Identification of four hub genes as promising biomarkers to evaluate the prognosis of ovarian cancer in silico.

ABSTRACT:

Background

Ovarian cancer (OvCa) is one of the most fatal cancers among females in the world. With growing numbers of individuals diagnosed with OvCa ending in deaths, it is urgent to further explore the potential mechanisms of OvCa oncogenesis and development and related biomarkers.

Methods

The gene expression profiles of GSE49997 were downloaded from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was applied to explore the most potent gene modules associated with the overall survival (OS) and progression-free survival (PFS) events of OvCa patients, and the prognostic values of these genes were exhibited and validated based on data from training and validation sets. Next, protein-protein interaction (PPI) networks were built

SUBMITTER: Chen J 

PROVIDER: S-EPMC7315561 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature