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and β as Determinants of Gene Expression: Influence of Ligand, Dose, and Chromatin BindingDepartments of Molecular and Integrative Physiology (E.C.C., S.-H.P., B.S.K.), Cell and Developmental Biology (B.S.K.), Food Science and Human Nutrition (W.G.H.), and Chemistry and Bioengineering (T.H.C., J.A.K.), University of Illinois at Urbana-Champaign, Urbana, Illinois 61801; and Women’s Health and Musculoskeletal Biology (B.K.), Wyeth Research, Collegeville, Pennsylvania 19426
Address all correspondence and requests for reprints to: Dr. Benita S. Katzenellenbogen, University of Illinois, Department of Molecular and Integrative Physiology, 524 Burrill Hall, 407 South Goodwin Avenue, Urbana, Illinois 61801-3704. E-mail: katzenel{at}uiuc.edu.
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ABSTRACT |
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and β (ER and ERβ) mediate the actions of estrogens in a variety of normal and cancer target cells. Estrogens differ in their preference for these ERs, and many phytoestrogens bind preferentially to ERβ. To investigate how phytoestrogens such as genistein impact ER-regulated gene expression, we used adenoviral gene delivery of ERβ coupled with ER depletion with small interfering RNA to generate human breast cancer (MCF-7) cells expressing four complements of ER and ERβ. We examined the dose-dependent effects of genistein on genome-wide gene expression by DNA microarrays and monitored the recruitment of ERs and coregulators to responsive regions of estrogen-regulated genes. At a low (6 nM) concentration, genistein regulated gene expression much more effectively in cells coexpressing ER and ERβ than in cells expressing ER alone, whereas at high concentration (300 nM), genistein induced transcriptome changes very similar to that of 17β-estradiol. We demonstrate that ERβ is preferentially activated by genistein and is recruited to estrogen-responsive genomic sites and that differential occupancy of ER and ERβ by genistein and 17β-estradiol in turn influences the recruitment patterns of coregulators such as steroid receptor coactivator 3 (SRC3) and receptor-interacting protein 140 (RIP140). Our observations indicate that genistein is a potency-selective ligand for gene expression regulation by ER and ERβ and that the ability of ER and ERβ to serve as determinants of gene expression is greatly influenced by the nature of the ligand, by ligand dose, and by the differential abilities of ligand-ER complexes to recruit different coregulators at ER binding sites of hormone-regulated genes. |
INTRODUCTION |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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and β (ER and ERβ) mediate the actions of diverse estrogens in estrogen target tissues and cells, both normal and cancerous, where the levels and ratios of the two receptors are known to vary substantially (1, 2). For example, ER is the predominant ER found in uterus and liver, whereas ERβ is highly expressed and is almost the exclusive ER in ovarian granulosa cells (3). ERs also mediate the actions of estrogens and selective ER modulators in breast cancers (4, 5). Although ER is usually the predominant ER in breast tumors, 70% of primary breast tumors express ERβ, and most tumors coexpress both ERs, with the levels of ERβ covering a broad range (5, 6, 7, 8, 9). The presence of ER is associated with the proliferative effects of estrogens, whereas the bulk of current evidence implies that ERβ has growth-suppressive activities (10, 11, 12, 13).
Soy-based products have gained much attention lately, in part because increased consumption is thought to contribute to the lower breast cancer incidence in Asian countries relative to the United States (14); however, it is unclear which biologically active components in soy offer these protective effects. In animal studies where soy-supplemented diets were shown to reduce the number of tumors induced by chemical carcinogens, the beneficial effects of soy were attributed to the isoflavones genistein and daidzein (15). However, evidence from clinical trials for efficacy of soy isoflavones for preventing or treating breast cancer is as yet very limited (16). Paradoxically, genistein is reported to have both antitumor benefits as well as growth-stimulatory effects, depending on the concentrations used. Genistein at physiological concentrations stimulates proliferation of ER-positive breast cancer cells both in vitro and in xenograft animal models (17, 18, 19) but is growth inhibitory at higher concentrations (IC50 at 6–8 µg/ml) (19, 20). It is widely presumed that anti-growth actions by genistein at levels greater than 10 µM are mediated through the inhibition of tyrosine kinases (19, 20, 21, 22).
