High Expression of NREP Correlated With Worse Survival and M2 Macrophage Infiltrates in Gastric Cancer

Abstract Background: Neuronal Regeneration Related Protein (NREP) is a highly conserved protein and is a newly discovered protein that may be closely related to tumor cell migration. We aim at investigating the prognostic role of NREP in gastric cancer (GC). Methods: Tumor Immune Estimation Resource (TIMER), The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used to analysis NREP mRNA expression in GC. Correlations between NREP mRNA expression and clinicopathological characteristic were analyzed. TCGA and GEO data were analyzed by The Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan–Meier plotter databases respectively to assess prognostic value of NREP in GC. Gene set enrichment analysis (GSEA) was performed to identify the keg pathways related to NREP expression. TIMER and CIBERSORT analysis were used to found tumor-infiltrating immune cells associated with NREP mRNA expression. Results: NREP was over expressed in GC and significantly associated with T stage (P<0.001), Histologic grade (P = 0.022) and OS events (P = 0.007) of GC patients. High mRNA expression of NREP correlated with worse survival. The significantly kegg pathways enriched in samples with NREP high expression involved in cell adhesion, tumorigenesis, and immune and inflammatory responses. NREP mRNA expression was positively associated with CD4+T cell(r = 0.294, P = 1.04e−08), CD8+T cell(r = 0.125, P = 0.0167), Neutrophil(r = 0.169, P = 0.00116), Dendritic(r = 0.314, P = 1.03e−09), and was strongly associated with Macrophage (r = 0.547, P = 5.44e−30). The CIBERSORT database revealed that NREP mRNA expression was correlated with the activated memory CD4+ T cells(p<0.01), Monocytes(p<0.001) and M2 Macrophages(p<0.001). NREP is strongly correlated with the markers genes of M2 macrophages and tumor-associated macrophages (TAMs). Conclusion: NREP might be served as a novel prognostic biomarker of GC and associated with M2 macrophage infiltrates.

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Expression of LOX Suggests Poor Prognosis in Gastric Cancer

Frontiers in Medicine ◽

10.3389/fmed.2021.718986 ◽

2021 ◽

Vol 8 ◽

Author(s):

Jinfeng Zhu ◽

Chen Luo ◽

Jiefeng Zhao ◽

Xiaojian Zhu ◽

Kang Lin ◽

...

Keyword(s):

Gene Expression ◽

Gastric Cancer ◽

Logistic Regression ◽

Regression Analysis ◽

Poor Prognosis ◽

Cox Regression ◽

Gene Set Enrichment Analysis ◽

High Expression ◽

Expression Level ◽

Cox Regression Analysis

Background: Lysyl oxidase (LOX) is a key enzyme for the cross-linking of collagen and elastin in the extracellular matrix. This study evaluated the prognostic role of LOX in gastric cancer (GC) by analyzing the data of The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) dataset.Methods: The Wilcoxon rank-sum test was used to calculate the expression difference of LOX gene in gastric cancer and normal tissues. Western blot and immunohistochemical staining were used to evaluate the expression level of LOX protein in gastric cancer. Kaplan-Meier analysis was used to calculate the survival difference between the high expression group and the low expression group in gastric cancer. The relationship between statistical clinicopathological characteristics and LOX gene expression was analyzed by Wilcoxon or Kruskal-Wallis test and logistic regression. Univariate and multivariate Cox regression analysis was used to find independent risk factors affecting the prognosis of GC patients. Gene set enrichment analysis (GSEA) was used to screen the possible mechanisms of LOX and GC. The CIBERSORT calculation method was used to evaluate the distribution of tumor-infiltrating immune cell (TIC) abundance.Results: LOX is highly expressed in gastric cancer tissues and is significantly related to poor overall survival. Wilcoxon or Kruskal-Wallis test and Logistic regression analysis showed, LOX overexpression is significantly correlated with T-stage progression in gastric cancer. Multivariate Cox regression analysis on TCGA and GEO data found that LOX (all p < 0.05) is an independent factor for poor GC prognosis. GSEA showed that high LOX expression is related to ECM receptor interaction, cancer, Hedgehog, TGF-beta, JAK-STAT, MAPK, Wnt, and mTOR signaling pathways. The expression level of LOX affects the immune activity of the tumor microenvironment in gastric cancer.Conclusion: High expression of LOX is a potential molecular indicator for poor prognosis of gastric cancer.

