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Regulators Associated with Clinical Outcomes Revealed by DNA Methylation Data in Breast Cancer
The regulatory architecture of breast cancer is extraordinarily complex and gene misregulation can occur at many levels, with transcriptional malfunction being a major cause. This dysfunctional process typically involves additional regulatory modulators including DNA methylation. Thus, the interplay...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4440643/ https://www.ncbi.nlm.nih.gov/pubmed/25996148 http://dx.doi.org/10.1371/journal.pcbi.1004269 |
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author | Ung, Matthew H. Varn, Frederick S. Lou, Shaoke Cheng, Chao |
author_facet | Ung, Matthew H. Varn, Frederick S. Lou, Shaoke Cheng, Chao |
author_sort | Ung, Matthew H. |
collection | PubMed |
description | The regulatory architecture of breast cancer is extraordinarily complex and gene misregulation can occur at many levels, with transcriptional malfunction being a major cause. This dysfunctional process typically involves additional regulatory modulators including DNA methylation. Thus, the interplay between transcription factor (TF) binding and DNA methylation are two components of a cancer regulatory interactome presumed to display correlated signals. As proof of concept, we performed a systematic motif-based in silico analysis to infer all potential TFs that are involved in breast cancer prognosis through an association with DNA methylation changes. Using breast cancer DNA methylation and clinical data derived from The Cancer Genome Atlas (TCGA), we carried out a systematic inference of TFs whose misregulation underlie different clinical subtypes of breast cancer. Our analysis identified TFs known to be associated with clinical outcomes of p53 and ER (estrogen receptor) subtypes of breast cancer, while also predicting new TFs that may also be involved. Furthermore, our results suggest that misregulation in breast cancer can be caused by the binding of alternative factors to the binding sites of TFs whose activity has been ablated. Overall, this study provides a comprehensive analysis that links DNA methylation to TF binding to patient prognosis. |
format | Online Article Text |
id | pubmed-4440643 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-44406432015-05-29 Regulators Associated with Clinical Outcomes Revealed by DNA Methylation Data in Breast Cancer Ung, Matthew H. Varn, Frederick S. Lou, Shaoke Cheng, Chao PLoS Comput Biol Research Article The regulatory architecture of breast cancer is extraordinarily complex and gene misregulation can occur at many levels, with transcriptional malfunction being a major cause. This dysfunctional process typically involves additional regulatory modulators including DNA methylation. Thus, the interplay between transcription factor (TF) binding and DNA methylation are two components of a cancer regulatory interactome presumed to display correlated signals. As proof of concept, we performed a systematic motif-based in silico analysis to infer all potential TFs that are involved in breast cancer prognosis through an association with DNA methylation changes. Using breast cancer DNA methylation and clinical data derived from The Cancer Genome Atlas (TCGA), we carried out a systematic inference of TFs whose misregulation underlie different clinical subtypes of breast cancer. Our analysis identified TFs known to be associated with clinical outcomes of p53 and ER (estrogen receptor) subtypes of breast cancer, while also predicting new TFs that may also be involved. Furthermore, our results suggest that misregulation in breast cancer can be caused by the binding of alternative factors to the binding sites of TFs whose activity has been ablated. Overall, this study provides a comprehensive analysis that links DNA methylation to TF binding to patient prognosis. Public Library of Science 2015-05-21 /pmc/articles/PMC4440643/ /pubmed/25996148 http://dx.doi.org/10.1371/journal.pcbi.1004269 Text en © 2015 Ung 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 Ung, Matthew H. Varn, Frederick S. Lou, Shaoke Cheng, Chao Regulators Associated with Clinical Outcomes Revealed by DNA Methylation Data in Breast Cancer |
title | Regulators Associated with Clinical Outcomes Revealed by DNA Methylation Data in Breast Cancer |
title_full | Regulators Associated with Clinical Outcomes Revealed by DNA Methylation Data in Breast Cancer |
title_fullStr | Regulators Associated with Clinical Outcomes Revealed by DNA Methylation Data in Breast Cancer |
title_full_unstemmed | Regulators Associated with Clinical Outcomes Revealed by DNA Methylation Data in Breast Cancer |
title_short | Regulators Associated with Clinical Outcomes Revealed by DNA Methylation Data in Breast Cancer |
title_sort | regulators associated with clinical outcomes revealed by dna methylation data in breast cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4440643/ https://www.ncbi.nlm.nih.gov/pubmed/25996148 http://dx.doi.org/10.1371/journal.pcbi.1004269 |
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