Growth inhibition by genistein might, however, also stem from its estrogenic properties unrelated to its anti-tyrosine kinase activity observed at extremely high pharmacological doses. Genistein activates ERβ at concentrations lower than required for activation of ER (3, 23), and because ERβ has anti-growth properties, selective activation of ERβ in cells may serve to suppress growth of estrogen-dependent tumor cells.
In this work, we examine the roles of ER and ERβ as determinants of gene expression in breast cancer cells and the influence of ligand, dose, and chromatin binding in the patterns of cellular gene expression. To this end, we have profiled global gene expression in breast cancer cells containing various complements of ER and ERβ treated with either 17β-estradiol (E2) or the phytoestrogen ligand genistein. We also examined ligand-induced chromatin binding by the two ERs, when present together or separately, in breast cancer cells. Our studies highlight that the ERβ-preferential gene regulatory effects of genistein are dose dependent and that chromatin binding of ligand-occupied ERs reflects their gene transcriptional output and is associated with differential recruitment of coregulators by ER and ERβ complexes.
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significantly impacted the E2-induced transcriptional response by ER (24, 25, 26, 27). To further examine the activities of ERβ or ER, we have used the phytoestrogen genistein because of its ERβ preferential binding and transcriptional potency in reporter gene assays. To assess the impact of ERβ on response profiles of endogenous gene expression to genistein and E2 in MCF-7 cells, which express only ER, we used adenoviral gene delivery to transduce ERβ expression. We then determined the time-dependent and ligand-specific changes in ER-mediated transcriptional response by profiling MCF-7 cells treated for 4 and 24 h with E2 and two concentrations of genistein using Affymetrix HG-U133A GeneChips. To assess the importance of ER subtype in response to genistein, we examined the dose dependence of genistein transcriptional activity, using low genistein (LG; 6 nM) and high genistein (HG; 300 nM) concentrations, which should activate ERβ preferentially or both ER and ERβ, respectively.
To find genes differentially expressed under our different ligand treatments, we used a multivariate analysis (LIMMA) to assign the statistical significance to the contrasts while controlling for multiple testing. We found 2682 probe sets significantly regulated by one or more treatment conditions after 4- and 24-h treatments. Using the TightCluster algorithm (28) to group genes of like expression profiles, 17 clusters of up-regulated genes and 17 clusters of down-regulated genes emerged (Fig. 1A
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and ERβ and elicited little effect on gene expression in cells containing ER alone. This pattern of response is evident from the cluster heat map (Fig. 1A
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To explore the underlying biological functions of these expression clusters, we used Expression Analysis Systematic Explorer (EASE) software (29) to test for overrepresented gene ontology biological function classes in each expression cluster (Fig. 2). The four clusters shown in Fig. 1B illustrate different patterns of response in terms of direction of regulation (up or down), time (4 and 24 h), influence of ERβ, and response to ligands. Clusters enriched for genes involved in cell cycle regulation (cluster A1) showed up-regulation via ER that was attenuated by the copresence of ERβ, whereas the gene cluster enriched for G protein-coupled receptor (GPCR) signaling (cluster B9) showed down-regulation by the ligands that was enhanced by ERβ (Fig. 1B). In addition, ERβ increased the expression of genes involved in negative regulation of cell proliferation (cluster B4). Other clusters were associated with RNA processing (clusters A7, A8, A17, and A19) and various transport processes (clusters B10 and B11) (Fig. 2). These findings support and extend previously published results that ERβ expression can positively and negatively modulate distinct ER-mediated gene expression patterns (24).
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only or both ERs (Fig. 1C) are consistent with the patterns of gene expression regulation we have observed for these ligands with the gene clusters associated with the cell cycle and proliferation (Fig. 1B, clusters A1 and B4). In parental cells expressing only ER, we find that HG (300 nM) is as stimulatory as E2 (6 nM), with LG (6 nM) eliciting lesser stimulation of proliferation (Fig. 1C). In cells coexpressing both ER and ERβ, E2 as well as genistein showed a markedly reduced ability to stimulate cell proliferation. The suppressive effect of ERβ on estrogen-stimulated cell proliferation is as we and others reported previously for E2 (24, 30), and it reflects, in ERβ-containing cells, the reduced ability of E2 and genistein to up-regulate genes as-sociated with regulation of cell cycle (Fig. 1B, cluster A1) and the enhanced expression of genes associated with negative regulation of proliferation (Fig. 1B, cluster B4).
