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Identification of key pathways and genes influencing prognosis in bladder urothelial carcinoma

Authors Ning X, Deng Y

Received 31 December 2016

Accepted for publication 15 February 2017

Published 20 March 2017 Volume 2017:10 Pages 1673—1686


Checked for plagiarism Yes

Review by Single-blind

Peer reviewer comments 3

Editor who approved publication: Dr Carlos E Vigil

Xin Ning, Yaoliang Deng

Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Province, People’s Republic of China

Background: Genomic profiling can be used to identify the predictive effect of genomic subsets for determining prognosis in bladder urothelial carcinoma (BUC) after radical cystectomy. This study aimed to investigate potential gene and pathway markers associated with prognosis in BUC.
Methods: A microarray dataset of BUC was obtained from The Cancer Genome Atlas database. Differentially expressed genes (DEGs) were identified by DESeq of the R platform. Kaplan–Meier analysis was applied for prognostic markers. Key pathways and genes were identified using bioinformatics tools, such as gene set enrichment analysis, gene ontology, the Kyoto Encyclopedia of Genes and Genomes, gene multiple association network integration algorithm (GeneMANIA), Search Tool for the Retrieval of Interacting Genes/Proteins, and Molecular Complex Detection.
Results: A comparative gene set enrichment analysis of tumor and adjacent normal tissues suggested BUC tumorigenesis resulted mainly from enrichment of cell cycle and DNA damage and repair-related biological processes and pathways, including TP53 and mitotic recombination. Two hundred and fifty-six genes were identified as potential prognosis-related DEGs. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed that the potential prognosis-related DEGs were enriched in angiogenesis, including the cyclic adenosine monophosphate biosynthetic process, cyclic guanosine monophosphate-protein kinase G, mitogen-activated protein kinase, Rap1, and phosphoinositide-3-kinase-AKT signaling pathway. Nine hub genes, TAGLN, ACTA2, MYH11, CALD1, MYLK, GEM, PRELP, TPM2, and OGN, were identified from the intersection of protein–protein interaction and GeneMANIA networks. Module analysis of protein–protein interaction and GeneMANIA networks mainly showed enrichment of the cyclic guanosine monophosphate-protein kinase G signaling pathway, angiogenesis, cell proliferation, and differentiation, which are associated with tumor angiogenesis and cancer prognosis.
Conclusion: Genes and pathways related to cell cycle and DNA damage and repair may play a crucial role in BUC pathogenesis, whereas those pertaining to tumor angiogenesis may be key factors in influencing BUC prognosis, especially in advanced disease stages.

Keywords: bioinformatics analytical tools, bladder urothelial carcinoma, microarray, differentially expressed gene, prognosis

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