Identification of potential therapeutic targets and biomarkers for glioblastomas through integrative analysis of gene expression data
• Identified seven immune-related hub genes as glioblastoma therapeutic targets. • Discovered six novel VEGFA inhibitors with potential to overcome drug resistance. • Two repurposed drugs, Sunitinib and Ticlopidine, show promise for glioblastoma treatment. • Highlighted down-regulated genes as potential biomarkers for glioblastoma prognosis. • Immune pathway modulation and VEGFA targeting proposed to enhance patient outcomes. In this study, we conducted a comprehensive analysis of differential gene expression data from studies GSE15824, GSE4290 and GEPIA2 data to identify up-regulated hub genes with potential as therapeutic targets for glioblastomas. Through virtual screening, we also aimed to identify novel VEGFA inhibitors. Seven up-regulated hub genes (TYROBP, ITGB2, C1QA, C1QB, CTSS, TLR2, and CD163) were identified. Virtual screening of VEGFA inhibitors led to the discovery of six significant hits, including three from the ChemDiv library (D519–0372, G868–0191, and Y031–5201) and three from the ZINC20 database (ZINC57658, ZINC57652, ZINC57679). Molecular dynamics simulations highlighted G868–0191 as the most stable VEGFA inhibitor. Two repurposed drugs, Sunitinib and Ticlopidine hydrochloride, were also identified as potential candidates. In addition, the down-regulated hub genes GABARAPL1, OPTN, and CDH8 were proposed as potential biomarkers for glioblastomas. This study underscores the significance of immune-related hub genes in glioblastoma pathology and suggests new VEGFA inhibitors as promising therapeutic agents. The identification of down-regulated genes as potential biomarkers offers further avenues for clinical application. However, experimental validation is needed to confirm the clinical utility of these findings.
Authors
- R. Romero
- Angélica Bautista
Institutions
- Optimal Solutions (United States) (US)
Publication Details
- Journal
- Next research.
- Published
- 2025-02-26
- DOI
- https://doi.org/10.1016/j.nexres.2025.100221
- Citations
- 1
- Primary Topic
- Bioinformatics and Genomic Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.81