Article

TNFa Signaling Exposes Latent Estrogen Receptor Binding Sites to Alter the Breast Cancer Cell Transcriptome Graphical Abstract

Authors Hector L. Franco, Anusha Nagari, W. Lee Kraus

Correspondence [email protected]

In Brief Using genomic and molecular analyses, Franco et al. show that the TNFa pathway alters estrogen signaling to promote the redistribution of NF-kB and FoxA1 binding sites across the genome. This creates latent ERa binding sites that drive altered patterns of gene expression underlying clinically relevant cellular responses in breast cancer.

Highlights d

E2 + TNFa promotes extensive transcriptional crosstalk in breast cancer cells

d

The target genes are strongly associated with clinical outcomes in breast cancers

d

TNFa signaling drives NF-kB and FoxA1 to latent enhancers to promote ERa binding

d

NF-kB and FoxA1 are required for establishing active ERa enhancers at latent sites

Franco et al., 2015, Molecular Cell 58, 1–14 April 2, 2015 ª2015 Elsevier Inc. http://dx.doi.org/10.1016/j.molcel.2015.02.001

Accession Numbers GSE59530 GSE59531 GSE59532

Please cite this article in press as: Franco et al., TNFa Signaling Exposes Latent Estrogen Receptor Binding Sites to Alter the Breast Cancer Cell Transcriptome, Molecular Cell (2015), http://dx.doi.org/10.1016/j.molcel.2015.02.001

Molecular Cell

Article TNFa Signaling Exposes Latent Estrogen Receptor Binding Sites to Alter the Breast Cancer Cell Transcriptome Hector L. Franco,1 Anusha Nagari,1 and W. Lee Kraus1,* 1Laboratory of Signaling and Gene Regulation, Cecil H. and Ida Green Center for Reproductive Biology Sciences and Division of Basic Reproductive Biology Research, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA *Correspondence: [email protected] http://dx.doi.org/10.1016/j.molcel.2015.02.001

SUMMARY

The interplay between mitogenic and proinflammatory signaling pathways plays key roles in determining the phenotypes and clinical outcomes of breast cancers. Using GRO-seq in MCF-7 cells, we defined the immediate transcriptional effects of crosstalk between estradiol (E2) and TNFa, identifying a large set of target genes whose expression is rapidly altered with combined E2 + TNFa treatment, but not with either agent alone. The pleiotropic effects on gene transcription in response to E2 + TNFa are orchestrated by extensive remodeling of the ERa enhancer landscape in an NF-kB- and FoxA1-dependent manner. In addition, expression of the de novo and synergistically regulated genes is strongly associated with clinical outcomes in breast cancers. Together, our genomic and molecular analyses indicate that TNFa signaling, acting in pathways culminating in the redistribution of NF-kB and FoxA1 binding sites across the genome, creates latent ERa binding sites that underlie altered patterns of gene expression and clinically relevant cellular responses.

INTRODUCTION Estrogen signaling through estrogen receptor alpha (ERa), a nuclear transcription factor, has potent mitogenic effects in breast cancer cells. About two-thirds of breast cancers are ERa positive and exhibit estrogen-dependent growth at the time of diagnosis, making them good targets for anti-hormone therapies (Ignatiadis and Sotiriou, 2013). As such, ERa status serves as an important diagnostic and prognostic indicator in breast cancer patients (Ignatiadis and Sotiriou, 2013). The estrogen signaling pathway exerts its growth-promoting effects by rapidly and transiently altering and expanding the breast cancer cell transcriptome, which leads to the altered expression of a wide variety of coding and non-coding RNAs (Hah et al., 2011, 2013). Estrogen signaling stimulates the binding of ERa to many thousands of

sites across the genome that are pre-established and ‘‘marked’’ by pioneer transcription factors, such as FoxA1 or AP2g (Hurtado et al., 2011; Tan et al., 2011), although access to new sites in the genome may be promoted by stimulation of mitogenic pathways (Ross-Innes et al., 2012). Once bound at these sites, ERa promotes the coordinated recruitment of coregulatory proteins and chromatin-modifying enzymes that establish an active enhancer, leading to chromatin looping and target gene transcription (Foulds et al., 2013; Fullwood et al., 2009; Hah et al., 2013; He et al., 2012; Shlyueva et al., 2014). In contrast to the potent proliferative effects of estrogens in breast cancers, proinflammatory signaling in the tumor microenvironment can have either proliferative or anti-proliferative effects, depending on the tumor context (Ben-Neriah and Karin, 2011; Coussens et al., 2013). Proinflammatory signaling in cancers derives from acute and chronic infections, tumor-infiltrating immune cells, and local adipose tissue, all of which are capable of supplying the tumor microenvironment with bioactive molecules that facilitate angiogenesis, invasion, and metastasis (Baumgarten and Frasor, 2012; Ben-Neriah and Karin, 2011). Consequently, inflammation is now considered a hallmark of cancer (Hanahan and Weinberg, 2011). One of the major integrators of proinflammatory signaling is the transcription factor NFkB, which is found in almost all cell types and is activated by a variety of chemokines, cytokines, and growth factors, including tumor necrosis factor alpha (TNFa). In the canonical NF-kB pathway, liganded receptors in the cell membrane initiate signaling cascades that ultimately lead to the nuclear translocation of NF-kB subunits (e.g., p65 and p50), which bind to NF-kB enhancer elements that control target gene expression (BenNeriah and Karin, 2011; Natoli, 2012). The interplay between mitogenic and proinflammatory signaling pathways plays key roles in determining the phenotypes and clinical outcomes of breast cancers. The distinct, but interrelated, responses to estrogens and TNFa (i.e., mitogenic versus proinflammatory) have the potential to create novel antagonistic or synergistic responses that can profoundly affect the biology of breast cancers (Baumgarten and Frasor, 2012). A number of recent studies have shown that proinflammatory signaling can lead to more aggressive hormone-dependent breast cancers. For example, constitutive activation of NF-kB is associated with more aggressive ERa-positive breast cancers and the development of resistance to endocrine therapy (Zhou Molecular Cell 58, 1–14, April 2, 2015 ª2015 Elsevier Inc. 1

Please cite this article in press as: Franco et al., TNFa Signaling Exposes Latent Estrogen Receptor Binding Sites to Alter the Breast Cancer Cell Transcriptome, Molecular Cell (2015), http://dx.doi.org/10.1016/j.molcel.2015.02.001

B 15

974

Up Regulated

TNF

De Novo (Gained) Genes

TNF

E2+TNF

E2

Veh

All Protein Coding Genes

159 2,141

819

E2 260

(Fold Change)

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Synergistically Regulated Genes 20

n = 304

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10

10 5 0

926

n = 509

c

15

a

a

E

T

a b

5 0

E+T

E

T

E+T

a

n = 1,595

Treatment

Up

Down Regulated

E2+TNF Down

+1 Rel. to Veh

E2

1,292

872

TNF

1,093

3,000

E2+TNF

1,708

3,838

(Fold Change)

1,660 1.2 1.0 0.8 0.6 0.4 0.2 0

n = 1,356 a

a

E

T

b

1.2 1.0 0.8 0.6 0.4 0.2 0

E+T

E

b

c

T

E+T

-1 n = 6940

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Proinflammatory Genes

100 90 80 70 60 50 40 30 20 10

Low Expression (n = 85) High Expression (n = 84) 0

De Novo and Synergistically Up-Regulated Genes 100 90 80 70 60 50 40 30 20 10

0.01945 p p= = 0.019

Low Expression (n = 77) High Expression (n = 92)

0 0

2

4

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8

100 90 80 70 60 50 40 30 20 10

6

8

Untreated Tumors

p = 0.030

Low Expression (n = 136) High Expression (n = 74)

0 10

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2

4

6

8

Years

Years

De Novo and Synergistically Up-Regulated Genes

De Novo and Synergistically Down-Regulated Genes

p = 1 x 10-05

Low Expression (n = 153) High Expression (n = 57)

0 10

4

Untreated Tumors

Overall Survival (%)

Overall Survival (%)

ER+ LN+ Tumors

2

100 90 80 70 60 50 40 30 20 10

Overall Survival (%)

Overall Survival (%)

0.00354 p p= = 0.004

0

E

Proinflammatory Genes

ER+ LN+ Tumors

0

Years

2

4

6

Years

8

100 90 80 70 60 50 40 30 20 10

p = 0.005

Low Expression (n = 220) High Expression (n = 160)

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ER+ LN Neg

Overall Survival (%)

C

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Years

Figure 1. Crosstalk between Mitogenic and Proinflammatory Signaling in Breast Cancer Cells: Effects on mRNA Expression, Cell Growth, and Breast Cancer Patient Outcomes MCF-7 cells were treated with vehicle (Veh or V), estradiol (E or E2), TNFa (T or TNF), or both E2 + TNFa (E+T) and subjected to GRO-seq or cell proliferation assays. The GRO-seq data were analyzed for patterns of gene expression and related to breast cancer patient outcomes. (A) Heatmap (left) and Venn diagram (right) showing the regulation of all protein-coding genes under each treatment condition as revealed by GRO-seq. The changes in expression shown in the heatmap were centered relative to the control (vehicle) condition and scaled relative to the maximum absolute value of the expression change for each gene. Thus, the values range between +1 and 1, where +1 or 1 denote the maximum or minimum value, respectively. (B) Boxplots showing changes in GRO-seq signals for genes that are newly (de novo or gained) or synergistically regulated by E2 + TNFa. Bars marked with different letters are significantly different from each other (Wilcoxon rank sum test, p < 1 3 10 6). For example, bars labeled with ‘‘a’’ are different from those labeled with ‘‘b’’ or ‘‘c,’’ but not from other bars labeled with ‘‘a.’’ (C) MCF-7 cell proliferation assay. Each data point represents the mean ± SEM, n = 3. (D and E) Kaplan-Meier survival analyses for different breast cancer types using three distinct gene sets as inputs: (1) a proinflammatory gene set defined by gene ontologies (D), (2) the E2 + TNFa de novo and synergistically upregulated gene set (E, left and middle), and (3) the E2 + TNFa de novo and synergistically (legend continued on next page)

2 Molecular Cell 58, 1–14, April 2, 2015 ª2015 Elsevier Inc.

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et al., 2005). Furthermore, TNFa-activated NF-kB and estrogenactivated ERa can work together to potentiate the expression of a number of genes associated with proliferation, invasion, and metastasis in breast cancer cells (Frasor et al., 2009; Ross-Innes et al., 2012). As shown in gene-specific studies, crosstalk between the estrogen and TNFa signaling pathways is mediated, in part, by the ability of ERa and NF-kB to physically interact and bind together at enhancers (Kalaitzidis and Gilmore, 2005; Pradhan et al., 2012; Pradhan et al., 2010). However, the functional relationships and outcomes of the crosstalk between NF-kB/proinflammatory signaling and ERa/mitogenic signaling are complex and context dependent, and they have the potential to promote clinical outcomes that are more favorable (Cunningham and Gilkeson, 2011; Frasor et al., 2009; Ross-Innes et al., 2012). In differentiated cells, cell state-determining transcription factors, such as ERa, are thought to bind to a predetermined or pre-established enhancer repertoire, ensuring a constrained and biologically appropriate response to stimuli (Ghavi-Helm et al., 2014; Heinz et al., 2010; Hurtado et al., 2011; Shlyueva et al., 2014). How a pre-established enhancer repertoire may be altered by crosstalk with other signaling pathways is not well understood. In this regard, recent studies have identified ‘‘latent’’ enhancers, which are formed and activated de novo in response to cellular signals at genomic sites that are not pre-established (Kaikkonen et al., 2013; Nord et al., 2013; Ostuni et al., 2013). In the studies described herein, we used a variety of genomic, molecular, and biochemical approaches to (1) examine the nature and extent of crosstalk between the estrogen and TNFa signaling pathways in breast cancer cells, (2) determine how this crosstalk alters the ERa cistrome, creating new ERa binding sites and opportunities for gene regulation, and (3) understand how the de novo transcriptome specifies biological outcomes. RESULTS The E2-Regulated Transcriptome and Cellular Mitogenic Responses Are Dramatically Altered by TNFa in Breast Cancer Cells To determine the interplay between mitogenic and proinflammatory signaling in breast cancer cells at the transcriptional level, we monitored the direct transcriptional output in ERa-positive MCF-7 cells treated with 17-b-estradiol (E2), TNFa, or both E2 + TNFa (Figure S1A) using global run-on coupled with deep sequencing (GRO-seq). By limiting the treatment times to 40 min, when both E2 and TNFa transcriptional responses are maximal for most genes (Danko et al., 2013; Hah et al., 2011; Luo et al., 2014), our analyses capture primary transcriptional outcomes. Across the genome, TNFa-induced proinflammatory signaling and E2-induced mitogenic signaling converged on many genes, including mRNA genes and long non-coding RNA

(lncRNA) genes, leading to numerous instances of antagonism or enhancement of gene expression (Figures 1A, 1B, and S1B). Notably, the immediate and extensive E2-regulated gene expression program was dramatically altered by the addition of TNFa, leading to the up- or downregulation of a new set of genes (de novo or ‘‘gained’’ genes, including 1,660 mRNA genes and 773 lncRNA genes) that were unaffected by either treatment alone (Figure 1B, left; Figure S1C, left). In addition, we observed a group of genes (synergistically regulated genes, including 2,104 mRNA genes and 649 lncRNA genes) whose E2-mediated up- or downregulation was synergistically enhanced by TNFa (Figure 1B, right; Figure S1C, right). These responses led to an E2 + TNFa-regulated transcriptome that is much larger than those observed with E2 or TNFa alone. The genes within this unique transcriptome are involved in molecular and cellular processes ranging from signaling and transcription to metabolism, proliferation, and apoptosis (Table S1). The altered patterns of E2-regulated gene expression in response to TNFa were associated with corresponding changes in the growth of MCF-7 cells. Specifically, TNFa completely blocked the potent mitogenic response to E2 in a dose-dependent manner (Figures 1C and S1D). The inhibitory effect of TNFa was also observed in two other ERa-positive breast cancer cell lines (i.e., ZR-75-1 and MDA-MB-361; Figure S1E). To determine if the unique E2 + TNFa-regulated transcriptome has a broader clinical significance, we mined breast cancer outcome-linked gene expression data using the Gene Expression-Based Outcome for Breast Cancer Online (GOBO) tool, expressing the outcomes in Kaplan-Meier survival plots. As a reference point, we determined if high expression levels of a proinflammatory gene set (defined by gene ontologies) are associated with good or poor outcomes in breast cancers. As expected given the complex nature of inflammation in breast cancers, we found that high expression levels of this gene set are associated with good outcomes in some breast cancers (Figure 1D, left; Figure S1F) and poor outcomes in others (Figure 1D, right; Figure S1F). Likewise, the expression levels of E2 + TNFa de novo and synergistically regulated gene sets are strong predictors of clinical outcomes, but good versus poor outcomes vary based on the particular breast cancer type (Figures 1E and S1G). For example, high-level expression of the E2 + TNFa upregulated gene set predicts good outcomes in ERa-positive, lymph node-positive breast cancers (Figure 1E, left) and poor outcomes in untreated breast cancers (Figure 1E, middle). Interestingly, the E2 + TNFa de novo and synergistically regulated gene sets are largely non-overlapping with the proinflammatory gene set defined by gene ontologies (Figure S1H). Collectively, these results indicate that the gene expression program induced by co-stimulation with E2 and TNFa is tied to robust biological outcomes that control the growth of breast cancer cells and predict distinct clinical outcomes across a range of breast cancer types. The studies described below are aimed at understanding

downregulated gene set (E, right). The breast cancer outcome-linked gene expression data were accessed using the Gene Expression-Based Outcome for Breast Cancer Online (GOBO) tool. In some cases, high expression levels of the gene sets are predictive of better outcomes in a particular breast cancer type (e.g., D, left; E, left), while in others it is predictive of a poor outcome (e.g., D, right; E, middle). See also Figure S1 and Table S1.

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the molecular mechanisms and the functional interplay between the estrogen and TNFa signaling pathways. Proinflammatory Signaling Alters the Repertoire of ERa Binding Sites and Unveils New Sites of Molecular Crosstalk To explore the molecular crosstalk between the estrogen and TNFa signaling pathways at the genomic level, we used ChIPseq for ERa (a transcription factor mediator of the estrogen signaling pathway) and the p65 subunit of NF-kB (a transcription factor mediator of the TNFa signaling pathway). Although the majority of the E2-induced ERa binding events were unchanged (‘‘maintained’’) by cotreatment with TNFa, the cotreatment caused a gain of 1,664 new ERa binding sites and a loss of 1,938 ERa binding sites (Figures 2A and 2B). We confirmed the presence of the gained sites, which were of particular interest given the transcription results in Figure 1A, in another ERa-positive breast cancer cell line, ZR-75-1, by ChIP-qPCR (Figure S2A). About half of the gained ERa binding sites were also occupied by NF-kB upon cotreatment with E2 and TNFa, while the lost ERa binding sites were generally not occupied by NF-kB (Figures 2A and 2B). Interestingly, TNFa-mediated NF-kB binding was enhanced in the presence of E2 at the gained (and to a lesser extent, maintained) ERa binding sites (Figure 2B, top and middle). These results suggest functional interactions between two signal-regulated transcription factors (i.e., ERa and NF-kB) across the genome. Such observations fit with studies of individual ERa binding sites showing that ERa and NF-kB can physically interact on chromatin, allowing for changes in gene expression (Kalaitzidis and Gilmore, 2005; Pradhan et al., 2010, 2012). DNA sequence analyses of the gained, maintained, and lost ERa binding sites showed an expected enrichment of ERa (ESR1), NF-kB (RELA), and FoxA1 (FOXA1) motifs, with the most prevalent motifs at the gained ERa binding sites being RELA and ESR1 (Figure 2C). Similar to what we observed with the ERa cistrome upon treatment with TNFa, we also observed alterations in the TNFa-induced NF-kB cistrome by cotreatment with E2, leading to the gain or loss of NF-kB binding sites across the genome (Figures S2B and S2C). Collectively, these results illustrate how distinct signaling pathways converge on nuclear transcription factors to alter their patterns of binding, creating new cistromes and, ultimately, target transcriptomes. E2-Dependent ERa Binding Sites Gained upon Cotreatment with TNFa Produce Enhancer RNAs and Are Associated with Target Gene Expression Signal-regulated enhancers can modulate target gene expression from distal positions in the genome through looping events that bring distal enhancers into contact with proximal promoters through the formation of chromatin loops (de Laat and Duboule, 2013). Recent studies from our lab and others have shown that enhancers with histone modifications indicative of activity, such as H3K4me1 and H3K27ac, are more likely to produce enhancer transcripts (eRNAs) and loop to target gene promoters (Hah et al., 2013; Kieffer-Kwon et al., 2013; Kim et al., 2010). Thus, eRNA production is a good marker of active enhancers that regulate target genes (Hah et al., 2013). To assess whether the E2-dependent ERa binding sites gained upon cotreatment 4 Molecular Cell 58, 1–14, April 2, 2015 ª2015 Elsevier Inc.

with TNFa are active and functional enhancers, we leveraged the power of GRO-seq to assay enhancer transcription and target gene transcription upon ERa binding (Figure 3A). First, we assayed enhancer transcription at the gained, maintained, and lost ERa binding sites. We observed that the amount of enhancer transcription in response to vehicle (V), E2 (E), TNFa (T), or E2 + TNFa (E+T) was positively correlated with the extent of ERa (or p65) binding under the same conditions; in general, more enhancer transcription was observed with more ERa binding, as determined by the correlation analyses shown in Figure S3A (see also Figure 3B, middle; compare to the extent of ERa binding in Figure 2B). For example, with the gained ERa binding sites, the levels of enhancer transcription were greatest with the TNFa or E2 + TNFa treatments (Figure 3B, middle bottom), reflecting the occupancy of those sites by p65 (for TNFa alone; Figure 2B, top right) or ERa and p65 (for E2 + TNFa; Figure 2B, top). Next, we used GRO-seq to determine the levels of transcription at the nearest neighboring gene (upstream or downstream) from each ERa binding site. For the genes located nearest to the gained and maintained ERa binding sites, we observed that the amount of target gene transcription in response to the four treatment conditions was proportional to the extent of enhancer transcription under the same conditions (i.e., in general, more target gene transcription was observed with more enhancer transcription) (Figure 3B). Furthermore, we found that gained ERa binding sites are significantly enriched for neighboring genes whose expression is stimulated by E2 + TNFa treatment (Figure S3B). Lost ERa binding sites, which showed persistent transcription of the nearest neighboring genes with E2 + TNFa treatment in spite of reduced enhancer transcription, were an exception (Figure S3C), suggesting a dissociation of ERa binding from gene expression in the presence of TNFa for this particular set of ERa binding sites. Gene-specific analyses confirmed that the E2 + TNFa-dependent gene regulatory events require ERa (Figures S3D and S3E). Together, these analyses link ERa binding (called by ChIPseq), enhancer transcription (called by GRO-seq at the ERa binding sites), and nearest gene transcription (called by GRO-seq), which is illustrated further using three-dimensional boxplots of the data (Figures 3C, 3D, and S3F). This representation also shows the impact that cotreatment with TNFa has on gained ERa binding sites and their target genes, producing new ERa binding events, as well as stimulating enhancer and target gene transcription (Figures 3C and 3D; note the significant displacement in all three dimensions with E2 + TNFa for the gained enhancers; see also Figure S3F). Collectively, these results indicate that the gained ERa binding sites are bona fide enhancers, representing a unique inducible ERa cistrome that controls the expression of a distinct and biologically relevant gene set. The Classical Estrogen-Induced ERa Cistrome Is Demarcated Prior to Stimulus, while the De Novo ERa Cistrome Requires TNFa Stimulation for Chromatin Accessibility Previous models of enhancer function suggested that signal-activated transcription factors, such as ERa, bind within a predetermined repertoire of accessible genomic loci that are established

Please cite this article in press as: Franco et al., TNFa Signaling Exposes Latent Estrogen Receptor Binding Sites to Alter the Breast Cancer Cell Transcriptome, Molecular Cell (2015), http://dx.doi.org/10.1016/j.molcel.2015.02.001

ER ChIP-Seq E2

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Figure 2. Co-Stimulation of the Estrogen and TNFa Signaling Pathways Alters the ERa Cistrome in MCF-7 Cells (A) Left, heatmaps of ERa ChIP-seq reads from MCF-7 cells treated with E2, TNFa, or both. Right, heatmap of p65 ChIP-seq reads at the genomic loci where ERa is bound. (B) Boxplot of the normalized read counts for three distinct sets of ERa binding sites (gained, maintained, lost). Bars marked with different letters are significantly different (Wilcoxon rank sum test, p < 1 3 10 6). (C) De novo motif analyses of the three sets of ERa binding sites noted in (B) were performed using MEME. The predicted motifs were matched to known motifs using TOMTOM. See also Figure S2.

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A

Figure 3. ERa Binding Sites Gained by Cotreatment with E2 and TNFa Are Positively Correlated with Transcription of the Enhancers and Nearby Target Genes

ER Binding ChIP-Seq

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GRO-seq (+1 kb to +40 kb)

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ER Enhancer Transcription

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(A) Overview of the pipeline for integrating ChIPseq data with GRO-seq data to link ERa binding with enhancer and target gene transcription in MCF-7 cells. (B) Boxplots showing GRO-seq RPKM values for enhancer transcription and nearest neighbor upregulated gene transcription at maintained and gained ERa binding sites. Bars marked with different letters are significantly different (Wilcoxon rank sum test, p < 0.001). (C) Three dimensional (3D) boxplots showing the positive relationships among ERa binding (called by ChIP-seq; from Figure 2B), enhancer transcription (called by GRO-seq at the ERa binding sites; from B), and nearest gene transcription (called by GRO-seq; from B) for the top 50% of ERa binding sites (see Supplemental Experimental Procedures). Solid lines represent the interquartile range; dotted lines represent Q1 1.5 3 IQR or Q3 + 1.5 3 IQR. (D) Relative displacement (i.e., fold change) in E2 versus E2 + TNFa (left) with associated p values (right) in each dimension for the 3D boxplots shown in (C). See Figure S3F for the actual median log2 fold change values, as well as the difference (D) in median log2 fold change values for E2 versus E2 + TNFa. See also Figure S3.

10 5

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tained (i.e., classical) and gained ERa enhancers prior to receptor binding. To E2 E2+TNF E2 E2+TNF do so, we aligned publicly available deep sequencing data sets for several enhancer b D Relative Displacement features (FoxA1, DNase1 accessibility, Displacement p-Values 1 (E2 versus E2+TNF ) chromatin marks, and CBP) to the mainin Each Dimension c Maintained Dimension Gained (E2 versus E2+TNF ) 1 tained and gained ERa cistrome (Figures 2.20 x 10-16 0.1553 a) ER Binding 4A and 4B). In untreated MCF-7 cells, the 2.20 x 10-16 0.0003 b) Enhancer Maintained ER maintained ERa enhancers have an open Enhancers Transcription chromatin architecture (i.e., enhanced a Gained ER 5.56 x 10-10 0.0042 c) Nearest Gene DNase1 accessibility), and are enriched Enhancers Transcription 1 in FoxA1 binding and features of active enhancers (e.g., H3K27ac and CBP), prior to upon cellular differentiation (Ghavi-Helm et al., 2014; Heinz et al., stimulation with E2 or TNFa (Figures 4A and 4B). These features 2010; Hurtado et al., 2011; Shlyueva et al., 2014). In addition, suggest that the maintained ERa enhancers are constitutively recent studies have identified ‘‘latent’’ enhancers, which are accessible in these cells under basal conditions, prior to signalformed and activated de novo in response to cellular signals at induced ERa binding (Figures 4A and 4B). We observed similar regenomic sites that are not pre-established (Kaikkonen et al., sults for the lost ER enhancers (data not shown). In contrast, the 2013; Nord et al., 2013; Ostuni et al., 2013). Accessibility at pre- gained ERa enhancers have a less accessible (‘‘closed’’) chroestablished enhancers is maintained by lineage-specific tran- matin architecture, and are not significantly enriched in FoxA1 scription factors and pioneer transcription factors that function binding or features of active enhancers (e.g., H3K27ac and to maintain an open chromatin architecture (Heinz et al., 2010; CBP) prior to stimulation with E2 or TNFa (Figures 4A and 4B). Hurtado et al., 2011; Shlyueva et al., 2014). In this regard, the Fork- Interestingly, treatment with TNFa or TNFa + E2, but not E2 alone, head protein FoxA1, a well-established pioneer factor for ERa, is drove NF-kB and FoxA1 binding to the gained ERa enhancers constitutively bound at ERa enhancers prior to estrogen stimula- (Figure 4C; see Figures S4A–S4D for specific examples). In addition (Hurtado et al., 2011). Thus, we sought to determine the chro- tion, as discussed in more detail below, we observed some differmatin state in the basal (i.e., unstimulated) condition at the main- ences in the FoxA1 responses to the treatments depending on the 6 Molecular Cell 58, 1–14, April 2, 2015 ª2015 Elsevier Inc.

Please cite this article in press as: Franco et al., TNFa Signaling Exposes Latent Estrogen Receptor Binding Sites to Alter the Breast Cancer Cell Transcriptome, Molecular Cell (2015), http://dx.doi.org/10.1016/j.molcel.2015.02.001

B

Steady State Levels at ER Enhancer Locations FoxA1

CBP

H3K4me3

E E+T

H3K27ac

Treatment: V

DNase1

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FoxA1

ChIP- or DNaseI-Seq (Prior to Treatment)

Gained (G) ER Peaks Maintained (M) ER Peaks

Gained ER Peaks (1,664)

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Figure 4. Latent ERa Binding Sites Exposed by Cotreatment with E2 and TNFa Have a Restrictive Chromatin State Prior to Treatment (A) Heatmap showing gained and maintained ERa binding sites aligned with genomic data (ChIP-seq and DNase1-seq) for known enhancer features from untreated MCF-7 cells (basal state). (B) Normalized ChIP-seq or DNase1-seq read counts for known enhancer features at gained versus maintained ERa binding sites in untreated MCF-7 cells. Bars marked with different letters are significantly different (Wilcoxon rank sum test, p < 0.001). (C) Heatmap (top) and boxplots (below) of NF-kB and FoxA1 occupancy at gained ERa binding sites, as determined by ChIP-seq. Bars marked with different letters are significantly different (Wilcoxon rank sum test, p < 0.001). See also Figure S4.

