Identification of hub genes and biological pathways in glioma via integrated bioinformatics analysis.

ABSTRACT:

Objective

Glioma is the most common intracranial primary malignancy, but its pathogenesis remains unclear.

Methods

We integrated four eligible glioma microarray datasets from the gene expression omnibus database using the robust rank aggregation method to identify a group of significantly differently expressed genes (DEGs) between glioma and normal samples. We used these DEGs to explore key genes closely associated with glioma survival through weighted gene co-expression network analysis. We then constructed validations of prognosis and survival analyses for the key genes via multiple databases. We also explored their potential biological functions using gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA).

Results

We selected DLGAP5, C

SUBMITTER: Chen L 

PROVIDER: S-EPMC9189557 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature