Identification of novel prognostic targets in glioblastoma using bioinformatics analysis.

ABSTRACT:

Background

Glioblastoma (GBM) is the most malignant grade of glioma. Highly aggressive characteristics of GBM and poor prognosis cause GBM-related deaths. The potential prognostic biomarkers remain to be demonstrated. This research builds up predictive gene targets of expression alterations in GBM utilizing bioinformatics analysis.

Methods and results

The microarray datasets (GSE15824 and GSE16011) associated with GBM were obtained from Gene Expression Omnibus (GEO) database to identify the differentially expressed genes (DEGs) between GBM and non-tumor tissues. In total, 719 DEGs were obtained and subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) for function enrichment analysis. Furthermore, we constructed protein-protein Interaction (PPI)

SUBMITTER: Yin X 

PROVIDER: S-EPMC9014588 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature