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Integrative Analysis of Identifying Methylation-Driven Genes Signature Predicts Prognosis in Colorectal Carcinoma
BACKGROUND: Aberrant DNA methylation is a critical regulator of gene expression and plays a crucial role in the occurrence, progression, and prognosis of colorectal cancer (CRC). We aimed to identify methylation-driven genes by integrative epigenetic and transcriptomic analysis to predict the progno...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8231008/ https://www.ncbi.nlm.nih.gov/pubmed/34178621 http://dx.doi.org/10.3389/fonc.2021.629860 |
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author | Huang, Hao Fu, Jinming Zhang, Lei Xu, Jing Li, Dapeng Onwuka, Justina Ucheojor Zhang, Ding Zhao, Liyuan Sun, Simin Zhu, Lin Zheng, Ting Jia, Chenyang Cui, Binbin Zhao, Yashuang |
author_facet | Huang, Hao Fu, Jinming Zhang, Lei Xu, Jing Li, Dapeng Onwuka, Justina Ucheojor Zhang, Ding Zhao, Liyuan Sun, Simin Zhu, Lin Zheng, Ting Jia, Chenyang Cui, Binbin Zhao, Yashuang |
author_sort | Huang, Hao |
collection | PubMed |
description | BACKGROUND: Aberrant DNA methylation is a critical regulator of gene expression and plays a crucial role in the occurrence, progression, and prognosis of colorectal cancer (CRC). We aimed to identify methylation-driven genes by integrative epigenetic and transcriptomic analysis to predict the prognosis of CRC patients. METHODS: Methylation-driven genes were selected for CRC using a MethylMix algorithm and LASSO regression screening strategy, and were further used to construct a prognostic risk-assessment model. The Cancer Genome Atlas (TCGA) database was obtained as the training set for both the screening of methylation-driven genes and the effect of genes signature on CRC prognosis. Then, the prognostic genes signature was validated in three independent expression arrays of CRC data from Gene Expression Omnibus (GEO). RESULTS: We identified 143 methylation-driven genes, of which the combination of BATF, PHYHIPL, RBP1, and PNPLA4 expression levels was screened as a better prognostic model with the best area under the curve (AUC) (AUC = 0.876). Compared with patients in the low-risk group, CRC patients in the high-risk group had significantly poorer overall survival in the training set (HR = 2.184, 95% CI: 1.404–3.396, P < 0.001). Similar results were observed in the validation set. Moreover, VanderWeele’s mediation analysis indicated that the effect of methylation on prognosis was mediated by the levels of their expression (HR(indirect) = 1.473, P = 0.001, Proportion mediated, 69.10%). CONCLUSIONS: We identified a four-gene prognostic signature by integrative analysis and developed a risk-assessment model that is significantly associated with patients’ survival. Methylation-driven genes might be a potential prognostic signature for CRC patients. |
format | Online Article Text |
id | pubmed-8231008 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82310082021-06-26 Integrative Analysis of Identifying Methylation-Driven Genes Signature Predicts Prognosis in Colorectal Carcinoma Huang, Hao Fu, Jinming Zhang, Lei Xu, Jing Li, Dapeng Onwuka, Justina Ucheojor Zhang, Ding Zhao, Liyuan Sun, Simin Zhu, Lin Zheng, Ting Jia, Chenyang Cui, Binbin Zhao, Yashuang Front Oncol Oncology BACKGROUND: Aberrant DNA methylation is a critical regulator of gene expression and plays a crucial role in the occurrence, progression, and prognosis of colorectal cancer (CRC). We aimed to identify methylation-driven genes by integrative epigenetic and transcriptomic analysis to predict the prognosis of CRC patients. METHODS: Methylation-driven genes were selected for CRC using a MethylMix algorithm and LASSO regression screening strategy, and were further used to construct a prognostic risk-assessment model. The Cancer Genome Atlas (TCGA) database was obtained as the training set for both the screening of methylation-driven genes and the effect of genes signature on CRC prognosis. Then, the prognostic genes signature was validated in three independent expression arrays of CRC data from Gene Expression Omnibus (GEO). RESULTS: We identified 143 methylation-driven genes, of which the combination of BATF, PHYHIPL, RBP1, and PNPLA4 expression levels was screened as a better prognostic model with the best area under the curve (AUC) (AUC = 0.876). Compared with patients in the low-risk group, CRC patients in the high-risk group had significantly poorer overall survival in the training set (HR = 2.184, 95% CI: 1.404–3.396, P < 0.001). Similar results were observed in the validation set. Moreover, VanderWeele’s mediation analysis indicated that the effect of methylation on prognosis was mediated by the levels of their expression (HR(indirect) = 1.473, P = 0.001, Proportion mediated, 69.10%). CONCLUSIONS: We identified a four-gene prognostic signature by integrative analysis and developed a risk-assessment model that is significantly associated with patients’ survival. Methylation-driven genes might be a potential prognostic signature for CRC patients. Frontiers Media S.A. 2021-06-11 /pmc/articles/PMC8231008/ /pubmed/34178621 http://dx.doi.org/10.3389/fonc.2021.629860 Text en Copyright © 2021 Huang, Fu, Zhang, Xu, Li, Onwuka, Zhang, Zhao, Sun, Zhu, Zheng, Jia, Cui and Zhao 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 Huang, Hao Fu, Jinming Zhang, Lei Xu, Jing Li, Dapeng Onwuka, Justina Ucheojor Zhang, Ding Zhao, Liyuan Sun, Simin Zhu, Lin Zheng, Ting Jia, Chenyang Cui, Binbin Zhao, Yashuang Integrative Analysis of Identifying Methylation-Driven Genes Signature Predicts Prognosis in Colorectal Carcinoma |
title | Integrative Analysis of Identifying Methylation-Driven Genes Signature Predicts Prognosis in Colorectal Carcinoma |
title_full | Integrative Analysis of Identifying Methylation-Driven Genes Signature Predicts Prognosis in Colorectal Carcinoma |
title_fullStr | Integrative Analysis of Identifying Methylation-Driven Genes Signature Predicts Prognosis in Colorectal Carcinoma |
title_full_unstemmed | Integrative Analysis of Identifying Methylation-Driven Genes Signature Predicts Prognosis in Colorectal Carcinoma |
title_short | Integrative Analysis of Identifying Methylation-Driven Genes Signature Predicts Prognosis in Colorectal Carcinoma |
title_sort | integrative analysis of identifying methylation-driven genes signature predicts prognosis in colorectal carcinoma |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8231008/ https://www.ncbi.nlm.nih.gov/pubmed/34178621 http://dx.doi.org/10.3389/fonc.2021.629860 |
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