Open Access

Screening and identification of key biomarkers in bladder carcinoma: Evidence from bioinformatics analysis

  • Authors:
    • Meiqin Yan
    • Xuan Jing
    • Yina Liu
    • Xiangrong Cui
  • View Affiliations

  • Published online on: June 21, 2018     https://doi.org/10.3892/ol.2018.9002
  • Pages: 3092-3100
  • Copyright: © Yan et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Bladder cancer (BC) is one of the most common urogenital malignancies. However, present studies of its multiple gene interaction and cellular pathways remain unable to accurately verify the genesis and the development of BC. The aim of the present study was to investigate the genetic signatures of BC and identify its potential molecular mechanisms. The gene expression profiles of GSE31189 were downloaded from the Gene Expression Omnibus database. The GSE31189 dataset contained 92 samples, including 52 BC and 40 non‑cancerous urothelial cells. To further examine the biological functions of the identified differentially expressed genes (DEGs), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed, and a protein‑protein interaction (PPI) network was mapped using Cytoscape software. In total, 976 DEGs were identified in BC, including 457 upregulated genes and 519 downregulated genes. GO and KEGG pathway enrichment analyses indicated that upregulated genes were significantly enriched in the cell cycle and the negative regulation of the apoptotic process, while the downregulated genes were mainly involved in cell proliferation, cell adhesion molecules and oxidative phosphorylation pathways (P<0.05). From the PPI network, the 12 nodes with the highest degrees were screened as hub genes; these genes were involved in certain pathways, including the chemokine‑mediated signaling pathway, fever generation, inflammatory response and the immune response nucleotide oligomerization domain‑like receptor signaling pathway. The present study used bioinformatics analysis of gene profile datasets and identified potential therapeutic targets for BC.
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September-2018
Volume 16 Issue 3

Print ISSN: 1792-1074
Online ISSN:1792-1082

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Spandidos Publications style
Yan M, Jing X, Liu Y and Cui X: Screening and identification of key biomarkers in bladder carcinoma: Evidence from bioinformatics analysis. Oncol Lett 16: 3092-3100, 2018.
APA
Yan, M., Jing, X., Liu, Y., & Cui, X. (2018). Screening and identification of key biomarkers in bladder carcinoma: Evidence from bioinformatics analysis. Oncology Letters, 16, 3092-3100. https://doi.org/10.3892/ol.2018.9002
MLA
Yan, M., Jing, X., Liu, Y., Cui, X."Screening and identification of key biomarkers in bladder carcinoma: Evidence from bioinformatics analysis". Oncology Letters 16.3 (2018): 3092-3100.
Chicago
Yan, M., Jing, X., Liu, Y., Cui, X."Screening and identification of key biomarkers in bladder carcinoma: Evidence from bioinformatics analysis". Oncology Letters 16, no. 3 (2018): 3092-3100. https://doi.org/10.3892/ol.2018.9002