Open Access

Screening and identification of key biomarkers in prostate cancer using bioinformatics

  • Authors:
    • Song Li
    • Junqing Hou
    • Weibo Xu
  • View Affiliations

  • Published online on: November 6, 2019     https://doi.org/10.3892/mmr.2019.10799
  • Pages: 311-319
  • Copyright: © Li et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Prostate cancer (PCa) is the second most common cancer amongst males worldwide. In the current study, microarray datasets GSE3325 and GSE6919 from the Gene Expression Omnibus database were screened to identify candidate genes that are associated with the progression of PCa. A total of 273 differentially expressed genes (DEGs) were identified, which included 173 downregulated genes and 100 upregulated genes, and a protein‑protein interaction network was constructed using Search Tool for the Retired of Interacting Genes. The enriched functions and pathways of the identified DEGs included cell adhesion, the negative regulation of cell proliferation, protein binding and focal adhesion. A total of 8 hub genes were identified, of which PDZ binding kinase, Krüppel‑like factor 4, collagen type XII α‑1 chain, RAP1A and RAP39B were indicated to be associated with the progression and recurrence of PCa. In conclusion, the DEGs and hub genes identified in the present study may aid in determining the molecular mechanisms associated with PCa carcinogenesis and progression.
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January-2020
Volume 21 Issue 1

Print ISSN: 1791-2997
Online ISSN:1791-3004

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Spandidos Publications style
Li S, Hou J and Xu W: Screening and identification of key biomarkers in prostate cancer using bioinformatics. Mol Med Rep 21: 311-319, 2020
APA
Li, S., Hou, J., & Xu, W. (2020). Screening and identification of key biomarkers in prostate cancer using bioinformatics. Molecular Medicine Reports, 21, 311-319. https://doi.org/10.3892/mmr.2019.10799
MLA
Li, S., Hou, J., Xu, W."Screening and identification of key biomarkers in prostate cancer using bioinformatics". Molecular Medicine Reports 21.1 (2020): 311-319.
Chicago
Li, S., Hou, J., Xu, W."Screening and identification of key biomarkers in prostate cancer using bioinformatics". Molecular Medicine Reports 21, no. 1 (2020): 311-319. https://doi.org/10.3892/mmr.2019.10799