Original Research ARTICLE
Transcriptome analysis identifies Piwi-interacting RNAs as prognostic markers for recurrence of prostate cancer
- 1Sichuan University, China
Prostate cancer remains the second leading cause of male cancer death and there is an unmet need for biomarkers to identify patients with such aggressive disease. Piwi-inteacting RNAs (piRNAs) has been classified as transcriptional and post-transcriptional regulators of gene expression in somatic cells. In this study, we discovered three piRNAs as novel independent prognostic markers and their association with prostate cancer biochemical recurrence (BCR) was confirmed in an independent validation dataset. To obtain a better understanding of piRNA expression patterns in prostate cancer and to find genes co-expression with piRNA, we performed weighted gene co-expression network analysis (WGCNA). Target genes of three piRNAs have also been predicted based on base complementarity and expression correlativity. Functional analysis revealed the relationships between target genes and prostate cancer. Our work also identified differential expression of piRNAs between Gleason stage 3+4 and 4+3 prostate cancer. Overall, this study may explain the roles and demonstrate the potential clinical utility of piRNAs in prostate cancer in a way.
Keywords: piRNA, prostate cancer, biomarker, survival analysis, WGCNA
Received: 23 Jan 2019;
Accepted: 24 Sep 2019.
Copyright: © 2019 Zuo, Liang, Zhang, Hao, Li, Wen and Zhao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Prof. Zhining Wen, Sichuan University, Chengdu, 610065, Sichuan Province, China, firstname.lastname@example.org
Prof. Yun Zhao, Sichuan University, Chengdu, 610065, Sichuan Province, China, email@example.com