepared in vitro, such as an enzyme, a protein, an antibody, a microorganism, an animal or plant cell and an organ, a nerve cell, DNA, and RNA DNA includes cDNA, genomic DNA, oligonucleotide, RNA includes genomic RNA, mRNA, oligonucleotide, and examples of the protein may include an antibody, an antigen, an enzyme, a peptide, and the like.

As used herein, the term "antisense oligonucleotide" refers to DNA or RNA or derivatives thereof containing a nucleic acid sequence complementary to the sequence of a specific mRNA, which binds to a complementary sequence in the mRNA and inhibits translation of the mRNA into a protein . An antisense oligonucleotide sequence refers to a DNA or RNA sequence that is complementary to and capable of binding to the mRNAs of the genes. This can interfere with translation of the gene mRNA, translocation into the cytoplasm, maturation, or essential activity for all other overall biological functions. The length of the antisense oligonucleotide may be 6 to 100 bases, preferably 8 to 60 bases, more preferably 10 to 40 bases. The antisense oligonucleotides may be synthesized in vitro by conventional methods and administered in vivo or may be used to synthesize antisense oligonucleotides in vivo. One example for the synthesis of antisense oligonucleotides in vitro is the use of RNA polymerase I. One example of allowing antisense RNA to be synthesized in vivo is to allow the antisense RNA to be transcribed using a vector whose origin is a multi-cloning site (MCS) in the opposite direction. It is preferred that the antisense RNA is such that translation stop codon is present in the sequence so that it is not translated into the peptide sequence.

The agent for measuring the protein expression level of the marker may be, for example, an antibody that specifically binds to a protein or a fragment of a protein encoded by the marker gene, and the antibody may be a polyclonal antibody or a monoclonal antibody .

The term "antibody ", as used herein, may refer to a specific protein molecule directed against an antigenic site. For purposes of the present invention, an antibody refers to an antibody that specifically binds to a marker protein and includes both polyclonal antibodies, monoclonal antibodies, and recombinant antibodies. The production of the antibody can be easily carried out using techniques well known in the art. The antibodies herein also include functional fragments of antibody molecules as well as complete forms with two full-length light chains and two full-length heavy chains. A functional fragment of an antibody molecule refers to a fragment having at least an antigen binding function, and includes Fab, F (ab ') 2, F (ab') 2 and Fv.

Another aspect provides an ovarian cancer diagnostic kit comprising the composition. Specific details of the composition are as described above. Specifically, the kit can be used for the diagnosis of ovarian cancer, such as AIM2, CD2, CD244, CD27, CD274, CD40, CD68, CD8A, CSF2RB, CSF3R, CTLA4, CXCR3, EVI2B, FOXL2, GZMA, GZMB, HAVCR1, IDO1, IL1R2, IL2RA Protein expression level of mRNA of the gene or the expression level of the protein is determined by the expression level of the mRNA of the gene or the expression level of the TNF-R protein, By measuring, ovarian cancer can be diagnosed. The kit may include an agent for measuring an mRNA expression level of an ovarian cancer diagnostic marker gene, for example, a primer pair specifically binding to the gene, a probe or an antisense nucleotide, For example, an antibody that specifically binds to the marker protein, or an immunobinding fraction of the antibody.

In one embodiment, the kit may be a reverse transcription polymerase chain reaction kit (RT-PCR), a DNA chip kit, an enzyme-linked immunosorbent assay (ELISA) kit, a protein chip kit, a rapid kit, have.

In addition, the ovarian cancer diagnostic kit may further comprise one or more other component compositions, solutions, or devices suitable for the assay method. For example, the diagnostic kit may be a diagnostic kit containing the necessary elements necessary for performing the reverse transcription reaction. The RT-PCR kit contains the respective primer pairs specific for the marker gene. The primer is a nucleotide having a sequence specific to the nucleic acid sequence of each of the above genes, and has a length of about 7 bp to 50 bp, more preferably about 10 bp to 30 bp. It may also contain a primer specific for the nucleic acid sequence of the control gene. Other reverse transcriptase reaction kits include enzymes such as test tubes or other appropriate containers, reaction buffer (pH and magnesium concentrations vary), deoxynucleotides (dNTPs), Taq polymerase and reverse transcriptase, DNAse, RNAse inhibitor DEPC- Water (DEPC-water), sterile water, and the like. Further, for example, the DNA chip kit may include a substrate on which a cDNA or oligonucleotide corresponding to a gene or a fragment thereof is attached, and a reagent, a preparation, and an enzyme for producing a fluorescent-labeled probe. The substrate may also comprise a cDNA or oligonucleotide corresponding to a control gene or fragment thereof. Also, for example, the kit may be a diagnostic kit that includes the necessary elements necessary to perform LISA. The ELISA kit comprises an antibody specific for the protein. Antibodies are monoclonal antibodies, polyclonal antibodies or recombinant antibodies with high specificity and affinity for each marker protein and little cross reactivity to other proteins. The ELISA kit may also include antibodies specific for the control protein. Other ELISA kits can be used to detect antibodies that can bind a reagent capable of detecting the bound antibody, such as a labeled secondary antibody, chromophores, an enzyme (e. G., Conjugated to an antibody) Other materials, and the like. Also, for example, the kit may be a rapid kit that includes the necessary elements necessary to perform a rapid test to know the analysis result. Rapid kits contain antibodies specific for proteins. Antibodies are monoclonal antibodies, polyclonal antibodies or recombinant antibodies with high specificity and affinity for each marker protein and little cross reactivity to other proteins. The rapid kit may also include antibodies specific for the control protein. Other rapid kits include reagents capable of detecting the bound antibody, such as a nitrocellulose membrane with a specific antibody and a secondary antibody immobilized thereon, a membrane bound to the bead conjugated with the antibody, Materials, and the like. Also, for example, the kit may be a multiple reaction monitoring (MRM) kit that is an MS / MS mode that includes the necessary elements to perform mass analysis. While SIM (Selected Ion Monitoring) is a method of using ions generated by collision with the source part of the mass spectrometer, MRM once again selects a specific ion among the broken ions to connect another consecutively connected MS source And then collide with another once more, and then use ions obtained from the collision. Through the above-described multiple reaction monitoring (MRM) analysis methods, it is possible to compare the protein expression level in the normal control group or the same individual with the protein expression level in the ovarian cancer-bearing individuals, It is possible to diagnose whether ovarian cancer is caused or not by judging whether the expression level is increased or decreased.

Another aspect is that the biological sample isolated from an individual is selected from the group consisting of AIM2, CD2, CD244, CD27, CD274, CD40, CD68, CD8A, CSF2RB, CSF3R, CTLA4, CXCR3, EVI2B, FOXL2, GZMA, GZMB, HAVCR1, IDO1, IL1R2, IL2RA, Measuring mRNA or protein expression levels of IL32, IL6, IRF8, LAG3, LTB, MNDA, PDCD1, PDCD1LG2, PRF1, RASGRP1, SELL, SLAMF1, SOD2, TAP1, TIGIT, TNFRSF6B or TNFSF15; And comparing the measured expression level to an expression level of a normal control; And a method for providing information for ovarian cancer diagnosis.

In one embodiment, the method of providing information comprises the steps of: (1) isolating a biological sample from an individual, wherein AIM2, CD2, CD244, CD27, CD27, CD40, CD68, CD8A, CSF2RB, CSF3R, CTLA4, CXCR3, EVI2B, FOXL2, GZMA, GZMB, HAVCR1, IDO1, The method comprising measuring mRNA or protein expression levels of IL1R2, IL2RA, IL32, IL6, IRF8, LAG3, LTB, MNDA, PDCD1, PDCD1LG2, PRF1, RASGRP1, SELL, SLAMF1, SOD2, TAP1, TIGIT, TNFRSF6B or TNFSF15 . Specifically, the expression level of the mRNA or protein can be determined by measuring the mRNA expression level of the marker gene or the expression level of the protein encoded by the gene. Separation of mRNA or protein from a sample of an individual can be suitably performed by those skilled in the art according to methods known in the art. For example, the ovarian cancer tissue of an individual can be homogenized with a buffer for protein extraction or a buffer for nucleic acid extraction, followed by centrifugation, and the resulting supernatant can be used as a sample of an individual. The subject refers to an object for predicting the prognosis after ovarian cancer diagnosis or ovarian cancer treatment, that is, recurrence. The subject may include a vertebrate animal, a mammal, or a human ( Homo sapiens ). For example, the human being may be a Korean. In addition, the biological sample may be tissue, cell, whole blood, serum, plasma, saliva, sputum, cerebrospinal fluid or urine. The measurement of the mRNA expression level can be performed by, for example, RT-PCR, competitive RT-PCR, real-time quantitative RT-PCR, Quantitative RT-PCR, RNase protection method, northern blotting or DNA chip technology may be used. In addition, the measurement of the protein expression level can be performed by, for example, Western blotting, immunohistochemical staining, immunoprecipitation assay, compliant fixation assay or immunofluorescence assay (immunofluorescence) can be used.

The method of providing information in one embodiment comprises comparing the measured expression level to an expression level of a normal control. Specifically, the mRNA or protein expression level of a marker gene is measured in a sample of a patient with ovarian cancer, and the expression level of the mRNA or protein of the same marker gene in the normal control group is measured and compared, Of ovarian cancer can be measured according to the degree of increase or decrease in the expression level of ovarian cancer and the degree of recurrence can be predicted when the ovarian cancer patient is treated or post-operative.

One aspect of the biomarker is not only the ability to diagnose ovarian cancer, but also the ability to predict the prognosis based on the gene expression of ovarian cancer tissue after surgery or treatment, thereby enabling patients with ovarian cancer to undergo appropriate prognostic measures . In addition, by securing genetic profiling data of Asian patients, particularly Korean ovarian cancer patients, and analyzing the data, it is possible to overcome the problems of prediction of prognosis of ovarian cancer patients based on conventional Western data.

1 is a schematic diagram showing a biomarker selection method for predicting the prognosis of ovarian cancer.
FIG. 2 is a diagram showing a network of genes having a large difference in expression amount according to the ovarian cancer prognosis.

Hereinafter, preferred embodiments of the present invention will be described in order to facilitate understanding of the present invention. However, the following examples are provided only for the purpose of easier understanding of the present invention, and the present invention is not limited by the following examples.

[ Preparation Example ]

Patient samples used in the study were patients who underwent ovarian cancer surgery at Bundang CHA General Hospital and were approved by the Institutional Review Board to obtain the tissues of the patients. The information of each sample is shown in Table 1 below. Among the 54 patients shown in Table 1, 17 patients had good prognosis, 29 patients had recurrence of ovarian cancer, and 8 patients had poor prognosis because they did not respond to chemotherapy.

Characteristic division Number of patients (54) age <40 3 [40-50] 15 [50-60] 23 (43.4%) [60-70] 6 [70-80] 7 ordnance I 4 II 2 III 44 (81.5%) IV 3 NA One

[ Example ]

Example  1. Data generation and selection of primary gene list

Whole-mRNA sequencing (RNAseq) data was generated using Illumina HiSeq 2500 for the 54 patients obtained in the above preparation example. Thereafter, 471 genes having a large expression difference according to the prognosis of ovarian cancer were selected from the whole genome expression data by mRNA expression profiling analysis, and mRNA expression was analyzed. Specifically, mRNA expression was analyzed using the Cancer Genome Atlas (TCGA) mRNA sequencing pipeline. In addition, MapSplice v2.1.6 was used to map to Transcript, and the amount of mRNA for each of the 471 genes was measured using RSEM-1.2.5 and NCBI hg19 RefSeq. Thereafter, the molecular pathways of decreased expression in 37 patients with poor prognosis of ovarian cancer and the genes whose expression is statistically significantly changed are shown in Table 2 below.

KEGG pathway p-value The corrected p-value Gene list Cytokine-cytokine receptor interaction &lt; RTI ID = 0.0 &gt; 6.08E-08 1.13E-15 TNFRSF6B, CCR5, CXCR1, IL6, CXCR6, FASLG, MET, CXCL5, CXCL9, TNFRSF1B, CXCR2, CSF3R, IL2RG, TNFRSF10C, IL12RB1, CCL5, CD40, IFNG, CSF3, CD27, CCL4L2, CCL4, IL1B, IL2RA, TNFSF15, TNFRSF6B, IL1R2, CXCL3, LTB, IL21R, CXCR3, CCL18, IL2RB, TNFRSF14, CSF2RB NK cell-mediated cytotoxicity (Natural killer cell mediated cytotoxicity) 4.06E-15 7.52E-13 CD244, ITGAL, IFNG, KIR2DL4, HCST, FCER1G, FASLG, ICAM2, RAC2, LCP2, TNFRSF10C, PRF1, ITGB2, GZMB, VAV1, KIR2DS4, CD48, FCGR3B, ZAP70, KLRD1, MICB, KLRK1, LCK Hematopoietic cell lineage 1.55E-11 2.85E-09 CD3, CD3, CS3, CD3, CD3, CD3, CD3, CD3, CD3, CD3, The chemokine signaling pathway 2.44E-10 4.46E-08 CCL5, VAV1, CXCL3, CCL18, GNAI1, FGR, CXCR3, DOCK2, HCK, CCL4, NCF1, WAS, CCL4L2, ITK, CXCR1, CCR5, CXCL5, CXCR6, RAC2, CXCR2, CXCL9 T cell receptor signaling pathway 4.54E-10 8.27E-08 CD8A, PDCD1, LCK, ZAP70, CD8B, RASGRP1, CD3D, VAV1, CD3E, CD3G, LCP2, GRAP2, IFNG, PTPRC, CTLA4, ITK Primary immunodeficiency 1.07E-09 1.93E-07 PTPRC, IL2RG, CD3E, CD3D, CD40, LCK, ZAP70, CD8B, CD8A, TAP1 Cell adhesion molecules 7.06E-08 1.27E-05 CD24, CD8B, CD8A, PDCD1, SPN, ITGB2, CD2, CD40, PDCD1LG2, ICAM2, ITGB7, SELL, PTPRC, ITGAL, CTLA4 Complement and coagulation cascades 6.85E-05 1.21E-02 C4BPA, TFPI, FGA, C1QA, SERPINA1, C1QC, C1QB, FGB Toll like receptor signaling pathway &lt; RTI ID = 0.0 &gt; 2.07E-04 3.63E-02 TLR8, IL6, IL1B, CCL4, CXCL9, LBP, TLR2, CCL5, CD40

As shown in Table 2, most of the molecular biological pathways are related to the immune response, and the expression of the genes related to the immune response is significantly changed. Thereafter, gene networks were constructed using the HumanNet (Web server) and Cytoscape v.3 for the 471 genes. Specifically, the color of the gene node of the gene network is indicated by a log (fold-change) indicating the difference in the amount of gene expression, and a gene whose expression decreases in a patient group having a poor prognosis as the light blue color is darker. This indicates that the expression of the gene is increased in an unfavorable group of patients. In addition, the fact that two genes are connected to each other in a network means that they have the same function. Then, the relationship between the network and the genes shown in Table 2 was analyzed.

As a result, as shown in FIG. 2, the genes whose expression was decreased in patients with poor prognosis of ovarian cancer (blue nodes in FIG. 2) were statistically significantly connected to each other in a network (Area Under a ROC curve: 0.74, p-value: 1.15e-55). That is, since the genes shown in Table 2 are mostly genes related to the immune function, the network shown in FIG. 2 is considered to be an immune module that works for the treatment of ovarian cancer.

Example  2. Expression gene Marker  Selection

Of the genes selected in Example 1, the expression marker markers meeting the following three criteria were selected. Specifically, the statistical significance of the difference in expression was measured using the edgeR method to select genes with large differences in expression according to the patient's prognosis. A gene with a large difference in expression is a gene with a false discovery ratio less than 0.05, with fold change 2 being abnormal. The functions of the 471 genes were analyzed using the KEGG molecular biology pathway and Fisher's exact test was used for statistical significance. In addition, human functional gene analysis network was used on the web server ServerNet ( http://www.functionalnet.org/humannet/ ).

First, among the top 50 genes with the highest statistical significance, 11 genes with high membrane resistance, which are important for cell function and at the same time, are selected as preference. Second, 23 genes were selected to represent the characteristics of the immune response among the genes showing different expression in order to select not only patients suitable for standard therapy, but also patients who are expected to be suitable for immunotherapy. Third, eight genes known as immune checkpoint genes were selected. The characteristics of the 37 genes selected by the above three conditions are shown in Table 3 below. At this time, the selected genes can be satisfied by overlapping the three conditions. For example, genes such as CD274 or GZMB are genes contained within the top 50 and represent immune responses or correspond to immune checkpoint genes.

gene log (fold-change) p-value false discovery rate Characteristic AIM2 -1.83 1.68.E-04 1.19.E-02 Immune checkpoint CD2 -1.56 2.76.E-04 1.64.E-02 T cell activity CD244 -1.39 1.26.E-03 4.17.E-02 T cell activity inhibition CD27 -1.45 3.58.E-04 1.97.E-02 T cell activity CD274 -2.18 9.06.E-08 5.56.E-05 High Gene Expression, APC, T Cell Suppression CD40 -1.17 3.74.E-05 4.61.E-03 APC activity CD68 -1.10 8.10.E-04 3.29.E-02 Macrophage CD8A -2.15 7.24.E-07 2.43.E-04 CD8 + T cells CSF2RB -2.11 6.25.E-07 2.33.E-04 Upper differential gene CSF3R -2.03 3.77.E-07 1.62.E-04 Upper differential gene CTLA4 -1.53 4.98.E-04 2.42.E-02 CD4 + T cells, immune checkpoints CXCR3 -1.42 5.66.E-04 2.63.E-02 Dendritic cell EVI2B -1.13 9.02.E-04 3.42.E-02 Neutral granulocyte FOXL2 2.43 1.17.E-03 4.02.E-02 Cancer gene GZMA -1.94 2.55.E-05 3.53.E-03 Cytolytic Activity GZMB -2.45 1.99.E-07 1.09.E-04 Top gene expression difference, dendritic cell HAVCR1 -4.62 4.17.E-08 3.06.E-05 Upper differential gene IDO1 -2.51 3.75.E-06 8.44.E-04 Immune checkpoint IL1R2 -3.22 5.81.E-10 9.98.E-07 Upper differential gene IL2RA -2.24 6.36.E-07 2.33.E-04 Upper differential gene IL32 -1.27 1.72.E-04 1.20.E-02 CD4 + T cells IL6 -3.77 1.12.E-08 1.01.E-05 Upper differential gene IRF8 -1.68 1.77.E-06 4.94.E-04 Dendritic cell LAG3 -1.50 4.11.E-04 2.12.E-02 T cell inhibition LTB -3.35 1.23.E-10 3.53.E-07 Upper differential gene MNDA -1.24 3.93.E-04 2.07.E-02 Neutral granulocyte PDCD1 -1.87 1.63.E-05 2.50.E-03 Immune checkpoint PDCD1LG2 -1.55 1.74.E-04 1.20.E-02 APC Suppression PRF1 -2.19 1.09.E-06 3.42.E-04 Cytolytic Acitivity RASGRP1 -1.45 7.11.E-07 2.43.E-04 Upper differential gene SELL -1.50 1.70.E-04 1.19.E-02 Neutral granulocyte SLAMF1 -1.54 3.51.E-04 1.97.E-02 APC, T cell activity SOD2 -1.33 9.94.E-05 8.30.E-03 Upper differential gene TAP1 -1.05 4.31.E-04 2.17.E-02 MHC TIGIT -1.60 9.49.E-05 8.21.E-03 T cell inhibition, immune checkpoint TNFRSF6B -3.53 1.64.E-12 2.82.E-08 Upper differential gene TNFSF15 -1.51 9.55.E-04 3.56.E-02 APC Suppression

Thus, through the profiling of gene markers selected by a screening method of one aspect, the therapeutic prognosis of ovarian cancer patients can be effectively predicted.

It will be understood by those skilled in the art that the foregoing description of the present invention is for illustrative purposes only and that those of ordinary skill in the art can readily understand that various changes and modifications may be made without departing from the spirit or essential characteristics of the present invention. will be. It is therefore to be understood that the above-described embodiments are illustrative in all aspects and not restrictive.

Claims (1)

A composition for measuring the mRNA or protein expression level of CD274, CSF2RB, CSF3R, GZMB, HAVCR1, IL1R2, IL2RA, IL6, LTB, RASGRP1, SOD2 and TNFRSF6B.

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