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Deconvolution of DNA methylation identifies differentially methylated gene regions on 1p36 across breast cancer subtypes

Breast cancer is a complex disease consisting of four distinct molecular subtypes. DNA methylation-based (DNAm) studies in tumors are complicated further by disease heterogeneity. In the present study, we compared DNAm in breast tumors with normal-adjacent breast samples from The Cancer Genome Atlas...

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Autores principales: Titus, Alexander J., Way, Gregory P., Johnson, Kevin C., Christensen, Brock C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5599639/
https://www.ncbi.nlm.nih.gov/pubmed/28912426
http://dx.doi.org/10.1038/s41598-017-10199-z
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author Titus, Alexander J.
Way, Gregory P.
Johnson, Kevin C.
Christensen, Brock C.
author_facet Titus, Alexander J.
Way, Gregory P.
Johnson, Kevin C.
Christensen, Brock C.
author_sort Titus, Alexander J.
collection PubMed
description Breast cancer is a complex disease consisting of four distinct molecular subtypes. DNA methylation-based (DNAm) studies in tumors are complicated further by disease heterogeneity. In the present study, we compared DNAm in breast tumors with normal-adjacent breast samples from The Cancer Genome Atlas (TCGA). We constructed models stratified by tumor stage and PAM50 molecular subtype and performed cell-type reference-free deconvolution to control for cellular heterogeneity. We identified nineteen differentially methylated gene regions (DMGRs) in early stage tumors across eleven genes (AGRN, C1orf170, FAM41C, FLJ39609, HES4, ISG15, KLHL17, NOC2L, PLEKHN1, SAMD11, WASH5P). These regions were consistently differentially methylated in every subtype and all implicated genes are localized to the chromosomal cytoband 1p36.3. Seventeen of these DMGRs were independently validated in a similar analysis of an external data set. The identification and validation of shared DNAm alterations across tumor subtypes in early stage tumors advances our understanding of common biology underlying breast carcinogenesis and may contribute to biomarker development. We also discuss evidence of the specific importance and potential function of 1p36 in cancer.
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spelling pubmed-55996392017-09-15 Deconvolution of DNA methylation identifies differentially methylated gene regions on 1p36 across breast cancer subtypes Titus, Alexander J. Way, Gregory P. Johnson, Kevin C. Christensen, Brock C. Sci Rep Article Breast cancer is a complex disease consisting of four distinct molecular subtypes. DNA methylation-based (DNAm) studies in tumors are complicated further by disease heterogeneity. In the present study, we compared DNAm in breast tumors with normal-adjacent breast samples from The Cancer Genome Atlas (TCGA). We constructed models stratified by tumor stage and PAM50 molecular subtype and performed cell-type reference-free deconvolution to control for cellular heterogeneity. We identified nineteen differentially methylated gene regions (DMGRs) in early stage tumors across eleven genes (AGRN, C1orf170, FAM41C, FLJ39609, HES4, ISG15, KLHL17, NOC2L, PLEKHN1, SAMD11, WASH5P). These regions were consistently differentially methylated in every subtype and all implicated genes are localized to the chromosomal cytoband 1p36.3. Seventeen of these DMGRs were independently validated in a similar analysis of an external data set. The identification and validation of shared DNAm alterations across tumor subtypes in early stage tumors advances our understanding of common biology underlying breast carcinogenesis and may contribute to biomarker development. We also discuss evidence of the specific importance and potential function of 1p36 in cancer. Nature Publishing Group UK 2017-09-14 /pmc/articles/PMC5599639/ /pubmed/28912426 http://dx.doi.org/10.1038/s41598-017-10199-z Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Titus, Alexander J.
Way, Gregory P.
Johnson, Kevin C.
Christensen, Brock C.
Deconvolution of DNA methylation identifies differentially methylated gene regions on 1p36 across breast cancer subtypes
title Deconvolution of DNA methylation identifies differentially methylated gene regions on 1p36 across breast cancer subtypes
title_full Deconvolution of DNA methylation identifies differentially methylated gene regions on 1p36 across breast cancer subtypes
title_fullStr Deconvolution of DNA methylation identifies differentially methylated gene regions on 1p36 across breast cancer subtypes
title_full_unstemmed Deconvolution of DNA methylation identifies differentially methylated gene regions on 1p36 across breast cancer subtypes
title_short Deconvolution of DNA methylation identifies differentially methylated gene regions on 1p36 across breast cancer subtypes
title_sort deconvolution of dna methylation identifies differentially methylated gene regions on 1p36 across breast cancer subtypes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5599639/
https://www.ncbi.nlm.nih.gov/pubmed/28912426
http://dx.doi.org/10.1038/s41598-017-10199-z
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