Glioblastoma (GBM) is the most aggressive intracranial tumors. Despite the comprehensive treatments, the median survival of GBM patients is still dismal. Consequently, it is critical to explore potential biomarkers and underlying molecular mechanisms of GBM. We integrated two datasets (GSE19728 and GSE 4290) to identify differentially expressed genes (DEGs) of GBM. Eighty-two GBM samples and 31 brain normal samples were screened by using GEO2R and Draw Venn Diagram. We carried out Database for Annotation, Visualization and Integrated Discovery (DAVID) to analyze gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) to analyze the DEGs. To further screen hub genes, protein-protein interaction (PPI) of these DEGs was visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING). GEPIA and UALCAN website were utilized to identify the hub genes expression and survival data. In total, 568 common DEGs were determined, including 141 upregulated genes and 427 downregulated genes. Thirty-five hub genes were identified in the highest module consisting of 35 nodes and 535 edges, which are mainly associated with cell cycle, p53 signaling pathway. According to the further analysis results of hub genes, we found that the PDZ-binding kinase (PBK) gene had a high expression and significantly worse survival in GBM contrasted to brain normal samples (P < 0.05). PBK could be a potential prognostic factor and therapeutic target for GBM treatment. In the future, the potential biomarkers for significant prognostic information can be preliminarily assessed using this method, although further experimentations are needed to verify the results.
Keywords: Biomarker; Glioblastoma (GBM); PBK; Prognosis.