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Prognostic value of CLIC3 mRNA overexpression in bladder cancer

PeerJ ◽

10.7717/peerj.8348 ◽

2020 ◽

Vol 8 ◽

pp. e8348

Author(s):

Mei Chen ◽

Shufang Zhang ◽

Xiaohong Wen ◽

Hui Cao ◽

Yuanhui Gao

Keyword(s):

Gene Expression ◽

Bladder Cancer ◽

Mrna Expression ◽

Prognostic Value ◽

Multivariate Analyses ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Receptor Interaction ◽

Normal Tissues

Background Human intracellular chloride channel 3 (CLIC3) is involved in the development of various cancers, but the expression and prognostic value of CLIC3 mRNA in bladder cancer (BC) remain unclear. Methods The gene expression data and clinical information of CLIC3 were obtained from the Gene Expression Omnibus (GEO) database and verified in the Oncomine and The Cancer Genome Atlas (TCGA) database. The expression of CLIC3 mRNA in BC tissues and adjacent normal tissues was detected by quantitative real-time polymerase chain reaction (qRT-PCR). The Kaplan-Meier method was used to analyze the relationship between the expression of CLIC3 mRNA and the prognosis of BC. Cox univariate and multivariate analyses were performed on the overall survival and tumor-specific survival of BC patients. The genes coexpressed with CLIC3 were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). CLIC3-related signal transduction pathways in BC were explored with gene set enrichment analysis (GSEA). Results The expression of CLIC3 mRNA in BC tissues was higher than that in normal tissues (P < 0.01). High CLIC3 mRNA expression was associated with age (P = 0.021) and grade (P = 0.045) in BC patients. High CLIC3 mRNA expression predicted a poor prognosis in BC patients (P < 0.05). Cox univariate and multivariate analyses showed that high CLIC3 mRNA expression was associated with tumor-specific survival in BC patients (P < 0.05). Functional enrichment analyses indicated that CLIC3 may be significantly associated with the cell cycle, focal adhesion, the extracellular matrix (ECM) receptor interaction and the P53 signaling pathway. Conclusions CLIC3 mRNA is highly expressed in BC, and its high expression is related to the adverse clinicopathological factors and prognosis of BC patients. CLIC3 can be used as a biomarker for the prognosis of BC patients.

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ANXA9 as a novel prognostic biomarker associated with immune infiltrates in gastric cancer

PeerJ ◽

10.7717/peerj.12605 ◽

2021 ◽

Vol 9 ◽

pp. e12605

Author(s):

Tongtong Zhang ◽

Suyang Yu ◽

Shipeng Zhao

Keyword(s):

Gene Expression ◽

Gastric Cancer ◽

Survival Curve ◽

Enrichment Analysis ◽

Prognostic Indicator ◽

Diagnostic Value ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Clinicopathological Parameters ◽

The Relationship

Background Gastric cancer (GC) is the most prevalent malignancy among the digestive system tumors. Increasing evidence has revealed that lower mRNA expression of ANXA9 is associated with a poor prognosis in colorectal cancer. However, the role of ANXA9 in GC remains largely unknown. Material and Methods The Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas databases were used to investigate the expression of ANXA9 in GC, which was then validated in the four Gene Expression Omnibus (GEO) datasets. The diagnostic value of ANXA9 for GC patients was demonstrated using a receiver operating characteristic (ROC) curve. The correlation between ANXA9 expression and clinicopathological parameters was analyzed in The Cancer Genome Atlas (TCGA) and UALCAN databases. The Kaplan-Meier (K-M) survival curve was used to elucidate the relationship between ANXA9 expression and the survival time of GC patients. We then performed a gene set enrichment analysis (GSEA) to explore the biological functions of ANXA9. The relationship of ANXA9 expression and cancer immune infiltrates was analyzed using the Tumor Immune Estimation Resource (TIMER). In addition, the potential mechanism of ANXA9 in GC was investigated by analyzing its related genes. Results ANXA9 was significantly up-regulated in GC tissues and showed obvious diagnostic value. The expression of ANXA9 was related to the age, gender, grade, TP53 mutation, and histological subtype of GC patients. We also found that ANXA9 expression was associated with immune-related biological function. ANXA9 expression was also correlated with the infiltration level of CD8+ T cells, neutrophils, and dendritic cells in GC. Additionally, copy number variation (VNV) of ANXA9 occurred in GC patients. Function enrichment analyses revealed that ANXA9 plays a role in the GC progression by interacting with its related genes. Conclusions Our results provide strong evidence of ANXA9 expression as a prognostic indicator related to immune responses in GC.

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P13.03 Sex-specific influence of androgen receptor gene expression on survival of glioblastoma patients

Neuro-Oncology ◽

10.1093/neuonc/noab180.113 ◽

2021 ◽

Vol 23 (Supplement_2) ◽

pp. ii33-ii33

Author(s):

M Łysiak ◽

M Trybuła ◽

A Malmström ◽

M Mudaisi ◽

C Bratthäll ◽

...

Keyword(s):

Gene Expression ◽

Androgen Receptor ◽

Mrna Expression ◽

Pearson Correlation ◽

Genetic Alterations ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

University Hospital ◽

Cpg Sites ◽

Males And Females

Abstract BACKGROUND The mRNA and protein expression of androgen receptor (AR) are upregulated in glioblastoma (GBM) and studies show that use of AR antagonists leads to apoptosis of GBM cells in vitro and reduction of tumor volume in a mouse model. With increased prevalence of GBM among males, the role and genetic alterations of AR are worth investigating, especially taking into account the location of AR on chromosome X and possible sex differences associated with it. MATERIAL AND METHODS Copy number (CN) and mRNA expression of AR were tested with droplet digital PCR in 106 fresh frozen GBM samples (34 females and 72 males) collected at Linköping University Hospital. This cohort was also subjected to AR promoter methylation analysis, where 17 CpG sites were the target of pyrosequencing. Methylation levels were then correlated with mRNA gene expression, independently for each sex, using Pearson correlation coefficient. Gene expression of AR was also analyzed in The Cancer Genome Atlas cohort of primary IDH wild type GBM (135 females and 219 males) and association of AR expression and overall survival (OS) was tested with Kaplan-Meier log rank analysis after dichotomization by maximally selected rank statistics. RESULTS DNA amplifications, as well as deletions of the AR were detected, with a higher frequency of alterations found in females (26.4% vs. 8.3%). AR gene expression correlated with methylation levels of two CpG sites in females (chrX:67543271, chrX:67543762) and three different CpG sites in males (chrX:67543889, chrX:67543895, chrX:67543899). There was no difference in the AR expression between males and females in neither of the cohorts, but significantly higher AR expression was found in the classical subtype of GBM in TCGA. Survival analysis of the TCGA cohort revealed the opposite effect of AR expression on OS of males and females, with high AR expression correlating with shorter OS in females (13.6 vs.15.7 months, p=0.035) and longer OS in males (16.6 vs. 12.2 months, p=0.04). Additional gene set enrichment analysis of these samples showed that high AR expression was strongly correlated with DNA repair but only in the male group. CONCLUSION Our results show that high AR mRNA expression in GBM exhibits different effects on patients’ survival depending on their sex, despite common occurrence of high AR expression and CN changes in males and females. The reasons for potential protective influence of AR in males remain unclear and require further investigations.

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An Immune Cell-Based Signature Associating With EMT Phenotype Predicts Postoperative Overall Survival of ESCC

Frontiers in Oncology ◽

10.3389/fonc.2021.636479 ◽

2021 ◽

Vol 11 ◽

Author(s):

Hongliang Yu ◽

Dayong Gu ◽

Chao Yue ◽

Jianhua Xu ◽

Feng Yan ◽

...

