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A modulated empirical Bayes model for identifying topological and temporal estrogen receptor α regulatory networks in breast cancer.

Shen C, Huang Y, Liu Y, Wang G, Zhao Y, Wang Z, Teng M, Wang Y, Flockhart DA, Skaar TC, Yan P, Nephew KP, Huang TH, Li L - BMC Syst Biol (2011)

Bottom Line: Estrogens regulate diverse physiological processes in various tissues through genomic and non-genomic mechanisms that result in activation or repression of gene expression.The significant loss of hormone responsiveness was associated with marked epigenomic changes, including hyper- or hypo-methylation of promoter CpG islands and repressive histone methylations.Many gene targets of this network were not active anymore in anti-estrogen resistant cell lines, possibly because their DNA methylation and histone acetylation patterns have changed.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center for Computational Biology, Indiana University School of Medicine, Indianapolis, IN 46202, USA.

ABSTRACT

Background: Estrogens regulate diverse physiological processes in various tissues through genomic and non-genomic mechanisms that result in activation or repression of gene expression. Transcription regulation upon estrogen stimulation is a critical biological process underlying the onset and progress of the majority of breast cancer. Dynamic gene expression changes have been shown to characterize the breast cancer cell response to estrogens, the every molecular mechanism of which is still not well understood.

Results: We developed a modulated empirical Bayes model, and constructed a novel topological and temporal transcription factor (TF) regulatory network in MCF7 breast cancer cell line upon stimulation by 17β-estradiol stimulation. In the network, significant TF genomic hubs were identified including ER-alpha and AP-1; significant non-genomic hubs include ZFP161, TFDP1, NRF1, TFAP2A, EGR1, E2F1, and PITX2. Although the early and late networks were distinct (<5% overlap of ERα target genes between the 4 and 24 h time points), all nine hubs were significantly represented in both networks. In MCF7 cells with acquired resistance to tamoxifen, the ERα regulatory network was unresponsive to 17β-estradiol stimulation. The significant loss of hormone responsiveness was associated with marked epigenomic changes, including hyper- or hypo-methylation of promoter CpG islands and repressive histone methylations.

Conclusions: We identified a number of estrogen regulated target genes and established estrogen-regulated network that distinguishes the genomic and non-genomic actions of estrogen receptor. Many gene targets of this network were not active anymore in anti-estrogen resistant cell lines, possibly because their DNA methylation and histone acetylation patterns have changed.

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Related in: MedlinePlus

Flow-Chat of ERα Regulatory Network Construction
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Figure 8: Flow-Chat of ERα Regulatory Network Construction

Mentions: A second application of the regulatory network was to examine the impact of epigenetics (DNA methylation and histone modifications) on the ERα regulatory network in a breast cancer cell model for acquired tamoxifen resistance of [16]. Transcriptionally active genes are typically marked by higher levels of di-/tri-methylated H3K4 (H3K4me2/3) and low trimethylated H3 lysine 27 (H3K27me3) levels [35], and in hormone responsive MCF7 cells, E2-stimulated target genes have been shown to posses enriched regions of H3K4me1/2 [36]. In contrast, MCF7 with acquired tamoxifen resistance (MCF7-T), groups of previously E2-responsive genes are now associated with low H3K4me2 and high H3K27me3 and are either downregulated or no longer strongly hormone inducible (Figure 8). The H3K27me3 mark is stable and invariably associated with transcriptional repression [37,38] and we show that this repressive histone modification plays a key role in the unresponsive ERα regulatory network in MCF7 cells with acquired resistance to tamoxifen (Figure 8). Although tumorigenic gene silencing mediated by H3K27me3 has been shown to occur in the absence of DNA methylation [38,39], repressive histone marks frequently coordinate with the more permanent mark of DNA methylation in heterochromatin [39-41]. We previously demonstrated that alterations in DNA methylation play an important role in acquired tamoxifen resistance [16]. By integrating both repressive epigenetic marks into our model, we demonstrate that H3K27me3 and DNA methylation significantly contribute to the non-responsive ERα regulatory network model in tamoxifen resistant breast cancer. Furthermore, having recently demonstrated that many TFBSs are enriched in regions of altered DNA methylation [42], we suggest that the functions of activators or repressors could be altered by changes to the DNA methylation landscape and further impact ERα networks in breast cancer, an active area of investigation in our laboratory.