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chromatin accessibility and promote ERa binding. To determine the roles of G M G M NF-kB and FoxA1 at gained/latent ERa 5 kb Peak Center enhancers in MCF-7 cells, we separated the enhancers into those with relatively ER ChIP-Seq NF- B ChIP-Seq FoxA1 ChIP-Seq C high NF-kB co-occupancy after stimulaTreatment: Veh E2 TNF E+T Veh E2 TNF E+T Veh E2 TNF E+T tion and those with relatively low NF-kB co-occupancy (Figure 5A). We then determined the role of NF-kB or FoxA1 at these ER Gained Peaks enhancers using siRNA-mediated knock(1664) down of NF-kB p65 or FoxA1, coupled with ChIP-qPCR (to assay the binding of p65, FoxA1, and ERa) and RT-qPCR NF- B FoxA1 ER (to assay gene expression outcomes for 150 150 300 c neighboring genes). ERa binding in the b c b presence of E2 + TNFa at gained/latent a a 100 100 200 b enhancers with high NF-kB occupancy a a 50 50 100 (e.g., those near POU3F1, EFNA1, and b a a B4GALT1) was dramatically reduced 0 0 0 upon p65 knockdown (Figure 5C; Figures V E T E+T V E T E+T V E T E+T 5B and S5A, middle panels), but was unaffected at maintained enhancers (e.g., level of NF-kB enrichment at these sites (low versus high; Figures those near FMN1, P2RY2, and GREB1; Figures 5B and S5A, S4A–S4C). These results suggest that TNFa or TNFa + E2 is top panels) or gained/latent enhancers with low NF-kB occurequired for the mobilization of NF-kB and FoxA1 to new genomic pancy (e.g., those near PTGER3, GALNTL4, and PPP1R3C; loci, where they help to create new ERa binding sites that are not Figures 5B and S5A, bottom panels). We also observed a correpart of the classical estrogen-induced ERa cistrome. These re- sponding effect of the expression of the nearest neighboring sults fit well with the gene expression analyses described above. gene in the presence of E2 + TNFa, namely that reduced ERa The de novo sites of ERa binding in response to E2 + TNFa in binding correlated with reduced expression upon p65 knockMCF-7 cells have the features of recently described latent en- down (Figures 5D and S5B, middle panels; compare to the largely hancers (Heinz et al., 2010; Kaikkonen et al., 2013; Ostuni et al., unaffected genes in the left/right and top/bottom panels, respec2013). tively). These results indicate that NF-kB is required for ERa binding at a subset of latent/gained enhancers, as well as correEstablishment of TNFa-Induced Latent ERa Enhancers sponding target gene expression in response to E2 + TNFa. Requires NF-kB and FoxA1 As noted above, gained/latent enhancers with low NF-kB ocThe TNFa-dependent binding of NF-kB and FoxA1 at latent ERa cupancy showed little dependence on NF-kB for ERa binding. enhancers suggested that these factors may act to increase We hypothesized that at these enhancers FoxA1, rather than 20

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Figure 5. NF-kB Helps to Unveil Some Latent ERa Enhancers in MCF-7 Cells after Treatment with TNFa (A) Genome browser views of ERa and NF-kB (p65) ChIP-seq data for different types of ERa enhancers. (B) NF-kB facilitates ERa binding at TNFa-responsive enhancers. ChIP-qPCR for ERa and NFkB in MCF-7 cells with or without RNAi-mediated knockdown (KD) of p65, followed by treatment with E2 + TNFa. The enhancers are designated by the nearest neighboring gene. Each bar represents the mean ± SEM, n = 3. The asterisks indicate significant differences from the corresponding control (Student’s t test, p value < 0.05). (C) Western blot showing KD of p65 using siRNAs. (D) NF-kB is required for the efficient expression of genes neighboring latent E2 + TNFa-responsive ERa enhancers. Target gene expression with or without RNAi-mediated KD of p65, with E2 + TNFa treatment. Each bar represents the mean ± SEM, n = 3. The asterisks indicate significant differences from the corresponding control (Student’s t test, p value < 0.05). See also Figure S5.

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NF-kB, might play a critical role in establishing a chromatin environment permissive for ERa binding. We tested this in MCF-7 cells using a set of experiments similar to those described above for NF-kB. At maintained ERa enhancers, FoxA1 was bound constitutively (Figure 4A) and as expected, siRNA-mediated knockdown of FoxA1 dramatically reduced ERa binding, as well as the expression of the nearest neighboring gene (Figure 6B; Figures 6A, 6C, S6A, and S6B, top panels). Likewise, at gained/latent enhancers with low NF-kB occupancy, knockdown of FoxA1 dramatically reduced ERa binding, as well as the expression of the nearest neighboring gene (Figures 6A, 8 Molecular Cell 58, 1–14, April 2, 2015 ª2015 Elsevier Inc.

6C, S6A, and S6B, bottom panels). In contrast, at gained/latent enhancers with high NF-kB occupancy, knockdown of FoxA1 had little effect on ERa binding or target gene expression (Figures 6A, 6C, S6A, and S6B, middle panels). A similar pattern of FoxA1 dependence was observed for gained ERa enhancers in ZR-75-1 cells (Figures S6C–S6F). These results indicate that FoxA1 is required for ERa binding at a subset of latent/gained enhancers with low NF-kB occupancy, as well as corresponding target gene expression in response to E2 + TNFa. In ChIP-seq assays in MCF-7 cells, we found that ERa binding at 30% of the gained enhancers was significantly reduced upon siRNA-mediated knockdown of FoxA1 (FDR < 0.05; Figures 6D and 6E; affected versus unaffected by FoxA1 knockdown). These results separated the gained/latent ERa enhancers into two groups: (1) FoxA1 dependent (i.e., affected by FoxA1 knockdown) and (2) FoxA1 independent (i.e., unaffected by FoxA1 knockdown). Both groups have similar levels of ERa binding with E2 + TNFa (Figure S6G) and similar levels of nearest neighboring gene transcription (Figure S6H). With these genomic data, we were able to test the hypothesis that gained enhancers with high NF-kB occupancy do not require FoxA1. We found that FoxA1-dependent latent ERa enhancers have lower occupancy of p65 than the FoxA1-independent enhancers, as expected (Figure 6F), and are sensitive to FoxA1 knockdown (Figure S6E).

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Our results showing loading of FoxA1 at new sites in the genome in response to TNFa treatment point to key links between cellular signaling pathways and the activity of pioneer factors. To explore the connections between TNFa signaling and FoxA1 loading on chromatin in more detail, we biochemically fractionated E2- and TNFa-treated MCF-7 cells into distinct cellular compartments (i.e., cytoplasm, nucleoplasm, and chromatin). As expected, FoxA1 did not localize to the cytoplasm, and the treatments (i.e., Veh, E2, TNFa, or E2 + TNFa) did not alter the levels of total FoxA1 protein, as determined by western blotting for FoxA1 (Figure 7A; see ‘‘Whole Cell Extract’’ and ‘‘Cytoplasm’’). Also as expected, FoxA1 was bound to chromatin under basal/unstimulated conditions and showed enhanced binding or stabilization upon E2 treatment (Figure 7A; see ‘‘Chromatin’’). Interestingly, treatment with TNFa, alone or in the presence of E2, resulted in a dramatic increase in chromatin-bound FoxA1 and a corresponding decrease of soluble FoxA1 in the nucleoplasm (Figure 7A; see ‘‘Chromatin’’ versus ‘‘Nucleoplasm’’). These results indicate that TNFa treatment can drive more FoxA1 to chromatin, providing new sites of accessible chromatin for the binding of ERa. Taken together, our data suggest a model where the majority of the E2-regulated target genes are controlled by poised ERa enhancers that are located in open regions of chromatin and are maintained by constitutively bound FoxA1 and other lineage-specific transcription factors (Figure 7B, top left). A subset of latent ERa enhancers, however, are located in less-accessible regions of the genome and require TNFa signaling to promote NF-kB and FoxA1 binding, leading to enhanced chromatin accessibility and subsequent ERa binding (Figure 7B, top right and bottom). DISCUSSION In the studies described herein, we have defined the molecular mechanisms that underlie crosstalk between estrogen-mediated mitogenic signaling and TNFa-mediated proinflammatory signaling in breast cancers, as well as the functional consequences and clinical relevance of this interplay. We have defined the immediate transcriptional effects of crosstalk between E2 and TNFa, identifying a large set of target genes whose expression is rapidly and dramatically altered (upregulated or downregulated) with combined E2 + TNFa treatment, but not with either agent alone. The target genes include classical mitogenic and proinflammatory genes, as well as lncRNA genes (Figures 1A and S1B). The pleiotropic effects on gene transcription in response to E2 + TNFa were orchestrated by the extensive remodeling of the ERa enhancer landscape (Figures 2A and 2B) in an NF-kB- and FoxA1-dependent manner (Figures 5, 6, S5, and S6). The altered patterns of gene regulation in the presence of TNFa inhibit the estrogen-dependent growth of MCF-7 cells. In addition, high-level expression of the de novo and synergistically regulated genes is associated with good outcomes in some types of breast cancer and poor outcomes in other types of breast cancer. Together, our genomic and molecular analyses indicate that TNFa signaling, acting in pathways culminating in the redistribution of NF-kB and FoxA1 binding sites across the genome, creates new

E2-dependent ERa binding sites that underlie altered patterns of gene expression. TNFa Signaling Exposes Latent ERa Enhancers in Breast Cancer Cells: Requirement for NF-kB and FoxA1 In the ‘‘classical’’ pathway for estrogen-induced gene activation, the estrogen-induced ERa cistrome is demarcated by FoxA1 binding prior to hormone exposure. In these cases, FoxA1 acts as a pioneer factor that facilitates chromatin opening, providing access to the genome for the liganded receptor (Hurtado et al., 2011). Once bound to estrogen response elements, liganded ERa promotes the formation of active enhancers, which includes recruitment of coregulators (e.g., SRCs and p300/CBP, Mediator) (Foulds et al., 2013), histone modifications and additional chromatin opening (He et al., 2012), recruitment of RNA polymerase II and enhancer transcription (Hah et al., 2013; Wang et al., 2011), and looping to target gene promoters (Fullwood et al., 2009). Herein, we show that the TNFa signaling pathway can redirect the pioneer factor FoxA1 to new sites in the genome that were not established during the ontology of the cell (Figure 7B, right). The interface of the signaling pathway with the transcription factor is evident at the genomic level, with a redistribution of FoxA1 to new loci, creating new opportunities for ERa binding. These results are consistent with a latent enhancer model, in which activation of cellular signaling pathways promotes the sequential binding of stimulus-activated and lineage-determining transcription factors (Heinz et al., 2010; Ostuni et al., 2013). Importantly, de novo or gained ERa binding at these latent enhancers is ligand dependent; the sites newly demarcated by FoxA1 in response to TNFa cannot be accessed by ERa in the absence of ligand. Thus, in this case, FoxA1 retains its pioneer functions, but they are not determined as a consequence of development or differentiation, but rather as an endpoint of proinflammatory signaling. The TNFa-induced redistribution of FoxA1 may occur in response to posttranslational modification of FoxA1 as an endpoint of TNFa signaling pathway, although further analyses are needed to test this hypothesis. We also observed that liganded ERa can access an additional set of latent enhancers demarcated by NF-kB upon TNFa signaling (Figure 7B, bottom left). Recent studies have suggested that proinflammatory signaling, primarily through NF-kB, plays a role in promoting an open chromatin state allowing for cell plasticity in response to environmental cues; however, the role of NF-kB as a pioneer factor has been debated (Lee et al., 2012; Molinero et al., 2012; Natoli, 2012; Ndlovu et al., 2009; Rao et al., 2011). Nonetheless, TNFa-mediated NF-kB binding, alone or perhaps in conjunction with other transcription factors, is required for ERa binding at these latent enhancers, contributing to extensive crosstalk between the estrogen and TNFa signaling pathways observed in the cistrome and the transcriptome. The salient features of the latent ERa enhancers are (1) limited chromatin accessibility (i.e., low FoxA1 occupancy and DNase1 sensitivity) and limited enhancer activity (i.e., low H3K27ac and CBP) prior to stimulation (Figures 4A and 4B) and (2) rapid and robust enhancer activation (as illustrated by increased enhancer transcription) and ERa binding after stimulation (Figure 3B). The signal-dependent unveiling of these latent ERa enhancers Molecular Cell 58, 1–14, April 2, 2015 ª2015 Elsevier Inc. 9

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Figure 6. Cytokine-Induced FoxA1 Binding at Latent Enhancers Is Required for ERa Binding (A) FoxA1 facilitates ERa binding at TNFa-responsive enhancers. ChIP-qPCR for ERa and FoxA1 in MCF-7 cells with or without RNAi-mediated knockdown (KD) of FoxA1, followed by treatment with E2 + TNFa. The enhancers are designated by the nearest neighboring gene. Each bar represents the mean ± SEM, n = 3. The asterisks indicate significant differences from the corresponding control (Student’s t test, p value < 0.05). (B) Western blot showing KD of FoxA1 using siRNAs. (C) FoxA1 is required for the efficient expression of genes neighboring latent E2 + TNFa-responsive ERa enhancers. Target gene expression with or without RNAi-mediated KD of FoxA1, with E2 + TNFa treatment. Each bar represents the mean ± SEM, n = 3. The asterisks indicate significant differences from the corresponding control (Student’s t test, p value < 0.05). (D) Approximately 30% of gained ERa enhancers show significant reductions in ERa binding upon FoxA1 KD (‘‘affected’’) (FDR < 0.05 using SICER). The results are from ChIP-seq of ERa in MCF-7 cells with or without siRNA-mediated KD of FoxA1 and treated with or without E2 + TNFa. (legend continued on next page)

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Figure 7. Stimulation with TNFa Drives FoxA1 to Chromatin in MCF-7 Cells (A) Western blots of different subcellular protein fractions showing a decrease in nucleoplasmic FoxA1 and a corresponding increase in chromatinbound FoxA1 in cells treated with TNFa in the presence or absence of E2. Fraction-specific markers and loading controls include b-tubulin (b-Tub), histone H3 (H3), and SNRP70. (B) A model for cytokine-induced latent ERa enhancers in breast cancer cells, as described in the text.