Keyword(s):

Gene Expression ◽

Overall Survival ◽

Immune Cell ◽

Gene Set Enrichment Analysis ◽

M2 Macrophage ◽

M2 Macrophages ◽

Survival Times ◽

Training Set ◽

Mesenchymal Transition ◽

Validation Set

Esophageal squamous cell carcinoma (ESCC) is one of the deadliest solid malignancies and has a poor survival rate worldwide. In this study, we aimed to establish a tumor-infiltrating immune cell-based prognosis signature (IPS) to predict patients’ survival times and aid in the development of targeted therapies or immunotherapies. The abundances of 22 types of immune cells were determined by the CIBERSORT algorithm from ESCC patient gene expression data in the Gene Expression Omnibus (GEO) training set (n = 179) and The Cancer Genome Atlas (TCGA) validation set (n = 95). Then, the IPS was established by using the least absolute shrinkage and selection operator (LASSO) regression method. Kaplan-Meier analysis showed that patients with high IPS scores had significantly worse overall survival times than patients with low IPS scores in both the training set and the validation set (log-rank p = 0.001, and p = 0.050, respectively). Univariate and multivariate Cox regression analyses proved that the IPS was a robust prognostic factor for ESCC, independent of age, sex, tumor node metastasis (TNM) stage, pathology grade, and tumor location. In the mechanistic study, the epithelial-mesenchymal transition (EMT) process was identified by both gene set enrichment analysis (GSEA) and weighted correlation network analysis (WGCNA) as the underlying mechanism by which the IPS affects the prognosis of ESCC. After systematic correlation analyses, we found that M2 macrophages were the only cell type in the IPS significantly correlated with the EMT process. This relationship between M2 macrophage infiltration and the EMT phenotype was also confirmed by our preliminary immunochemistry (IHC) and multiplexed immunofluorescence study. In conclusion, we constructed an IPS that predicts the postoperative prognosis of ESCC patients and uncovered the critical role of M2 macrophages in the interplay between immune status and the EMT phenotype in ESCC.

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CLCA1 Has a Prognostic Indicator for the Colorectal Cancer by Weighted Gene Co-Expression Network Analysis

10.21203/rs.3.rs-209748/v1 ◽

2021 ◽

Author(s):

jiajng lin ◽

lingzhi yang ◽

suyong lin ◽

zhihua chen ◽

shaoqin chen

Keyword(s):

Gene Expression ◽

Colorectal Cancer ◽

Colon Cancer ◽

Network Analysis ◽

Mrna Expression ◽

Disease Free Survival ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cancer Tissue ◽

Hub Gene

Abstract Colorectal cancer (CRC) has become the second most common digestive tract tumor. Even though the means to treat colon cancer have improved, patients prognosis is low due to the lack of accurate molecular targets. Hence, it urgently demanded better biomarkers for prognosis and progression of colon cancer. This study explores the hub gene associated with the prognosis of colorectal cancer and further analyzes the hub gene function. In this study, all genes mRNA expression data were from the cancer genome atlas (TCGA) colon cancer database and the Gene Expression Omnibus (GEO). These databases were used to screen the differentially expressed co-genes between colon cancer tissue and normal tissue. Weighted Gene Co-expression Network Analysis screened out a total of 103 differential co-expression genes (WGCNA). According to the R cluster profile package annotation analysis, these genes biological functions mainly concentrate on energy metabolism. Moreover, in the protein-protein interaction (PPI) network, the CytoHubba plugin of Cytoscape was used to screen out ten genes (CLCA1, ZG16, GUCA2B, GUCA2A, CLCA4, SLC26A3, MS4A12, GCG, SI, and NR1H4). According to the survival analysis results, high expression of CLCA1has better overall survival and disease-free survival in patients with CRC. Simultaneously, the mRNA expression of CLCA1 in normal tissues was higher than that in CRC tissues. Besides, there were significant differences in the expression of CLCA1 in pathological stage, T stage, and M stage. By using a gene set enrichment analysis, we found several considerable enrichment pathways in the high-groups. CIBERSORT analysis for the proportion of TICs revealed that B-cell naive, dendritic cells, plasma cells, and CD4+ T cells were positively correlated with CLCA1 expression, suggesting that CLCA1 might be responsible for the preservation of immune-dominant status for TME. Finally, in the Human Protein Atlas (HPA) database, the protein level of CLCA1 in the colorectal cancer samples decreased, consistent with the down-regulation of the mRNA expression level CLCA1. To sum up, by integrating WGCNA with differential gene expression analysis, this research generated a significant survival correlative gene called CLCA1 that can predict prognosis prediction in colon cancer.

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The relationship between PLOD1 expression level and glioma prognosis investigated using public databases

PeerJ ◽

10.7717/peerj.11422 ◽

2021 ◽

Vol 9 ◽

pp. e11422

Author(s):

Lei Tian ◽

Huandi Zhou ◽

Guohui Wang ◽

Wen yan Wang ◽

Yuehong Li ◽

...

Keyword(s):

Gene Expression ◽

Expression Analysis ◽

Poor Prognosis ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

High Expression ◽

Expression Level ◽

Clinicopathologic Characteristics ◽

Genome Atlas

Background Glioma is the most common type of intracranial tumor with high malignancy and poor prognosis despite the use of various aggressive treatments. Targeted therapy and immunotherapy are not effective and new biomarkers need to be explored. Some Procollagen-lysine 2-oxyglutarate 5-dioxygenase (PLOD) family members have been found to be involved in the metastasis and progression of tumors. Both PLOD2 and PLOD3 had been reported to be highly expressed in gliomas, while the prognostic value of PLOD1 remains to be further illustrated, so we want to investigate the PLOD1 expression in glioma and its clinical implication. Methods We collected gene expression and corresponding clinical data of glioma from the Chinese Glioma Genome Atlas (CGGA) database, The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. First, we analyzed the expression and mutation of PLOD1 in gliomas and its relationship with clinicopathologic characteristics. Then, we conducted survival analysis, prognostic analysis and nomogram construction of the PLOD1 gene. Finally, we conducted gene ontology (GO) enrichment analysis and gene set enrichment analysis (GSEA) to explore possible mechanisms and gene co-expression analysis was also be performed. Results The results showed that the expression level of PLOD1 was higher in gliomas than normal tissues, and high expression of PLOD1 was related to poor survival which can serve as an oncogenic factor and an independent prognostic indicator for glioma patients. Both the GO and GSEA analysis showed high expression of PLOD1 were enriched in Extracellular matrix (ECM) related pathways, the co-expression analysis revealed that PLOD1 was positively related to HSPG2, COL6A2, COL4A2, FN1, COL1A1, COL4A1, CD44, COL3A1, COL1A2 and SPP1, and high expression of these genes were also correlated to poor prognosis of glioma. Conclusions The results showed that high expression of PLOD1 leads to poor prognosis, and PLOD1 is an independent prognostic factor and a novel biomarker for the treatment of glioma. Furthermore, targeting PLOD1 is most likely a potential therapeutic strategy for glioma patients.

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A Sparse and Low-Rank Regression Model for Identifying the Relationships Between DNA Methylation and Gene Expression Levels in Gastric Cancer and the Prediction of Prognosis

Genes ◽

10.3390/genes12060854 ◽

2021 ◽

Vol 12 (6) ◽

pp. 854

Author(s):

Yishu Wang ◽

Lingyun Xu ◽

Dongmei Ai

Keyword(s):

Gene Expression ◽

Gastric Cancer ◽

Dna Methylation ◽

Regression Model ◽

The Cancer Genome Atlas ◽

Low Rank ◽

Expression Levels ◽

Rank Regression ◽

Prediction Of Prognosis ◽

Gene Expression Levels

DNA methylation is an important regulator of gene expression that can influence tumor heterogeneity and shows weak and varying expression levels among different genes. Gastric cancer (GC) is a highly heterogeneous cancer of the digestive system with a high mortality rate worldwide. The heterogeneous subtypes of GC lead to different prognoses. In this study, we explored the relationships between DNA methylation and gene expression levels by introducing a sparse low-rank regression model based on a GC dataset with 375 tumor samples and 32 normal samples from The Cancer Genome Atlas database. Differences in the DNA methylation levels and sites were found to be associated with differences in the expressed genes related to GC development. Overall, 29 methylation-driven genes were found to be related to the GC subtypes, and in the prognostic model, we explored five prognoses related to the methylation sites. Finally, based on a low-rank matrix, seven subgroups were identified with different methylation statuses. These specific classifications based on DNA methylation levels may help to account for heterogeneity and aid in personalized treatments.

