Abstract
Background:Bladder cancer(BC) is one of the most common tumors worldwide. Its incidence and mortality rate rank first in urological malignancies. Due to the lack of credible predictors, most patients are not timely diagnosed and treated. Moreover, in the past 30 years, the clinical treatment of BC had seen little progress, and the 5-year survival rates of patients were flat.Therefore,identifying novel potential markers or therapeutic targets are urgently required for the diagnosis and prognosis of BC.Methods: The BC gene expression chip data (GSE121711)were downloaded from the GEO database and the BLCA RNA-seq data were downloaded from the TCGA database. The differentially expressed genes (DEGs) were identified by R software using limma package and the edgeR package, and obtained the overlapped DEGs from two databases. Then, the Gene Ontology(GO) function analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of overlapped DEGs were performed through DAVID database, and the protein–protein interaction(PPI) network was constructed to screen Hub genes for regulatory protein expression in BC. Expression and prognostic analysis of the hub genes were performed by UALCAN and Kaplan-Meier plotter.Results: A total of 372 overlap DEGs were obtained, of which 93 were up-regulated and 279 were down-regulated. These genes were mainly associated with the function and pathway enrichment such as glycosaminoglycan binding, vasculature development, Cell cycle, Proteoglycans in cancer. The protein-protein interaction network analysis obtained 12 hub genes. Among these hub genes,HMMR,NCAPG2,SMC4, TROAP were closely related to the survival rate of bladder cancer patients revealed that these genes might be the key genes play an important role in the occurrence and progression.Conclusion:Therefore, our current studies demonstrated thatHMMR, NCAPG2, SMC4, TROAP are potential prognostic biomarkers for BC.In the future, these may also become clinical therapeutic targets.