Related Experiment Video
Updated: Dec 18, 2025

Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Published on: November 2, 2013
The Identification of Key Gene Expression Signature in Prostate Cancer
Yu Huang1, Qi Cao1, Zhengshuai Song1
1Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Abstract:
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.

