Introduction: Glioblastoma (GBM) is among the deadliest tumors affecting the central nervous system (CNS) in adults. This type of primary brain tumor is known as the most aggressive, with a highly unfavorable prognosis in cases of recurrence and limited effective treatment options. One of the most common changes in human cancers is the occurrence of somatic mutations in the TP53 gene. This gene encodes the p53 protein, which functions as a tumor suppressor and plays a key role in various biological processes, including cell cycle arrest, senescence, apoptosis, autophagy, metabolism, and aging. The inactivation of the p53 tumor suppressor gene is a common event in cancer development, often resulting in a mutant protein that accumulates in cancer cells. These mutant proteins not only lose their tumor-suppressing functions but also gain oncogenic properties, promoting cell growth and survival. The aim of this study was to identify potential molecular biomarkers, including lncRNAs and miRNAs, that contribute to the early diagnosis of GBM, providing insight into novel therapeutic targets.
Methods: The GEO database was used for searching the best GEO datasets associated to GBM, and the data from two selected groups (Tumor vs. Control) were analyzed through GEO2R. Based on the data from the GSE186057 dataset in the GEO Database, the The TP53 gene pathway was analyzed using the KEGG and the interaction of involved proteins were analyzed in STRING databases. Associated miRNAs were identified using the miRWalk database. The interaction between miRNA and single nucleotide polymorphism (SNP) was assessed through the miRNASNP database. In addition, DIANA Tools database was conducted to reveal the interaction between miRNA and long non-coding RNA (lncRNA).
Results: According to the data from the GSE186057 dataset, TP53 gene was identified as having significant expression changes in GBM, and is considered one of the key genes involved in this disease. TP53 exhibited significant expression changes in tumor samples compared to control ones, highlighting its critical role in contributing to glioblastoma. The miRWalk database gave the most potential microRNA, hsa-miR-92a-1-5p, in regulation of TP53 gene expression, which can contribute to glioblastoma. This miRNA was selected based on its high number of base pair interactions and low binding free energy. Based on the data analysis in the miRNASNP database, rs890231900 was identified as the most relevant SNP interacting with hsa-miR-92a-1-5p. According to the analysis in the DIANA Tools database, lncRNA CASC2 interacts with hsa-miR-92a-1-5p in brain tissue, suggesting its role in the molecular regulation of glioblastoma.
Conclusion: In conclusion, this study identified TP53 gene, hsa-miR-92a-1-5p miRNA, SNP rs890231900, and lncRNA CASC2 as potential biomarkers for GBM through bioinformatics analysis. These biomarkers may play crucial roles in the molecular mechanisms underlying GBM progression and offer promising targets for early diagnosis and therapeutic interventions.