Identification of upregulated genes in glioblastoma and glioblastoma cancer stem cells using bioinformatics analysis

by Selleckchem | Dec 29 2023

Glioblastoma (GBM) is the most common malignant brain tumor among adults. Cancer stem cells (CSCs) are known to drive treatment resistance and recurrence. However, a few CSC markers have been identified as therapeutic targets for GBM. This study aimed to show highly coexpressed genes in GBM CSCs and TCGA GBM samples and to identify possible therapeutic targets for GBM. The gene expression profiles of GBM CSCs were obtained from Gene Expression Omnibus database. After the differentially upregulated genes were screened, functional enrichment analyses were performed using DAVID and Reactome databases. For upregulated genes, biological processes were mainly associated with the regulation of transcription. Subsequently, a protein-protein interaction network was constructed for upregulated genes through STRING, in which DUSP6, FGFR3, EGFR, SOX2, NES, and PLP1 were further identified as hub genes via MCC and MNC methods. Expression profiles of hub genes and their association with survival were examined in TCGA GBM dataset using GEPIA2 platform. The expression levels of four hub genes were found to be increased in TCGA GBM samples. Of these, DUSP6 and SOX2 had prognostic value for patients with GBM. Molecular compounds targeting DUSP6 were searched through PubChem database. (E/Z)-BCI and BCI were found to be inhibitors of DUSP6. The molecular docking was performed using Autodock vina 1.02. The compounds showed strong binding capacities by forming various interactions with the ERK2 binding domain of DUSP6. Hence, the current study unravels the potential of (E/Z)-BCI and BCI compounds as possible anti-cancer molecules for GBM treatment.

Comments:

That's an intricate and detailed study! It's fascinating how it combines bioinformatics, molecular biology, and computational analysis to identify potential therapeutic targets for glioblastoma.

Identifying highly coexpressed genes in cancer stem cells (CSCs) and their correlation with GBM samples from TCGA is a promising approach. The focus on DUSP6, FGFR3, EGFR, SOX2, NES, and PLP1 as hub genes through protein-protein interaction analysis is intriguing. Their increased expression levels in GBM samples, especially with prognostic value for DUSP6 and SOX2, could provide valuable insights into prognosis and potential treatment avenues.

The search for molecular compounds targeting DUSP6 using databases like PubChem and subsequent molecular docking studies with (E/Z)-BCI and BCI compounds is a significant step. The observation of strong binding capacities with the ERK2 binding domain of DUSP6 suggests the potential efficacy of these compounds as anti-cancer molecules for GBM treatment.

This study's multi-layered approach—from gene expression profiling to functional enrichment analysis, protein interaction network construction, survival analysis in TCGA datasets, and molecular docking—provides a comprehensive framework for identifying and validating potential therapeutic targets for GBM. It's a great example of how diverse methodologies can converge to reveal promising candidates for further research and potential clinical applications.