Influence of Estrogen Treatment on ESR1+ and ESR1- Cells in ER+ Breast Cancer: Insights from Single-Cell Analysis of Patient-Derived Xenograft Models.

A 100% ER positivity is not required for an endocrine therapy response. Furthermore, while estrogen typically promotes the progression of hormone-dependent breast cancer via the activation of estrogen receptor (ER)-α, estrogen-induced tumor suppression in ER+ breast cancer has been clinically observed. With the success in establishing estrogen-stimulated (SC31) and estrogen-suppressed (GS3) patient-derived xenograft (PDX) models, single-cell RNA sequencing analysis was performed to determine the impact of estrogen on ESR1+ and ESR1- tumor cells. We found that 17ß-estradiol (E2)-induced suppression of GS3 transpired through wild-type and unamplified ERα. E2 upregulated the expression of estrogen-dependent genes in both SC31 and GS3; however, E2 induced cell cycle advance in SC31, while it resulted in cell cycle arrest in GS3. Importantly, these gene expression changes occurred in both ESR1+ and ESR1- cells within the same breast tumors, demonstrating for the first time a differential effect of estrogen on ESR1- cells. E2 also upregulated a tumor-suppressor gene, IL-24, in GS3. The apoptosis gene set was upregulated and the G2M checkpoint gene set was downregulated in most IL-24+ cells after E2 treatment. In summary, estrogen affected pathologically defined ER+ tumors differently, influencing both ESR1+ and ESR1- cells. Our results also suggest IL-24 to be a potential marker of estrogen-suppressed tumors.

Detection of DNA Methylation by MeDIP and MBDCap Assays: An Overview of Techniques.

DNA methylation has been characterized as the representative example of epigenetic modifications and implicated in numerous biological processes, such as genomic imprinting and X chromosome inactivation. It primarily occurs at CpG dinucleotides in mammals and plays a critical role in transcriptional regulations. Examination of DNA methylation patterns in gene(s) or across a genome is vital to understand the role of epigenetic modulation in the progress of development and tumorigenesis. Currently, lots of approaches have been developed to investigate DNA methylation patterns for either limited regions or genome-scale studies, but some of them rely on using restriction enzymes. In this chapter, we describe two commonly used protocols to detect enrichment of methylated DNA regions, namely methylated immunoprecipitation (MeDIP) and capture of methylated DNA by methyl-CpG binding domain-based (MBD) proteins (MBDCap). They are the most economical and effective methods to study DNA methylation in either single locus or genome-wide scale.

ERα-mediated cell cycle progression is an important requisite for CDK4/6 inhibitor response in HR+ breast cancer.

While ER has multiple biological effects, ER-cyclin D1-CDK4/6-RB is a critical pathway for the action of estrogen on the cell cycle, especially for breast cancers that rely on estrogen for growth. The latest and most efficient CDK4/6 inhibitors target the phosphorylation of retinoblastoma (RB) tumor suppressor gene; thus, altering levels of many cell cycle molecules. Estrogen receptor (ER)+/HER2- breast cancers have shown great progression free survival when CDK4/6 inhibitors are combined with endocrine therapies. Here we report the mechanism of antiestrogen (fulvestrant) combination with CDK4/6 inhibitors is due to synergism in the suppression of ER-mediated cell cycle progression. Furthermore, we performed single cell analysis of cells from an estrogen dependent/hormone receptor-positive patient derived xenograft (PDX) tumor model treated with palbociclib. These single cells expressed various levels of ER and RB which are involved in cell cycle regulation; and the response to palbociclib treatment relies not only on the ER-cyclin D1-CDK4/6-RB pathway but it is also dependent on elevated levels of ER and/or RB. Our preclinical studies show that palbociclib response is dependent on cells with ER, which is directly involved in cell cycle progression in hormone receptor positive (HR+) breast cancer.

Dual mTOR Kinase Inhibitor MLN0128 Sensitizes HR+/HER2+ Breast Cancer Patient-Derived Xenografts to Trastuzumab or Fulvestrant.