A modulated empirical Bayes model for identifying topological and temporal estrogen receptor α regulatory networks in breast cancer.

Shen C, Huang Y, Liu Y, Wang G, Zhao Y, Wang Z, Teng M, Wang Y, Flockhart DA, Skaar TC, Yan P, Nephew KP, Huang TH, Li L - BMC Syst Biol (2011)

Flow-Chat of ERα Regulatory Network Construction
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3117732&req=5

Figure 8: Flow-Chat of ERα Regulatory Network Construction
Mentions: A second application of the regulatory network was to examine the impact of epigenetics (DNA methylation and histone modifications) on the ERα regulatory network in a breast cancer cell model for acquired tamoxifen resistance of [16]. Transcriptionally active genes are typically marked by higher levels of di-/tri-methylated H3K4 (H3K4me2/3) and low trimethylated H3 lysine 27 (H3K27me3) levels [35], and in hormone responsive MCF7 cells, E2-stimulated target genes have been shown to posses enriched regions of H3K4me1/2 [36]. In contrast, MCF7 with acquired tamoxifen resistance (MCF7-T), groups of previously E2-responsive genes are now associated with low H3K4me2 and high H3K27me3 and are either downregulated or no longer strongly hormone inducible (Figure 8). The H3K27me3 mark is stable and invariably associated with transcriptional repression [37,38] and we show that this repressive histone modification plays a key role in the unresponsive ERα regulatory network in MCF7 cells with acquired resistance to tamoxifen (Figure 8). Although tumorigenic gene silencing mediated by H3K27me3 has been shown to occur in the absence of DNA methylation [38,39], repressive histone marks frequently coordinate with the more permanent mark of DNA methylation in heterochromatin [39-41]. We previously demonstrated that alterations in DNA methylation play an important role in acquired tamoxifen resistance [16]. By integrating both repressive epigenetic marks into our model, we demonstrate that H3K27me3 and DNA methylation significantly contribute to the non-responsive ERα regulatory network model in tamoxifen resistant breast cancer. Furthermore, having recently demonstrated that many TFBSs are enriched in regions of altered DNA methylation [42], we suggest that the functions of activators or repressors could be altered by changes to the DNA methylation landscape and further impact ERα networks in breast cancer, an active area of investigation in our laboratory.

Bottom Line: Estrogens regulate diverse physiological processes in various tissues through genomic and non-genomic mechanisms that result in activation or repression of gene expression.The significant loss of hormone responsiveness was associated with marked epigenomic changes, including hyper- or hypo-methylation of promoter CpG islands and repressive histone methylations.Many gene targets of this network were not active anymore in anti-estrogen resistant cell lines, possibly because their DNA methylation and histone acetylation patterns have changed.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center for Computational Biology, Indiana University School of Medicine, Indianapolis, IN 46202, USA.

ABSTRACT

Background: Estrogens regulate diverse physiological processes in various tissues through genomic and non-genomic mechanisms that result in activation or repression of gene expression. Transcription regulation upon estrogen stimulation is a critical biological process underlying the onset and progress of the majority of breast cancer. Dynamic gene expression changes have been shown to characterize the breast cancer cell response to estrogens, the every molecular mechanism of which is still not well understood.

Results: We developed a modulated empirical Bayes model, and constructed a novel topological and temporal transcription factor (TF) regulatory network in MCF7 breast cancer cell line upon stimulation by 17β-estradiol stimulation. In the network, significant TF genomic hubs were identified including ER-alpha and AP-1; significant non-genomic hubs include ZFP161, TFDP1, NRF1, TFAP2A, EGR1, E2F1, and PITX2. Although the early and late networks were distinct (<5% overlap of ERα target genes between the 4 and 24 h time points), all nine hubs were significantly represented in both networks. In MCF7 cells with acquired resistance to tamoxifen, the ERα regulatory network was unresponsive to 17β-estradiol stimulation. The significant loss of hormone responsiveness was associated with marked epigenomic changes, including hyper- or hypo-methylation of promoter CpG islands and repressive histone methylations.

Conclusions: We identified a number of estrogen regulated target genes and established estrogen-regulated network that distinguishes the genomic and non-genomic actions of estrogen receptor. Many gene targets of this network were not active anymore in anti-estrogen resistant cell lines, possibly because their DNA methylation and histone acetylation patterns have changed.

Show MeSH
Related in: MedlinePlus