Transcriptome analysis revealed CENPF associated with glioma prognosis

Area of Science:

• Neuro-oncology
• Molecular Biology
• Bioinformatics

Background:

• Gliomas are aggressive central nervous system tumors with poor prognosis despite current treatments.
• Understanding the molecular mechanisms driving glioma progression is crucial for developing effective therapies.

Purpose of the Study:

• To identify key molecular mechanisms and potential biomarkers involved in glioma development and progression.
• To analyze differentially expressed genes (DEGs) and core modules in glioma using bioinformatics approaches.

Main Methods:

• Utilized Gene Expression Omnibus (GEO) datasets and GEO2R for DEG identification.
• Performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis.
• Constructed protein-protein interaction (PPI) networks and identified hub genes using STRING, MCODE, and CytoHubba.

Main Results:

• Identified a core module of 428 DEGs significantly enriched in pathways like 'cell cycle' and 'p53 signaling pathway'.
• Highlighted AURKA, CDC20, CDK1, CENPF, and TOP2A as top modular genes associated with glioma.
• CENPF emerged as an independent prognostic factor and was significantly enriched in multiple cancer-related pathways, including cell cycle and glioma pathways.

Conclusions:

• CENPF is a critical gene implicated in glioma development and progression.
• CENPF shows potential as a candidate biomarker for glioma.
• The identified molecular pathways provide insights into glioma pathogenesis.