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An integrated genomics analysis of epigenetic subtypes in human breast tumors links DNA methylation patterns to chromatin states in normal mammary cells

BACKGROUND: Aberrant DNA methylation is frequently observed in breast cancer. However, the relationship between methylation patterns and the heterogeneity of breast cancer has not been comprehensively characterized. METHODS: Whole-genome DNA methylation analysis using Illumina Infinium HumanMethylat...

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Autores principales: Holm, Karolina, Staaf, Johan, Lauss, Martin, Aine, Mattias, Lindgren, David, Bendahl, Pär-Ola, Vallon-Christersson, Johan, Barkardottir, Rosa Bjork, Höglund, Mattias, Borg, Åke, Jönsson, Göran, Ringnér, Markus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4770527/
https://www.ncbi.nlm.nih.gov/pubmed/26923702
http://dx.doi.org/10.1186/s13058-016-0685-5
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author Holm, Karolina
Staaf, Johan
Lauss, Martin
Aine, Mattias
Lindgren, David
Bendahl, Pär-Ola
Vallon-Christersson, Johan
Barkardottir, Rosa Bjork
Höglund, Mattias
Borg, Åke
Jönsson, Göran
Ringnér, Markus
author_facet Holm, Karolina
Staaf, Johan
Lauss, Martin
Aine, Mattias
Lindgren, David
Bendahl, Pär-Ola
Vallon-Christersson, Johan
Barkardottir, Rosa Bjork
Höglund, Mattias
Borg, Åke
Jönsson, Göran
Ringnér, Markus
author_sort Holm, Karolina
collection PubMed
description BACKGROUND: Aberrant DNA methylation is frequently observed in breast cancer. However, the relationship between methylation patterns and the heterogeneity of breast cancer has not been comprehensively characterized. METHODS: Whole-genome DNA methylation analysis using Illumina Infinium HumanMethylation450 BeadChip arrays was performed on 188 human breast tumors. Unsupervised bootstrap consensus clustering was performed to identify DNA methylation epigenetic subgroups (epitypes). The Cancer Genome Atlas data, including methylation profiles of 669 human breast tumors, was used for validation. The identified epitypes were characterized by integration with publicly available genome-wide data, including gene expression levels, DNA copy numbers, whole-exome sequencing data, and chromatin states. RESULTS: We identified seven breast cancer epitypes. One epitype was distinctly associated with basal-like tumors and with BRCA1 mutations, one epitype contained a subset of ERBB2-amplified tumors characterized by multiple additional amplifications and the most complex genomes, and one epitype displayed a methylation profile similar to normal epithelial cells. Luminal tumors were stratified into the remaining four epitypes, with differences in promoter hypermethylation, global hypomethylation, proliferative rates, and genomic instability. Specific hyper- and hypomethylation across the basal-like epitype was rare. However, we observed that the candidate genomic instability drivers BRCA1 and HORMAD1 displayed aberrant methylation linked to gene expression levels in some basal-like tumors. Hypomethylation in luminal tumors was associated with DNA repeats and subtelomeric regions. We observed two dominant patterns of aberrant methylation in breast cancer. One pattern, constitutively methylated in both basal-like and luminal breast cancer, was linked to genes with promoters in a Polycomb-repressed state in normal epithelial cells and displayed no correlation with gene expression levels. The second pattern correlated with gene expression levels and was associated with methylation in luminal tumors and genes with active promoters in normal epithelial cells. CONCLUSIONS: Our results suggest that hypermethylation patterns across basal-like breast cancer may have limited influence on tumor progression and instead reflect the repressed chromatin state of the tissue of origin. On the contrary, hypermethylation patterns specific to luminal breast cancer influence gene expression, may contribute to tumor progression, and may present an actionable epigenetic alteration in a subset of luminal breast cancers. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13058-016-0685-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-47705272016-03-01 An integrated genomics analysis of epigenetic subtypes in human breast tumors links DNA methylation patterns to chromatin states in normal mammary cells Holm, Karolina Staaf, Johan Lauss, Martin Aine, Mattias Lindgren, David Bendahl, Pär-Ola Vallon-Christersson, Johan Barkardottir, Rosa Bjork Höglund, Mattias Borg, Åke Jönsson, Göran Ringnér, Markus Breast Cancer Res Research Article BACKGROUND: Aberrant DNA methylation is frequently observed in breast cancer. However, the relationship between methylation patterns and the heterogeneity of breast cancer has not been comprehensively characterized. METHODS: Whole-genome DNA methylation analysis using Illumina Infinium HumanMethylation450 BeadChip arrays was performed on 188 human breast tumors. Unsupervised bootstrap consensus clustering was performed to identify DNA methylation epigenetic subgroups (epitypes). The Cancer Genome Atlas data, including methylation profiles of 669 human breast tumors, was used for validation. The identified epitypes were characterized by integration with publicly available genome-wide data, including gene expression levels, DNA copy numbers, whole-exome sequencing data, and chromatin states. RESULTS: We identified seven breast cancer epitypes. One epitype was distinctly associated with basal-like tumors and with BRCA1 mutations, one epitype contained a subset of ERBB2-amplified tumors characterized by multiple additional amplifications and the most complex genomes, and one epitype displayed a methylation profile similar to normal epithelial cells. Luminal tumors were stratified into the remaining four epitypes, with differences in promoter hypermethylation, global hypomethylation, proliferative rates, and genomic instability. Specific hyper- and hypomethylation across the basal-like epitype was rare. However, we observed that the candidate genomic instability drivers BRCA1 and HORMAD1 displayed aberrant methylation linked to gene expression levels in some basal-like tumors. Hypomethylation in luminal tumors was associated with DNA repeats and subtelomeric regions. We observed two dominant patterns of aberrant methylation in breast cancer. One pattern, constitutively methylated in both basal-like and luminal breast cancer, was linked to genes with promoters in a Polycomb-repressed state in normal epithelial cells and displayed no correlation with gene expression levels. The second pattern correlated with gene expression levels and was associated with methylation in luminal tumors and genes with active promoters in normal epithelial cells. CONCLUSIONS: Our results suggest that hypermethylation patterns across basal-like breast cancer may have limited influence on tumor progression and instead reflect the repressed chromatin state of the tissue of origin. On the contrary, hypermethylation patterns specific to luminal breast cancer influence gene expression, may contribute to tumor progression, and may present an actionable epigenetic alteration in a subset of luminal breast cancers. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13058-016-0685-5) contains supplementary material, which is available to authorized users. BioMed Central 2016-02-29 2016 /pmc/articles/PMC4770527/ /pubmed/26923702 http://dx.doi.org/10.1186/s13058-016-0685-5 Text en © Holm et al. 2016 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 Article
Holm, Karolina
Staaf, Johan
Lauss, Martin
Aine, Mattias
Lindgren, David
Bendahl, Pär-Ola
Vallon-Christersson, Johan
Barkardottir, Rosa Bjork
Höglund, Mattias
Borg, Åke
Jönsson, Göran
Ringnér, Markus
An integrated genomics analysis of epigenetic subtypes in human breast tumors links DNA methylation patterns to chromatin states in normal mammary cells
title An integrated genomics analysis of epigenetic subtypes in human breast tumors links DNA methylation patterns to chromatin states in normal mammary cells
title_full An integrated genomics analysis of epigenetic subtypes in human breast tumors links DNA methylation patterns to chromatin states in normal mammary cells
title_fullStr An integrated genomics analysis of epigenetic subtypes in human breast tumors links DNA methylation patterns to chromatin states in normal mammary cells
title_full_unstemmed An integrated genomics analysis of epigenetic subtypes in human breast tumors links DNA methylation patterns to chromatin states in normal mammary cells
title_short An integrated genomics analysis of epigenetic subtypes in human breast tumors links DNA methylation patterns to chromatin states in normal mammary cells
title_sort integrated genomics analysis of epigenetic subtypes in human breast tumors links dna methylation patterns to chromatin states in normal mammary cells
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4770527/
https://www.ncbi.nlm.nih.gov/pubmed/26923702
http://dx.doi.org/10.1186/s13058-016-0685-5
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