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ADAMTS12 acts as a tumor microenvironment related cancer promoter in gastric cancer

Scientific Reports ◽

10.1038/s41598-021-90330-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Yangming Hou ◽

Yingjuan Xu ◽

Dequan Wu

Keyword(s):

Gastric Cancer ◽

Tumor Microenvironment ◽

Immune Cell ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Tumor Promoter ◽

Protein Protein Interaction ◽

Oxidative Phosphorylation Pathway ◽

Cox Proportional Hazard Regression

AbstractThe infiltration degree of immune and stromal cells has been shown clinically significant in tumor microenvironment (TME). However, the utility of stromal and immune components in Gastric cancer (GC) has not been investigated in detail. In the present study, ESTIMATE and CIBERSORT algorithms were applied to calculate the immune/stromal scores and the proportion of tumor-infiltrating immune cell (TIC) in GC cohort, including 415 cases from The Cancer Genome Atlas (TCGA) database. The differentially expressed genes (DEGs) were screened by Cox proportional hazard regression analysis and protein–protein interaction (PPI) network construction. Then ADAMTS12 was regarded as one of the most predictive factors. Further analysis showed that ADAMTS12 expression was significantly higher in tumor samples and correlated with poor prognosis. Gene Set Enrichment Analysis (GSEA) indicated that in high ADAMTS12 expression group gene sets were mainly enriched in cancer and immune-related activities. In the low ADAMTS12 expression group, the genes were enriched in the oxidative phosphorylation pathway. CIBERSORT analysis for the proportion of TICs revealed that ADAMTS12 expression was positively correlated with Macrophages M0/M1/M2 and negatively correlated with T cells follicular helper. Therefore, ADAMTS12 might be a tumor promoter and responsible for TME status and tumor energy metabolic conversion.

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A novel prognostic model based on epithelial-mesenchymal transition-related genes predicts patient survival in gastric cancer

World Journal of Surgical Oncology ◽

10.1186/s12957-021-02329-9 ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Wanting Song ◽

Yi Bai ◽

Jialin Zhu ◽

Fanxin Zeng ◽

Chunmeng Yang ◽

...

Keyword(s):

Gene Expression ◽

Gastric Cancer ◽

Risk Model ◽

Cox Regression ◽

Epithelial Mesenchymal Transition ◽

Risk Groups ◽

The Cancer Genome Atlas ◽

Critical Function ◽

Mesenchymal Transition ◽

Patient Prognosis

Abstract Background Gastric cancer (GC) represents a major malignancy and is the third deathliest cancer globally. Several lines of evidence indicate that the epithelial-mesenchymal transition (EMT) has a critical function in the development of gastric cancer. Although plentiful molecular biomarkers have been identified, a precise risk model is still necessary to help doctors determine patient prognosis in GC. Methods Gene expression data and clinical information for GC were acquired from The Cancer Genome Atlas (TCGA) database and 200 EMT-related genes (ERGs) from the Molecular Signatures Database (MSigDB). Then, ERGs correlated with patient prognosis in GC were assessed by univariable and multivariable Cox regression analyses. Next, a risk score formula was established for evaluating patient outcome in GC and validated by survival and ROC curves. In addition, Kaplan-Meier curves were generated to assess the associations of the clinicopathological data with prognosis. And a cohort from the Gene Expression Omnibus (GEO) database was used for validation. Results Six EMT-related genes, including CDH6, COL5A2, ITGAV, MATN3, PLOD2, and POSTN, were identified. Based on the risk model, GC patients were assigned to the high- and low-risk groups. The results revealed that the model had good performance in predicting patient prognosis in GC. Conclusions We constructed a prognosis risk model for GC. Then, we verified the performance of the model, which may help doctors predict patient prognosis.

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