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Critical Reviews™ in Eukaryotic Gene Expression
IF: 2.156 5-Year IF: 2.255 SJR: 0.649 SNIP: 0.599 CiteScore™: 3

ISSN Print: 1045-4403
ISSN Online: 2162-6502

Critical Reviews™ in Eukaryotic Gene Expression

DOI: 10.1615/CritRevEukaryotGeneExpr.2020029243
pages 153-168

The Identification of Key Gene Expression Signature in Prostate Cancer

Yu Huang
Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
Qi Cao
Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
Zhengshuai Song
Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
Hailong Ruan
Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
Keshan Wang
Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
Ke Chen
Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
Xiaoping Zhang
Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China


Prostate cancer (PCa) is one of the most common malignancies affecting men's health worldwide. The aim of this study is to identify key genes and their regulatory networks and evaluate the usefulness of these genes on diagnosis of and prognosis for prostate cancer. The gene expression microarray dataset GSE55945 was downloaded for analysis. The differentially expressed genes (DEGs) were accessed with RStudio. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using the database for annotation, visualization and integrated discovery (DAVID) database. A protein-protein interaction network was carried out using STRING. The survival and diagnostic analysis of hub genes were conducted using the cancer genome atlas (TCGA) data. Finally, we identified 387 DEGs. GO and KEGG analyses reveled that the DEGs in PCa were mainly enriched in the bone morphogenetic protein (BMP) signaling pathway and cytochrome P450. Among 15 hub genes, we found that only a different expression level of MYH11 affected patient survival. And further gene set enrichment analysis (GSEA) showed that low expression of MYH11 was associated with the cell cycle, DNA replication, TGF-P1 signal pathway, and PCa. In conclusion, we identified 387 DEGs that may be involved in core pathways such as the BMP pathway and cytochrome P450, which may contribute to the progression of PCa. In addition, hub gene MYH11 has the potential to be a novel biomarker for diagnosing and determining the prognosis for PCa.

KEY WORDS: MYH11, biomarker, survival


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