Glioblastoma Multiforme: A Meta-Analysis of Driver Genes, Current Diagnosis, and Tumor Heterogeneity

Abstract

Glioblastoma (GBM) is the most aggressive and common brain cancer in adults with the lowest life expectancy. The current neuro-oncology practice has incorporated genes involved in key molecular events that drive GBM tumorigenesis as biomarkers to guide diagnosis and design treatment. This study summarizes findings describing the significant heterogeneity of GBM at the transcriptional and genomic levels, emphasizing eighteen driver genes with clinical relevance. A pattern was identified fitting the stem cell model for GBM ontogenesis, with an up-regulation profile for MGMT and down-regulation for ATRX, H3F3A, TP53, and EGFR in the mesenchymal subtype. We also detected overexpression of EGFR, NES, VIM, and TP53 in the classical subtype and of MKi67 and OLIG2 genes in the proneural subtype. In keeping with this, we found a combination of eight biomarkers with a strong potential to determine the GBM molecular subtype. A unique distribution of somatic mutations was found for the young and adult population, particularly for genes related to DNA repair and chromatin remodeling, highlighting ATRX, MGMT, and IDH1. Our results also revealed that highly lesioned genes undergo differential regulation with particular biological pathways for young patients. This meta-analysis will help delineate future strategies related to the use of these molecular markers for clinical decision-making in the medical routine.

A novel necroptosis-related gene signature for predict prognosis of glioma based on single-cell and bulk RNA sequencing

“…Thioredoxininteracting protein (TXNIP) was reported as a tumorsuppressor gene in glioma (Zhang et al, 2017). VIM had been identified as a potential biopsy marker for glioma in several bioinformatics analyses (Gao et al, 2019;Wang J. J. et al, 2021;Herrera-Oropeza et al, 2021). Also, our results corroborated these analyses.…”