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results in the formation of bona fide active enhancers with dramatic effects on target gene transcription (Figure 3C). The transition from a quiescent to activated chromatin landscape at the latent ERa enhancers is largely mediated by TNFa-induced recruitment of NF-kB or FoxA1 to these sites (Figures 5 and 6).

Distinct Breast Cancer Cell Transcriptomes Are Controlled by Poised versus Latent ERa Enhancers Our results show that the majority of E2regulated target genes in MCF-7 cells are controlled by poised (‘‘maintained’’) ERa enhancers that are located in open regions of chromatin and are constitutively bound by FoxA1 (or other lineagespecific transcription factors). The estrogen-dependent expression of the genes targeted by these enhancers is largely unaffected by TNFa signaling (Figure 3C, left). In contrast, a smaller set of estrogen-dependent latent ERa enhancers, which are created in response to TNFa signaling and are dependent on the actions of NF-kB and FoxA1, specifies a distinct transcriptome that is uniquely responsive to the combined actions of E2 and TNFa (Figure 3C, right). This unique transcriptome, which is created upon the convergence of mitogenic and proinflammatory signaling, contains mRNA and lncRNA genes that are newly or synergistically regulated (either up or down) only upon the combined actions of E2 and TNFa. The genes within this unique transcriptome, which are involved in molecular and cellular processes ranging from signaling and transcription to metabolism, proliferation, and apoptosis (Table S1), are likely to control the unique cellular outcomes upon combined treatment with E2 and TNFa (e.g., inhibition of the mitogenic growth of MCF-7 cells; Figure 1C). Although it is formally possible that TNFa signaling acts dominantly to E2 signaling to repress cell proliferation

(E) Average fold changes in ERa binding at gained ERa binding sites affected versus unaffected upon FoxA1 KD. Bars marked with different letters are significantly different (Wilcoxon rank sum test, p < 0.001). (F) Boxplots showing p65 occupancy at gained ERa binding sites affected versus unaffected upon FoxA1 KD. Bars marked with different letters are significantly different (Wilcoxon rank sum test, p < 0.001). See also Figure S6.

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through the expression of a TNFa-regulated target gene set, rather than through the unique E2 + TNFa-regulated transcriptome described above, we think this is unlikely for the following reasons. First, the unique E2 + TNFa-regulated gene set is a strong predictor of clinical outcomes in breast cancers, independent of the classical TNFa-regulated proinflammatory gene set (Figures 1E and S1F). Second, the unique E2 + TNFa-regulated gene set is enriched for gene ontologies related to cell growth control (Table S1). Third, the FoxA1 dependence of the effects we observed, coupled with the key role that FoxA1 plays in ERa-dependent breast cancer cell growth (Hurtado et al., 2011; Ross-Innes et al., 2012), supports a role for positive functional interplay between E2/ERa, TNFa, and FoxA1 in controlling a transcriptome that dictates cell growth responses. Proinflammatory Signaling in Breast Cancers: Unexpected Clinical Outcomes Recent studies have identified important effects of proinflammatory signaling in cancers, which supplies the tumor microenvironment with bioactive molecules that facilitate angiogenesis, invasion, and metastasis (Baumgarten and Frasor, 2012; BenNeriah and Karin, 2011). In this regard, a number of recent studies have shown that proinflammatory signaling can lead to more aggressive hormone-dependent breast cancers (Coussens et al., 2013; Frasor et al., 2009; Kalaitzidis and Gilmore, 2005; Pradhan et al., 2012; Ross-Innes et al., 2012; Zhou et al., 2005). However, as our data show, the functional relationships and outcomes of the crosstalk between NF-kB/proinflammatory signaling and ERa/mitogenic signaling in breast cancers are complex and context dependent. This is observed at the level of the proinflammatory transcriptome, even in the absence of estrogen signaling, where high-level expression of a proinflammatory gene set can be associated with good or poor clinical outcomes depending on the breast cancer type (Figures 1D and S1F). We have identified a unique transcriptome, which is created upon the convergence of mitogenic and proinflammatory signaling, that is a robust predictor of clinical outcomes. Similar to the proinflammatory transcriptome, this gene set can be associated with good or poor clinical outcomes depending on the breast cancer type (Figures 1D and S1F). This variability may be controlled, in part, by differences in the length of exposure to the proinflammatory mediators (e.g., chronic versus acute, as in our studies herein), the type of cytokine (e.g., TNFa versus IL4), and the presence of other activated signaling pathways (e.g., with or without ligand-activated ERa). Taken together, our results highlight the potential varied responses and clinical outcomes of breast cancers upon proinflammatory signaling.

treatments were performed for 40 min with 100 nM 17-b-estradiol, 25 ng/ml TNFa, or both. For siRNA transfections, commercially available siRNA oligonucleotides (Sigma) were transfected at a final concentration of 10 nM using Lipofectamine RNAiMAX reagent (Invitrogen). Antibodies The antibodies used for both western blotting and ChIP were as follows: ERa (rabbit polyclonal generated in the W.L.K. lab), p65 (Abcam ab7970), FoxA1 (Abcam ab23738), SNRP70 (Abcam ab83306), b-tubulin (Abcam ab6046), and histone H3 (Abcam ab1791). Cell Proliferation Assays Treatments and cell collections were performed at 2-day intervals. Cells were fixed with 10% formaldehyde and stained with a 0.1% crystal violet. Incorporated crystal violet was extracted using 10% glacial acetic acid and the absorbance was read at 595 nm. Kaplan-Meier Analyses Kaplan-Meier estimators (Dinse and Lagakos, 1982) were generated using the GOBO tool (http://co.bmc.lu.se/gobo) (Ringne´r et al., 2011). Gene sets determined by GRO-seq were provided as inputs to assess patient outcomes in ER-positive breast cancer subtypes. GRO-seq Nuclei isolation, nuclear run-on, and library preparation were performed as previously described (Danko et al., 2013; Hah et al., 2011), with modifications (Danko et al., 2013; Luo et al., 2014). The libraries were generated from two biological replicates using a circularized ligation-based protocol for adaptor ligation used to improve the efficiency of library preparation, reduce sequence bias, and allow for barcoding (Luo et al., 2014; Wang et al., 2011). The GROseq data were analyzed using the groHMM software package described previously (Danko et al., 2013; Hah et al., 2011; Luo et al., 2014). The effects of E2, TNFa, and E2 + TNFa on the expression of coding and non-coding genes were analyzed using edgeR (Robinson et al., 2010). Further GRO-seq data analyses, including data visualization, are described in detail in the Supplemental Information. ChIP ChIP was performed as previously described (Kininis et al., 2007) with a few modifications. For ChIP involving siRNA knockdown of p65 or FoxA1, cells were transfected with siRNA complexes 48 hr prior to E2 and/or TNFa treatment. The enriched genomic DNA was analyzed by qPCR using the enhancer-specific primers listed in the Supplemental Information. ChIP-seq ChIP-seq libraries were generated from two biological replicates for each condition. A total of 50 ng of ChIPed DNA were used to generate libraries for sequencing, as previously described (Quail et al., 2008), with some modifications. Sequencing adaptors were attached using the Illumina TruSeq DNA Sample Prep Kit and sequenced using an Illumina HiSeq 2000. The ChIP-seq libraries were aligned to hg19 genome using default parameters of BOWTIE (Langmead et al., 2009). Uniquely mappable reads were converted into bigWig files using BEDTools for visualization in the UCSC genome browser (Quinlan and Hall, 2010). ERa, p65, and FoxA1 ChIP-seq samples from the untreated condition were used as controls for peak calling using MACS software (Zhang et al., 2008). Further ChIP-seq data analysis is described in detail in the Supplemental Information.

EXPERIMENTAL PROCEDURES Additional details on the experimental procedures can be found in the Supplemental Information. Cell Culture, Treatments, and RNAi-Mediated Knockdown MCF-7 breast cancer cells were obtained from the ATCC and maintained in Minimum Essential Medium (MEM) Eagle supplemented with 5% calf serum. Prior to all treatments, the cells were grown for 3 days in phenol red-free MEM Eagle supplemented with 5% charcoal-dextran-treated calf serum. All

12 Molecular Cell 58, 1–14, April 2, 2015 ª2015 Elsevier Inc.

mRNA Expression Analyses by RT-qPCR Total RNA was isolated using Trizol Reagent (Invitrogen), reverse transcribed, and subjected to real-time qPCR using the gene-specific primers listed in the Supplemental Information. Target gene transcripts were normalized to the b-actin transcript. Subcellular Fractionation and Analyses Whole-cell extracts were prepared in 50 mM Tris-HCl (pH 8), 150 mM NaCl, 1% NP-40, 0.5% sodium deoxycholate, and 0.1% SDS containing protease

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inhibitors. Cytoplasmic and nuclear extracts were made using the CelLytic NuCLEAR Extraction Kit from Sigma. The remaining chromatin pellet was solubilized with benzonase nuclease (Sigma) and boiled in 13 SDS sample buffer. The different subcellular fractions were analyzed for FoxA1 by western blotting using a set of fraction-specific markers and loading controls (b-tubulin, histone H3, and SNRP70). ACCESSION NUMBERS

Ghavi-Helm, Y., Klein, F.A., Pakozdi, T., Ciglar, L., Noordermeer, D., Huber, W., and Furlong, E.E. (2014). Enhancer loops appear stable during development and are associated with paused polymerase. Nature 512, 96–100. Hah, N., Danko, C.G., Core, L., Waterfall, J.J., Siepel, A., Lis, J.T., and Kraus, W.L. (2011). A rapid, extensive, and transient transcriptional response to estrogen signaling in breast cancer cells. Cell 145, 622–634. Hah, N., Murakami, S., Nagari, A., Danko, C.G., and Kraus, W.L. (2013). Enhancer transcripts mark active estrogen receptor binding sites. Genome Res. 23, 1210–1223.

The GRO-seq, ERa ChIP-seq, FoxA1 knockdown ERa ChIP-seq, NF-kB p65 ChIP-seq, and FoxA1 ChIP-seq data sets for all four treatments (Veh, E2, TNF, and E2 + TNFa) are available from the NCBI’s GEO database using accession numbers GSE59530, GSE59531, and GSE59532.

Hanahan, D., and Weinberg, R.A. (2011). Hallmarks of cancer: the next generation. Cell 144, 646–674.

SUPPLEMENTAL INFORMATION

Heinz, S., Benner, C., Spann, N., Bertolino, E., Lin, Y.C., Laslo, P., Cheng, J.X., Murre, C., Singh, H., and Glass, C.K. (2010). Simple combinations of lineagedetermining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589.

Supplemental Information includes six figures, one table, and Supplemental Experimental Procedures and can be found with this article online at http:// dx.doi.org/10.1016/j.molcel.2015.02.001. ACKNOWLEDGMENTS We thank Christopher K. Glass and Josh D. Stender at UCSD for their helpful insights and suggestions about this work. We also thank members of the W.L.K. lab for helpful discussions about this manuscript, and Rosemary Conry for technical assistance. This work was supported by a postdoctoral fellowship from the American Cancer Society - Lee National Denim Day Fellowship to H.L.F. and a grant from the NIH/NIDDK (DK058110) to W.L.K. Received: July 30, 2014 Revised: November 18, 2014 Accepted: January 27, 2015 Published: March 5, 2015 REFERENCES Baumgarten, S.C., and Frasor, J. (2012). Minireview: inflammation: an instigator of more aggressive estrogen receptor (ER) positive breast cancers. Mol. Endocrinol. 26, 360–371. Ben-Neriah, Y., and Karin, M. (2011). Inflammation meets cancer, with NF-kB as the matchmaker. Nat. Immunol. 12, 715–723. Coussens, L.M., Zitvogel, L., and Palucka, A.K. (2013). Neutralizing tumor-promoting chronic inflammation: a magic bullet? Science 339, 286–291. Cunningham, M., and Gilkeson, G. (2011). Estrogen receptors in immunity and autoimmunity. Clin. Rev. Allergy Immunol. 40, 66–73. Danko, C.G., Hah, N., Luo, X., Martins, A.L., Core, L., Lis, J.T., Siepel, A., and Kraus, W.L. (2013). Signaling pathways differentially affect RNA polymerase II initiation, pausing, and elongation rate in cells. Mol. Cell 50, 212–222. de Laat, W., and Duboule, D. (2013). Topology of mammalian developmental enhancers and their regulatory landscapes. Nature 502, 499–506. Dinse, G.E., and Lagakos, S.W. (1982). Nonparametric estimation of lifetime and disease onset distributions from incomplete observations. Biometrics 38, 921–932. Foulds, C.E., Feng, Q., Ding, C., Bailey, S., Hunsaker, T.L., Malovannaya, A., Hamilton, R.A., Gates, L.A., Zhang, Z., Li, C., et al. (2013). Proteomic analysis of coregulators bound to ERa on DNA and nucleosomes reveals coregulator dynamics. Mol. Cell 51, 185–199. Frasor, J., Weaver, A., Pradhan, M., Dai, Y., Miller, L.D., Lin, C.Y., and Stanculescu, A. (2009). Positive cross-talk between estrogen receptor and NF-kappaB in breast cancer. Cancer Res. 69, 8918–8925. Fullwood, M.J., Liu, M.H., Pan, Y.F., Liu, J., Xu, H., Mohamed, Y.B., Orlov, Y.L., Velkov, S., Ho, A., Mei, P.H., et al. (2009). An oestrogen-receptor-alpha-bound human chromatin interactome. Nature 462, 58–64.

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Please cite this article in press as: Franco et al., TNFa Signaling Exposes Latent Estrogen Receptor Binding Sites to Alter the Breast Cancer Cell Transcriptome, Molecular Cell (2015), http://dx.doi.org/10.1016/j.molcel.2015.02.001

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TNFα signaling exposes latent estrogen receptor binding sites to alter the breast cancer cell transcriptome.

The interplay between mitogenic and proinflammatory signaling pathways plays key roles in determining the phenotypes and clinical outcomes of breast c...
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