Identification of a key glioblastoma candidate gene, FUBP3, based on weighted gene co-expression network analysis.

ABSTRACT:

Background

Glioblastoma multiforme (GBM) is the most common aggressive malignant brain tumor. However, the molecular mechanism of glioblastoma formation is still poorly understood. To identify candidate genes that may be connected to glioma growth and development, weighted gene co-expression network analysis (WGCNA) was performed to construct a gene co-expression network between gene sets and clinical characteristics. We also explored the function of the key candidate gene.

Methods

Two GBM datasets were selected from GEO Datasets. The R language was used to identify differentially expressed genes. WGCNA was performed to construct a gene co-expression network in the GEO glioblastoma samples. A custom Venn diagram website was used to find the intersecting genes. The GEPIA webs

SUBMITTER: Li J 

PROVIDER: S-EPMC9004042 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature