Identification key genes influence cell cycle process in glioma by bioinformatics analysis

Abstract The aim of the present study was to identify key genes that influence cell cycle in gliomas by bioinformatics analysis, these genes may play an important role in tumorigenesis. We downloaded GSE50161 and GSE4290 from the gene expression omnibus (GEO) dataset and then with the using of GEO Diver web tool, 1882 differential expressed genes (DEGs) included 662 up-regulated genes and 1220 down-regulated genes were identified between 117 glioma samples and 13 normal brain tissue samples. Subsequently, the top 50 genes with the most significant difference were selected to construct protein-protein interaction (PPI) network, and functional enrichment analysis was carried out. Most of these genes such as WEE1, CDK1, PBK, CCNB2, NUSAP1, MELK, KIAA0101, TOP2A and CAMK2A had been shown to be involved in cell cycle process. Then Gene Ontology (GO) and Kyoto Encyclopedia were performed. Protein-protein interaction (PPI) networks and pathway analysis were also conducted. Furthermore, CDK1, TPO2A, NUSAP1, PBK and CHEK1 genes were identified with the higher degrees in protein-protein interaction network and enriched in cell cycle. We verified these genes in GSE4290. Further on, overall survival analysis showed the prognostic value of these genes and we confirmed the low expression of CAMK2A and CDK1 in glioma tissues on TCGA and the Human Protein Atlas database. In conclusion, these genes associated with the cell cycle process such as CAMK2A, CDK1, PBK, WEE1 and CHEK1 may play an important role in the occurrence and development of glioma.