Screening and identification of key biomarkers in prostate cancer using bioinformatics.

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.

journal_name

Mol Med Rep

authors

Li S,Hou J,Xu W

doi

10.3892/mmr.2019.10799

subject

Has Abstract

pub_date

2020-01-01 00:00:00

pages

311-319

issue

1

eissn

1791-2997

issn

1791-3004

journal_volume

21

pub_type

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