A 6-Gene Risk Signature Predicts Survival of Glioblastoma Multiforme.

ABSTRACT:

Background

This study aims to develop novel signatures for glioblastoma multiforme (GBM).

Methods

GBM expression profiles from The Cancer Genome Atlas (TCGA) were downloaded and DEGs between tumor and normal samples were identified by differential expression analysis (DEA). A risk signature was developed by applying weighted gene coexpression network analysis (WGCNA) and Cox regression analysis. Patients were divided into high and low risk group, followed by evaluating the performance of the signature via Kaplan-Meier curve analysis. In addition, the prognostic significance of the signature was further validated using an independent validation dataset from Chinese Glioma Genome Atlas (CGGA). DEGs between high and low risk group were subjected to functional annotation.

Res

SUBMITTER: Zhao J 

PROVIDER: S-EPMC6720050 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature