Identify Key Genes and Construct the lncRNA-miRNA-mRNA Regulatory Networks Associated with Glioblastoma by Bioinformatics Analysis.

Introduction: Glioblastoma is the most common and aggressive brain tumor, with low survival rates and high recurrence rates. Therefore, it is crucial to understand the precise molecular mechanisms involved in the oncogenesis of glioblastoma.

Material And Methods: To investigate the regulatory mechanisms of long non-coding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (miRNA) network related to glioblastoma, in the present study, a comprehensive analysis of the genomic landscape between glioblastoma and normal brain tissues from the Gene Expression Omnibus (GEO) dataset was first conducted to identify differentially expressed genes (DEGs) in glioblastoma. Following a series of analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, protein-protein interaction (PPI), and key model analyses. In addition, we used the L1000CDS2 database bioinformatic tool to identify candidates for therapy based on glioblastoma specific genetic profile.

Results: In our results, 100 key genes, 50 upregulated and 50 downregulated, were ultimately identified. The results of KEGG pathway enrichment gene analysis showed that the five regulatory pathways. Furthermore, 3 small molecule signatures (trichostatin A, TG-101348, and vorinostat) were recommended as the top-ranked candidate therapeutic agents. Nevertheless, the constructed miRNA-mRNA network revealed a convergence on 40 miRNAs. We found that dysregulation of lncRNAs such as KCNQ1OT1 and RP11-13N13.5 could sequester several miRNAs such as hsa-miR-27a-3p, hsamiR- 27b-3p, hsa-miR-106a-5p, etc., and promote the development and progression of glioblastoma.

Conclusions: Our study identified key genes and related lncRNA-miRNA-mRNA network that contribute to the oncogenesis of glioblastoma.