Purpose: Therapeutic strategies against hormonal receptor-positive (HR+)/HER2+ breast cancers with poor response to trastuzumab need to be optimized.Experimental Design: Two HR+/HER2+ patient-derived xenograft (PDX) models named as COH-SC1 and COH-SC31 were established to explore targeted therapies for HER2+ breast cancers. RNA sequencing and RPPA (reverse phase protein array) analyses were conducted to decipher molecular features of the two PDXs and define the therapeutic strategy of interest, validated by in vivo drug efficacy examination and in vitro cell proliferation analysis.Results: Estrogen acted as a growth driver of trastuzumab-resistant COH-SC31 tumors but an accelerator in the trastuzumab-sensitive COH-SC1 model. In vivo trastuzumab efficacy examination further confirmed the consistent responses between PDXs and the corresponding tumors. Integrative omics analysis revealed that mammalian target of rapamycin (mTOR) and ERα signaling predominantly regulate tumor growth of the two HR+/HER2+ PDXs. Combination of the dual mTOR complex inhibitor MLN0128 and anti-HER2 trastuzumab strongly suppressed tumor growth of COH-SC1 PDX accompanied by increasing ER-positive cell population in vivo Instead, MLN0128 in combination with antiestrogen fulvestrant significantly halted the growth of HR+/HER2+ cancer cells in vitro and trastuzumab-resistant COH-SC31 as well as trastuzumab-sensitive COH-SC1 tumors in vivoConclusions: Compared with the standard trastuzumab treatment, this study demonstrates alternative therapeutic strategies against HR+/HER2+ tumors through establishment of two PDXs coupled with integrative omics analyses and in vivo drug efficacy examination. This work presents a prototype of future "co-clinical" trials to tailor personalized medicine in clinical practice. Clin Cancer Res; 24(2); 395-406. ©2017 AACR.

Promoter Methylation Modulates Indoleamine 2,3-Dioxygenase 1 Induction by Activated T Cells in Human Breast Cancers.

Triple-negative breast cancer (TNBC) cells are modulated in reaction to tumor-infiltrating lymphocytes. However, their specific responses to this immune pressure are unknown. In order to address this question, we first used mRNA sequencing to compare the immunophenotype of the TNBC cell line MDA-MB-231 and the luminal breast cancer cell line MCF7 after both were cocultured with activated human T cells. Despite similarities in the cytokine-induced immune signatures of the two cell lines, MDA-MD-231 cells were able to transcribe more IDO1 than MCF7 cells. The two cell lines had similar upstream JAK/STAT1 signaling and IDO1 mRNA stability. However, using a series of breast cancer cell lines, IFNγ stimulated IDO1 protein expression and enzymatic activity only in ER-, not ER+, cell lines. Treatment with 5-aza-deoxycytidine reversed the suppression of IDO1 expression in MCF7 cells, suggesting that DNA methylation was potentially involved in IDO1 induction. By analyzing several breast cancer datasets, we discovered subtype-specific mRNA and promoter methylation differences in IDO1, with TNBC/basal subtypes exhibiting lower methylation/higher expression and ER+/luminal subtypes exhibiting higher methylation/lower expression. We confirmed this trend of IDO1 methylation by bisulfite pyrosequencing breast cancer cell lines and an independent cohort of primary breast tumors. Taken together, these findings suggest that IDO1 promoter methylation regulates anti-immune responses in breast cancer subtypes and could be used as a predictive biomarker for IDO1 inhibitor-based immunotherapy. Cancer Immunol Res; 5(4); 330-44. ©2017 AACR.

Differential network analysis reveals the genome-wide landscape of estrogen receptor modulation in hormonal cancers.

Several mutual information (MI)-based algorithms have been developed to identify dynamic gene-gene and function-function interactions governed by key modulators (genes, proteins, etc.). Due to intensive computation, however, these methods rely heavily on prior knowledge and are limited in genome-wide analysis. We present the modulated gene/gene set interaction (MAGIC) analysis to systematically identify genome-wide modulation of interaction networks. Based on a novel statistical test employing conjugate Fisher transformations of correlation coefficients, MAGIC features fast computation and adaption to variations of clinical cohorts. In simulated datasets MAGIC achieved greatly improved computation efficiency and overall superior performance than the MI-based method. We applied MAGIC to construct the estrogen receptor (ER) modulated gene and gene set (representing biological function) interaction networks in breast cancer. Several novel interaction hubs and functional interactions were discovered. ER+ dependent interaction between TGFß and NFκB was further shown to be associated with patient survival. The findings were verified in independent datasets. Using MAGIC, we also assessed the essential roles of ER modulation in another hormonal cancer, ovarian cancer. Overall, MAGIC is a systematic framework for comprehensively identifying and constructing the modulated interaction networks in a whole-genome landscape. MATLAB implementation of MAGIC is available for academic uses at https://github.com/chiuyc/MAGIC.

Genome-wide DNA methylation analysis reveals estrogen-mediated epigenetic repression of metallothionein-1 gene cluster in breast cancer.

BACKGROUND: Recent genome-wide analysis has shown that DNA methylation spans long stretches of chromosome regions consisting of clusters of contiguous CpG islands or gene families. Hypermethylation of various gene clusters has been reported in many types of cancer. In this study, we conducted methyl-binding domain capture (MBDCap) sequencing (MBD-seq) analysis on a breast cancer cohort consisting of 77 patients and 10 normal controls, as well as a panel of 38 breast cancer cell lines. RESULTS: Bioinformatics analysis determined seven gene clusters with a significant difference in overall survival (OS) and further revealed a distinct feature that the conservation of a large gene cluster (approximately 70 kb) metallothionein-1 (MT1) among 45 species is much lower than the average of all RefSeq genes. Furthermore, we found that DNA methylation is an important epigenetic regulator contributing to gene repression of MT1 gene cluster in both ERα positive (ERα+) and ERα negative (ERα-) breast tumors. In silico analysis revealed much lower gene expression of this cluster in The Cancer Genome Atlas (TCGA) cohort for ERα + tumors. To further investigate the role of estrogen, we conducted 17ß-estradiol (E2) and demethylating agent 5-aza-2'-deoxycytidine (DAC) treatment in various breast cancer cell types. Cell proliferation and invasion assays suggested MT1F and MT1M may play an anti-oncogenic role in breast cancer. CONCLUSIONS: Our data suggests that DNA methylation in large contiguous gene clusters can be potential prognostic markers of breast cancer. Further investigation of these clusters revealed that estrogen mediates epigenetic repression of MT1 cluster in ERα + breast cancer cell lines. In all, our studies identify thousands of breast tumor hypermethylated regions for the first time, in particular, discovering seven large contiguous hypermethylated gene clusters.

Estrogen induces global reorganization of chromatin structure in human breast cancer cells.

In the cell nucleus, each chromosome is confined to a chromosome territory. This spatial organization of chromosomes plays a crucial role in gene regulation and genome stability. An additional level of organization has been discovered at the chromosome scale: the spatial segregation into open and closed chromatins to form two genome-wide compartments. Although considerable progress has been made in our knowledge of chromatin organization, a fundamental issue remains the understanding of its dynamics, especially in cancer. To address this issue, we performed genome-wide mapping of chromatin interactions (Hi-C) over the time after estrogen stimulation of breast cancer cells. To biologically interpret these interactions, we integrated with estrogen receptor α (ERα) binding events, gene expression and epigenetic marks. We show that gene-rich chromosomes as well as areas of open and highly transcribed chromatins are rearranged to greater spatial proximity, thus enabling genes to share transcriptional machinery and regulatory elements. At a smaller scale, differentially interacting loci are enriched for cancer proliferation and estrogen-related genes. Moreover, these loci are correlated with higher ERα binding events and gene expression. Taken together these results reveal the role of a hormone--estrogen--on genome organization, and its effect on gene regulation in cancer.

Detection of DNA methylation by MeDIP and MBDCap assays: an overview of techniques.

DNA methylation has been characterized as the representative example of epigenetic modifications and implicated in numerous biological processes, such as genomic imprinting and X chromosome inactivation. It primarily occurs at CpG dinucleotides in mammals and plays a critical role in transcriptional regulations. Examination of DNA methylation patterns in gene(s) or across a genome is vital to understand the role of epigenetic modulation in the progress of development and tumorigenesis. Currently, lots of approaches have been developed to investigate DNA methylation patterns for either limited regions or for genome-scale studies, but some of them rely on using restriction enzymes. In this chapter, we describe two commonly used protocols to detect enrichment of methylated DNA regions, namely, methylated DNA immunoprecipitation (MeDIP) and capture of methylated DNA by methyl-CpG binding domain-based (MBD) proteins (MBDCap). They are the most economical and effective methods to study DNA methylation either at a single locus or in genome-wide scale.

Amplification of distant estrogen response elements deregulates target genes associated with tamoxifen resistance in breast cancer.

