Integrative Analysis of Methylation and Copy Number Variations of Prostate Adenocarcinoma Based on Weighted Gene Co-expression Network Analysis

• Main Authors: Yaxin Hou, Junyi Hu, Lijie Zhou, Lilong Liu, Ke Chen, Xiong Yang
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2021-04-01
• Series: Frontiers in Oncology
• Subjects: bioinformatics analysis; prostate adenocarcinoma; biomarker; prognosis; therapeutic target
• Online Access: https://www.frontiersin.org/articles/10.3389/fonc.2021.647253/full

Prostate adenocarcinoma (PRAD) is the most pervasive carcinoma diagnosed in men with over 170,000 new cases every year in the United States and is the second leading cause of death from cancer in men despite its indolent clinical course. Prostate-specific antigen testing, which is the most commonly used non-invasive diagnostic method for PRAD, has improved early detection rates in the past decade, but its effectiveness for monitoring disease progression and predicting prognosis is controversial. To identify novel biomarkers for these purposes, we carried out weighted gene co-expression network analysis of the top 10,000 variant genes in PRAD from The Cancer Genome Atlas in order to identify gene modules associated with clinical outcomes. Methylation and copy number variation analysis were performed to screen aberrantly expressed genes, and the Kaplan–Meier survival and gene set enrichment analyses were conducted to evaluate the prognostic value and potential mechanisms of the identified genes. Cyclin E2 (CCNE2), rhophilin Rho GTPase-binding protein (RHPN1), enhancer of zeste homolog 2 (EZH2), tonsoku-like DNA repair protein (TONSL), epoxide hydrolase 2 (EPHX2), fibromodulin (FMOD), and solute carrier family 7 member (SLC7A4) were identified as potential prognostic indicators and possible therapeutic targets as well. These findings can improve diagnosis and disease monitoring to achieve better clinical outcomes in PRAD.