Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Hou, Yaxin, Hu, Junyi, Zhou, Lijie, Liu, Lilong, Chen, Ke, Yang, Xiong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8047072/
https://www.ncbi.nlm.nih.gov/pubmed/33869043
http://dx.doi.org/10.3389/fonc.2021.647253
_version_ 1783678969538674688
author Hou, Yaxin
Hu, Junyi
Zhou, Lijie
Liu, Lilong
Chen, Ke
Yang, Xiong
author_facet Hou, Yaxin
Hu, Junyi
Zhou, Lijie
Liu, Lilong
Chen, Ke
Yang, Xiong
author_sort Hou, Yaxin
collection PubMed
description 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.
format Online
Article
Text
id pubmed-8047072
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-80470722021-04-16 Integrative Analysis of Methylation and Copy Number Variations of Prostate Adenocarcinoma Based on Weighted Gene Co-expression Network Analysis Hou, Yaxin Hu, Junyi Zhou, Lijie Liu, Lilong Chen, Ke Yang, Xiong Front Oncol Oncology 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. Frontiers Media S.A. 2021-04-01 /pmc/articles/PMC8047072/ /pubmed/33869043 http://dx.doi.org/10.3389/fonc.2021.647253 Text en Copyright © 2021 Hou, Hu, Zhou, Liu, Chen and Yang. https://creativecommons.org/licenses/by/4.0/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.
spellingShingle Oncology
Hou, Yaxin
Hu, Junyi
Zhou, Lijie
Liu, Lilong
Chen, Ke
Yang, Xiong
Integrative Analysis of Methylation and Copy Number Variations of Prostate Adenocarcinoma Based on Weighted Gene Co-expression Network Analysis
title Integrative Analysis of Methylation and Copy Number Variations of Prostate Adenocarcinoma Based on Weighted Gene Co-expression Network Analysis
title_full Integrative Analysis of Methylation and Copy Number Variations of Prostate Adenocarcinoma Based on Weighted Gene Co-expression Network Analysis
title_fullStr Integrative Analysis of Methylation and Copy Number Variations of Prostate Adenocarcinoma Based on Weighted Gene Co-expression Network Analysis
title_full_unstemmed Integrative Analysis of Methylation and Copy Number Variations of Prostate Adenocarcinoma Based on Weighted Gene Co-expression Network Analysis
title_short Integrative Analysis of Methylation and Copy Number Variations of Prostate Adenocarcinoma Based on Weighted Gene Co-expression Network Analysis
title_sort integrative analysis of methylation and copy number variations of prostate adenocarcinoma based on weighted gene co-expression network analysis
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8047072/
https://www.ncbi.nlm.nih.gov/pubmed/33869043
http://dx.doi.org/10.3389/fonc.2021.647253
work_keys_str_mv AT houyaxin integrativeanalysisofmethylationandcopynumbervariationsofprostateadenocarcinomabasedonweightedgenecoexpressionnetworkanalysis
AT hujunyi integrativeanalysisofmethylationandcopynumbervariationsofprostateadenocarcinomabasedonweightedgenecoexpressionnetworkanalysis
AT zhoulijie integrativeanalysisofmethylationandcopynumbervariationsofprostateadenocarcinomabasedonweightedgenecoexpressionnetworkanalysis
AT liulilong integrativeanalysisofmethylationandcopynumbervariationsofprostateadenocarcinomabasedonweightedgenecoexpressionnetworkanalysis
AT chenke integrativeanalysisofmethylationandcopynumbervariationsofprostateadenocarcinomabasedonweightedgenecoexpressionnetworkanalysis
AT yangxiong integrativeanalysisofmethylationandcopynumbervariationsofprostateadenocarcinomabasedonweightedgenecoexpressionnetworkanalysis