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Application Of Weighted Gene Co-Expression Network Analysis(WGCNA)in Exploring The Prognosis-Related Genes Of Gastric Adenocarcinoma

Posted on:2021-09-17Degree:MasterType:Thesis
Country:ChinaCandidate:X H ZhengFull Text:PDF
GTID:2504306308983089Subject:Oncology
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BackgroundWGCNA is a statistical method widely used in recent years to explore gene co-expression modules.The competing endogenous RNA(ceRNA)is one of the most common gene expression regulation mechanisms among cancer.A handful of ceRNA networks has been recognized in gastric cancer,however,the prognosis-associated ceRNA network has not been fully identified using WGCNA.MethodsWe performed the weighted correlation network analysis(WGCNA)analysis in datasets of The Cancer Genome Atlas(TCGA)and the Genotype-Tissue Expression(GTEx)to identify the cancer-associated modules.Differential analysis was performed between normal stomach samples and gastric cancer samples with the standard of false discovery rate(FDR)<0.01 and |fold change(FC)|>1.3.The ceRNA relationships obtained from the RNAinter database were examined by both the Pearson correlation tests and the hypergeometric tests to confirmed the regulation of mRNA-lncRNA in gastric cancer.Overlapped genes were recognized in the intersection of genes predicted by the ceRNA relationships,differentially expressed genes,genes in the cancer-specific modules,which then were put into the univariate and multivariate cox analysis to construct the risk-score model.The ceRNA network was constructed based on genes in the risk-model model.ResultsWGCNA uncovered genes in the green and turquoise module are the most cancer-associated ones in gastric cancer.80 cancer-associated different expressed genes were found to have potential prognostic value,which further led to the identification of 12 prognosis-related mRNAs(KIF15,FEN1,ZFP69B,SP6,SPARC,TTF2,MSI2,KYNU,ACLY,KIF21B,SLC12A7,and ZNF823)for constructing a risk score model.The risk genes were validated by the datasets of the GSE62254 and GSE84433 using 0.82 as the universal cut-off value.Finally,12 genes,12 lncRNAs,and 35 miRNAs were used to build a ceRNA network with 86 dysregulated lncRNA-mRNA ceRNA pairs.ConclusionsWe discovered a ceRNA network constructed by both prognosis-related and cancer-associated co-expression genes using WGCNA,which may deliver novel insight into the treatment method of gastric cancer.
Keywords/Search Tags:gastric cancer, risk score, ceRNA, WGCNA, gene signature
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