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Updated: Jun 6, 2026
Profiling of Estrogen-regulated MicroRNAs in Breast Cancer Cells
Published on: February 21, 2014
An empirical Bayes model for gene expression and methylation profiles in antiestrogen resistant breast cancer
Jaesik Jeong1, Lang Li, Yunlong Liu
1Department of Medicine/Division of Biostatistics, Indiana University, Indianapolis, IN, USA.
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.
Insights
Estrogen receptor alpha (ER-alpha) targeted breast cancer therapies face resistance due to altered DNA methylation. This study reveals methylation changes in resistant cells, offering insights to re-sensitize cancer cells to treatment.
Area of Science:
- Oncology
- Epigenetics
- Molecular Biology
Background:
- Estrogen receptor alpha (ER-alpha) is a key target for breast cancer therapies.
- Many ER-alpha positive breast cancers develop resistance to antiestrogen treatments.
- DNA methylation plays a role in regulating gene transcription and may influence drug resistance.
Purpose of the Study:
- To investigate the relationship between gene expression and DNA methylation profiles in breast cancer cells resistant to antiestrogen therapy.
- To understand how DNA methylation patterns change in resistant cell lines compared to wild-type cells.
- To identify potential epigenetic targets for overcoming treatment resistance.
Main Methods:
- Developed a hierarchical empirical Bayes model.
- Analyzed simultaneous changes in gene expression and promoter DNA methylation.
- Compared wild-type (WT) MCF7 breast cancer cells with OHT/ICI resistant MCF7 cell lines.
- Integrated DNA methylation data with H3K4me2 data.
Main Results:
- Resistant cell lines predominantly showed no methylation change or hypomethylation compared to WT.
- Gene expression and methylation correlations were heterogeneous, indicating complex regulatory networks.
- A clear interplay between DNA methylation and H3K4me2 in gene expression regulation was observed.
- Approximately 80% of hypomethylated genes with altered expression were up-regulated.
Conclusions:
- An empirical Bayes model was developed to associate promoter DNA methylation with gene expression.
- The model provides both global and local insights into the interplay between DNA methylation and gene expression.
- Findings offer crucial insights for developing therapeutic strategies to re-sensitize breast cancer cells to antiestrogen treatments.
