Journal of Proteomics & Bioinformatics
Open Access

Abstract

Identification of Potential Key Genes Associated with GBM using Computational Methods

Donthula Niveditha* and M Jahanavi

Glioblastoma multiforme (GBM) is a malignant tumor affecting the brain or spine, is a fast growing and aggressive brain tumor. There is a need to identify novel targets in GBM to improve our understanding of disease biology and that can be used for developing new therapeutics. Hence, the aim of our study was to explore key genes which are associated with GBM using computational methods. In the present study, we have constructed an interaction network of 159 genes in GBM. 13 out of 159 genes were selected as hub genes using topological analysis methods i.e. CYTOHUBBA and MCODE. Functional enrichment analysis for these 13 genes were performed using DAVID and found that the genes were enriched in various functions and pathways among which regulation of apoptotic process, cell proliferation were the most associated with it. Gene ontology analysis reveals that 14, 111 and 17 terms were found in the cellular process, biological process and molecular function respectively. The survival analysis for these 13 genes was performed using the Kaplan Meier plot. This revealed that 9 out of 13 hub genes were related to overall survival of GBM patients. VEGFA, TP53, STAT3, EGFR, NOTCH2, MMP9, MYC, HRAS, PTEN may serve as potential key genes which are associated with GBM for diagnosis, prognosis and treatment of GBM.

Published Date: 2021-08-30; Received Date: 2021-08-09