Exploring the potential biomarkers for prognosis of glioblastoma via weighted gene co-expression network analysis.

ABSTRACT:

Background

Glioblastoma (GBM) is the most common malignant tumor in the central system with a poor prognosis. Due to the complexity of its molecular mechanism, the recurrence rate and mortality rate of GBM patients are still high. Therefore, there is an urgent need to screen GBM biomarkers to prove the therapeutic effect and improve the prognosis.

Results

We extracted data from GBM patients from the Gene Expression Integration Database (GEO), analyzed differentially expressed genes in GEO and identified key modules by weighted gene co-expression network analysis (WGCNA). GSE145128 data was obtained from the GEO database, and the darkturquoise module was determined to be the most relevant to the GBM prognosis by WGCNA (r =  - 0.62, p = 0.01). We performed enrich

SUBMITTER: Zhang M 

PROVIDER: S-EPMC8781321 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature