KR102016216B1 - Biomarker for predicting prognosis of gastric cancer and use thereof - Google Patents

Abstract

The present invention relates to a biomarker for predicting the prognosis of gastric cancer and its use. More specifically, the marker gene which can predict the poor prognosis according to mesenchymal gastric cancer by dividing gastric cancer into mesenchymal / non-mesenchymal subtypes, It relates to a composition and kit for predicting gastric cancer prognosis comprising an agent for measuring expression level, and to a method for predicting prognosis using the marker. Biomarker for predicting prognosis of gastric cancer according to the present invention can determine the mesenchymal status of gastric cancer by measuring the expression level of the marker gene, through which recurrence, metastasis, low survival rate, and short survival of mesenchymal gastric cancer It can be used to anticipate poor prognosis and to apply more appropriate treatment from the beginning of diagnosis. In addition, the marker for predicting gastric cancer prognosis of the present invention can check the expression level by nanostring encounter analysis using a storage tissue such as paraffin embedded tissue of gastric cancer patients, thus having a convenience that does not require separate sampling and thus is usefully used. Could be.

Description

Biomarker for predicting prognosis of gastric cancer and use about

The present invention relates to a biomarker for predicting the prognosis of gastric cancer and its use. More specifically, the present invention relates to a marker gene capable of predicting the prognosis according to mesenchymal gastric cancer by determining whether the gastric cancer is mesenchymal. It relates to a composition and kit for predicting gastric cancer prognosis, and a method for predicting prognosis using the marker.

Gastric cancer (GC) is one of the most common malignancies in the world and is known as the third leading cause of death from cancer. In addition, most gastric cancer patients are in the advanced stage and most have been reported to have a very poor prognosis. In metastatic gastric cancer, platinum-based combination chemotherapy is considered a standard treatment, but many patients are refractory to such treatment, and even patients who respond are known to have a short response time of several months. In addition, clinical trials of novel target drugs, with the exception of trastuzumab and ramucirumab as the second therapeutic agent in human epidermal growth factor receptor 2 (EGFR2) positive tumor patients, There was no successful treatment for gastric cancer. The reason for the low survival rate in gastric cancer is that gastric cancer is a heterogeneous disease with significantly different aggressiveness and responsiveness to therapy, and the clinical results and prognosis in each patient do not always agree with the reported data. Cancer subtypes with different prognosis and therapeutic effects in chemotherapy allow patients to receive the most appropriate treatment, thereby avoiding toxicity associated with unnecessary treatment and ultimately improving the overall treatment outcome.

Most recently, molecularly defined types of gastric cancer have been reported in the field of gastric cancer. The Asia Cancer Research Group (ACRG) has established a non-profit cooperative group of pharmaceutical industry, academic medical centers and sequencing companies to characterize gastric cancer subtypes. As a result, the Asian Cancer Research Group has published four types of gastric cancer subtypes: 1) stomach cancer with microsatellite instability (MSI subtype); 2) gastric cancer (MSS / EMT subtype) showing microsatellite stability (MSS) and epithelial mesenchymal transition (EMT); 3) gastric cancer with p53 characteristics (CDKN1A and MDM2 expression) (MSS / TP53 + subtype); Or 4) gastric cancer that does not show p53 characteristics (MSS / TP53-subtype). Among the four types of gastric cancer subtypes, MSS / EMT is significantly higher in recurrence rate, more likely to develop peritoneal metastasis at the first site of recurrence, and is diagnosed and diagnosed at a younger age. Low survival rates have been reported (Nat Med 21: 449-456, 2015). Moreover, the relapse leading to death has reduced the survival curve by more than five years.

Mesenchymal gastric cancer, meanwhile, refers to gastric cancer that has a poor prognosis and refractory to conventional chemotherapy, and is likely to fail in most clinical trials. For this reason, patients with mesenchymal gastric cancer can be isolated and conducted in separate clinical trials or excluded from other clinical trials to improve the accuracy and success of each clinical trial. Therefore, it is necessary to develop a method for confirming whether or not mesenchymal is clinically significant and to develop a treatment for improving survival rate of mesenchymal gastric cancer patients.

The present inventors completed the present invention by identifying a biomarker for judging the mesenchymal status of gastric cancer so as to distinguish the mesenchymal / non-mesenchymal gastric cancer in advance and predict the bad prognosis of the mesenchymal gastric cancer in advance. .

Accordingly, an object of the present invention is to provide a marker composition for predicting the prognosis of gastric cancer that can determine mesenchymal gastric cancer.

The present invention also provides a composition for predicting gastric cancer prognosis, comprising a composition for measuring mRNA level of the marker gene or a protein encoded by the gene, a kit for predicting gastric cancer prognosis including the composition, and providing information for prognostic prediction. It is another object to provide a method.

However, the technical problem to be achieved by the present invention is not limited to the above-mentioned problem, another task that is not mentioned will be clearly understood by those skilled in the art from the following description.

In order to achieve the object of the present invention as described above, the present invention is ADAM23 (A disintegrin and metalloprotease domain-containing protein 23, NCBI accession number: NM_003812), ADAMTS1 (A disintegrin and metalloproteinase with thrombospondin motifs 1, NM_006988. 3), AKAP12 (A-kinase anchor protein 12, NM_005100.3), ALPK2 (Alpha Kinase 2, NM_052947), AP1S2 (Adaptor Related Protein Complex 1 Sigma 2, NM_003916), ARMCX1 (Armadillo Repeat Containing, X-Linked 1, NM_016608), Tyrosine-protein kinase receptor UFO, NM_021913.2), BICC1 (BicC Family RNA Binding Protein 1, NM_001080512.1), BNC2 (Basonuclin 2, NM_017637.5), C16orf45 (Chromosome 16 Open Reading Frame 45, NM_033201), C1S (complement C1s subcomponent, NM_001734.2), CLDN11 (Claudin 11, NM_005602), CMTM3 (CKLF-like MARVEL transmembrane domain-containing protein 3, NM_181555), CTGF (Connective Tissue Growth Factor, NM_001901), CYBRD1 (CYBRD1) Cytochrome B Reductase 1, NM_024843), DIO2 (Type II iodothyronine deiodinase, NM_013989), DKK3 (Dic kkopf WNT Signaling Pathway Inhibitor 3, NM_015881), DOCK10 (dedicator of cytokinesis 10, NM_017718), DPYSL3 (Dihydropyrimidinase-related protein 3, NM_001387.2), EML1 (Echinoderm Microtubule Associated Protein Like 1, NM_004434), EVI2A Integration (Ecotropic) Site 2A, NM_014210.3), FAM101B (Family With Sequence Similarity 101 Member B, NM_182705), FAT4 (FAT Atypical Cadherin 4, NM_024582), FGF2 (Fibroblast Growth Factor 2, NM_002006.4), FGFR1 (Fibroblast Growth Factor Receptor 1 , NM_015850.2), FHL1 (Four And A Half LIM Domains 1, NM_001449.4), FLRT2 (Fibronectin Leucine Rich Transmembrane Protein 2, NM_013231), FSTL1 (Follistatin Like 1, NM_007085.4), GLIPR1 (GLI Pathogenesis Related 1 , NM_006851), GNB4 (G Protein Subunit Beta 4, NM_021629), GNG11 (G Protein Subunit Gamma 11, NM_004126), HEG1 (Heart Development Protein With EGF Like Domains 1, NM_020733.1), IGFBP7 (Insulin Like Growth Factor Binding Protein 7, NM_001553.1), JAM3 (Junctional Adhesion Molecule 3, NM_032801.3), LEPREL1 (Leprecan-Like 1, NM_001001530), LHFP (lipoma HMGIC fusion partner, NM_005780.2), MAP1B ((Microtubule Associated Protein 1B, NM_032010), MMP2 (matrix metalloproteinase-2, NM_004530.2), MRAS (Muscle RAS, NM_012219), MSRB3 ( Methionine Sulfoxide Reductase B3, NM_198080), Nucleosome Assembly Protein 1 Like 3, NM_002487, NEGR1 (Neuronal Growth Regulator 1, NM_173808), NEXN (Nexilin F-Actin Binding Protein, NM_144573), NID1 (Nidogen 1, NM_002) PLAGL1 (PLAG1 Like Zinc Finger 1, NM_006718), PMP22 (Peripheral Myelin Protein 22, NM_000304.2), PRKD1 (Protein Kinase D1, NM_002742), PTGIS (Prostaglandin I2, NM_000961.3), RBMS3 (RNA Binding Motifing Single Stranded) Protein 3, NM_014483), RECK (Reversion Inducing Cysteine Rich Protein With Kazal Motifs, NM_021111), RFTN1 (Raftlin, Lipid Raft Linker 1, NM_015150), SRPX (Sushi Repeat Containing Protein, NM_006307), TCF4 (Transcription Factor 4, NM_003199. 1), TMEM47 (Transmembrane Protein 47, NM_031442), TTC28 (Tetratricopeptide Repeat Domain 28, NM_015281), UCHL1 (Ubi quitin C-Terminal Hydrolase L1, NM_004181), VIM (Vimentin, NM_003380.2), ZEB1 (Zinc Finger E-Box Binding Homeobox 1, NM_001128128.1), ZEB2 (Zinc Finger E-Box Binding Homeobox 2, NM_014795.3) , ZFPM2 (Zinc Finger Protein, FOG Family Member 2, NM_012082.3), C19orf21 (chromosome 19 open reading frame 21, NM_173481.2), CLDN4 (Claudin 4, NM_001305.3), CLDN7 (Claudin 7, NM_001307.3) , DSC2 (Desmocollin 2, NM_024422.3), GOLT1A (Golgi Transport 1A, NM_198447), LIPG (Lipase G, NM_006033), MAP7 (Microtubule Associated Protein 7, NM_003980), PAK6 (P21-Activated Kinase 6, NM_020168), PKP3 Gastric cancer prognosis, including (Plakophilin 3, NM_007183), SH2D3A (SH2 domain-containing protein 3A, NM_005490.2), and SPINT1 (Serine Peptidase Inhibitor, Kunitz Type 1, NM_001032367.1) gene or protein encoded by the gene Provided is a marker composition for prediction.

The present invention also provides a composition for predicting gastric cancer prognosis and a kit for predicting gastric cancer prognosis comprising the composition comprising an agent for measuring the mRNA level of the gene or the protein encoded by the gene.

In one embodiment of the present invention, the gastric cancer may be mesenchymal subtype gastric cancer.

In another embodiment of the invention, the agent for measuring the mRNA level of the gene may be a sense and antisense primer, or probe that complementarily binds to the mRNA of the gene.

In another embodiment of the invention, the agent for measuring the protein level may be an antibody that specifically binds to the protein encoded by the gene.

In addition, the present invention is a disintegrin and metalloprotease domain-containing protein 23, NCBI accession number: NM_003812, ADAMTS1 (A disintegrin and metalloproteinase with thrombospondin motifs 1, NM_006988.3), AKAP12 (A-kinase anchor protein 12, NM_005100.3), ALPK2 (Alpha Kinase 2, NM_052947), AP1S2 (Adaptor Related Protein Complex 1 Sigma 2, NM_003916), ARMCX1 (Armadillo Repeat Containing, X-Linked 1, NM_016608), AXL (Tyrosine-protein kinase receptor UFO, NM_021913.2), BICC1 (BicC Family RNA Binding Protein 1, NM_001080512.1), BNC2 (Basonuclin 2, NM_017637.5), C16orf45 (Chromosome 16 Open Reading Frame 45, NM_033201), C1S (complement C1s subcomponent, NM_001734.2), CLDN11 (Claudin 11, NM_005602), CMTM3 (CKLF-like MARVEL transmembrane domain-containing protein 3, NM_181555), CTGF (Connective Tissue Growth Factor, NM_001901), CYBRD1 (Cytochrome B Reductase 1 , NM_024843), DIO2 (Type II iodothyronine deiodinase, NM_013989), DKK3 (Dickkopf WNT S ignaling Pathway Inhibitor 3, NM_015881), DOCK10 (dedicator of cytokinesis 10, NM_017718), DPYSL3 (Dihydropyrimidinase-related protein 3, NM_001387.2), EML1 (Echinoderm Microtubule Associated Protein Like 1, NM_004434), EVI2A (Ecotropic Viral Integration) , NM_014210.3), FAM101B (Family With Sequence Similarity 101 Member B, NM_182705), FAT4 (FAT Atypical Cadherin 4, NM_024582), FGF2 (Fibroblast Growth Factor 2, NM_002006.4), FGFR1 (Fibroblast Growth Factor Receptor 1, NM_015850 .2), FHL1 (Four And A Half LIM Domains 1, NM_001449.4), FLRT2 (Fibronectin Leucine Rich Transmembrane Protein 2, NM_013231), FSTL1 (Follistatin Like 1, NM_007085.4), GLIPR1 (GLI Pathogenesis Related 1, NM_006851 ), GNB4 (G Protein Subunit Beta 4, NM_021629), GNG11 (G Protein Subunit Gamma 11, NM_004126), HEG1 (Heart Development Protein With EGF Like Domains 1, NM_020733.1), IGFBP7 (Insulin Like Growth Factor Binding Protein 7, NM_001553.1), JAM3 (Junctional Adhesion Molecule 3, NM_032801.3), LEPREL1 (Leprecan-Like 1, NM_0010 01530), LHFP (lipoma HMGIC fusion partner, NM_005780.2), MAP1B (Microtubule Associated Protein 1B, NM_032010), MMP2 (matrix metalloproteinase-2, NM_004530.2), MRAS (Muscle RAS, NM_012219), MSRB3 (Methionine Sulfoxide) Reductase B3, NM_198080), Nucleosome Assembly Protein 1 Like 3, NM_002487, NEGR1 (Neuronal Growth Regulator 1, NM_173808), NEXN (Nexilin F-Actin Binding Protein, NM_144573), NID1 (Nidogen 1, NM_002508), PLAGL1 (N PLAG1 Like Zinc Finger 1, NM_006718), PMP22 (Peripheral Myelin Protein 22, NM_000304.2), PRKD1 (Protein Kinase D1, NM_002742), PTGIS (Prostaglandin I2, NM_000961.3), RBMS3 (RNA Binding Motif Single Stranded Interacting Protein 3) , NM_014483), RECK (Reversion Inducing Cysteine Rich Protein With Kazal Motifs, NM_021111), RFTN1 (Raftlin, Lipid Raft Linker 1, NM_015150), SRPX (Sushi Repeat Containing Protein, NM_006307), TCF4 (Transcription Factor 4, NM_003199.1) , TMEM47 (Transmembrane Protein 47, NM_031442), TTC28 (Tetratricopeptide Repeat Domain 28, NM_015281), UCHL1 (Ubiquitin C-Te rminal Hydrolase L1, NM_004181), VIM (Vimentin, NM_003380.2), ZEB1 (Zinc Finger E-Box Binding Homeobox 1, NM_001128128.1), ZEB2 (Zinc Finger E-Box Binding Homeobox 2, NM_014795.3), ZFPM2 ( Zinc Finger Protein, FOG Family Member 2, NM_012082.3), C19orf21 (chromosome 19 open reading frame 21, NM_173481.2), CLDN4 (Claudin 4, NM_001305.3), CLDN7 (Claudin 7, NM_001307.3), DSC2 ( Desmocollin 2, NM_024422.3), GOLT1A (Golgi Transport 1A, NM_198447), LIPG (Lipase G, NM_006033), MAP7 (Microtubule Associated Protein 7, NM_003980), PAK6 (P21-Activated Kinase 6, NM_020168), PKP3 (Plakophilin , NM_007183), SH2D3A (SH2 domain-containing protein 3A, NM_005490.2), and SPINT1 (Serine Peptidase Inhibitor, Kunitz Type 1, NM_001032367.1) gene or measuring the level of protein encoded by the gene. To provide a method for providing information for gastric cancer prognosis prediction.

In one embodiment of the present invention, the ADAM23, ADAMTS1, AKAP12, ALPK2, AP1S2, ARMCX1, AXL, BICC1, BNC2, C16orf45, C1S, CLDN11, CMTM3, CTGF, CYBRD1, DIO2, DKK3, DOCK10, DPYSL3, EML , FAM101B, FAT4, FGF2, FGFR1, FHL1, FLRT2, FSTL1, GLIPR1, GNB4, GNG11, HEG1, IGFBP7, JAM3, LEPREL1, LHFP, MAP1B, MMP2, MRAS, MSRB3, NDN, NEGR1, NEX22, NEXNGL , MRNA of PRKD1, PTGIS, RBMS3, RECK, RFTN1, SRPX, TCF4, TMEM47, TTC28, UCHL1, VIM, ZEB1, ZEB2, and ZFPM2 genes or gastric cancer patients with known prognostic expression levels If the expression level of the mRNA or protein of the gene is higher than the prognosis can be judged to be poor.

In another embodiment of the present invention, the gastric cancer patient whose expression level of the C19orf21, CLDN4, CLDN7, DSC2, GOLT1A, LIPG, MAP7, PAK6, PKP3, SH2D3A, and the protein of the gene encoding SPINT1 is known If the expression level of the mRNA or protein of the gene is lower than the prognosis may be judged to be poor.

In another embodiment of the invention, the biological sample may be gastric tumor tissue.

In another embodiment, the expression level of the mRNA is NanoString nCounter analysis (NanoString nCounter analysis), polymerase chain reaction (PCR), reverse transcription polymerase chain reaction (RT-PCR), real-time polymerase chain reaction (Real-time PCR), RNase protection assay (RPA), microarray, and northern blotting can be measured by one or more methods selected from the group consisting of.

In another embodiment of the present invention, the protein expression level is Western blotting, radioimmunoassay (RIA), radioimmunodiffusion, enzyme immunoassay (ELISA), immunoprecipitation (immunoprecipitation) ), Flow cytometry, immunofluorescence, ouchterlony, complement fixation assay, and protein chip. It can be measured through.

In another embodiment of the invention, the prognosis may be relapse, metastasis, drug resistance, survival, or disease free survival.

Biomarker for predicting prognosis of gastric cancer according to the present invention can determine the mesenchymal status of gastric cancer by measuring the expression level of the marker gene, through which recurrence, metastasis, low survival rate, and short survival of mesenchymal gastric cancer It can be used to anticipate poor prognosis and to apply more appropriate treatment from the beginning of diagnosis. In addition, the marker for predicting gastric cancer prognosis of the present invention can confirm the expression level by using a nanostring encoder analysis using a storage tissue such as paraffin embedded tissue of gastric cancer patients, and thus has no convenience of collecting additional samples. May be used.

1 depicts an experimental protocol for discovering and validating gene signatures for mesenchymal subtypes of gastric cancer.
FIG. 2 shows the results of analyzing the correspondence between test subtypes classified according to gene expression profiling results through Affymetrix microarrays and mesenchymal subtypes classified according to nanostring results.
FIG. 3A shows the overall survival of ARTIST patients (n = 73) according to nanostring mesenchymal scores, and FIG. 3B shows overall of all patients (ARTIST / ACRG cohort synthesis) (n = 143) according to nanostring mesenchymal scores. The result shows survival rate.

The present inventors completed the present invention by discovering a biomarker that can determine the mesenchymal properties of gastric cancer known to have a poor prognosis.

Accordingly, the present invention provides a disintegrin and metalloprotease domain-containing protein 23, NCBI accession number: NM_003812, ADAMTS1 (A disintegrin and metalloproteinase with thrombospondin motifs 1, NM_006988.3), and AKAP12 (A-kinase anchor protein). 12, NM_005100.3), ALPK2 (Alpha Kinase 2, NM_052947), AP1S2 (Adaptor Related Protein Complex 1 Sigma 2, NM_003916), ARMCX1 (Armadillo Repeat Containing, X-Linked 1, NM_016608), Tyrosine-protein kinase receptor UFO, NM_021913.2), BICC1 (BicC Family RNA Binding Protein 1, NM_001080512.1), BNC2 (Basonuclin 2, NM_017637.5), C16orf45 (Chromosome 16 Open Reading Frame 45, NM_033201), C1S (complement C1s subcomponent, NM_001734 .2), CLDN11 (Claudin 11, NM_005602), CMTM3 (CKLF-like MARVEL transmembrane domain-containing protein 3, NM_181555), CTGF (Connective Tissue Growth Factor, NM_001901), CYBRD1 (Cytochrome B Reductase 1, NM_024843), DIO2 ( Type II iodothyronine deiodinase, NM_013989), DKK3 (Dickkopf WNT Signaling Pathway Inhibitor 3, NM_015881), DOCK 10 (dedicator of cytokinesis 10, NM_017718), DPYSL3 (Dihydropyrimidinase-related protein 3, NM_001387.2), EML1 (Echinoderm Microtubule Associated Protein Like 1, NM_004434), EVI2A (Ecotropic Viral Integration Site 2A, NM_014210.3), FAM101B ( Family With Sequence Similarity 101 Member B, NM_182705), FAT Atypical Cadherin 4, NM_024582), FGF2 (Fibroblast Growth Factor 2, NM_002006.4), FGFR1 (Fibroblast Growth Factor Receptor 1, NM_015850.2), FHL1 (Four And A Half LIM Domains 1, NM_001449.4), FLRT2 (Fibronectin Leucine Rich Transmembrane Protein 2, NM_013231), FSTL1 (Follistatin Like 1, NM_007085.4), GLIPR1 (GLI Pathogenesis Related 1, NM_006851), GNB4 (G Protein Subunit Beta 4, NM_021629), GNG11 (G Protein Subunit Gamma 11, NM_004126), HEG1 (Heart Development Protein With EGF Like Domains 1, NM_020733.1), IGFBP7 (Insulin Like Growth Factor Binding Protein 7, NM_001553.1), JAM3 (Junctional Adhesion Molecule 3, NM_032801.3), LEPREL1 (Leprecan-Like 1, NM_001001530), LHFP (lipoma HMGIC fusion partner, NM_0 05780.2), MAP1B (Microtubule Associated Protein 1B, NM_032010), MMP2 (matrix metalloproteinase-2, NM_004530.2), MRAS (Muscle RAS, NM_012219), MSRB3 (Methionine Sulfoxide Reductase B3, NM_198080), NDN (Nucleosome Assembly Protein Like 3, NM_002487), NEGR1 (Neuronal Growth Regulator 1, NM_173808), NEXN (Nexilin F-Actin Binding Protein, NM_144573), NID1 (Nidogen 1, NM_002508), PLAGL1 (PLAG1 Like Zinc Finger 1, NM_006718), PMP22 (Peripheral Myelin Protein 22, NM_000304.2), PRKD1 (Protein Kinase D1, NM_002742), PTGIS (Prostaglandin I2, NM_000961.3), RBMS3 (RNA Binding Motif Single Stranded Interacting Protein 3, NM_014483), RECK (Reversion Inducing Cysteine Rich Protein With Kazal Motifs, NM_021111), RFTN1 (Raftlin, Lipid Raft Linker 1, NM_015150), SRPX (Sushi Repeat Containing Protein, NM_006307), TCF4 (Transcription Factor 4, NM_003199.1), TMEM47 (Transmembrane Protein 47, NM_031442), TTC Tetratricopeptide Repeat Domain 28, NM_015281), UCHL1 (Ubiquitin C-Terminal Hydrolase L1, NM_004181), VIM (Vimentin, NM_003380.2), ZEB1 (Zinc Finger E-Box Binding Homeobox 1, NM_001128128.1), ZEB2 (Zinc Finger E-Box Binding Homeobox 2, NM_014795.3), ZFPM2 (Zinc Finger Protein, FOG Family Member 2, NM_012082. 3), C19orf21 (chromosome 19 open reading frame 21, NM_173481.2), CLDN4 (Claudin 4, NM_001305.3), CLDN7 (Claudin 7, NM_001307.3), DSC2 (Desmocollin 2, NM_024422.3), GOLT1A (Golgi Transport 1A, NM_198447), LIPG (Lipase G, NM_006033), MAP7 (Microtubule Associated Protein 7, NM_003980), PAK6 (P21-Activated Kinase 6, NM_020168), PKP3 (Plakophilin 3, NM_007183), SH2D3A (SH2 domain-containing protein 3A, NM_005490.2), and SPINT1 (Serine Peptidase Inhibitor, Kunitz Type 1, NM_001032367.1) gene or a protein encoding the gene provides a marker composition for predicting gastric cancer prognosis.

The present invention also provides a composition for predicting gastric cancer prognosis comprising an agent for measuring the mRNA level of the gene or a protein encoded by the gene and a kit for predicting gastric cancer prognosis comprising the composition.

As used herein, the term “gastric cancer” is a malignant tumor occurring in the stomach, and includes gastric adenocarcinoma of the gastric mucosa and malignant lymphoma, muscle sarcoma, and interstitial tumor occurring in the submucosa, but usually refers to gastric adenocarcinoma. . In the present invention, gastric cancer more preferably means mesenchymal gastric cancer which may exhibit a poor prognosis such as high recurrence rate, metastasis, low survival rate, and short survival time.

Agents for measuring mRNA levels of the gene may be, but are not limited to, sense and antisense primers, or probes that bind complementarily to mRNA.

As used herein, the term “primer” refers to an oligonucleotide synthesized for use in diagnosis, DNA sequencing and the like as a short gene sequence that is a starting point for DNA synthesis. The primers can be synthesized in a conventional length of 15 to 30 base pairs, but may vary depending on the purpose of use, and may be modified by methylation, capping, or the like by a known method.

As used herein, the term “probe” refers to a nucleic acid capable of specifically binding to mRNA of several to several hundred bases in length, which has been produced through enzymatic chemical separation or purification. Radioisotopes, enzymes, or phosphors can be labeled to confirm the presence or absence of mRNA and can be designed and modified by known methods.

The agent for measuring the protein level may be an antibody that specifically binds to a protein encoded by a gene, but is not limited thereto.

As used herein, the term “antibody” includes immunoglobulin molecules that are immunologically reactive with specific antigens, and include both monoclonal and polyclonal antibodies. In addition, such antibodies include forms produced by genetic engineering such as chimeric antibodies (eg, humanized murine antibodies) and heterologous antibodies (eg, bispecific antibodies).

The kit for predicting prognosis of the present invention may be composed of one or more other component compositions, solutions or devices suitable for analytical methods.

In another embodiment of the present invention, the present invention provides a disintegrin and metalloprotease domain-containing protein 23, NCBI accession number: NM_003812, A disintegrin and metalloproteinase with thrombospondin motifs 1, NM_006988 .3), AKAP12 (A-kinase anchor protein 12, NM_005100.3), ALPK2 (Alpha Kinase 2, NM_052947), AP1S2 (Adaptor Related Protein Complex 1 Sigma 2, NM_003916), ARMCX1 (Armadillo Repeat Containing, X-Linked 1 , NM_016608), Tyrosine-protein kinase receptor UFO, NM_021913.2), BICC1 (BicC Family RNA Binding Protein 1, NM_001080512.1), BNC2 (Basonuclin 2, NM_017637.5), C16orf45 (Chromosome 16 Open Reading Frame 45 , NM_033201), C1S (complement C1s subcomponent, NM_001734.2), CLDN11 (Claudin 11, NM_005602), CMTM3 (CKLF-like MARVEL transmembrane domain-containing protein 3, NM_181555), CTGF (Connective Tissue Growth Factor, NM_001901), CYBRD1 (Cytochrome B Reductase 1, NM_024843), DIO2 (Type II iodothyronine deiodinase, NM_0 13989), DKK3 (Dickkopf WNT Signaling Pathway Inhibitor 3, NM_015881), DOCK10 (dedicator of cytokinesis 10, NM_017718), DPYSL3 (Dihydropyrimidinase-related protein 3, NM_001387.2), EML1 (Echinoderm Microtubule Associated Protein Like 1, NM_004 EVI2A (Ecotropic Viral Integration Site 2A, NM_014210.3), FAM101B (Family With Sequence Similarity 101 Member B, NM_182705), FAT4 (FAT Atypical Cadherin 4, NM_024582), FGF2 (Fibroblast Growth Factor 2, NM_002006.4), FGFR1 ( Fibroblast Growth Factor Receptor 1, NM_015850.2), FHL1 (Four And A Half LIM Domains 1, NM_001449.4), FLRT2 (Fibronectin Leucine Rich Transmembrane Protein 2, NM_013231), FSTL1 (Follistatin Like 1, NM_007085.4), GLIPR1 (GLI Pathogenesis Related 1, NM_006851), GNB4 (G Protein Subunit Beta 4, NM_021629), GNG11 (G Protein Subunit Gamma 11, NM_004126), HEG1 (Heart Development Protein With EGF Like Domains 1, NM_020733.1), IGFBP7 (Insulin Like Growth Factor Binding Protein 7, NM_001553.1), JAM3 (Junctional Adhesion Molecule 3, NM_032801.3), LEPRE L1 (Leprecan-Like 1, NM_001001530), LHFP (lipoma HMGIC fusion partner, NM_005780.2), MAP1B ((Microtubule Associated Protein 1B, NM_032010), MMP2 (matrix metalloproteinase-2, NM_004530.2), MRAS (Muscle RAS, NM_012219), MSRB3 (Methionine Sulfoxide Reductase B3, NM_198080), NDN (Nucleosome Assembly Protein 1 Like 3, NM_002487), NEGR1 (Neuronal Growth Regulator 1, NM_173808), NEXN (Nexilin F-Actin Binding Protein, NM_144573) 1, NM_002508), PLAGL1 (PLAG1 Like Zinc Finger 1, NM_006718), PMP22 (Peripheral Myelin Protein 22, NM_000304.2), PRKD1 (Protein Kinase D1, NM_002742), PTGIS (Prostaglandin I2, NM_000961.3), RBMS3 (RNA Binding Motif Single Stranded Interacting Protein 3, NM_014483), RECK (Reversion Inducing Cysteine Rich Protein With Kazal Motifs, NM_021111), RFTN1 (Raftlin, Lipid Raft Linker 1, NM_015150), SRPX (Sushi Repeat Containing Protein, NM_006307), TCF4 (T Factor 4, NM_003199.1), TMEM47 (Transmembrane Protein 47, NM_031442), TTC28 (Tetratricopeptide Repeat Domain 28, NM_01 5281), UCHL1 (Ubiquitin C-Terminal Hydrolase L1, NM_004181), VIM (Vimentin, NM_003380.2), ZEB1 (Zinc Finger E-Box Binding Homeobox 1, NM_001128128.1), ZEB2 (Zinc Finger E-Box Binding Homeobox 2 , NM_014795.3), ZFPM2 (Zinc Finger Protein, FOG Family Member 2, NM_012082.3), C19orf21 (chromosome 19 open reading frame 21, NM_173481.2), CLDN4 (Claudin 4, NM_001305.3), CLDN7 (Claudin 7 , NM_001307.3), DSC2 (Desmocollin 2, NM_024422.3), GOLT1A (Golgi Transport 1A, NM_198447), LIPG (Lipase G, NM_006033), MAP7 (Microtubule Associated Protein 7, NM_003980), PAK6 (P21-Activated Kinase 6 , NM_020168), PKP3 (Plakophilin 3, NM_007183), SH2D3A (SH2 domain-containing protein 3A, NM_005490.2), and SPINT1 (Serine Peptidase Inhibitor, Kunitz Type 1, NM_001032367.1) genes or encoded by the gene It provides an information providing method for predicting the prognosis of gastric cancer, comprising measuring protein levels.

In the present invention, the ADAM23, ADAMTS1, AKAP12, ALPK2, AP1S2, ARMCX1, AXL, BICC1, BNC2, C16orf45, C1S, CLDN11, CMTM3, CTGF, CYBRD1, DIO2, DKK3, DOCK10, DPYSL3, EML1, EVI2, EVI2, EVI2 FAT4, FGF2, FGFR1, FHL1, FLRT2, FSTL1, GLIPR1, GNB4, GNG11, HEG1, IGFBP7, JAM3, LEPREL1, LHFP, MAP1B, MMP2, MRAS, MSRB3, NDN, NEGR1, NEXN, NID1, PLAGL1RK MRNA of PTGIS, RBMS3, RECK, RFTN1, SRPX, TCF4, TMEM47, TTC28, UCHL1, VIM, ZEB1, ZEB2, and ZFPM2 genes or mRNAs of corresponding genes of gastric cancer patients whose prognosis is known Or if the expression level of the protein is higher than the prognosis can be judged to be poor.

In addition, in the present invention, the expression level of the mRNA of the C19orf21, CLDN4, CLDN7, DSC2, GOLT1A, LIPG, MAP7, PAK6, PKP3, SH2D3A, and SPINT1 gene or protein encoded by the gene is known to the corresponding cancer patients If the expression level of the mRNA or protein of the gene is lower than the prognosis may be judged to be poor.

As used herein, the term “information rice method for predicting gastric cancer prognosis” means providing objective basic information necessary for predicting the prognosis of gastric cancer as a preliminary step for predicting prognosis, and more preferably, the gastric cancer is mesenchymal. (mesenchymal) gastric cancer, except the doctor's clinical judgment or findings.

The term "prognosis" used in the present invention may mean, but is not limited to, recurrence, metastasis, drug resistance, survival, or disease-free survival of gastric cancer.

In the present invention, the biological sample may be gastric tumor tissue, and more preferably, gastric tumor tissue embedded in paraffin by fixation with a fixed solution such as formalin, but is not limited thereto.

The expression level of the mRNA according to conventional methods known in the art NanoString nCounter analysis (NanoString nCounter analysis), polymerase chain reaction (PCR), reverse transcription polymerase chain reaction (RT-PCR), real-time polymerase chain reaction (Real-time PCR), RNase protection assay (RPA), microarray, and northern blotting can be measured by one or more methods selected from the group consisting of Preferably, it may be measured by nanostring encoder analysis, but is not limited thereto.

The protein expression level is Western blotting, radioimmunoassay (RIA), radioimmunodiffusion, enzyme-linked immunoassay (ELISA), immunoprecipitation (immunoprecipitation) according to conventional methods known in the art ), Flow cytometry, immunofluorescence, ouchterlony, complement fixation assay, and protein chip. It may be measured through, but is not limited thereto.

The present inventors found 71 biomarker genes that can predict the prognosis of gastric cancer patients by determining the mesenchymal status of gastric cancer, and verified the effectiveness thereof.

In one embodiment of the present invention, a concordance analysis between Affymetrix microarray gene expression analysis of 70 tissue samples randomly selected from the Asian Cancer Research Group (ACRG) cohort and gene expression levels on a nanostring platform containing 584 genes Finally, 71 biomarker genes (60 genes with increased expression and 11 genes with reduced expression) were derived. Further, the case of EMT / MSS, which is a known molecular subtype in the ACRG cohort, was examined using the Affymetrix method, and it was confirmed that the results were almost identical to the results of nanostring analysis using the 71 biomarkers derived above (Example 2).

In another embodiment of the present invention, mesenchymal subtypes were predicted using the highest quartiles of the mesenchymal signatures of the 71 biomarker genes of the present invention in 73 samples of the ARTIST cohort. Gastric cancer patients of lobe subtypes were found to have significantly lower survival compared to patients with non-mesenchymal subtypes of the cohort, and confirmed that overall survival was significantly shorter in patients with mesenchymal subtypes (see Example 3). ).

The results of the present embodiment confirmed the effectiveness of 71 biomarkers. Therefore, the biomarker can be used to diagnose mesenchymal gastric cancer, a subtype of gastric cancer, and to predict the prognosis of patients by judging whether or not such mesenchymal gastric cancer is present. It can be usefully used.

Hereinafter, preferred examples are provided to aid in understanding the present invention. However, the following examples are merely provided to more easily understand the present invention, and the contents of the present invention are not limited by the following examples.

EXAMPLE

Example 1 Experiment Preparation and Experiment Method

1-1. Gastric cancer patient selection

The Asian Cancer Research Group (ACRG) cohort, consisting of 300 primary gastric cancer specimens, was used during the healing or conventional gastrectomy at Samsung Medical Center, Seoul, Korea between 2004 and 2007. Were collected and cryopreserved at -80 ° C. The protocol was reviewed and approved by Samsung Medical Center Institutional Review Board (IRB No. 2010-12-088), and the purpose and characteristics of the study for all subjects. The experiment was conducted after providing information on and receiving written consent. Subjects were selected according to the following criteria: 1) histologically adenocarcinoma of the stomach, 2) surgical resection of primary gastric cancer, 3) 18 years of age and older, 4) complete pathological, surgical, Therapeutic and survival tracking data present. The primary gastric cancer tissue was used for genomic analysis. More specifically, 70 tumor samples were randomly selected according to the usefulness of tissue samples among 300 subjects. For validation, 73 patients were selected from the ARTIST cohort, a phase 3 adjuvant chemoradiotherapy out of 458 gastric cancer patients, and tissue samples were used for RNA extraction. All tumor samples in the two cohorts were prepared as primary surgical samples. The clinical characteristics of the patients are summarized in Table 1 below, and all of them were Korean.

ACRG (N = 70) ARTIST (N = 73) Age, years
Median
Range
63
25-78
51
35-76 Gender
Male
Female
51
19
46
27 Tumor stage
1-2
3-4
16
54
36
37 Lauren classification
Intestinal
Diffuse
Mixed or not available
27
36
7
15
53
5 MSI high 19 (27%) 7 (15%) Mesenchymal subtype 13 (19%) 20 (27%)

1-2. RNA extraction

Hematoxylin & eosin (H & E) staining was performed on one tumor section per patient, and the extent of tumor distribution was assessed by a pathologist. Excluded from

For extracting RNA from tumor tissues, the RNeasy FFPE Extraction kit (Qiagen, Hilden, Germany) or the QIAamp DNA Mini Kit (Qiagen) can be used for formalin-fixed paraffin-embedded tissue sections cut to 2 x 5 μm thickness or for frozen stored live tissue samples. RNA was extracted according to the manufacturer's protocol. Subsequently, using a Broad Range RNA kit, Qubit 2.0 Flourometer was used to quantify the extracted RNA concentration according to the standard protocol. Only samples containing more than 20 ng / μL of total RNA were used for nanostring analysis.

1-3. Gene Expression Profiling: Affymetrix Microarray Analysis

To verify the gene selection algorithm for signatures, a known data set (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE62254) was used. RNA was extracted from the 300 tumor samples according to the manufacturer's protocol, used for Affymetrix Human Genome U133plus 2.0 Array for gene expression profiling, and raw files were processed using standard Affymetrix software including RMA.

1-4. Gene Expression Profiling: Nanostring Analysis

Nanostring analysis used known 584 genes to define four subtypes, including 15 housekeeping genes and 14 technical control genes, and the standard protocol, Setting up 12 nCounter. Proceed according to Assays (MAN-C0003-03, 2008-2013). Hybridization incubation was performed between 17-18 hours and stored in dark at 4 ° C. (using aluminum foil) until the cartridge was read immediately or read. All cartridges were read within 2 days of preparation in the selected AZ GEN2 digital analyzer station at high resolution. The read data were then processed using the nCounter PanCancer pathway, and the results were corrected by dividing the raw count by the geometric mean of the manufacturer's defined antizone genes and transformed to a log10 scale.

1-5. Gene expression cross-platform identity analysis

For each gene, the correlation between the gene expression level on the nanostring platform and the gene expression level on the micro array platform of the training set (n = 70) was analyzed. As a result of the analysis of the correlation distribution, a cutoff of 0.4 correlation was selected to select matching genes between the two platforms.

1-6. Gene Signature Analysis

We calculated the mesenchymal signature for the nanostring platform using the mean of gastric mesenchymal signature genes defined in the previous study, down-selecting the genes present in the nanostring platform, and using the cross-platform identity defined in the previous section. It was.

Example 2 Identification of Mesenchymal Subtype Marker Genes

A total of 143 tumor samples, 70 tissue samples from the Asian Cancer Research Group (ACRG) cohort and 73 adjuvant chemoradiotherapy (ARTIST) clinical cohorts, were analyzed. As a result of analyzing the clinical characteristics of the subjects, as shown in Table 1 of Example 1-1, it was confirmed that the mean age of ARTIST patients was lower than that of ACRG cohort patients, and there were more early stage patients as expected. .

Meanwhile, an experimental protocol for identifying marker genes of mesenchymal subtype gastric cancer using the tumor samples is shown in FIG. 1. More specifically, cross-platform identity tests were performed on the gene expression level on the nanostring platform and the gene expression level on the microarray platform of the ACRG tissue sample (n = 70) shown in Examples 1-4, respectively. Correlation was analyzed. As a result of selecting and analyzing 0.4 correlation cutoffs to select a matching gene between the two platforms, 300 genes were found to be correlated, and among 300 genes, genes expressed differently in EMT and MSS 71 Dogs (up-60 species, down-11 species) were derived as biomarkers. Specifically, 71 biomarkers derived by the above method are as shown below.

Highly expressed genes AADA23 (A disintegrin and metalloprotease domain-containing protein 23), ADAMTS1 (A disintegrin and metalloproteinase with thrombospondin motifs 1), AKAP12 (A-kinase anchor protein 12), ALPK2 (Alpha Kinase 2), AP1S2 (AP1S2) Adaptor Related Protein Complex 1 Sigma 2), ARMCX1 (Armadillo Repeat Containing, X-Linked 1), Tyrosine-protein kinase receptor UFO (AXL), BICC Family RNA Binding Protein 1 (BICC1), Basonuclin 2 (BNC2), Chromosome C16orf45 16 Open Reading Frame 45), C1S (complement C1s subcomponent), CLDN11 (Claudin 11), CMTM3 (CKLF-like MARVEL transmembrane domain-containing protein 3), Connective Tissue Growth Factor (CTGF), Cytochrome B Reductase 1 (CYBRD1), DII2 (Type II iodothyronine deiodinase), DKK3 (Dickkopf WNT Signaling Pathway Inhibitor 3), DOCK10 (dedicator of cytokinesis 10), DPYSL3 (Dihydropyrimidinase-related protein 3), EML1 (Echinoderm Microtubule Associated Protein Like 1), EVI2A (Ecotropic Viral Integration Site 2A), FAM101B (Family With Sequence Similarity 10) 1 Member B), FAT Atypical Cadherin 4 (FAT4), Fibroblast Growth Factor 2 (FGF2), Fibroblast Growth Factor Receptor 1 (FGFR1), Four And A Half LIM Domains 1 (FHL1), Fibronectin Leucine Rich Transmembrane Protein 2 (FLRT2) , Follistatin Like 1 (FSTL1), GLIPRogenesis (GLI Pathogenesis Related 1), GNB4 (G Protein Subunit Beta 4), GNG11 (G Protein Subunit Gamma 11), HEG1 (Heart Development Protein With EGF Like Domains 1), IGFBP7 (Insulin Like) Growth Factor Binding Protein 7), Junctional Adhesion Molecule 3 (JAM3), Leprecan-Like 1 (LEPREL1), Lipoma HMGIC fusion partner (LHFP), Microtubule Associated Protein 1B (MAP1B), Matrix Metalloproteinase-2 (MMP2), MRAS (MRAS) Muscle RAS), Methionine Sulfoxide Reductase B3 (MSRB3), Nucleosome Assembly Protein 1 Like 3 (NDN), Neuronal Growth Regulator 1 (NEGR1), Nexilin F-Actin Binding Protein (NEXN), Nid1 (Nidogen 1), PLAGL1 (PLAG1 Like Zinc Finger 1), Peripheral Myelin Protein 22 (PMP22), Protein Kinase D1 (PRKD1), Prostaglandin I2 (PTGIS), RNA Binding Motif Single Stranded Interactin g Protein 3), RECK (Reversion Inducing Cysteine Rich Protein With Kazal Motifs), RFTN1 (Raftlin, Lipid Raft Linker 1), SRPX (Sushi Repeat Containing Protein), TCF4 (Transcription Factor 4), TMEM47 (Transmembrane Protein 47), TTC28 Tetratricopeptide Repeat Domain 28, UCHL1 (Ubiquitin C-Terminal Hydrolase L1), VIM (Vimentin), ZEB1 (Zinc Finger E-Box Binding Homeobox 1), ZEB2 (Zinc Finger E-Box Binding Homeobox 2), ZFPM2 (Zinc Finger) Protein, FOG Family Member 2).

Low expression levels of genes-C19orf21 (chromosome 19 open reading frame 21), CLDN4 (Claudin 4), CLDN7 (Claudin 7), DSC2 (Desmocollin 2), GOLT1A (Golgi Transport 1A), LIPG (Lipase G), MAP7 (Microtubule) Associated Protein 7), PAK6 (P21-Activated Kinase 6), PKP3 (Plakophilin 3), SH2D3A (SH2 domain-containing protein 3A), and SPINT1 (Serine Peptidase Inhibitor, Kunitz Type 1).

Next, the results of the investigation of the case of the known molecular subtype EMT / MSS in the ACRG cohort using the typical Affymetrix method and the results of the nanostring analysis using the 71 biomarkers derived above were compared. Analyzed. As a result, it was confirmed that the agreement between the two platforms is very high as shown in Table 2. More specifically, only two of the 70 ACRG samples classified as mesenchymal subtypes by the Affymetrix platform were classified as non-mesenchymal subtypes via nanostring analysis. In addition, the cohort was found to contain 16 MSS / EMT, 20 MSI, 23 P53, and 11 P53 inactive / MSS subtypes, 14 (88%) in the 16 MSS / EMT subtype samples. ) Has been identified as mesenchymal subtype through nanostring analysis. Two samples representing the non-mesenchymal or MSS / EMT subtypes were the signal ring cell subtypes (ACRG # 42, # 47). The histological results showed that the # 42 sample used for the ACRG analysis was isolated from the serous side, whereas the sample used for the nanostring was isolated from the tumor located in the gastric mucosa. Similarly, ACRG # 47 tumors were found to be a mixture of signal ring cell carcinoma and tubular moderately differentiated adenocarcinoma. All samples corresponding to MSI, P53 active / MSS, and P53 inactive / MSS ACRG subtypes were classified as non-mesenchymal subtypes showing 100% concordance based on the scoring system.

Sample # Mesenchymal ACRG subtype EBV-ISH MSI MLH1 by IHC Lauren classification Pathology Stage ACRG # 1 non-mesenchymal MSI -0.17 negative MSS partial loss intestinal moderately differentiated adenocarcinoma IB ACRG # 2 mesenchymal MSS / EMT 0.32 negative MSS preserved diffuse signet ring cell carcinoma III ACRG # 3 mesenchymal MSS / EMT 0.37 positive MSS
preserved diffuse poorly differentiated adenocarcinoma III ACRG # 4 mesenchymal MSS / EMT 0.53 negative MSS preserved mixed mucinous adenocarcinoma II ACRG # 5 mesenchymal MSS / EMT 0.19 negative MSS preserved diffuse poorly differentiated adenocarcinoma III ACRG # 6 non-mesenchymal MSI 0.24 negative MSS loss diffuse signet ring cell carcinoma III ACRG # 7 mesenchymal MSS / EMT 0.3 negative MSS preserved diffuse poorly differentiated adenocarcinoma IV ACRG # 8 mesenchymal MSS / EMT 0.12 negative MSS preserved diffuse poorly differentiated adenocarcinoma IV ACRG # 9 mesenchymal MSS / EMT 0.2 negative MSS preserved intestinal moderately differentiated adenocarcinoma III ACRG # 10 non-mesenchymal MSS / p53 active 0.03 negative MSS preserved intestinal moderately differentiated adenocarcinoma IB ACRG # 11 non-mesenchymal MSI -0.7 negative MSI-high loss diffuse moderately differentiated adenocarcinoma IB ACRG # 12 non-mesenchymal MSS / p53 active -0.3 negative MSS preserved intestinal moderately differentiated adenocarcinoma IB ACRG # 13 non-mesenchymal MSS / p53 inactive -0.44 negative MSS preserved diffuse poorly differentiated adenocarcinoma III ACRG # 14 non-mesenchymal MSI -0.27 negative MSI-high loss diffuse moderately differentiated adenocarcinoma II ACRG # 15 non-mesenchymal MSS / p53 active -0.28 negative MSS preserved diffuse poorly differentiated adenocarcinoma III ACRG # 16 non-mesenchymal MSS / p53 active -0.15 negative MSS preserved diffuse poorly differentiated adenocarcinoma III ACRG # 17 non-mesenchymal MSS / p53 inactive -0.15 ND ND preserved intestinal poorly differentiated adenocarcinoma IV ACRG # 18 non-mesenchymal MSI -0.52 negative MSS loss intestinal moderately differentiated adenocarcinoma IB ACRG # 19 non-mesenchymal MSS / p53 inactive -0.08 negative MSS preserved intestinal moderately differentiated adenocarcinoma III ACRG # 20 non-mesenchymal MSS / p53 inactive -0.49 negative MSS preserved intestinal moderately differentiated adenocarcinoma III ACRG # 21 non-mesenchymal MSI -0.72 negative MSS loss mixed moderately differentiated adenocarcinoma III ACRG # 22 non-mesenchymal MSS / p53 active 0.01 negative MSS preserved intestinal well differentiated adenocarcinoma II ACRG # 23 non-mesenchymal MSS / p53 inactive -0.24 positive MSS preserved diffuse poorly differentiated adenocarcinoma IV ACRG # 24 non-mesenchymal MSS / p53 inactive 0.01 negative MSS preserved diffuse poorly differentiated adenocarcinoma III ACRG # 25 non-mesenchymal MSI 0.02 negative MSS preserved diffuse poorly differentiated adenocarcinoma IV ACRG # 26 mesenchymal MSS / EMT 0.26 negative MSS preserved diffuse poorly differentiated adenocarcinoma III ACRG # 27 non-mesenchymal MSS / p53 inactive -0.58 negative MSI-high preserved diffuse poorly differentiated adenocarcinoma II ACRG # 28 non-mesenchymal MSS / p53 active 0.06 negative MSS preserved diffuse poorly differentiated adenocarcinoma IV ACRG # 29 non-mesenchymal MSS / p53 inactive -0.57 negative MSS preserved intestinal moderately differentiated adenocarcinoma III ACRG # 30 non-mesenchymal MSI 0.49 negative MSS preserved mixed moderately differentiated adenocarcinoma III ACRG # 31 non-mesenchymal MSI -0.58 ND MSI-high preserved intestinal poorly differentiated adenocarcinoma IB ACRG # 32 non-mesenchymal MSI -0.55 negative MSS preserved intestinal well differentiated adenocarcinoma IB ACRG # 33 non-mesenchymal MSS / p53 active -0.09 negative MSS preserved intestinal moderately differentiated adenocarcinoma III ACRG # 34 non-mesenchymal MSS / p53 active -0.2 negative MSS preserved diffuse poorly differentiated adenocarcinoma III ACRG # 35 non-mesenchymal MSS / p53 active -0.07 negative MSS preserved intestinal poorly differentiated adenocarcinoma IV ACRG # 36 non-mesenchymal MSS / p53 inactive -0.01 negative MSS preserved diffuse signet ring cell carcinoma IV ACRG # 37 non-mesenchymal MSS / p53 active -0.92 negative MSI-high preserved intestinal moderately differentiated adenocarcinoma IV ACRG # 38 non-mesenchymal MSI -0.29 negative MSS loss diffuse poorly differentiated adenocarcinoma III ACRG # 39 mesenchymal MSS / EMT -0.01 negative MSS preserved diffuse signet ring cell carcinoma III ACRG # 40 non-mesenchymal MSI -0.6 negative MSI-high loss intestinal moderately differentiated adenocarcinoma IB ACRG # 41 non-mesenchymal MSS / p53 active -0.46 negative MSS preserved intestinal poorly differentiated adenocarcinoma III ACRG # 42 non-mesenchymal MSS / EMT 0.12 negative loss diffuse signet ring cell carcinoma IV ACRG # 43 non-mesenchymal MSS / p53 active -0.22 negative MSS preserved intestinal moderately differentiated adenocarcinoma IV ACRG # 44 non-mesenchymal MSI -0.28 negative MSS loss intestinal moderately differentiated adenocarcinoma IV ACRG # 45 non-mesenchymal MSS / p53 active 0.12 positive MSS preserved intestinal poorly differentiated adenocarcinoma IV ACRG # 46 mesenchymal MSS / EMT 0.32 negative MSS preserved diffuse poorly differentiated adenocarcinoma IV ACRG # 47 non-mesenchymal MSS / p53 inactive -0.58 negative MSS preserved intestinal moderately differentiated adenocarcinoma II ACRG # 48 mesenchymal MSS / EMT 0.34 negative MSS preserved diffuse signet ring cell carcinoma III ACRG # 49 non-mesenchymal MSS / EMT -0.44 negative preserved diffuse signet ring cell carcinoma IV ACRG # 50 non-mesenchymal MSS / p53 active -0.22 positive preserved diffuse poorly differentiated adenocarcinoma IV ACRG # 51 non-mesenchymal MSI -0.22 negative NR24 only MSI preserved diffuse poorly differentiated adenocarcinoma IV ACRG # 52 non-mesenchymal MSI -0.43 negative NR24 only MSI preserved intestinal moderately differentiated adenocarcinoma III ACRG # 53 non-mesenchymal MSS / p53 active 0.22 negative preserved diffuse mucinous adenocarcinoma III ACRG # 55 non-mesenchymal MSS / p53 active -0.34 negative preserved diffuse others II ACRG # 56 non-mesenchymal MSI -0.15 negative preserved diffuse mucinous adenocarcinoma III ACRG # 57 non-mesenchymal MSS / p53 active 0.09 positive preserved diffuse poorly differentiated adenocarcinoma III ACRG # 58 non-mesenchymal MSI -0.67 negative loss intestinal moderately differentiated adenocarcinoma IV ACRG # 59 non-mesenchymal MSI -0.83 negative loss intestinal poorly differentiated adenocarcinoma III ACRG # 60 non-mesenchymal MSS / p53 active 0.27 negative preserved intestinal poorly differentiated adenocarcinoma III ACRG # 61 non-mesenchymal MSI -0.27 294 MSI-high loss 00283129 67 ACRG # 62 non-mesenchymal MSS / p53 active 0.22 ND preserved diffuse signet ring cell carcinoma III ACRG # 63 non-mesenchymal MSS / p53 active 0.01 negative preserved intestinal poorly differentiated adenocarcinoma III ACRG # 64 non-mesenchymal MSS / p53 active 0.08 negative preserved diffuse poorly differentiated adenocarcinoma III ACRG # 65 mesenchymal MSS / EMT -0.07 negative preserved intestinal poorly differentiated adenocarcinoma III ACRG # 66 mesenchymal MSS / EMT 0.45 negative preserved diffuse signet ring cell carcinoma IV ACRG # 67 non-mesenchymal MSS / p53 inactive -0.2 negative preserved intestinal moderately differentiated adenocarcinoma III ACRG # 68 mesenchymal MSS / EMT 0.29 negative loss diffuse signet ring cell carcinoma IV ACRG # 69 non-mesenchymal MSI -0.7 negative loss mixed poorly differentiated adenocarcinoma III ACRG # 70 non-mesenchymal MSS / p53 active -0.44 negative preserved intestinal papillary adenocarcinoma II ACRG # 71 non-mesenchymal MSS / p53 active 0.24 positive preserved diffuse poorly differentiated adenocarcinoma III

Example 3. Mesenchymal Subtype Verification in ARTIST Cohort

Furthermore, mesenchymal subtypes were evaluated in the ARTIST cohort (n = 73) to verify that the 71 marker genes derived above could predict the clinical characteristics of MSS / EMT. We chose a displacement-based cutoff (highest quartile) for each data group (0.325 for ARTIST and 0.14 for ACRG).

As a result, 20 of 73 patients were predicted to be mesenchymal subtype tumors. The proportion of mesenchymal subtypes equivalent to MSS / EMT was found to be within the previously reported range. Comparing the overall survival of patients with mesenchymal gastric cancer and patients with non-mesenchymal subtype (n = 73) in the ARTIST cohort, as shown in FIG. 3A The survival rate of patients with gastric cancer of the type was found to be significantly lower (P = 0.01).

In addition, a combination of data sets from the ARTIST and ACRG cohorts was used to compare clinical characteristics between mesenchymal and non-mesenchymal subtypes. , Similar to gastric cancer, poor differentiation or ring cell carcinoma, and MSI low disease occurring in the entire stomach.

Non-mesenchymal (N = 110) Mesenchymal
 (N = 33) P Median age, years 60 (range, 25-78) 56 (range, 36-75) 0.061 Male gender 79 (72%) 19 (58%) 0.095 Tumor location: cardia / body / antrum
vs. whole
Cardia
Body
Antrum
Whole stomach
2 (2%)
41 (37%)
46 (42%)
21 (19%)
0
14 (42%)
7 (21%)
12 (36%) 0.041 Tumor grade: PD / signet ring cell vs. others
Well or moderate
Poorly differentiated tubular
Signet ring cell
Mucinous
Others or unavailable
22 (20%)
44 (40%)
29 (26%)
11 (10%)
4 (4%)
1 (3%)
11 (33%)
21 (64%)
0
0 0.012 Lauren classification
Intestinal
Diffuse
Mixed or indeterminate
41 (37%)
59 (54%)
10 (9%)
1 (3%)
30 (91%)
2 (6%) 0.001 Tumor stage
I or II
III or IV
39 (35%)
71 (65%)
12 (36%)
21 (64%) 0.460 EBV positivity 1 (1%) 2 (6%) 0.001 MSI high 24 (22%) 2 (6%) 0.035 Lymphovascular invasion 74 (67%) 20 (61%) 0.961 Perineural invasion 41 (37%) 12 (36%) 0.767

In addition, overall survival was shown to be significantly short in the mesenchymal subtype as shown in FIG. 3b (risk ratio [HR], 2.262, 95% confidence interval [CI], 1.410-3.636, P = 0.001). In regression analysis with clinical features such as covariates, only mesenchymal subtypes (HR, 2.045; 95% CI, 1.205-3.472; P = 0.008) were associated with short survival. A step-by-step Cox model was used to investigate whether the interaction between these clinical characteristics was related to this probability. In other words, only mesenchymal subtypes were significantly associated with survival.

The description of the present invention set forth above is for illustrative purposes, and one of ordinary skill in the art may understand that the present invention may be easily modified into other specific forms without changing the technical spirit or essential features of the present invention. There will be. Therefore, it should be understood that the embodiments described above are exemplary in all respects and not restrictive.

Claims (15)

A disintegrin and metalloprotease domain-containing protein 23, NCBI accession number: NM_003812, A disintegrin and metalloproteinase with thrombospondin motifs 1, NM_006988.3, AKAP12 (A-kinase anchor protein 12, NM_005100.3) ), ALPK2 (Alpha Kinase 2, NM_052947), AP1S2 (Adaptor Related Protein Complex 1 Sigma 2, NM_003916), ARMCX1 (Armadillo Repeat Containing, X-Linked 1, NM_016608), Tyrosine-protein kinase receptor UFO, NM_021913.2 ), BICC1 (BicC Family RNA Binding Protein 1, NM_001080512.1), BNC2 (Basonuclin 2, NM_017637.5), C16orf45 (Chromosome 16 Open Reading Frame 45, NM_033201), C1S (complement C1s subcomponent, NM_001734.2), CLDN11 (Claudin 11, NM_005602), CMTM3 (CKLF-like MARVEL transmembrane domain-containing protein 3, NM_181555), CTGF (Connective Tissue Growth Factor, NM_001901), CYBRD1 (Cytochrome B Reductase 1, NM_024843), DIO2 (Type II iodothyronine deiodinase NM_013989), DKK3 (Dickkopf WNT Signaling Pathway Inhibitor 3, NM_015881), DOCK10 (dedicator of cytoki nesis 10, NM_017718), DPYSL3 (Dihydropyrimidinase-related protein 3, NM_001387.2), EML1 (Echinoderm Microtubule Associated Protein Like 1, NM_004434), EVI2A (Ecotropic Viral Integration Site 2A, NM_014210.3), FAM101B (Family With Sequence Similarity) 101 Member B, NM_182705), FAT Atypical Cadherin 4, NM_024582), FGF2 (Fibroblast Growth Factor 2, NM_002006.4), FGFR1 (Fibroblast Growth Factor Receptor 1, NM_015850.2), FHL1 (Four And A Half LIM Domains 1, NM_001449.4), FLRT2 (Fibronectin Leucine Rich Transmembrane Protein 2, NM_013231), FSTL1 (Follistatin Like 1, NM_007085.4), GLIPR1 (GLI Pathogenesis Related 1, NM_006851), GNB4 (G Protein Subunit Beta 4, NM_021629) , GNG11 (G Protein Subunit Gamma 11, NM_004126), HEG1 (Heart Development Protein With EGF Like Domains 1, NM_020733.1), IGFBP7 (Insulin Like Growth Factor Binding Protein 7, NM_001553.1), JAM3 (Junctional Adhesion Molecule 3, NM_032801.3), LEPREL1 (Leprecan-Like 1, NM_001001530), LHFP (lipoma HMGIC fusion partner, NM_005780.2), MAP1B ((Micro tubule Associated Protein 1B, NM_032010), MMP2 (matrix metalloproteinase-2, NM_004530.2), MRAS (Muscle RAS, NM_012219), MSRB3 (Methionine Sulfoxide Reductase B3, NM_198080), NDN (Nucleosome Assembly Protein 1 Like 3, NM_002487), NEGR1 (Neuronal Growth Regulator 1, NM_173808), NEXN (Nexilin F-Actin Binding Protein, NM_144573), NID1 (Nidogen 1, NM_002508), PLAGL1 (PLAG1 Like Zinc Finger 1, NM_006718), PMP22 (Peripheral Myelin Protein 22, NM_000304. 2), PRKD1 (Protein Kinase D1, NM_002742), PTGIS (Prostaglandin I2, NM_000961.3), RBMS3 (RNA Binding Motif Single Stranded Interacting Protein 3, NM_014483), RECK (Reversion Inducing Cysteine Rich Protein With Kazal Motifs, NM_021111) RFTN1 (Raftlin, Lipid Raft Linker 1, NM_015150), SRPX (Sushi Repeat Containing Protein, NM_006307), TCF4 (Transcription Factor 4, NM_003199.1), TMEM47 (Transmembrane Protein 47, NM_031442), TTC28 (Tetratricopeptide Repeat Domain 28, NM_015150) ), UCHL1 (Ubiquitin C-Terminal Hydrolase L1, NM_004181), VIM (Vimentin, NM_003380.2), ZEB1 (Zi nc Finger E-Box Binding Homeobox 1, NM_001128128.1), ZEB2 (Zinc Finger E-Box Binding Homeobox 2, NM_014795.3), ZFPM2 (Zinc Finger Protein, FOG Family Member 2, NM_012082.3), C19orf21 (chromosome 19 open reading frame 21, NM_173481.2), CLDN4 (Claudin 4, NM_001305.3), CLDN7 (Claudin 7, NM_001307.3), DSC2 (Desmocollin 2, NM_024422.3), GOLT1A (Golgi Transport 1A, NM_198447), LIPG (Lipase G, NM_006033), MAP7 (Microtubule Associated Protein 7, NM_003980), PAK6 (P21-Activated Kinase 6, NM_020168), PKP3 (Plakophilin 3, NM_007183), SH2D3A (SH2 domain-containing protein 3A, NM_005490.2), And SPINT1 (Serine Peptidase Inhibitor, Kunitz Type 1, NM_001032367.1) gene or a protein encoding the gene, comprising a marker composition for predicting survival of gastric cancer patients.
The method of claim 1,
The gastric cancer is characterized in that the mesenchymal subtype gastric cancer, marker composition.
A disintegrin and metalloprotease domain-containing protein 23, NCBI accession number: NM_003812, A disintegrin and metalloproteinase with thrombospondin motifs 1, NM_006988.3, AKAP12 (A-kinase anchor protein 12, NM_005100.3) ), ALPK2 (Alpha Kinase 2, NM_052947), AP1S2 (Adaptor Related Protein Complex 1 Sigma 2, NM_003916), ARMCX1 (Armadillo Repeat Containing, X-Linked 1, NM_016608), Tyrosine-protein kinase receptor UFO, NM_021913.2 ), BICC1 (BicC Family RNA Binding Protein 1, NM_001080512.1), BNC2 (Basonuclin 2, NM_017637.5), C16orf45 (Chromosome 16 Open Reading Frame 45, NM_033201), C1S (complement C1s subcomponent, NM_001734.2), CLDN11 (Claudin 11, NM_005602), CMTM3 (CKLF-like MARVEL transmembrane domain-containing protein 3, NM_181555), CTGF (Connective Tissue Growth Factor, NM_001901), CYBRD1 (Cytochrome B Reductase 1, NM_024843), DIO2 (Type II iodothyronine deiodinase NM_013989), DKK3 (Dickkopf WNT Signaling Pathway Inhibitor 3, NM_015881), DOCK10 (dedicator of cytoki nesis 10, NM_017718), DPYSL3 (Dihydropyrimidinase-related protein 3, NM_001387.2), EML1 (Echinoderm Microtubule Associated Protein Like 1, NM_004434), EVI2A (Ecotropic Viral Integration Site 2A, NM_014210.3), FAM101B (Family With Sequence Similarity) 101 Member B, NM_182705), FAT Atypical Cadherin 4, NM_024582), FGF2 (Fibroblast Growth Factor 2, NM_002006.4), FGFR1 (Fibroblast Growth Factor Receptor 1, NM_015850.2), FHL1 (Four And A Half LIM Domains 1, NM_001449.4), FLRT2 (Fibronectin Leucine Rich Transmembrane Protein 2, NM_013231), FSTL1 (Follistatin Like 1, NM_007085.4), GLIPR1 (GLI Pathogenesis Related 1, NM_006851), GNB4 (G Protein Subunit Beta 4, NM_021629) , GNG11 (G Protein Subunit Gamma 11, NM_004126), HEG1 (Heart Development Protein With EGF Like Domains 1, NM_020733.1), IGFBP7 (Insulin Like Growth Factor Binding Protein 7, NM_001553.1), JAM3 (Junctional Adhesion Molecule 3, NM_032801.3), LEPREL1 (Leprecan-Like 1, NM_001001530), LHFP (lipoma HMGIC fusion partner, NM_005780.2), MAP1B ((Micro tubule Associated Protein 1B, NM_032010), MMP2 (matrix metalloproteinase-2, NM_004530.2), MRAS (Muscle RAS, NM_012219), MSRB3 (Methionine Sulfoxide Reductase B3, NM_198080), NDN (Nucleosome Assembly Protein 1 Like 3, NM_002487), NEGR1 (Neuronal Growth Regulator 1, NM_173808), NEXN (Nexilin F-Actin Binding Protein, NM_144573), NID1 (Nidogen 1, NM_002508), PLAGL1 (PLAG1 Like Zinc Finger 1, NM_006718), PMP22 (Peripheral Myelin Protein 22, NM_000304. 2), PRKD1 (Protein Kinase D1, NM_002742), PTGIS (Prostaglandin I2, NM_000961.3), RBMS3 (RNA Binding Motif Single Stranded Interacting Protein 3, NM_014483), RECK (Reversion Inducing Cysteine Rich Protein With Kazal Motifs, NM_021111) RFTN1 (Raftlin, Lipid Raft Linker 1, NM_015150), SRPX (Sushi Repeat Containing Protein, NM_006307), TCF4 (Transcription Factor 4, NM_003199.1), TMEM47 (Transmembrane Protein 47, NM_031442), TTC28 (Tetratricopeptide Repeat Domain 28, NM_015150) ), UCHL1 (Ubiquitin C-Terminal Hydrolase L1, NM_004181), VIM (Vimentin, NM_003380.2), ZEB1 (Zi nc Finger E-Box Binding Homeobox 1, NM_001128128.1), ZEB2 (Zinc Finger E-Box Binding Homeobox 2, NM_014795.3), ZFPM2 (Zinc Finger Protein, FOG Family Member 2, NM_012082.3), C19orf21 (chromosome 19 open reading frame 21, NM_173481.2), CLDN4 (Claudin 4, NM_001305.3), CLDN7 (Claudin 7, NM_001307.3), DSC2 (Desmocollin 2, NM_024422.3), GOLT1A (Golgi Transport 1A, NM_198447), LIPG (Lipase G, NM_006033), MAP7 (Microtubule Associated Protein 7, NM_003980), PAK6 (P21-Activated Kinase 6, NM_020168), PKP3 (Plakophilin 3, NM_007183), SH2D3A (SH2 domain-containing protein 3A, NM_005490.2), And SPINT1 (Serine Peptidase Inhibitor, Kunitz Type 1, NM_001032367.1) comprising a mRNA or a formulation for measuring the level of protein encoded by the gene, the composition for predicting survival of gastric cancer patients.
The method of claim 3,
The gastric cancer is characterized in that the mesenchymal subtype gastric cancer, composition.
The method of claim 3,
The agent for measuring the mRNA level of the gene is characterized in that the sense and antisense primers, or probes that complementarily bind to the mRNA of the gene, composition.
The method of claim 3,
The agent for measuring the protein level is characterized in that the antibody that specifically binds to a protein encoded by the gene, composition.
Comprising the composition of claim 3, the kit for predicting survival of gastric cancer patients.
A disintegrin and metalloprotease domain-containing protein 23, NCBI accession number NM_003812, A disintegrin and metalloproteinase with thrombospondin motifs 1, NM_006988.3, AKAP12 (A-kinase anchor) in a biological sample derived from gastric cancer patients protein 12, NM_005100.3), ALPK2 (Alpha Kinase 2, NM_052947), AP1S2 (Adaptor Related Protein Complex 1 Sigma 2, NM_003916), ARMCX1 (Armadillo Repeat Containing, X-Linked 1, NM_016608), AXL (Tyrosine-protein kinase) receptor UFO, NM_021913.2), BICC Family RNA Binding Protein 1, NM_001080512.1), BNC2 (Basonuclin 2, NM_017637.5), C16orf45 (Chromosome 16 Open Reading Frame 45, NM_033201), C1S (complement C1s subcomponent, NM_001734.2), CLDN11 (Claudin 11, NM_005602), CMTM3 (CKLF-like MARVEL transmembrane domain-containing protein 3, NM_181555), CTGF (Connective Tissue Growth Factor, NM_001901), CYBRD1 (Cytochrome B Reductase 1, NM_024843), DIO2 (Type II iodothyronine deiodinase, NM_013989), DKK3 (Dickkopf WNT Signaling Pathway Inhib itor 3, NM_015881), DOCK10 (dedicator of cytokinesis 10, NM_017718), DPYSL3 (Dihydropyrimidinase-related protein 3, NM_001387.2), EML1 (Echinoderm Microtubule Associated Protein Like 1, NM_004434), EVI2A (Ecotropic Viral Integration Site 2 1A, NM_004 .3), FAM101B (Family With Sequence Similarity 101 Member B, NM_182705), FAT4 (FAT Atypical Cadherin 4, NM_024582), FGF2 (Fibroblast Growth Factor 2, NM_002006.4), FGFR1 (Fibroblast Growth Factor Receptor 1, NM_015850.2 ), FHL1 (Four And A Half LIM Domains 1, NM_001449.4), FLRT2 (Fibronectin Leucine Rich Transmembrane Protein 2, NM_013231), FSTL1 (Follistatin Like 1, NM_007085.4), GLIPR1 (GLI Pathogenesis Related 1, NM_006851), G Protein Subunit Beta 4, NM_021629), GNG11 (G Protein Subunit Gamma 11, NM_004126), HEG1 (Heart Development Protein With EGF Like Domains 1, NM_020733.1), IGFBP7 (Insulin Like Growth Factor Binding Protein 7, NM_001553. 1), JAM3 (Junctional Adhesion Molecule 3, NM_032801.3), LEPREL1 (Leprecan-Like 1, NM_001001530), LHFP (lipoma HM GIC fusion partner, NM_005780.2), MAP1B (Microtubule Associated Protein 1B, NM_032010), MMP2 (matrix metalloproteinase-2, NM_004530.2), MRAS (Muscle RAS, NM_012219), MSRB3 (Methionine Sulfoxide Reductase B3, NM_198080), Nucleosome Assembly Protein 1 Like 3, NM_002487, NGR1 (Neuronal Growth Regulator 1, NM_173808), NEXN (Nexilin F-Actin Binding Protein, NM_144573), NID1 (Nidogen 1, NM_002508), PLAGL1 (PLAG1 Like Zinc Finger 1, NM_006718), PMP22 (Peripheral Myelin Protein 22, NM_000304.2), PRKD1 (Protein Kinase D1, NM_002742), PTGIS (Prostaglandin I2, NM_000961.3), RBMS3 (RNA Binding Motif Single Stranded Interacting Protein 3, NM_014483) Reversion Inducing Cysteine Rich Protein With Kazal Motifs, NM_021111), RFTN1 (Raftlin, Lipid Raft Linker 1, NM_015150), SRPX (Sushi Repeat Containing Protein, NM_006307), TCF4 (Transcription Factor 4, NM_003199.1), TMEM47 (Transmembrane Protein 47 , NM_031442), TTC28 (Tetratricopeptide Repeat Domain 28, NM_015281), UCHL1 (Ubiquitin C-Terminal Hydrolase L1, N M_004181), VIM (Vimentin, NM_003380.2), ZEB1 (Zinc Finger E-Box Binding Homeobox 1, NM_001128128.1), ZEB2 (Zinc Finger E-Box Binding Homeobox 2, NM_014795.3), ZFPM2 (Zinc Finger Protein, FOG Family Member 2, NM_012082.3), C19orf21 (chromosome 19 open reading frame 21, NM_173481.2), CLDN4 (Claudin 4, NM_001305.3), CLDN7 (Claudin 7, NM_001307.3), DSC2 (Desmocollin 2, NM_024422 .3), GOLT1A (Golgi Transport 1A, NM_198447), LIPG (Lipase G, NM_006033), MAP7 (Microtubule Associated Protein 7, NM_003980), PAK6 (P21-Activated Kinase 6, NM_020168), PKP3 (Plakophilin 3, NM_007183), Gastric cancer patients comprising measuring mRNA of the SH2D3A (SH2 domain-containing protein 3A, NM_005490.2), and SPINT1 (Serine Peptidase Inhibitor, Kunitz Type 1, NM_001032367.1) genes or the protein levels encoded by the genes Information method for predicting survival rate.
The method of claim 8,
The gastric cancer is characterized in that the mesenchymal subtype gastric cancer, information providing method.
The method of claim 8,
The ADAM23, ADAMTS1, AKAP12, ALPK2, AP1S2, ARMCX1, AXL, BICC1, BNC2, C16orf45, C1S, CLDN11, CMTM3, CTGF, CYBRD1, DIO2, DKK3, DOCK10, DPYSL3, EML1, EVI2, FFR2A, FFR2A, FG2 , FHL1, FLRT2, FSTL1, GLIPR1, GNB4, GNG11, HEG1, IGFBP7, JAM3, LEPREL1, LHFP, MAP1B, MMP2, MRAS, MSRB3, NDN, NEGR1, NEXN, NID1, PLAGL1, PMP22, PRKDB, PTGK REC , MRNA levels of RFTN1, SRPX, TCF4, TMEM47, TTC28, UCHL1, VIM, ZEB1, ZEB2, and ZFPM2 genes or the proteins encoded by these genes are expressed in mRNA or protein of the corresponding genes in patients with non-mesenchymal gastric cancer. Wherein if higher than the level, the survival rate is predicted to be lower than that of non-mesenchymal gastric cancer patients.
The method of claim 8,
The mRNA or protein levels of the mRNA of the C19orf21, CLDN4, CLDN7, DSC2, GOLT1A, LIPG, MAP7, PAK6, PKP3, SH2D3A, and SPINT1 genes or the protein encoded by the gene is non-mesenchymal gastric cancer patients If the expression level is lower than the non-mesenchymal gastric cancer patients, characterized in that the survival rate is predicted to be low, information providing method.
The method of claim 8,
The biological sample is characterized in that the gastric tumor tissue, information providing method.
The method of claim 8,
The expression level of the mRNA is NanoString nCounter analysis, polymerase chain reaction (PCR), reverse transcription polymerase chain reaction (RT-PCR), real-time polymerase chain reaction (Real-time PCR), RNase protection A method of providing information, characterized in that measured by one or more methods selected from the group consisting of RNase protection assay (RPA), microarray, and northern blotting.
The method of claim 8,
The protein expression level is Western blotting, radioimmunoassay (RIA), radioimmunodiffusion, enzyme immunoassay (ELISA), immunoprecipitation, flow cytometry, Characterized in that it is measured by one or more methods selected from the group consisting of immunofluorescence, ouchterlony, complement fixation assay, and protein chip, How to Provide Information.
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