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has been cited by the following article:

• TITLE: Identification of Hub Genes in Prostate Cancer by Bioinformatics Analysis

  AUTHORS: Rui Zhang, Wenhua Guo, Luhong Yang

  KEYWORDS: Prostate Cancer (PCa), DEGs, Bioinformatics Analysis

  JOURNAL NAME: Open Access Library Journal, Vol.10 No.3, March 31, 2023

  ABSTRACT: Objective: To identify the candidate hub genes of prostate cancer (PCa) and investigate the relevance of the genes on the development of PCa by bioinformatics methods. Methods: The mRNA expression profile datasets GSE103512 was collected from GEO database, and find out differential expression genes (DEGs) between PCa and normal tissues using the GEO2R tool. Subsequently, to further elucidate the interaction of DEGs and screen the hub genes, we conducted GO and KEGG enrichment analysis by DAVID 6.8 database, and constructed protein-protein interaction (PPI) network by the STRING database. The GEPIA database was utilized to analyze the expression levels of hub genes in PCa and normal tissues. Results: A total of 755 DEGs were identified, including 211 upregulated genes and 544 downregulated genes. GO analysis was mainly enriched in extracellular exosome, glutathione metabolic process, and composition of organelle membranes. Fatty acid metabolism, metabolic pathways, and cGMP-PKG signaling pathways were mainly enriched signaling pathways based on KEGG analysis. Ten hub genes were obtained by analyzing the PPI network using cytoHubba plug-in of Cytoscape software. CDH1, CD24, ACACA, and SCD were upregulated in PCa tissues, whereas VEGFA was downregulated in PCa tissues. Conclusion: 10 hub genes of PCa were screened out by bioinformatical analysis in this study and are expected to play crucial roles in the treatment of PCa.