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The integrative epigenomic-transcriptomic landscape of ER positive breast cancer

BACKGROUND: While recent integrative analyses of copy number and gene expression data in breast cancer have revealed a complex molecular landscape with multiple subtypes and many oncogenic/tumour suppressor driver events, much less is known about the role of DNA methylation in shaping breast cancer...

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Autores principales: Gao, Yang, Jones, Allison, Fasching, Peter A., Ruebner, Matthias, Beckmann, Matthias W., Widschwendter, Martin, Teschendorff, Andrew E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4673726/
https://www.ncbi.nlm.nih.gov/pubmed/26664652
http://dx.doi.org/10.1186/s13148-015-0159-0
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author Gao, Yang
Jones, Allison
Fasching, Peter A.
Ruebner, Matthias
Beckmann, Matthias W.
Widschwendter, Martin
Teschendorff, Andrew E.
author_facet Gao, Yang
Jones, Allison
Fasching, Peter A.
Ruebner, Matthias
Beckmann, Matthias W.
Widschwendter, Martin
Teschendorff, Andrew E.
author_sort Gao, Yang
collection PubMed
description BACKGROUND: While recent integrative analyses of copy number and gene expression data in breast cancer have revealed a complex molecular landscape with multiple subtypes and many oncogenic/tumour suppressor driver events, much less is known about the role of DNA methylation in shaping breast cancer taxonomy and defining driver events. RESULTS: Here, we applied a powerful integrative network algorithm to matched DNA methylation and RNA-Seq data for 724 estrogen receptor (ER)-positive (ER+) breast cancers and 111 normal adjacent tissue specimens from The Cancer Genome Atlas (TCGA) project, in order to identify putative epigenetic driver events and to explore the resulting molecular taxonomy. This revealed the existence of nine functionally deregulated epigenetic hotspots encompassing a total of 146 genes, which we were able to validate in independent data sets encompassing over 1000 ER+ breast cancers. Integrative clustering of the matched messenger RNA (mRNA) and DNA methylation data over these genes resulted in only two clusters, which correlated very strongly with the luminal-A and luminal B subtypes. Overall, luminal-A and luminal-B breast cancers shared the same epigenetically deregulated hotspots but with luminal-B cancers exhibiting increased aberrant DNA methylation patterns relative to normal tissue. We show that increased levels of DNA methylation and mRNA expression deviation from the normal state define a marker of poor prognosis. Our data further implicates epigenetic silencing of WNT signalling antagonists and bone morphogenetic proteins (BMP) as key events underlying both luminal subtypes but specially of luminal-B breast cancer. Finally, we show that DNA methylation changes within the identified epigenetic interactome hotspots do not exhibit mutually exclusive patterns within the same cancer sample, instead exhibiting coordinated changes within the sample. CONCLUSIONS: Our results indicate that the integrative DNA methylation and transcriptomic landscape of ER+ breast cancer is surprisingly homogeneous, defining two main subtypes which strongly correlate with luminal-A/B subtype status. In particular, we identify WNT and BMP signalling as key epigenetically deregulated tumour suppressor pathways in luminal ER+ breast cancer, with increased deregulation seen in luminal-B breast cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13148-015-0159-0) contains supplementary material, which is available to authorized users.
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spelling pubmed-46737262015-12-10 The integrative epigenomic-transcriptomic landscape of ER positive breast cancer Gao, Yang Jones, Allison Fasching, Peter A. Ruebner, Matthias Beckmann, Matthias W. Widschwendter, Martin Teschendorff, Andrew E. Clin Epigenetics Research BACKGROUND: While recent integrative analyses of copy number and gene expression data in breast cancer have revealed a complex molecular landscape with multiple subtypes and many oncogenic/tumour suppressor driver events, much less is known about the role of DNA methylation in shaping breast cancer taxonomy and defining driver events. RESULTS: Here, we applied a powerful integrative network algorithm to matched DNA methylation and RNA-Seq data for 724 estrogen receptor (ER)-positive (ER+) breast cancers and 111 normal adjacent tissue specimens from The Cancer Genome Atlas (TCGA) project, in order to identify putative epigenetic driver events and to explore the resulting molecular taxonomy. This revealed the existence of nine functionally deregulated epigenetic hotspots encompassing a total of 146 genes, which we were able to validate in independent data sets encompassing over 1000 ER+ breast cancers. Integrative clustering of the matched messenger RNA (mRNA) and DNA methylation data over these genes resulted in only two clusters, which correlated very strongly with the luminal-A and luminal B subtypes. Overall, luminal-A and luminal-B breast cancers shared the same epigenetically deregulated hotspots but with luminal-B cancers exhibiting increased aberrant DNA methylation patterns relative to normal tissue. We show that increased levels of DNA methylation and mRNA expression deviation from the normal state define a marker of poor prognosis. Our data further implicates epigenetic silencing of WNT signalling antagonists and bone morphogenetic proteins (BMP) as key events underlying both luminal subtypes but specially of luminal-B breast cancer. Finally, we show that DNA methylation changes within the identified epigenetic interactome hotspots do not exhibit mutually exclusive patterns within the same cancer sample, instead exhibiting coordinated changes within the sample. CONCLUSIONS: Our results indicate that the integrative DNA methylation and transcriptomic landscape of ER+ breast cancer is surprisingly homogeneous, defining two main subtypes which strongly correlate with luminal-A/B subtype status. In particular, we identify WNT and BMP signalling as key epigenetically deregulated tumour suppressor pathways in luminal ER+ breast cancer, with increased deregulation seen in luminal-B breast cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13148-015-0159-0) contains supplementary material, which is available to authorized users. BioMed Central 2015-12-09 /pmc/articles/PMC4673726/ /pubmed/26664652 http://dx.doi.org/10.1186/s13148-015-0159-0 Text en © Gao et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Gao, Yang
Jones, Allison
Fasching, Peter A.
Ruebner, Matthias
Beckmann, Matthias W.
Widschwendter, Martin
Teschendorff, Andrew E.
The integrative epigenomic-transcriptomic landscape of ER positive breast cancer
title The integrative epigenomic-transcriptomic landscape of ER positive breast cancer
title_full The integrative epigenomic-transcriptomic landscape of ER positive breast cancer
title_fullStr The integrative epigenomic-transcriptomic landscape of ER positive breast cancer
title_full_unstemmed The integrative epigenomic-transcriptomic landscape of ER positive breast cancer
title_short The integrative epigenomic-transcriptomic landscape of ER positive breast cancer
title_sort integrative epigenomic-transcriptomic landscape of er positive breast cancer
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4673726/
https://www.ncbi.nlm.nih.gov/pubmed/26664652
http://dx.doi.org/10.1186/s13148-015-0159-0
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