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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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ERα regulatory network in drug-resistant cells. ERα regulatory network in MCF7 cell after 4 hour E2 stimulation becomes non-responsive to E2 in the MCF7-T cell (only one target gene remains responsive).
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Figure 5: ERα regulatory network in drug-resistant cells. ERα regulatory network in MCF7 cell after 4 hour E2 stimulation becomes non-responsive to E2 in the MCF7-T cell (only one target gene remains responsive).

Mentions: Breast cancer cell models for acquired resistance to tamoxifen display progressive loss of estrogen-dependent signaling for cell growth and proliferation and a disrupted ERα regulatory network [16]. Among the ERα targets observed after 4 hour E2 stimulation of MCF7, only one target remained hormone responsive in the tamoxifen-resistant MCF7-T subline (NRF1; Figure 5). In order to understand the role of epigenetics in this non-responsive ERα network, we investigated five possible mechanisms (additional file 5): (A) high basal gene expression in the MCF7-T cell; (B) hypermethylation (MCF7-T vs MCF7) (C) hypomethylation (MCF7-T vs MCF7); (D) high methylation level in MCF7-T; and (C) high H3K27/H3K4 ratio. As shown in Figure 6, these mechanisms account for approximately 27%, 19%, 15%, 34%, and 22% of the non-responsive targets (Figure 6A); however, these five mechanisms are not able to account for approx. 28% of targets. Substantial (36%) overlap was seen between hypermethylation (mechanism 2) and high basal methylation in MCF7-T cell (mechanism 4) (Figure 6B).


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)

ERα regulatory network in drug-resistant cells. ERα regulatory network in MCF7 cell after 4 hour E2 stimulation becomes non-responsive to E2 in the MCF7-T cell (only one target gene remains responsive).
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 5: ERα regulatory network in drug-resistant cells. ERα regulatory network in MCF7 cell after 4 hour E2 stimulation becomes non-responsive to E2 in the MCF7-T cell (only one target gene remains responsive).
Mentions: Breast cancer cell models for acquired resistance to tamoxifen display progressive loss of estrogen-dependent signaling for cell growth and proliferation and a disrupted ERα regulatory network [16]. Among the ERα targets observed after 4 hour E2 stimulation of MCF7, only one target remained hormone responsive in the tamoxifen-resistant MCF7-T subline (NRF1; Figure 5). In order to understand the role of epigenetics in this non-responsive ERα network, we investigated five possible mechanisms (additional file 5): (A) high basal gene expression in the MCF7-T cell; (B) hypermethylation (MCF7-T vs MCF7) (C) hypomethylation (MCF7-T vs MCF7); (D) high methylation level in MCF7-T; and (C) high H3K27/H3K4 ratio. As shown in Figure 6, these mechanisms account for approximately 27%, 19%, 15%, 34%, and 22% of the non-responsive targets (Figure 6A); however, these five mechanisms are not able to account for approx. 28% of targets. Substantial (36%) overlap was seen between hypermethylation (mechanism 2) and high basal methylation in MCF7-T cell (mechanism 4) (Figure 6B).

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