Molecular dissection of glioblastoma: Identification of prognostic hub genes through integrated bioinformatics analysis

Objectives: Glioblastoma multiforme (GBM) is the deadliest and therapeutically challenging primary brain malignancies, with dismal prognosis. Identifying robust molecular drivers is critical to improving prognostic accuracy and developing targeted therapies. Material and Methods: An integrative bioinformatics pipeline was implemented, starting with the retrieval of GBM-associated genes from GeneCards and DisGeNET. Protein-protein interaction networks were constructed using STRING and analyzed in Cytoscape through CytoNCA for centrality measures. Functional enrichment analyses (Gene ontology, kyoto encyclopedia of genes and genomes) characterized biological roles. Gene expression profiles were assessed using the cancer genome atlas datasets. Kaplan–Meier survival analysis on 22 hub genes guided the selection of core genes. Core hub genes were evaluated for promoter methylation profiling, immune cell infiltration correlation, and genomic alteration mapping using cBioPortal and TISIDB as well as protein expression validation using Human Protein Atlas. Results: From 464 GBM-related genes, 22 hub genes were identified through network centrality metrics. Expression profiling revealed 14 significantly dysregulated genes in GBM versus normal brain tissue. Promoter methylation analysis indicated interleukin-1 beta hypomethylation and tumor necrosis factor hypermethylation. Four core hub genes – ACTB, CASP3, ERBB2 , and GAPDH – were overexpressed, associated with immune infiltration and genetic alterations. Kaplan–Meier analysis demonstrated significant prognostic impact: ACTB ( P = 0.029, hazard ratio [HR] =1.5), CASP3 ( P = 0.033, HR =1.5), ERBB2 ( P = 0.038, HR =1.5), and GAPDH ( P = 0.023, HR =1.5), linking high expression to reduced overall survival. Protein-level validation reinforced transcriptomic findings. Conclusion: ACTB, CASP3, ERBB2, and GAPDH emerge as key regulators in GBM progression, contributing to cytoskeletal remodeling, apoptosis resistance, immune modulation, and metabolic adaptation. These genes hold promise as prognostic biomarkers and therapeutic targets for GBM.