Identifying Key Pathogenic Mechanisms in Recurrent Glioblastoma Through Bioinformatics Analysis

Area of Science:

• Neuro-oncology
• Genomics
• Bioinformatics

Background:

• Glioblastoma frequently recurs despite aggressive treatments.
• Identifying molecular drivers of recurrence is crucial for improving patient outcomes.

Purpose of the Study:

• To identify key genes, microRNAs (miRNAs), and mRNA regulatory networks in recurrent glioblastoma.
• To nominate potential repurposable drugs for treating glioblastoma recurrence.

Main Methods:

• Differential gene expression analysis of primary vs. recurrent glioblastoma.
• Construction of protein-protein interaction networks and miRNA-mRNA interaction networks.
• Utilized Connectivity Map (CMap) for drug repurposing and Kaplan-Meier analysis for survival outcomes.

Main Results:

• Identified 201 differentially expressed genes (DEGs) and 10 hub genes.
• Synaptotagmin 1 (SYT1) was identified as a hub gene, targeted by 12 miRNAs, with elevated expression linked to poorer survival.
• Five compounds (levamisole, chlorzoxazone, ranitidine, atovaquone, chrysin) were nominated as potential therapeutics.

Conclusions:

• SYT1 and its upstream miRNAs are potential biomarkers and therapeutic targets for recurrent glioblastoma.
• Repurposable compounds warrant experimental validation for glioblastoma treatment.
• Findings provide a foundation for personalized glioblastoma therapies.