Glioblastomas (GBM), having a poor prognosis, are some of the most aggressive intracranial tumors in adults. Through advances in bioinformatic analysis, precise candidate biomarkers can be screened out effectively. To explore hub genes and related signaling pathways of GBM, gene expression profiles were downloaded from The Cancer Genome Atlas (TCGA) dataset and Gene Expression Omnibus (GEO) datasets GSE15824 and GSE90886. Differentially expressed genes (DEGs) were identified using the Edger package in the R software. Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed for DEGs through the DAVID database. Subsequently, target genes were predicted using the Venn Diagram package in the R software. Next, correlation analysis of public database GSE15824 was examined to evaluate the correlation between expression of NDC80 and levels of other target genes. Finally, the R2: Genomics Analysis and Visualization Platform was probed to study the association of expression of NDC80, CDC45, KIF2C, WEE1, OIP5, CD74, PRKCG, and other hub genes with overall survival (OS) of patients with GBM. DEGs were mainly enriched in cell division, cell proliferation, mitotic cell cycle, epithelial to mesenchymal transition, P53, and MAPK signaling pathways. A total of 15 overlapping DEGs were screened among these 3 datasets. A total of 8 were certified to be related to prognosis of patients with GBM. NDC80 was significantly positively correlated with cell division and mitotic cell cycle markers CCNB1, NUF2, KNTC1, OIP5, WEE1, KIF2C and PLK1, but inversely related to OTUD7A. Therefore, functional and pathway enrichment analysis may reveal the pathogenesis and progression of GBM. NDC80, CDC45, KIF2C, WEE1, OIP5, CD74, PRKCG and WNT1 are expected to be important molecular targets for early diagnosis, therapeutics, and prognosis of patients with GBM.