Bioinformatics analysis of gene expression profiles to diagnose crucial and novel genes in glioblastoma multiform.

Therefore, the current study aimed to diagnose the genes associated in the pathogenesis of GBM. The differentially expressed genes (DEGs) were diagnosed using the limma software package. The ToppFun was used to perform pathway and Gene Ontology (GO) enrichment analysis of the DEGs. Protein-protein interaction (PPI) networks, extracted modules, miRNA-target genes regulatory network and miRNA-target genes regulatory network were used to obtain insight into the actions of DEGs. Survival analysis for DEGs carried out. A total of 701 DEGs, including 413 upregulated and 288 downregulated genes, were diagnosed between U1118MG cell line (PK 11195 treated with 1 h exposure) and U1118MG cell line (PK 11195 treated with 24 h exposure). The up-regulated genes were enriched in superpathway of pyrimidine deoxyribonucleotides de novo biosynthesis, cell cycle, cell cycle process and chromosome. The down-regulated genes were enriched in folate transformations I, biosynthesis of amino acids, cellular amino acid metabolic process and vacuolar membrane. The current study screened the genes in PPI network, extracted modules, miRNA-target genes regulatory network and miRNA-target genes regulatory network with higher degrees as hub genes, which included MYC, TERF2IP, CDK1, EEF1G, TXNIP, SLC1A5, RGS4 and IER5L Survival suggested that low expressed NR4A2, SLC7 A5, CYR61 and ID1 in patients with GBM was linked with a positive prognosis for overall survival. In conclusion, the current study could improve our understanding of the molecular mechanisms in the progression of GBM, and these crucial as well as new molecular markers might be used as therapeutic targets for GBM.