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DNA Methylation Patterns in Normal Tissue Correlate more Strongly with Breast Cancer Status than Copy-Number Variants

Normal tissue at risk of neoplastic transformation is characterized by somatic mutations, copy-number variation and DNA methylation changes. It is unclear however, which type of alteration may be more informative of cancer risk. We analyzed genome-wide DNA methylation and copy-number calls from the...

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Autores principales: Gao, Yang, Widschwendter, Martin, Teschendorff, Andrew E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6013931/
https://www.ncbi.nlm.nih.gov/pubmed/29735413
http://dx.doi.org/10.1016/j.ebiom.2018.04.025
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author Gao, Yang
Widschwendter, Martin
Teschendorff, Andrew E.
author_facet Gao, Yang
Widschwendter, Martin
Teschendorff, Andrew E.
author_sort Gao, Yang
collection PubMed
description Normal tissue at risk of neoplastic transformation is characterized by somatic mutations, copy-number variation and DNA methylation changes. It is unclear however, which type of alteration may be more informative of cancer risk. We analyzed genome-wide DNA methylation and copy-number calls from the same DNA assay in a cohort of healthy breast samples and age-matched normal samples collected adjacent to breast cancer. Using statistical methods to adjust for cell type heterogeneity, we show that DNA methylation changes can discriminate normal-adjacent from normal samples better than somatic copy-number variants. We validate this important finding in an independent dataset. These results suggest that DNA methylation alterations in the normal cell of origin may offer better cancer risk prediction and early detection markers than copy-number changes.
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spelling pubmed-60139312018-06-26 DNA Methylation Patterns in Normal Tissue Correlate more Strongly with Breast Cancer Status than Copy-Number Variants Gao, Yang Widschwendter, Martin Teschendorff, Andrew E. EBioMedicine Research Paper Normal tissue at risk of neoplastic transformation is characterized by somatic mutations, copy-number variation and DNA methylation changes. It is unclear however, which type of alteration may be more informative of cancer risk. We analyzed genome-wide DNA methylation and copy-number calls from the same DNA assay in a cohort of healthy breast samples and age-matched normal samples collected adjacent to breast cancer. Using statistical methods to adjust for cell type heterogeneity, we show that DNA methylation changes can discriminate normal-adjacent from normal samples better than somatic copy-number variants. We validate this important finding in an independent dataset. These results suggest that DNA methylation alterations in the normal cell of origin may offer better cancer risk prediction and early detection markers than copy-number changes. Elsevier 2018-05-04 /pmc/articles/PMC6013931/ /pubmed/29735413 http://dx.doi.org/10.1016/j.ebiom.2018.04.025 Text en © 2018 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Paper
Gao, Yang
Widschwendter, Martin
Teschendorff, Andrew E.
DNA Methylation Patterns in Normal Tissue Correlate more Strongly with Breast Cancer Status than Copy-Number Variants
title DNA Methylation Patterns in Normal Tissue Correlate more Strongly with Breast Cancer Status than Copy-Number Variants
title_full DNA Methylation Patterns in Normal Tissue Correlate more Strongly with Breast Cancer Status than Copy-Number Variants
title_fullStr DNA Methylation Patterns in Normal Tissue Correlate more Strongly with Breast Cancer Status than Copy-Number Variants
title_full_unstemmed DNA Methylation Patterns in Normal Tissue Correlate more Strongly with Breast Cancer Status than Copy-Number Variants
title_short DNA Methylation Patterns in Normal Tissue Correlate more Strongly with Breast Cancer Status than Copy-Number Variants
title_sort dna methylation patterns in normal tissue correlate more strongly with breast cancer status than copy-number variants
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6013931/
https://www.ncbi.nlm.nih.gov/pubmed/29735413
http://dx.doi.org/10.1016/j.ebiom.2018.04.025
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