A causal role of gene amplification in tumorigenesis is well known, whereas amplification of DNA regulatory elements as an oncogenic driver remains unclear. In this study, we integrated next-generation sequencing approaches to map distant estrogen response elements (DEREs) that remotely control the transcription of target genes through chromatin proximity. Two densely mapped DERE regions located on chromosomes 17q23 and 20q13 were frequently amplified in estrogen receptor-α-positive luminal breast cancer. These aberrantly amplified DEREs deregulated target gene expression potentially linked to cancer development and tamoxifen resistance. Progressive accumulation of DERE copies was observed in normal breast progenitor cells chronically exposed to estrogenic chemicals. These findings may extend to other DNA regulatory elements, the amplification of which can profoundly alter target transcriptome during tumorigenesis.

LOcating non-unique matched tags (LONUT) to improve the detection of the enriched regions for ChIP-seq data.

One big limitation of computational tools for analyzing ChIP-seq data is that most of them ignore non-unique tags (NUTs) that match the human genome even though NUTs comprise up to 60% of all raw tags in ChIP-seq data. Effectively utilizing these NUTs would increase the sequencing depth and allow a more accurate detection of enriched binding sites, which in turn could lead to more precise and significant biological interpretations. In this study, we have developed a computational tool, LOcating Non-Unique matched Tags (LONUT), to improve the detection of enriched regions from ChIP-seq data. Our LONUT algorithm applies a linear and polynomial regression model to establish an empirical score (ES) formula by considering two influential factors, the distance of NUTs to peaks identified using uniquely matched tags (UMTs) and the enrichment score for those peaks resulting in each NUT being assigned to a unique location on the reference genome. The newly located tags from the set of NUTs are combined with the original UMTs to produce a final set of combined matched tags (CMTs). LONUT was tested on many different datasets representing three different characteristics of biological data types. The detected sites were validated using de novo motif discovery and ChIP-PCR. We demonstrate the specificity and accuracy of LONUT and show that our program not only improves the detection of binding sites for ChIP-seq, but also identifies additional binding sites.

Genome-wide analysis uncovers high frequency, strong differential chromosomal interactions and their associated epigenetic patterns in E2-mediated gene regulation.

BACKGROUND: An emerging Hi-C protocol has the ability to probe three-dimensional (3D) architecture and capture chromatin interactions in a genome-wide scale. It provides informative results to address how chromatin organization changes contribute to disease/tumor occurrence and progression in response to stimulation of environmental chemicals or hormones. RESULTS: In this study, using MCF7 cells as a model system, we found estrogen stimulation significantly impact chromatin interactions, leading to alteration of gene regulation and the associated histone modification states. Many chromosomal interaction regions at different levels of interaction frequency were identified. In particular, the top 10 hot regions with the highest interaction frequency are enriched with breast cancer specific genes. Furthermore, four types of E2-mediated strong differential (gain- or loss-) chromosomal (intra- or inter-) interactions were classified, in which the number of gain-chromosomal interactions is less than the number of loss-chromosomal interactions upon E2 stimulation. Finally, by integrating with eight histone modification marks, DNA methylation, regulatory elements regions, ERα and Pol-II binding activities, associations between epigenetic patterns and high chromosomal interaction frequency were revealed in E2-mediated gene regulation. CONCLUSIONS: The work provides insight into the effect of chromatin interaction on E2/ERα regulated downstream genes in breast cancer cells.

Cancer omics: from regulatory networks to clinical outcomes.

Current limitation in cancer genomic studies is a lack of the integration of various omics data generated through next generation sequencing technologies, as well as a lack of the sounding and comprehensive epigenomic and genomic information about a particular cancer cell type. In this review, we will discuss main aspects of current genomics research with its application in cancer topics. We will first overview the next-generation sequencing technologies, then outline the major computational approaches, particularly focusing on ChIP-based omics data, and list several remaining open questions facing computational biologists, further present regulatory network analysis inferred from the ChIP-based omics data; finally implicate the clinical outcomes from the network and pathway analysis.

Hierarchical modularity in ERα transcriptional network is associated with distinct functions and implicates clinical outcomes.

Recent genome-wide profiling reveals highly complex regulation networks among ERα and its targets. We integrated estrogen (E2)-stimulated time-series ERα ChIP-seq and gene expression data to identify the ERα-centered transcription factor (TF) hubs and their target genes, and inferred the time-variant hierarchical network structures using a Bayesian multivariate modeling approach. With its recurrent motif patterns, we determined three embedded regulatory modules from the ERα core transcriptional network. The GO analyses revealed the distinct biological function associated with each of three embedded modules. The survival analysis showed the genes in each module were able to render a significant survival correlation in breast cancer patient cohorts. In summary, our Bayesian statistical modeling and modularity analysis not only reveals the dynamic properties of the ERα-centered regulatory network and associated distinct biological functions, but also provides a reliable and effective genomic analytical approach for the analysis of dynamic regulatory network for any given TF.

Estrogen-mediated epigenetic repression of the imprinted gene cyclin-dependent kinase inhibitor 1C in breast cancer cells.

While tumor suppressor genes frequently undergo epigenetic silencing in cancer, how the instructions directing this transcriptional repression are transmitted in cancer cells remain largely unclear. Expression of cyclin-dependent kinase inhibitor 1C (CDKN1C), an imprinted gene on chromosomal band 11 p15.5, is reduced or lost in the majority of breast cancers. Here, we report that CDKN1C is suppressed by estrogen through epigenetic mechanisms involving the chromatin-interacting noncoding RNA KCNQ1OT1 and CCCTC-binding factor (CTCF). Activation of estrogen signaling reduced CDKN1C expression 3-fold (P < 0.001) and established repressive histone modifications at the 5' regulatory region of the locus. These events were concomitant with induction of KCNQ1OT1 expression as well as increased recruitment of CTCF to both the distal KCNQ1OT1 promoter-associated imprinting control region (ICR) and the CDKN1C locus. Transient depletion of CTCF by small interfering RNA increased CDKN1C expression and significantly reduced the estrogen-mediated repression of CDKN1C. Further studies in breast cancer cell lines indicated that the epigenetic silencing of CDKN1C occurs in part as the result of genetic loss of the inactive methylated 11p15.5 ICR allele (R(2) = 0.612, P < 0.001). We also found a novel cis-encoded antisense transcript, CDKN1C-AS, which is induced by estrogen signaling following pharmacologic inhibition of DNA methyltransferase and histone deacetylase activity. Forced expression of CDKN1C-AS was capable of repressing endogenous CDKN1C in vivo. Our findings suggest that in addition to promoter hypermethylation, epigenetic repression of tumor suppressor genes by CTCF and noncoding RNA transcripts could be more common and important than previously understood.

Epigenetic silencing mediated through activated PI3K/AKT signaling in breast cancer.

Trimethylation of histone 3 lysine 27 (H3K27me3) is a critical epigenetic mark for the maintenance of gene silencing. Additional accumulation of DNA methylation in target loci is thought to cooperatively support this epigenetic silencing during tumorigenesis. However, molecular mechanisms underlying the complex interplay between the two marks remain to be explored. Here we show that activation of PI3K/AKT signaling can be a trigger of this epigenetic processing at many downstream target genes. We also find that DNA methylation can be acquired at the same loci in cancer cells, thereby reinforcing permanent repression in those losing the H3K27me3 mark. Because of a link between PI3K/AKT signaling and epigenetic alterations, we conducted epigenetic therapies in conjunction with the signaling-targeted treatment. These combined treatments synergistically relieve gene silencing and suppress cancer cell growth in vitro and in xenografts. The new finding has important implications for improving targeted cancer therapies in the future.

Inference of hierarchical regulatory network of estrogen-dependent breast cancer through ChIP-based data.

BACKGROUND: Global profiling of in vivo protein-DNA interactions using ChIP-based technologies has evolved rapidly in recent years. Although many genome-wide studies have identified thousands of ERα binding sites and have revealed the associated transcription factor (TF) partners, such as AP1, FOXA1 and CEBP, little is known about ERα associated hierarchical transcriptional regulatory networks. RESULTS: In this study, we applied computational approaches to analyze three public available ChIP-based datasets: ChIP-seq, ChIP-PET and ChIP-chip, and to investigate the hierarchical regulatory network for ERα and ERα partner TFs regulation in estrogen-dependent breast cancer MCF7 cells. 16 common TFs and two common new TF partners (RORA and PITX2) were found among ChIP-seq, ChIP-chip and ChIP-PET datasets. The regulatory networks were constructed by scanning the ChIP-peak region with TF specific position weight matrix (PWM). A permutation test was performed to test the reliability of each connection of the network. We then used DREM software to perform gene ontology function analysis on the common genes. We found that FOS, PITX2, RORA and FOXA1 were involved in the up-regulated genes.We also conducted the ERα and Pol-II ChIP-seq experiments in tamoxifen resistance MCF7 cells (denoted as MCF7-T in this study) and compared the difference between MCF7 and MCF7-T cells. The result showed very little overlap between these two cells in terms of targeted genes (21.2% of common genes) and targeted TFs (25% of common TFs). The significant dissimilarity may indicate totally different transcriptional regulatory mechanisms between these two cancer cells. CONCLUSIONS: Our study uncovers new estrogen-mediated regulatory networks by mining three ChIP-based data in MCF7 cells and ChIP-seq data in MCF7-T cells. We compared the different ChIP-based technologies as well as different breast cancer cells. Our computational analytical approach may guide biologists to further study the underlying mechanisms in breast cancer cells or other human diseases.

Epigenetic influences of low-dose bisphenol A in primary human breast epithelial cells.

Substantial evidence indicates that exposure to bisphenol A (BPA) during early development may increase breast cancer risk later in life. The changes may persist into puberty and adulthood, suggesting an epigenetic process being imposed in differentiated breast epithelial cells. The molecular mechanisms by which early memory of BPA exposure is imprinted in breast progenitor cells and then passed onto their epithelial progeny are not well understood. The aim of this study was to examine epigenetic changes in breast epithelial cells treated with low-dose BPA. We also investigated the effect of BPA on the ERα signaling pathway and global gene expression profiles. Compared to control cells, nuclear internalization of ERα was observed in epithelial cells preexposed to BPA. We identified 170 genes with similar expression changes in response to BPA. Functional analysis confirms that gene suppression was mediated in part through an ERα-dependent pathway. As a result of exposure to BPA or other estrogen-like chemicals, the expression of lysosomal-associated membrane protein 3 (LAMP3) became epigenetically silenced in breast epithelial cells. Furthermore, increased DNA methylation in the LAMP3 CpG island was this repressive mark preferentially occurred in ERα-positive breast tumors. These results suggest that the in vitro system developed in our laboratory is a valuable tool for exposure studies of BPA and other xenoestrogens in human cells. Individual and geographical differences may contribute to altered patterns of gene expression and DNA methylation in susceptible loci. Combination of our exposure model with epigenetic analysis and other biochemical assays can give insight into the heritable effect of low-dose BPA in human cells.

An unusual function of RON receptor tyrosine kinase as a transcriptional regulator in cooperation with EGFR in human cancer cells.

Homodimerization of RON (MST1R), a receptor tyrosine kinase, usually occurs in cells stimulated by a ligand and leads to the downstream activation of signaling pathways. Here we report that bladder cancer cells, in response to physiological stress, use an alternative mechanism for signaling activation. Time-course studies indicated that RON migrated directly from the membrane to the nucleus of bladder cancer cells in response to serum starvation. Biochemical and genetic studies implied that this nuclear internalization was complexed with epidermal growth factor receptor (EGFR) and required the docking of importins. In vivo analysis confirmed that nuclear RON was present in 38.4% (28/73) of primary bladder tumors. Chromatin immunoprecipitation (ChIP) on microarray analysis further revealed that this internalized complex bound to at least 134 target genes known to participate in three stress-responsive networks: p53, stress-activated protein kinase/c-jun N-terminal kinase and phosphatidylinositol 3-kinase/Akt. These findings suggest that RON, in a complex with EGFR, acts as a transcriptional regulator in response to acute disturbances (e.g. serum starvation) imposed on cancer cells. In an attempt to re-establish homeostasis, these cells bypass regular mechanisms required by ligand stimulation and trigger the RON-directed transcriptional response, which confers a survival advantage.

Estrogen-mediated epigenetic repression of large chromosomal regions through DNA looping.

The current concept of epigenetic repression is based on one repressor unit corresponding to one silent gene. This notion, however, cannot adequately explain concurrent silencing of multiple loci observed in large chromosome regions. The long-range epigenetic silencing (LRES) can be a frequent occurrence throughout the human genome. To comprehensively characterize the influence of estrogen signaling on LRES, we analyzed transcriptome, methylome, and estrogen receptor alpha (ESR1)-binding datasets from normal breast epithelia and breast cancer cells. This "omics" approach uncovered 11 large repressive zones (range, 0.35 approximately 5.98 megabases), including a 14-gene cluster located on 16p11.2. In normal cells, estrogen signaling induced transient formation of multiple DNA loops in the 16p11.2 region by bringing 14 distant loci to focal ESR1-docking sites for coordinate repression. However, the plasticity of this free DNA movement was reduced in breast cancer cells. Together with the acquisition of DNA methylation and repressive chromatin modifications at the 16p11.2 loci, an inflexible DNA scaffold may be a novel determinant used by breast cancer cells to reinforce estrogen-mediated repression.