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Analysis of DNA methylation-driven genes for predicting the prognosis of patients with colorectal cancer

Aberrant promoter methylation and ensuing abnormal gene expression are important epigenetic mechanisms that contribute to colorectal oncogenesis. Yet, the prognostic significance of such methylation-driven genes in colorectal cancer (CRC) remains obscure. Herein, a total of 181 genes were identified...

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Autores principales: Fu, Boshi, Du, Cheng, Wu, Zhikun, Li, Mingwei, Zhao, Yi, Liu, Xinli, Wu, Huizhe, Wei, Minjie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7746389/
https://www.ncbi.nlm.nih.gov/pubmed/33203797
http://dx.doi.org/10.18632/aging.103949
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author Fu, Boshi
Du, Cheng
Wu, Zhikun
Li, Mingwei
Zhao, Yi
Liu, Xinli
Wu, Huizhe
Wei, Minjie
author_facet Fu, Boshi
Du, Cheng
Wu, Zhikun
Li, Mingwei
Zhao, Yi
Liu, Xinli
Wu, Huizhe
Wei, Minjie
author_sort Fu, Boshi
collection PubMed
description Aberrant promoter methylation and ensuing abnormal gene expression are important epigenetic mechanisms that contribute to colorectal oncogenesis. Yet, the prognostic significance of such methylation-driven genes in colorectal cancer (CRC) remains obscure. Herein, a total of 181 genes were identified as the methylation-driven molecular features of CRC by integrated analysis of the expression profiles and the matched DNA methylation data from The Cancer Genome Atlas (TCGA) database. Among them, a five-gene signature (POU4F1, NOVA1, MAGEA1, SLCO4C1, and IZUMO2) was developed as a risk assessment model for predicting the clinical outcomes in CRC. The Kaplan–Meier analysis and Harrell’s C index demonstrated that the risk assessment model significantly distinguished the patients in high or low-risk groups (p-value < 0.0001 log-rank test, HR: 2.034, 95% CI: 1.419-2.916, C index: 0.655). The sensitivity and specificity were validated by the receiver operating characteristic (ROC) analysis. Furthermore, different pharmaceutical treatment responses were observed between the high-risk and low-risk groups. Indeed, the methylation-driven gene signature could act as an independent prognostic evaluation biomarker for assessing the OS of CRC patients and guiding the pharmaceutical treatment. Compared with known biomarkers, the methylation-driven gene signature could reveal cross-omics molecular features for improving clinical stratification and prognosis.
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spelling pubmed-77463892021-01-04 Analysis of DNA methylation-driven genes for predicting the prognosis of patients with colorectal cancer Fu, Boshi Du, Cheng Wu, Zhikun Li, Mingwei Zhao, Yi Liu, Xinli Wu, Huizhe Wei, Minjie Aging (Albany NY) Research Paper Aberrant promoter methylation and ensuing abnormal gene expression are important epigenetic mechanisms that contribute to colorectal oncogenesis. Yet, the prognostic significance of such methylation-driven genes in colorectal cancer (CRC) remains obscure. Herein, a total of 181 genes were identified as the methylation-driven molecular features of CRC by integrated analysis of the expression profiles and the matched DNA methylation data from The Cancer Genome Atlas (TCGA) database. Among them, a five-gene signature (POU4F1, NOVA1, MAGEA1, SLCO4C1, and IZUMO2) was developed as a risk assessment model for predicting the clinical outcomes in CRC. The Kaplan–Meier analysis and Harrell’s C index demonstrated that the risk assessment model significantly distinguished the patients in high or low-risk groups (p-value < 0.0001 log-rank test, HR: 2.034, 95% CI: 1.419-2.916, C index: 0.655). The sensitivity and specificity were validated by the receiver operating characteristic (ROC) analysis. Furthermore, different pharmaceutical treatment responses were observed between the high-risk and low-risk groups. Indeed, the methylation-driven gene signature could act as an independent prognostic evaluation biomarker for assessing the OS of CRC patients and guiding the pharmaceutical treatment. Compared with known biomarkers, the methylation-driven gene signature could reveal cross-omics molecular features for improving clinical stratification and prognosis. Impact Journals 2020-11-16 /pmc/articles/PMC7746389/ /pubmed/33203797 http://dx.doi.org/10.18632/aging.103949 Text en Copyright: © 2020 Fu et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Fu, Boshi
Du, Cheng
Wu, Zhikun
Li, Mingwei
Zhao, Yi
Liu, Xinli
Wu, Huizhe
Wei, Minjie
Analysis of DNA methylation-driven genes for predicting the prognosis of patients with colorectal cancer
title Analysis of DNA methylation-driven genes for predicting the prognosis of patients with colorectal cancer
title_full Analysis of DNA methylation-driven genes for predicting the prognosis of patients with colorectal cancer
title_fullStr Analysis of DNA methylation-driven genes for predicting the prognosis of patients with colorectal cancer
title_full_unstemmed Analysis of DNA methylation-driven genes for predicting the prognosis of patients with colorectal cancer
title_short Analysis of DNA methylation-driven genes for predicting the prognosis of patients with colorectal cancer
title_sort analysis of dna methylation-driven genes for predicting the prognosis of patients with colorectal cancer
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7746389/
https://www.ncbi.nlm.nih.gov/pubmed/33203797
http://dx.doi.org/10.18632/aging.103949
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