Identification and interaction analysis of key genes, microRNAs and Pathways in Glioblastoma cell lines by bioinformatics analysis

Introduction: Glioblastoma has a high mortality and prevalence among brain tumors and has a poor prognosis and an average survival of about 8 to 10 months. To select the most effective treatment and strategies for malignant glioma, understanding the molecular mechanisms, genetic and metabolic pathways involved seems very necessary and important. The aim of this study was to find the association of decrease or elevated genes in glioblastoma cell lines with metabolic pathways and genes involved in glioblastoma.Methods: The microarray datasets GSE50173,GSE9171 and GSE15824 was composed of gene expression data using the [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array(GPL570) were downloaded from the GEO database. Each dataset was processed using the log2 transformation and normalization with Package Affy and RMA in R software. P.value <0.05 was set as the cutoff criteria for differently expressed genes (DEGs). DEGs with P.value <0.05 and fold change (|FC|)> 2 in all three datasets were selected as biomarkers. Then Functional and pathway enrichment analyses were performed using the BioDB and EnrichR databases, and the protein–protein interaction (PPI) network was constructed using the Cytoscape software.Results: The total of about 35446 Gene that in the three dataset with expression changes significantly (P Value less than 0.05), there were approximately 67 genes Up regulation with log Fold change more than 2 and about 683 genes Down regulation with log Fold change less than -2. To assess the function of the DEGs, the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses from EnrichR with adjusted. p-value <0.05 showed that up regulated genes were significantly enriched in cytosolic part , ribosome , focal adhesion and The down regulated genes were significantly enriched in RNA binding , insulin receptor binding , double-stranded DNA binding . at end identify MicroRNA contact with down regulate genes with adjusted. p-value <0.05 (In miRTarBase and TargetScan_microRNA) for example: hsa-miR-155-5p , hsa-miR-192-5p, hsa-miR-16-5p .Conclusions: Bioinformatics analysis such as BioDB database, GO biological process, GO molecular function, Kyoto encyclopedia of genes, revealed that target genes of differentially expressed genes and miRNAs in glioblastoma cell lines were connected to pivotal biological pathways.

Keywords:

GBM , Glioblastoma cell line , bioinformatics analysis , enrichment analysis