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Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Published on: November 2, 2013
Identification of castration-resistant prostate cancer-related hub genes using weighted gene co-expression network
Yifei Cheng1,2, Lu Li3, Zongshi Qin4
1Department of Urologic Surgery, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China.
Abstract:
Prostate cancer is the most common malignancy in urinary system and brings heavy burdens in men. We downloaded gene expression profile of mRNA and related clinical data of GSE70768 data set from public database. Weighted gene co-expression network analysis (WGCNA) was used to identify the relationships between gene modules and clinical features, as well as the candidate genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were developed to investigate the potential functions of related hub genes. Importantly, basic experiments were performed to verify the relationship between hub genes and the phenotype previously identified. Lastly, copy number variation (CNV) analysis was conducted to explore the genetical alteration. WGCNA identified that black module was the most relevant module which was tightly related to castration-resistant prostate cancer (CRPC) phenotype. KEGG and GO analysis results revealed genes in black module were mainly related to RNA splicing. Additionally, 9 genes were chosen as hub genes and heterogeneous nuclear ribonucleoprotein A2/B1 (HNRNPA2B1), golgin A8 family member B (GOLGA8B) and mitogen-activated protein kinase 8 interacting protein 3 (MAPK8IP3) were identified to be associated with PCa progression and prognosis. Moreover, all above three genes were highly expressed in CRPC-like cells and their suppression led to hindered cell proliferation in vitro. Finally, CNV analysis found that amplification was the main type of alteration of the 3 hub genes. Our study found that HNRNPA2B1, GOLGA8B and MAPK8IP3 were identified to be tightly associated with tumour progression and prognosis, and further researches are needed before clinical application.