High-Concentration (300 nM) Genistein Treatment Elicits Global Gene Expression Changes Nearly Identical to Those of E2 in Cells Expressing ER Alone or ER plus ERβ, whereas ERβ Coexpression Greatly Enhances Gene Regulation by Low-Concentration (6 nM) Genistein
To examine whether genistein elicits a transcriptional response different from E2, we compared probe sets regulated by maximally effective concentrations of E2 (6 nM) and genistein (300 nM, HG). Probe sets specifically regulated in each treatment group were identified using a B-statistic cutoff (B > 0) from pairwise contrasts defined between untreated and treated samples (Fig. 3, A and B).
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). Of the 910 probe sets regulated by E2 at 4 h, 607 were also regulated by HG using B-statistic cutoff greater than 0 (73.6% of all 4-h HG-regulated probe sets). And of the 218 genes induced by HG but not by E2, cotreatment with ICI 182,780 antagonized HG agonism for all except three genes. To further identify probe sets where HG regulation was significantly different from E2, we used the volcano plot to visualize both the significance statistic and fold change of the HG vs. E2 contrast (Fig. 3C). Only nine probe sets from ER-only cells and 22 probe sets from the ER+ERβ cells passed our cutoff after 4 h treatment (B-statistic > 0; fold change > 2; Fig. 3C, panels 1 and 2). By the same criteria, few genes were differentially regulated at 24 h by HG vs. E2 (Fig. 3C, panels 3 and 4).
Previous studies using binding and reporter gene-based transactivation assays have demonstrated that genistein preferentially binds to and transactivates ERβ over ER (3, 23). We therefore also explored the impact of ERβ coexpression on genome-wide gene expression using a low concentration of genistein (6 nM, LG) expected to be ERβ preferential. To find genes preferentially regulated by genistein-bound ERβ, we performed statistical analysis using LIMMA and extracted genes with B-statistic score greater than 0.
In MCF-7 cells, which express only ER, LG regulated few genes at 4 and 24 h, compared with E2 (Figs. 3, A and B, and 4). By contrast, in cells expressing ER+ERβ, LG was considerably more effective in eliciting gene regulation (Fig. 4A). This is illustrated further by the heat map (Fig. 4B) in which the LG panel in the ER+ERβ cells looks quite similar to that of E2, whereas LG is much less effective in regulating gene expression in the ER-only cells.
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and ERβ expression with ERβ adenoviral gene delivery. Our siRNA conditions resulted in the depletion of more than 95% of ER protein, as determined by Western blot (not shown). This enabled us to generate four conditions with varying ER complements in MCF-7 cells: ER-only (siCNTRL), ER+ERβ (siCNTRL+ERβ), low ER (siER), and ERβ-only (siER+ERβ). We then monitored the expression of three well-known E2-regulated genes, FOS, TFF1, and CASP7, by quantitative PCR, in response to E2 or genistein (Fig. 5).
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-only cells, all three genes showed robust stimulation by E2 (black bars), whereas LG (hatched bars) had little effect. By contrast, in ER+ERβ cells, E2 activity was maintained, and LG evoked substantial stimulation of expression of these three genes. With the knockdown of ER, gene stimulation was completely lost, but the expression of ERβ at a level equal to that of ER in the original MCF-7 cells substantially, but not fully, restored gene regulation by all ligands.
Of note, genistein stimulation was comparable between cells expressing ERβ only and ER+ERβ cells (i.e. +β 
β >> ). By contrast, the magnitude of E2 stimulation was reduced in ERβ-only cells relative to ER+ERβ cells (i.e. +β > β). These findings suggest that genistein regulation of gene expression, under the conditions tested, is largely mediated by ERβ, whereas E2 stimulation can be mediated by either ER or ERβ.
Recruitment of ER and ERβ to ER Binding Sites of Estrogen-Responsive Genes by E2 and Genistein
To understand the effects of genistein and E2 on ER-mediated gene regulation, we examined ER recruitment to estrogen-responsive sites using chromatin immunoprecipitation (ChIP) with antibodies against ER and ERβ. We queried ER binding sites as recently mapped by the ChIP-on-chip method (31, 32) and also by ChIP-PET methods (33) to be within 100 kb upstream/downstream of the transcription start site of FOS, TFF1, and CASP7 and hence considered to be potential regulatory sites for these genes (Fig. 6). For each site of interest, we quantitatively measured immunoprecipitated yield normalized to input chromatin. Figure 6 shows recruitment of ER or ERβ to these sites, under the four cell conditions (cells containing ER only, ER+ERβ, low ER, and ERβ only), after exposure to control vehicle, E2, LG, or HG.
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and ERβ recruitment to these three gene regions were quite similar in response to ligands. In MCF-7 cells expressing only ER, E2 and HG effectively recruited ER, whereas LG elicited no ER recruitment. In cells containing ERβ along with ER, both ERs were recruited in response to E2 or HG, but of note, only ERβ was recruited by LG. We also observed some ligand-independent ERβ recruitment in cells containing ER+ERβ, although recruitment of ERβ was greatly increased by ligand. In cells depleted of ER by siRNA treatment (low ER cells), recruitment of ERs in response to ligands was completely lost.
In cells expressing ERβ only, recruitment of ERβ in response to ligand showed gene-dependent differences. All three ligand treatments (E2, LG, and HG) elicited good recruitment of ERβ at the FOS binding site, whereas LG was less effective in recruiting ERβ compared with E2 and HG at the TFF1 site. Recruitment of ERβ to the CASP7 site was low with all three ligand treatments, suggesting that recruitment of ERβ to this site is facilitated by the copresence of ER.
Differential Recruitment of Coregulators Steroid Receptor Coactivator 3 (SRC3) and Receptor-Interacting Protein 140 (RIP140) to ER Binding Sites by ER and ERβ Ligand Complexes
Because the transcriptional activity of chromatin-recruited ERs depends on the recruitment of coregulators, we assessed the recruitment of the p160 coactivator SRC3 and of the putative corepressor RIP140 to the estrogen-responsive sites (Fig. 7). SRC3 was selected because we found it to be the most abundant of the three SRC family members in MCF-7 cells, and RIP140 was evaluated because it has been demonstrated to interact with ER and modulate estrogen-induced gene activity (34, 35).
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only, we observed recruitment of SRC3 and RIP140 in response to E2 and HG, whereas LG elicited no coregulator recruitment, consistent with its low affinity for ER. As expected, in cells depleted of ER, there was little to no recruitment of either coregulator. In cells expressing ER+ERβ, however, SRC3 recruitment by E2 was reduced, but E2 recruitment of RIP140 remained constant relative to ER-only cells for TFF1 and CASP7 and was increased at the FOS binding site in cells expressing ER+ERβ. Interestingly, in cells coexpressing ER and ERβ or expressing ERβ alone, we observed essentially no SRC3 recruitment with genistein at low or high concentration. Although RIP140 recruitment was similar in ER-only and ER+ERβ cells with E2 and HG, we observed no recruitment of RIP140 when ER was depleted by siRNA transfection, and likewise, there was no recruitment of RIP140 in response to E2 or genistein in cells containing ERβ only. It is notable that although RIP140 is not recruited by LG in ER-only cells, there is substantial RIP140 recruitment by LG in ER+ERβ cells, suggesting that ERβ may be responsible for this recruitment of RIP140 in cells containing both receptors. Hence, at the sites queried, both SRC3 and RIP140 recruitment mirrored the general pattern of ER recruitment observed in Fig. 6.
Effects of Knockdown of the Coregulators SRC3 and RIP140 on ER-Mediated Gene Expression
To examine the effects of coregulators on gene expression, we performed siRNA-mediated knockdown of SRC3 and RIP140 in MCF-7 cells expressing different complements of ER and/or ERβ. We then measured the transcript level of the three genes, FOS, TFF1, and CASP7, by quantitative RT-PCR, in response to E2 or genistein treatment (Fig. 8). Use of the siRNA SMART pools gave 85–90% knockdown of SRC3 and 60–70% knockdown of RIP140 in the different cell types (data not shown).
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-only cells, E2-stimulated expression of the three genes was reduced by SRC3 knockdown, with TFF1 being reduced to the greatest extent. In contrast, RIP140 knockdown in ER cells resulted in increased E2-stimulated expression of all three genes (CASP7 and FOS > TFF1). The response to LG in ER-only cells was very low compared with that of E2, as shown here (and also in Fig. 5), and knockdown of SRC3 had no effect on gene expression under LG treatment in ER-only cells, relative to siCNTRL, whereas knockdown of RIP140 maintained or increased slightly both the basal and LG response of the three genes. Hence, in ER-only cells, SRC3 appears to be functioning as a coactivator for E2 and RIP140 as a corepressor on these genes.
In ER+ERβ cells, LG treatment evoked a greater stimulation of gene expression (cf. Fig. 5), whereas gene response to E2 was similar to that in ER-only cells (compare siCNTRL values). As in the ER-only cells, knockdown of SRC3 reduced or maintained expression levels of the three genes in response to E2 or LG. Knockdown of RIP140 enhanced both E2 and LG stimulation of CASP7 and minimally enhanced the response of FOS to these ligands, while having no effect on TFF1. Of particular interest, in cells expressing ERβ only, the targeted knockdown of SRC3 or RIP140 had essentially no effect on E2 or LG stimulation of these three genes. Thus, our findings imply that estrogen action, when only through ERβ, does not rely upon SRC3 or RIP140 and may involve other coregulators. However, when ER is present, SRC3 functions largely as a coactivator and RIP140 as a corepressor. Our findings also highlight gene and ER subtype-specific differences in regulation of gene expression.
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DISCUSSION |
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and ERβ: the nature of the ligand, the ligand dose, the presence of ER and ERβ separately or together in cells, and the recruitment of different coregulators at ER binding sites of hormone-regulated genes by ER and ERβ ligand complexes. Thus, we observed that a low concentration of the phytoestrogen genistein regulated gene expression preferentially through ERβ and that this preferential regulation of endogenous estrogen-responsive gene expression by ERβ was no longer observed in cells treated with a higher concentration of genistein where ER and ERβ were equally well recruited to gene regulatory sites and both functioned as effective ligand-regulated transcription factors.
There is much current interest in understanding the effects of genistein in the normal breast and in breast cancers, and reports linking soy consumption and reduced breast cancer incidence have contributed to the marked increase in the consumption of soy-based products in the United States. Many have speculated on the possible mechanisms for genistein action, one possibility being the activation of ERβ to either attenuate ER activity or induce a set of ERβ-specific antiproliferative genes (36).
In this work, we examined the impact of ERβ coexpression on ER-regulated gene expression and compared responses with E2 and with two doses of genistein in MCF-7 breast cancer cells expressing different complements of ER and ERβ. At the lower genistein dose, we observed greater response in cells expressing both ER and ERβ than in cells expressing only ER. Preferential activation of ERβ by genistein was lost when genistein dose was increased to 300 nM, whereby genistein activated both ERs and elicited the same transcriptional profile as E2. Regardless of ERβ expression, global analysis of the genistein response at either low or high dose revealed very few genes exclusively induced by genistein and not by E2. Our results suggest that the transcriptional activity of the phytoestrogen ligand genistein at the concentrations tested in our studies is primarily mediated by ERs and is not due to inhibition of other cellular enzymes (e.g. tyrosine kinases), as previously suggested in studies using very high (>10 µM) genistein concentrations (20). In addition, that genistein regulation of gene expression in our studies was completely reversed by the antiestrogen ICI 182,780 further supports our conclusion that this phytoestrogen is acting through the ERs at the 6 and 300 nM concentrations used.
By clustering genes of like expression and testing for enriched biological functions, we found that the presence of ERβ along with ER attenuated expression of genes involved in growth regulation, with ERβ up-regulating genes important in negative regulation of proliferation (such as cluster B4) and down-regulating genes that enhance cell cycle progression (such as cluster A1). These modulatory effects were observed in E2-treated and HG-treated cells alike, but less so in the LG-treated cells, where ERβ appears to be the chief mediator of genistein action. ERβ also impacted expression of genes encoding proteins associated with RNA processing and metabolism, GPCR signaling, integrin-mediated signaling, and various transport processes.
To examine ERβ activity in the copresence or absence of ER, we used RNA interference strategies coupled with adenoviral gene delivery to generate cells expressing: ER alone, ER+ERβ, no ER, and ERβ alone. We then assessed ligand response in terms of changes in estrogen target gene transcripts and the recruitment of ERs to target gene regulatory regions. We confirmed that although both ER and ERβ were recruited to estrogen-responsive sites after E2 and HG inductions, only ERβ was recruited to the target sites after LG treatment. The presence of ERβ alone was sufficient to mediate genistein action, and ERβ was still recruited to estrogen binding sites in cells depleted of ER.
Interestingly, we find that recruitment of the coregulator SRC3 after E2 or HG treatment was diminished in ER+ERβ cells vs. ER-only cells. Additionally, in cells expressing ERβ (either ER+ERβ or ERβ only), LG treatment was unable to induce recruitment of SRC3 to estrogen-responsive sites. Therefore, we conclude that the SRC3 recruitment pattern is influenced by the ER subtype complements at gene regulatory sites and that ERβ recruits SRC3 very poorly.
In contrast, RIP140 recruitment at ER binding sites persisted when ERβ was coexpressed with ER. RIP140 is a coregulator recruited by agonist-bound ER, for which repressor effects are well documented (34). Notably, RIP140 can recruit both negative effectors such as histone deacetylases as well as compete for receptor interactions with coactivators such as glucocorticoid receptor-interacting protein 1 (GRIP1) (35). That ERβ disfavors recruitment of a coactivator (SRC3) in cells containing both ER subtypes while maintaining the recruitment of a protein with corepressor activity (RIP140) may contribute to the overall suppressive effect of ERβ on ER activities including cell proliferation (12, 13, 24). Of note, both SRC3 and RIP140 were minimally recruited by ERβ to ER binding sites of the regulated genes we examined in response to either genistein or E2, suggesting that ERβ regulation of the expression of these genes involves coregulators other than SRC3 and RIP140. Consistent with this, we observed that knockdown of SRC3 or RIP140 had little impact on the stimulation of gene expression by E2 or genistein in cells expressing ERβ only.
These findings exemplify that the relationships between transcription factor and coregulator recruitments and gene expression are complex and can be ER subtype and gene dependent. We should note that the genomic sites queried here were originally identified through their ability to bind ER (32, 33). Nevertheless, our data show that ERβ can be recruited to these sites. Future studies that define a genome-wide map of ERβ binding sites will be informative in providing additional insights into the relationships between factor recruitment and gene regulation.
In conclusion, our study provides new insights into the cross-modulatory actions of ER and ERβ in breast cancer cells. We probed ER action through pharmacological means and by gain- and loss-of-expression methods and demonstrated for endogenously regulated genes that the effects of genistein at low nanomolar concentrations were preferentially mediated by ERβ. Although low nanomolar genistein has preferential activities through ERβ, higher concentration of genistein (e.g. 300 nM) activated both ER and ERβ. Our findings imply that the ratios of the ER subtypes and the concentrations of genistein will be important factors in the estrogen-regulated activities observed in different breast cancers.
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siRNA Transfection
To knock down the endogenous ER in MCF-7 cells, siRNA duplex against the F-domain of ER was transfected at a final concentration of 20 nM using the DharmaFECT transfection reagent (Dharmacon, Lafayette, CO) as per the manufacturer’s recommendations at 48 h before ligand treatment. The siER forward sequence is UCAUCGCAUUCCUUGCAAAdTdT, and reverse sequence is UUUGCAAGGAAUGCGAUGAdTdT. To knock down endogenous SRC3 or RIP140, we used the SMART pools of siRNA from Dharmacon.
GeneChip Microarrays and Statistical Analysis
Total RNA was harvested for cRNA labeling and hybridization to Affymetrix HG-U133A GeneChips as described previously (10). After washing, the arrays were scanned and analyzed using the GeneChip Operating Software (Affymetrix, Santa Clara, CA). CEL files were processed using the affy and gcrma package protocols in R/BioConductor (37, 38). Statistical multivariate analysis was done by the limma package (39). For simplicity’s sake, interactions with the time effect were ignored and the CEL files for 4- and 24-h treatments were analyzed separately. The remaining two major effects were defined as ERβ effect (minus and plus ERβ) and ligand effect (vehicle, E2, LG, HG, and ICI+HG). For pairwise comparisons, probe sets were considered significant if the B-statistic was greater than 0 (B-statistic is also known as log odds score).
Several prefiltering steps were taken to reduce the number of false positives in the final analysis. Probe sets with consistently low expression values were discarded (i.e. all calls were absent). Probe sets were also filtered for best overall significance by the F-test statistic. The F-test statistic is calculated from fitting a multivariate model to the data. The entire data set will be available through the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (33) and is accessible through GEO Series accession number GSE9936.
Functional Categorization of Target Genes
Gene functions were curated based on available published data in PubMed (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed) and the NetAffx databases (http://www.affymetrix.com), and loaded into the GeneSpring software version 7 (Silicon Genetics, Redwood City, CA). Global analysis for overrepresented GenMAPPs (40), KEGG pathways (41), and gene ontology biological function categories was performed using the EASE annotation tool developed by the NIH (29).
Recombinant Ad Preparation
Recombinant Ads were constructed and prepared as described (42). Briefly, replication-deficient Ad serotype 5 was propagated in HEK293 cells (Microbix, Toronto, Ontario, Canada) and then harvested. Approximately 60 µl of the transfected stock was used to reinfect HEK293 cells approaching 70% confluence in 100-mm dishes, and within 2–3 d, more than 90% of the HEK293 cells detached from the dish surface. The cells were harvested as described earlier and used to reinfect up to 20 150-mm dishes of cells using 500 µl of 107 effective plaque-forming units/ml per 150-mm dish. Again, in 2–3 d, more than 90% of the HEK293 cells became detached from the plates. Virus was concentrated up to 1012 effective plaque-forming units/ml, using the CsCl gradient protocol of He et al. (http://www.coloncancer.org/adeasy).
RT-PCR and Quantitative PCR
Total RNA was isolated from MCF-7 cells using TRIzol (Invitrogen) following the manufacturer’s recommendations. RNA samples were reverse transcribed by SuperScript II reverse transcriptase (Invitrogen) in 20 µl and subsequently diluted to 500 µl with sterile water. Real-time PCR was performed on the ABI Prism 7900HT using SYBR Green PCR Master Mix (Applied Biosystems, Foster City, CA) according to the manufacturer’s recommendations. Briefly, each PCR contained: 1x Master Mix, 5 µl of the diluted cDNA reaction, and 125 nM forward and reverse primers designed to yield 80- to 125-bp amplicons. Relative expression levels were calculated using the 
CT method (43).
Protein Extraction and Western Blot Analysis
Whole-cell extracts were prepared using lysis buffer [20 mM Tris (pH 8.1), 150 mM NaCl, 1% Nonidet P-40, 1% SDS, 5% glycerol], and the Complete-Mini protease inhibitor cocktail tablet (Roche, Indianapolis, IN). Samples were boiled in Laemmli buffer and run on mini-blot SDS-PAGE gels (Bio-Rad, Hercules, CA). Proteins were transferred onto nitrocellulose membrane overnight (20 V constant) and blocked with 5% nonfat milk in Tris-buffered saline solution [10 mM Tris (pH 7.4), 150 mM NaCl, and 0.5% Tween 20] before incubation with primary antibody. Anti-ER antibodies (polyclonal rabbit HC-20) were from Santa Cruz Biotechnologies (Santa Cruz, CA). Anti-ERβ antibodies (monoclonal mouse, CWK-F12) were produced by our lab (44). Secondary antibodies to the respective primary antibodies were purchased from Zymed Laboratories (South San Francisco, CA).
Cell Proliferation Assays
MCF-7 cells were infected with AdGal or AdERβ in 100-mm dishes (Corning) for 8 h before seeding in phenol red-free MEM supplemented with 5% charcoal-dextran-treated calf serum at 1000 cells per well in 96-well plates (BD Falcon, Franklin Lakes, NJ). The next day, cells received fresh medium and vehicle or ligands every 72 h. Cell growth was monitored using the CellTiter 96 AQueous One Solution Cell Proliferation Assay, according to the manufacturer’s recommendations (Promega, Madison, WI).
