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The Dynamics of DNA Methylation Covariation Patterns in Carcinogenesis

Recently it has been observed that cancer tissue is characterised by an increased variability in DNA methylation patterns. However, how the correlative patterns in genome-wide DNA methylation change during the carcinogenic progress has not yet been explored. Here we study genome-wide inter-CpG corre...

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Autores principales: Teschendorff, Andrew E., Liu, Xiaoping, Caren, Helena, Pollard, Steve M., Beck, Stephan, Widschwendter, Martin, Chen, Luonan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4091688/
https://www.ncbi.nlm.nih.gov/pubmed/25010556
http://dx.doi.org/10.1371/journal.pcbi.1003709
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author Teschendorff, Andrew E.
Liu, Xiaoping
Caren, Helena
Pollard, Steve M.
Beck, Stephan
Widschwendter, Martin
Chen, Luonan
author_facet Teschendorff, Andrew E.
Liu, Xiaoping
Caren, Helena
Pollard, Steve M.
Beck, Stephan
Widschwendter, Martin
Chen, Luonan
author_sort Teschendorff, Andrew E.
collection PubMed
description Recently it has been observed that cancer tissue is characterised by an increased variability in DNA methylation patterns. However, how the correlative patterns in genome-wide DNA methylation change during the carcinogenic progress has not yet been explored. Here we study genome-wide inter-CpG correlations in DNA methylation, in addition to single site variability, during cervical carcinogenesis. We demonstrate how the study of changes in DNA methylation covariation patterns across normal, intra-epithelial neoplasia and invasive cancer allows the identification of CpG sites that indicate the risk of neoplastic transformation in stages prior to neoplasia. Importantly, we show that the covariation in DNA methylation at these risk CpG loci is maximal immediately prior to the onset of cancer, supporting the view that high epigenetic diversity in normal cells increases the risk of cancer. Consistent with this, we observe that invasive cancers exhibit increased covariation in DNA methylation at the risk CpG sites relative to normal tissue, but lower levels relative to pre-cancerous lesions. We further show that the identified risk CpG sites undergo preferential DNA methylation changes in relation to human papilloma virus infection and age. Results are validated in independent data including prospectively collected samples prior to neoplastic transformation. Our data are consistent with a phase transition model of carcinogenesis, in which epigenetic diversity is maximal prior to the onset of cancer. The model and algorithm proposed here may allow, in future, network biomarkers predicting the risk of neoplastic transformation to be identified.
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spelling pubmed-40916882014-07-18 The Dynamics of DNA Methylation Covariation Patterns in Carcinogenesis Teschendorff, Andrew E. Liu, Xiaoping Caren, Helena Pollard, Steve M. Beck, Stephan Widschwendter, Martin Chen, Luonan PLoS Comput Biol Research Article Recently it has been observed that cancer tissue is characterised by an increased variability in DNA methylation patterns. However, how the correlative patterns in genome-wide DNA methylation change during the carcinogenic progress has not yet been explored. Here we study genome-wide inter-CpG correlations in DNA methylation, in addition to single site variability, during cervical carcinogenesis. We demonstrate how the study of changes in DNA methylation covariation patterns across normal, intra-epithelial neoplasia and invasive cancer allows the identification of CpG sites that indicate the risk of neoplastic transformation in stages prior to neoplasia. Importantly, we show that the covariation in DNA methylation at these risk CpG loci is maximal immediately prior to the onset of cancer, supporting the view that high epigenetic diversity in normal cells increases the risk of cancer. Consistent with this, we observe that invasive cancers exhibit increased covariation in DNA methylation at the risk CpG sites relative to normal tissue, but lower levels relative to pre-cancerous lesions. We further show that the identified risk CpG sites undergo preferential DNA methylation changes in relation to human papilloma virus infection and age. Results are validated in independent data including prospectively collected samples prior to neoplastic transformation. Our data are consistent with a phase transition model of carcinogenesis, in which epigenetic diversity is maximal prior to the onset of cancer. The model and algorithm proposed here may allow, in future, network biomarkers predicting the risk of neoplastic transformation to be identified. Public Library of Science 2014-07-10 /pmc/articles/PMC4091688/ /pubmed/25010556 http://dx.doi.org/10.1371/journal.pcbi.1003709 Text en © 2014 Teschendorff et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Teschendorff, Andrew E.
Liu, Xiaoping
Caren, Helena
Pollard, Steve M.
Beck, Stephan
Widschwendter, Martin
Chen, Luonan
The Dynamics of DNA Methylation Covariation Patterns in Carcinogenesis
title The Dynamics of DNA Methylation Covariation Patterns in Carcinogenesis
title_full The Dynamics of DNA Methylation Covariation Patterns in Carcinogenesis
title_fullStr The Dynamics of DNA Methylation Covariation Patterns in Carcinogenesis
title_full_unstemmed The Dynamics of DNA Methylation Covariation Patterns in Carcinogenesis
title_short The Dynamics of DNA Methylation Covariation Patterns in Carcinogenesis
title_sort dynamics of dna methylation covariation patterns in carcinogenesis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4091688/
https://www.ncbi.nlm.nih.gov/pubmed/25010556
http://dx.doi.org/10.1371/journal.pcbi.1003709
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