A Potential Prognostic Gene Signature for Predicting Survival for Glioblastoma Patients.

ABSTRACT:

Objective

This study aimed to screen prognostic gene signature of glioblastoma (GBM) to construct prognostic model.

Methods

Based on the GBM information in the Cancer Genome Atlas (TCGA, training set), prognostic genes (Set X) were screened by Cox regression. Then, the optimized prognostic gene signature (Set Y) was further screened by the Cox-Proportional Hazards (Cox-PH). Next, two prognostic models were constructed: model A was based on the Set Y; model B was based on part of the Set X. The samples were divided into low- and high-risk groups according to the median prognosis index (PI). GBM datasets in Gene Expression Ominous (GEO, GSE13041) and Chinese Glioma Genome Atlas (CGGA) were used as the testing datasets to confirm the prognostic models constructed based on TCGA.

SUBMITTER: Hou Z 

PROVIDER: S-EPMC6457303 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature