A glance at glioblastoma molecular culprits through in-silico analysis

Abstract

Background: Glioblastoma multiforme (GBM) is the most malignant type of brain tumor derived from astrocytes. According to the World Health Organization (WHO), it is considered a grade IV tumor. Due to the heterogenic causative of GBM, the identification of novel biomarkers could help better prognosis and improve therapeutic methods in cancerous patients. The expression profile data analysis has been able to identify highly altered expression level genes associated with GBM. The present study aims to introduce the most potent module and identify the hub genes and tip miRNAs associated with gliomagenesis. Methods: Differentially expressed genes (DEGs) were obtained from three GEO datasets, including 40 glioblastoma samples and 20 normal brain tissues. Next, using the GEO2R tool, DEGs between glioblastoma tissues and standard brain samples were picked out. Finally, using in silico analysis, the hub genes, and the most significant miRNAs which target these hubs were selected. Results: 32 DEGs based on protein-protein interaction (PPI) and molecular functions were considered as hub genes. SNAP25 is supposed to have a critical role in mechanisms underlying glioblastoma. Four miRNAs were introduced as novel potential biomarkers according to the number of miRNA-hubs interaction numbers. Conclusion: This bioinformatics analysis study provided a better understanding of the mechanisms underlying glioblastoma. However, further studies are needed to find the exact molecular mechanisms in tumorigenesis of this type of high-grade glioma.