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An empirical Bayes model for gene expression and methylation profiles in antiestrogen resistant breast cancer
BACKGROUND: The nuclear transcription factor estrogen receptor alpha (ER-alpha) is the target of several antiestrogen therapeutic agents for breast cancer. However, many ER-alpha positive patients do not respond to these treatments from the beginning, or stop responding after being treated for a per...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2010
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3003621/ https://www.ncbi.nlm.nih.gov/pubmed/21108837 http://dx.doi.org/10.1186/1755-8794-3-55 |
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author | Jeong, Jaesik Li, Lang Liu, Yunlong Nephew, Kenneth P Huang, Tim Hui-Ming Shen, Changyu |
author_facet | Jeong, Jaesik Li, Lang Liu, Yunlong Nephew, Kenneth P Huang, Tim Hui-Ming Shen, Changyu |
author_sort | Jeong, Jaesik |
collection | PubMed |
description | BACKGROUND: The nuclear transcription factor estrogen receptor alpha (ER-alpha) is the target of several antiestrogen therapeutic agents for breast cancer. However, many ER-alpha positive patients do not respond to these treatments from the beginning, or stop responding after being treated for a period of time. Because of the association of gene transcription alteration and drug resistance and the emerging evidence on the role of DNA methylation on transcription regulation, understanding of these relationships can facilitate development of approaches to re-sensitize breast cancer cells to treatment by restoring DNA methylation patterns. METHODS: We constructed a hierarchical empirical Bayes model to investigate the simultaneous change of gene expression and promoter DNA methylation profiles among wild type (WT) and OHT/ICI resistant MCF7 breast cancer cell lines. RESULTS: We found that compared with the WT cell lines, almost all of the genes in OHT or ICI resistant cell lines either do not show methylation change or hypomethylated. Moreover, the correlations between gene expression and methylation are quite heterogeneous across genes, suggesting the involvement of other factors in regulating transcription. Analysis of our results in combination with H3K4me2 data on OHT resistant cell lines suggests a clear interplay between DNA methylation and H3K4me2 in the regulation of gene expression. For hypomethylated genes with alteration of gene expression, most (~80%) are up-regulated, consistent with current view on the relationship between promoter methylation and gene expression. CONCLUSIONS: We developed an empirical Bayes model to study the association between DNA methylation in the promoter region and gene expression. Our approach generates both global (across all genes) and local (individual gene) views of the interplay. It provides important insight on future effort to develop therapeutic agent to re-sensitize breast cancer cells to treatment. |
format | Text |
id | pubmed-3003621 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-30036212011-01-06 An empirical Bayes model for gene expression and methylation profiles in antiestrogen resistant breast cancer Jeong, Jaesik Li, Lang Liu, Yunlong Nephew, Kenneth P Huang, Tim Hui-Ming Shen, Changyu BMC Med Genomics Research Article BACKGROUND: The nuclear transcription factor estrogen receptor alpha (ER-alpha) is the target of several antiestrogen therapeutic agents for breast cancer. However, many ER-alpha positive patients do not respond to these treatments from the beginning, or stop responding after being treated for a period of time. Because of the association of gene transcription alteration and drug resistance and the emerging evidence on the role of DNA methylation on transcription regulation, understanding of these relationships can facilitate development of approaches to re-sensitize breast cancer cells to treatment by restoring DNA methylation patterns. METHODS: We constructed a hierarchical empirical Bayes model to investigate the simultaneous change of gene expression and promoter DNA methylation profiles among wild type (WT) and OHT/ICI resistant MCF7 breast cancer cell lines. RESULTS: We found that compared with the WT cell lines, almost all of the genes in OHT or ICI resistant cell lines either do not show methylation change or hypomethylated. Moreover, the correlations between gene expression and methylation are quite heterogeneous across genes, suggesting the involvement of other factors in regulating transcription. Analysis of our results in combination with H3K4me2 data on OHT resistant cell lines suggests a clear interplay between DNA methylation and H3K4me2 in the regulation of gene expression. For hypomethylated genes with alteration of gene expression, most (~80%) are up-regulated, consistent with current view on the relationship between promoter methylation and gene expression. CONCLUSIONS: We developed an empirical Bayes model to study the association between DNA methylation in the promoter region and gene expression. Our approach generates both global (across all genes) and local (individual gene) views of the interplay. It provides important insight on future effort to develop therapeutic agent to re-sensitize breast cancer cells to treatment. BioMed Central 2010-11-25 /pmc/articles/PMC3003621/ /pubmed/21108837 http://dx.doi.org/10.1186/1755-8794-3-55 Text en Copyright ©2010 Jeong et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<url>http://creativecommons.org/licenses/by/2.0</url>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Jeong, Jaesik Li, Lang Liu, Yunlong Nephew, Kenneth P Huang, Tim Hui-Ming Shen, Changyu An empirical Bayes model for gene expression and methylation profiles in antiestrogen resistant breast cancer |
title | An empirical Bayes model for gene expression and methylation profiles in antiestrogen resistant breast cancer |
title_full | An empirical Bayes model for gene expression and methylation profiles in antiestrogen resistant breast cancer |
title_fullStr | An empirical Bayes model for gene expression and methylation profiles in antiestrogen resistant breast cancer |
title_full_unstemmed | An empirical Bayes model for gene expression and methylation profiles in antiestrogen resistant breast cancer |
title_short | An empirical Bayes model for gene expression and methylation profiles in antiestrogen resistant breast cancer |
title_sort | empirical bayes model for gene expression and methylation profiles in antiestrogen resistant breast cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3003621/ https://www.ncbi.nlm.nih.gov/pubmed/21108837 http://dx.doi.org/10.1186/1755-8794-3-55 |
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