ChIP Assays
ChIP assays were carried out as described by Metivier and colleagues (45). Confluent 150-mm dishes of MCF-7 cells (
17 x 106 cells per dish) were treated with control 0.1% ethanol vehicle or ligands (E2, LG, or HG) for 45 min and were then fixed with 1.5% formaldehyde. Fixation was subsequently stopped by 125 mM glycine quench and 2x cold PBS washes. Cross-linked chromatin complexes were collected in nuclei lysis buffer and sonicated three times on ice at setting 8 for 10-sec pulses (output 20 W; Dismembrator model 100; Fisher Scientific, Pittsburgh, PA). To immunoprecipitate chromatin complexes, the following antibodies were used: ER antibody HC-20 (Santa Cruz Biotechnology); ERβ antibodies combination with equal parts of GeneTex ERβ mouse monoclonal 7B10.7 (GTX70182; GeneTex, San Antonio, TX), Calbiochem mouse monoclonal 10.76 (GR40; Calbiochem, La Jolla, CA), and ABR rabbit polyclonal (PA1–311; ABR Antibodies, Golden, CO); SRC3/AIB1 antibody H-270 (Santa Cruz Biotechnology); and RIP140 antibody (Santa Cruz Biotechnology). We incubated with the specific antibodies and protein A/G agarose beads (Pierce, Rockford, IL) overnight at 4 C followed by washes and elution with 1% SDS. The DNA was recovered by reversing the cross-links with 20 mM NaCl at 65 C overnight and dissolving in a final volume of 100 µl per immunoprecipitation. To quantitatively detect immunoprecipitated chromatin, 1 µl eluent was mixed with SYBR Green Taq mix and 125 nM forward and reverse specific primers directed against known ER binding sites (32).
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Disclosure Statement: E.C.C., T.H.C., S.-H.P., W.G.H., J.A.K., and B.S.K. have nothing to declare. B.K. is employed by Wyeth Research.
First Published Online February 7, 2008
Abbreviations: Ad, Adenovirus; ChIP, chromatin immunoprecipitation; EASE, Expression Analysis Systematic Explorer; E2, 17β-estradiol; ER, estrogen receptor; GPCR, G protein-coupled receptor; HG, high genistein; LG, low genistein; RIP140, receptor-interacting protein 140; SRC3, steroid receptor coactivator 3; siRNA, small interfering RNA.
Received for publication July 19, 2007. Accepted for publication January 30, 2008.
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and β. Endocrinology 138:863–870 transcriptional activity and is a key regulator of the cellular response to estrogens and antiestrogens. Endocrinology 140:5566–5578 and PR and associated with nodal status, grade, and proliferation rate in breast cancer. Am J Pathol 156:29–35, estrogen receptor-β, coactivators, and corepressors in breast cancer. Clin Cancer Res 6:512–518 and β on cyclin D1 gene expression. J Biol Chem 277:24353–24360 and β. Bioorg Med Chem 12:1559–1567[CrossRef][Medline] in breast cancer cells. Endocrinology 147:4831–4842 and β. Mol Biol Cell 15:1262–1272 and β heterodimers exert unique effects on estrogen- and tamoxifen-dependent gene expression in human U2OS osteosarcoma cells. Mol Endocrinol 19:1555–1568 or ERβ in human osteosarcoma cells: distinct and common target genes for these receptors. Endocrinology 145:3473–3486 signaling in breast cancer cells. Oncogene 27:1019–1032[CrossRef][Medline] binding sites. PLoS Genetics 3:e87CT method. Methods 25:402–408[CrossRef][Medline] activation by ligands, emphasizing the role of interactions between distant A and E domains. Mol Cell 10:1019–1032[CrossRef][Medline]NURSA Molecule Pages Link:
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) and ER
). Clusters enriched for genes involved in cell cycle progression (cluster A1), regulation of transcription (cluster A4), negative regulation of cell proliferation (cluster B4), and GPCR signaling pathway (cluster B9) are shown. C, Proliferation of MCF-7 cells expressing either ER
