A comprehensive bioinformatics analysis to identify a candidate prognostic biomarker for ovarian cancer.

ABSTRACT:

Background

This study aimed to investigate prognostic genes in ovarian cancer (OC) and to explore their potential underlying biological mechanisms through a comprehensive bioinformatics analysis.

Methods

Common differentially expressed genes (DEGs) in 3 OC datasets from the Gene Expression Omnibus (GEO) (GSE26712, GSE18520, and GSE14407) were screened out. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed by Metascape. The protein-protein interaction (PPI) network of the DEGs was constructed using the STRING database. The prognostic value of DEGs were determined using the Kaplan-Meier plotter. The ONCOMINE and Human Protein Atlas databases were used to verify the expression levels of prognostic genes in OC. Genomic analysis

SUBMITTER: Zhu H 

PROVIDER: S-EPMC8797831 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature