Identification of key pathways and candidate genes in gliomas by bioinformatics analysis

Gliomas account for a quarter of all primary brain and central nervous system tumors, and are always followed by a high mortality rate and very low life expectancy. However, genetic alterations nor molecular pathogenesis have not been clearly defined in gliomas. Herein, we applied a bioinformatics analysis to identify diagnostic biomarkers and reveal potential therapeutic targets for gliomas. In the present study, the microarray data set GSE31095 database was downloaded from the Gene Expression Omnibus (GEO), and a total of 244 DEGs were screened out from blood samples of human glioma patients, including 183 upregulated DEGs and 61 downregulated DEGs. Of which, CX3CR1, GZMB, and GZMA were the top three most up-regulated DEGs; WFDC1, FKBP5, and IL1R2 were the top three most down-regulated DEGs. Additionally, GO and KEGG analysis revealed that 244 DEGs were mainly enriched in 11 terms and 10 pathways. GZMB, CD48, and GZMA were screened as the top 3 hub genes in protein-protein interaction networks. Survival analysis by UALCAN showed high expression of CD48, GZMA, GZMH, IL2RB, KLRB1, LCK, LCP1, LEF1, NKG7, RPL18, TRAF3IP3 and ZAP70 that presented a better overall survival. Through identifying these candidate genes and pathways by bioinformatics analysis, this study sheds light on the pathogenic and prognostic molecular mechanisms of gliomas and may help us understand the underlying mechanism of gliomas, furthermore, providing clear candidates for clinical application.