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The identification of age-associated cancer markers by an integrative analysis of dynamic DNA methylation changes
As one of the most widely studied epigenetic modifications, DNA methylation has an important influence on human traits and cancers. Dynamic variations in DNA methylation have been reported in malignant neoplasm and aging; however, the mechanisms remain poorly understood. By constructing an age-assoc...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4779991/ https://www.ncbi.nlm.nih.gov/pubmed/26949191 http://dx.doi.org/10.1038/srep22722 |
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author | Wang, Yihan Zhang, Jingyu Xiao, Xingjun Liu, Hongbo Wang, Fang Li, Song Wen, Yanhua Wei, Yanjun Su, Jianzhong Zhang, Yunming Zhang, Yan |
author_facet | Wang, Yihan Zhang, Jingyu Xiao, Xingjun Liu, Hongbo Wang, Fang Li, Song Wen, Yanhua Wei, Yanjun Su, Jianzhong Zhang, Yunming Zhang, Yan |
author_sort | Wang, Yihan |
collection | PubMed |
description | As one of the most widely studied epigenetic modifications, DNA methylation has an important influence on human traits and cancers. Dynamic variations in DNA methylation have been reported in malignant neoplasm and aging; however, the mechanisms remain poorly understood. By constructing an age-associated and cancer-related weighted network (ACWN) based on the correlation of the methylation level and the protein-protein interaction, we found that DNA methylation changes associated with age were closely related to the occurrence of cancer. Additional analysis of 102 module genes mined from the ACWN revealed discrimination based on two main patterns. One pattern involved methylation levels that increased with aging and were higher in cancer patients compared with normal controls (HH pattern). The other pattern involved methylation levels that decreased with aging and were lower in cancer compared with normal (LL pattern). Upon incorporation with gene expression levels, 25 genes were filtered based on negative regulation by DNA methylation. These genes were regarded as potential cancer risk markers that were influenced by age in the process of carcinogenesis. Our results will facilitate further studies regarding the impact of the epigenetic effects of aging on diseases and will aid in the development of tailored cancer preventive strategies. |
format | Online Article Text |
id | pubmed-4779991 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-47799912016-03-09 The identification of age-associated cancer markers by an integrative analysis of dynamic DNA methylation changes Wang, Yihan Zhang, Jingyu Xiao, Xingjun Liu, Hongbo Wang, Fang Li, Song Wen, Yanhua Wei, Yanjun Su, Jianzhong Zhang, Yunming Zhang, Yan Sci Rep Article As one of the most widely studied epigenetic modifications, DNA methylation has an important influence on human traits and cancers. Dynamic variations in DNA methylation have been reported in malignant neoplasm and aging; however, the mechanisms remain poorly understood. By constructing an age-associated and cancer-related weighted network (ACWN) based on the correlation of the methylation level and the protein-protein interaction, we found that DNA methylation changes associated with age were closely related to the occurrence of cancer. Additional analysis of 102 module genes mined from the ACWN revealed discrimination based on two main patterns. One pattern involved methylation levels that increased with aging and were higher in cancer patients compared with normal controls (HH pattern). The other pattern involved methylation levels that decreased with aging and were lower in cancer compared with normal (LL pattern). Upon incorporation with gene expression levels, 25 genes were filtered based on negative regulation by DNA methylation. These genes were regarded as potential cancer risk markers that were influenced by age in the process of carcinogenesis. Our results will facilitate further studies regarding the impact of the epigenetic effects of aging on diseases and will aid in the development of tailored cancer preventive strategies. Nature Publishing Group 2016-03-07 /pmc/articles/PMC4779991/ /pubmed/26949191 http://dx.doi.org/10.1038/srep22722 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Wang, Yihan Zhang, Jingyu Xiao, Xingjun Liu, Hongbo Wang, Fang Li, Song Wen, Yanhua Wei, Yanjun Su, Jianzhong Zhang, Yunming Zhang, Yan The identification of age-associated cancer markers by an integrative analysis of dynamic DNA methylation changes |
title | The identification of age-associated cancer markers by an integrative analysis of dynamic DNA methylation changes |
title_full | The identification of age-associated cancer markers by an integrative analysis of dynamic DNA methylation changes |
title_fullStr | The identification of age-associated cancer markers by an integrative analysis of dynamic DNA methylation changes |
title_full_unstemmed | The identification of age-associated cancer markers by an integrative analysis of dynamic DNA methylation changes |
title_short | The identification of age-associated cancer markers by an integrative analysis of dynamic DNA methylation changes |
title_sort | identification of age-associated cancer markers by an integrative analysis of dynamic dna methylation changes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4779991/ https://www.ncbi.nlm.nih.gov/pubmed/26949191 http://dx.doi.org/10.1038/srep22722 |
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