Identification of candidate biomarkers associated with gastric cancer prognosis based on an integrated bioinformatics analysis.

ABSTRACT:

Background

This study sought to identify candidate biomarkers associated with gastric cancer (GC) prognosis based on an integrated bioinformatics analysis.

Methods

First, the GSE54129 and GSE79973 data sets were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) identified between the 2 data sets were screened using the limma software package in R, and the intersection DEGs were obtained by a Venn analysis. Subsequently, gene clustering and a functional analysis were performed to explore the roles of the DEGs. The protein-protein interaction (PPI) network of the genes in clusters was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins. A survival analysis evaluated the associations between the c

SUBMITTER: Liu Y 

PROVIDER: S-EPMC9459179 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature