A transcriptional co-expression network-based approach to identify prognostic biomarkers in gastric carcinoma.

ABSTRACT:

Background

Gastric carcinoma is a very diverse disease. The progression of gastric carcinoma is influenced by complicated gene networks. This study aims to investigate the actual and potential prognostic biomarkers related to survival in gastric carcinoma patients to further our understanding of tumor biology.

Methods

A weighted gene co-expression network analysis was performed with a transcriptome dataset to identify networks and hub genes relevant to gastric carcinoma prognosis. Data was obtained from 300 primary gastric carcinomas (GSE62254). A validation dataset (GSE34942 and GSE15459) and TCGA dataset confirmed the results. Gene ontology, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and gene set enrichment analysis (GSEA) were performe

SUBMITTER: Liu D 

PROVIDER: S-EPMC7025707 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature