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• W4200319315 abstract "Article Figures and data Abstract Editor's evaluation eLife digest Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract Heat shock factor 1 (HSF1), a key regulator of transcriptional responses to proteotoxic stress, was linked to estrogen (E2) signaling through estrogen receptor α (ERα). We found that an HSF1 deficiency may decrease ERα level, attenuate the mitogenic action of E2, counteract E2-stimulated cell scattering, and reduce adhesion to collagens and cell motility in ER-positive breast cancer cells. The stimulatory effect of E2 on the transcriptome is largely weaker in HSF1-deficient cells, in part due to the higher basal expression of E2-dependent genes, which correlates with the enhanced binding of unliganded ERα to chromatin in such cells. HSF1 and ERα can cooperate directly in E2-stimulated regulation of transcription, and HSF1 potentiates the action of ERα through a mechanism involving chromatin reorganization. Furthermore, HSF1 deficiency may increase the sensitivity to hormonal therapy (4-hydroxytamoxifen) or CDK4/6 inhibitors (palbociclib). Analyses of data from The Cancer Genome Atlas database indicate that HSF1 increases the transcriptome disparity in ER-positive breast cancer and can enhance the genomic action of ERα. Moreover, only in ER-positive cancers an elevated HSF1 level is associated with metastatic disease. Editor's evaluation The authors present an interesting genomics approach to understanding the role of heat shock factor 1 (HSF1) in breast cancer cells. They show that HSF1 indirectly interacts with estrogen receptor α (ERα) by regulating the transcription of HSP90, which is essential for normal folding and function of the receptor. They also show that HSF1 and ERα tether within the genome to enhance the transcription of a subset of genes associated with disease progression. Finally, they show the relevance to the breast tumors through comparing their data to publicly available data. https://doi.org/10.7554/eLife.69843.sa0 Decision letter eLife's review process eLife digest About 70% of breast cancers rely on supplies of a hormone called estrogen – which is the main hormone responsible for female physical characteristics – to grow. Breast cancer cells that are sensitive to estrogen possess proteins known as estrogen receptors and are classified as estrogen-receptor positive. When estrogen interacts with its receptor in a cancer cell, it stimulates the cell to grow and migrate to other parts of the body. Therefore, therapies that decrease the amount of estrogen the body produces, or inhibit the receptor itself, are widely used to treat patients with estrogen receptor-positive breast cancers. When estrogen interacts with an estrogen receptor known as ERα it can also activate a protein called HSF1, which helps cells to survive under stress. In turn, HSF1 regulates several other proteins that are necessary for ERα and other estrogen receptors to work properly. Previous studies have suggested that high levels of HSF1 may worsen the outcomes for patients with estrogen receptor-positive breast cancers, but it remains unclear how HSF1 acts in breast cancer cells. Vydra, Janus, Kuś et al. used genetics and bioinformatics approaches to study HSF1 in human breast cancer cells. The experiments revealed that breast cancer cells with lower levels of HSF1 also had lower levels of ERα and responded less well to estrogen than cells with higher levels of HSF1. Further experiments suggested that in the absence of estrogen, HSF1 helps to keep ERα inactive. However, when estrogen is present, HSF1 cooperates with ERα and enhances its activity to help cells grow and migrate. Vydra, Janus, Kuś et al. also found that cells with higher levels of HSF1 were less sensitive to two drug therapies that are commonly used to treat estrogen receptor-positive breast cancers. These findings reveal that the effect HSF1 has on ERα activity depends on the presence of estrogen. Therefore, cancer therapies that decrease the amount of estrogen a patient produces may have a different effect on estrogen receptor-positive tumors with high HSF1 levels than tumors with low HSF1 levels. Introduction Breast cancer is the most common malignancy in women worldwide. Four clinically relevant molecular types are distinguished based on the expression of estrogen receptors (ERs) and HER2 (ERBB2). Among them, luminal adenocarcinomas, characterized by the expression of estrogen receptors, constitute about 70% of all breast cancer cases. There are two classical nuclear estrogen receptors, ERα and ERβ (encoded by ESR1 and ESR2 genes, respectively), and structurally different GPR30 (GPER1), which is a member of the rhodopsin-like family of the G protein-coupled and seven-transmembrane receptors. ERα expression is most common in breast cancer, and its evaluation is the basis for determining the ER status. The activity of estrogen receptors is modulated by steroid hormones, mainly estrogens, which are synthesized from cholesterol via androgens in the reaction catalyzed by aromatase (Fuentes and Silveyra, 2019). According to epidemiological and experimental data, estrogens alongside the mutations in BRCA1 and BRCA2, CHEK2, TP53, STK11 (LKB1), PIK3CA, PTEN, and other genes, are key etiological factors of breast cancer development (Yaşar et al., 2017; Verigos and Magklara, 2015). The mechanism of estrogen-stimulated breast carcinogenesis is not clear. According to the widely accepted hypothesis, estrogens acting through ERα stimulate cell proliferation and can support the growth of cells harboring mutations that then accumulate, ultimately resulting in cancer. Another hypothesis suggests the ERα-independent action of estrogens via their metabolites, which can exert genotoxic effects, contributing to cancer development (Yager and Davidson, 2006; Pescatori et al., 2021). Nevertheless, hormonal therapies targeting either estrogen production (i.e., aromatase inhibitors) or the hormone receptor itself such as selective ER modulators (SERMs; i.e., tamoxifen) and selective ER degraders (SERDs; i.e., fulvestrant) are widely used to block the mitogenic action of estrogens in patients with ER-positive breast cancer (Renoir, 2012; Farcas et al., 2021), contributing to the decline in mortality from breast cancer in recent decades (Iwase et al., 2021). Previously, we have found that the major female sex hormone 17β-estradiol (E2) stimulates activation of heat shock factor 1 (HSF1) in estrogen-dependent breast cancer cells via MAPK signaling (Vydra et al., 2019). HSF1 is a well-known regulator of response to cellular stress induced by various environmental stimuli. It mainly regulates the expression of the heat shock proteins (HSPs), which function as molecular chaperones and regulate protein homeostasis (Ran et al., 2007). HSF1-regulated chaperones control, among others, the activity of estrogen receptors (Echeverria and Picard, 2010). ERs remain in an inactive state trapped in multimolecular chaperone complexes organized around HSP90, containing p23 (PTGES3), and immunophilins (FKBP4 or FKPB5) (Segnitz and Gehring, 1995). Upon binding to E2, ERs dissociate from the chaperone complexes and become competent to dimerize and regulate the transcription. ERs bind DNA directly to the estrogen-response elements (EREs), or indirectly, via tethering factors, and promote the transcription at either nearby promoters or through chromatin loops from distal enhancers. The dynamic action of ERs, which enables the adaptation of cancer cells and impacts the clinical outcome, relies on many transcriptional coactivators and corepressors (Heldring et al., 2007; Renoir, 2012; Farcas et al., 2021). HSP90 is essential for ERα hormone binding (Fliss et al., 2000), dimer formation (Powell et al., 2010), and binding to the EREs (Inano et al., 1994). Also, the passage of the ER to the cell membrane requires association with the HSP27 (HSPB1) oligomers in the cytoplasm (Razandi et al., 2010). More than 20 chaperones and co-chaperones associated with ERα in human cells have been identified through a quantitative proteomic approach (Dhamad et al., 2016), but their specific contribution in the receptor action still needs to be investigated. Moreover, HSF1 is involved in the regulation of a plethora of non-HSP genes, which support oncogenic processes: cell cycle regulation, signaling, metabolism, adhesion, and translation (Mendillo et al., 2012). A high level of HSF1 expression was found in cancer cell lines and many human tumors (Vydra et al., 2014; De Thonel et al., 2011) and was shown to be associated with the increased mortality of ER-positive breast cancer patients (Santagata et al., 2011; Gökmen-Polar and Badve, 2016). E2-activated HSF1 is transcriptionally potent and takes part in the regulation of several genes essential for breast cancer cell growth (Vydra et al., 2019). Furthermore, HSF1-regulated chaperones are necessary for ERα proper function. Thus, a hypothetical positive feedback loop between E2/ERα and HSF1 signaling may exist, which putatively supports the growth of estrogen-dependent tumors. Here, to study the cooperation of HSF1 and ERα in estrogen signaling and the influence of HSF1 on E2-stimulated transcription and cell growth and mobility, we created novel experimental models based on HSF1-deficient cells and performed an in-depth bioinformatics analysis of the relevant genomics data. We also compared the influence of HSF1 on ER-positive and ER-negative breast cancers transcriptomes from The Cancer Genome Atlas (TCGA) database. Results HSF1 deficiency reduces the estrogen-stimulated proliferation and mobility of ERα-positive MCF7 cells To study the contribution of HSF1 in E2 signaling, we established MCF7 cell lines with reduced HSF1 expression. Firstly, we tested a few HSF1-targeting shRNAs (Figure 1—figure supplement 1A). Then, the most potent variant that reduced HSF1 level about 10-fold (termed afterward shHSF1) was chosen for further studies. Although the heat shock response was significantly reduced, the expression of HSP genes (HSPA1A, HSPH1, HSPB1, and HSPB8) was still induced after this HSF1 knockdown (Figure 1—figure supplement 1B). Thus, we additionally created MCF7 variants with HSF1 functional knockout using the CRISPR/Cas9 gene targeting approach (clones arisen from two individual cells termed KO#1 and KO#2 afterward). Then, considering the slight differences between clones, we created an additional experimental model: six new individual HSF1-negative (HSF1−) and six HSF1-positive (HSF1+) MCF7 clones obtained using the DNA-free CRISPR/Cas9 system (which was more effective) were pooled before analyses. The complete elimination of HSF1 (Figure 1A, Figure 1—figure supplement 1A) was connected with a substantial loss of inducibility of HSP genes (Figure 1—figure supplement 1B) and proteins (HSP105/HSPH1, HSP90, HSP70/HSPA1) following hyperthermia (Figure 1B). The ability of cells to form colonies in the clonogenic assay was reduced in all MCF7 experimental models of HSF1 depletion (using shRNA and sgRNA; Figure 1C, Figure 1—figure supplement 1C). Moreover, the population size of ALDH-positive (stem/progenitor) cells correlated with the HSF1 level and was reduced in HSF1-deficient cells (Figure 1—figure supplement 1D). Also, the increased contribution of cells in the G1 phase was associated with the HSF1 knockout (Figure 1—figure supplement 1E). HSF1 knockdown did not affect the proliferation rate, while the functional HSF1 knockout led to a slight reduction in the proliferation rate under standard conditions (this effect was not visible under less favorable growing conditions, i.e., in phenol red-free 5% dextran-activated charcoal-stripped fetal bovine serum (FBS); Figure 1D, Figure 1—figure supplement 1F). To check if HSF1 deficiency would affect the growth of another ERα-positive cell line, we modified T47D cells using the CRISPR/Cas9 method (Figure 1—figure supplement 2A). Under standard conditions, we did not observe differences between HSF1+ and HSF1− T47D cells in the proliferation and clonogenic assay (not shown). Unlike MCF7 cells, HSF1− T47D cells grew slightly faster than HSF1+ cells, but this difference was not statistically significant and no differences were observed in the cell cycle (Figure 1—figure supplement 2B and C). Figure 1 with 2 supplements see all Download asset Open asset Effect of HSF1 depletion on MCF7 cell growth and migration. (A) HSF1 level and (B) heat shock response assessed by western blot in unmodified cells (WT) and in cells obtained using DNA-free CRISPR/Cas9 system: HSF1+ (six clones with the normal HSF1 level were pooled) and HSF1− (six HSF1-negative clones were pooled). Actin (ACTB) was used as a protein loading control. Heat shock: 43°C/1 hr + recovery 37°C/6 hr. (C) The number of colonies formed in the clonogenic assay: representative images of single-cell clones stained with crystal violet and their quantification (mean ± SD, n = 4). (D) Growth curves of untreated (Ctr) and E2-stimulated cells in phenol red-free media with 5% or 10% charcoal-stripped FBS (assessed using crystal violet staining). Mean and standard deviation from three independent experiments (each in three technical replicates) are shown. (E) F-actin staining in cells treated with E2 (10 nM for 14 days), then seeded for 24 hr on fibronectin-coated slides. Arrowheads, ameboid-like cells; arrows, mesenchymal-like cells; scale bar, 50 μm. (F) The number of cells after F-actin staining was counted in 10 random fields and single cells (ameboid-like and mesenchymal-like) were calculated as a percent of all cells. (G) Cell adhesion to collagens and vitronectin analyzed after E2 treatment (10 nM for 14 days); adhesion to BSA serves as a negative control (n = 4) (H) The number of migrating cells assessed by Boyden chamber assay after E2 treatment (10 nM for 14 days) (n = 3, each in three technical replicates). Boxplots represent the median, upper and lower quartiles, maximum and minimum; ***p<0.0001, **p<0.001, *p<0.05 (significance of differences versus the corresponding control – next to the curve/box/bar or between cell variants). See Figure 1—figure supplement 1 and Figure 1—figure supplement 2 for an extended characteristic of other HSF1-deficient MCF7 and T47D cell models. We have previously demonstrated that HSF1 was activated after E2 treatment of ERα-positive cells and it was able to bind to the regulatory sequences of several target genes, which correlated with the upregulation of their transcription (Vydra et al., 2019). Since most of these genes code for proteins involved in E2 signaling, we expected that HSF1 downregulation could affect E2-dependent processes, especially cell proliferation. Therefore, we compared E2-stimulated proliferation of HSF1-proficient and HSF1-deficient MCF7 cells in all experimental models. HSF1 deficiency resulted in weaker growth stimulation by E2 (than in the corresponding control cells), but a statistically significant difference was not observed in all experimental conditions/cell variants (Figure 1D, Figure 1—figure supplement 1G). However, E2-stimulated proliferation was not significantly reduced in HSF1-deficient T47D cells (Figure 1—figure supplement 2B). These results indicate that HSF1 may influence the growth of ER-positive breast cancer cells, unstimulated and stimulated by estrogen, although the effect also depends on other factors (differences between cells, culture conditions). We then searched for differences between modified cells in response to longer E2 treatment. We noticed that stimulation of HSF1-proficient MCF7 cells with E2 for 7–14 days resulted in cell-cell dissociation, the acquisition of an ameboid- or mesenchymal-like morphology (Figure 1E and F, Figure 1—figure supplement 1I), and enhanced adhesion to collagens (I and IV) but reduced to vitronectin (Figure 1G; adhesion to fibronectin, laminin, and tenascin was not affected; not shown). These changes enabled cells to migrate faster (Figure 1H, Figure 1—figure supplement 1H). HSF1 deficiency counteracted cell scattering after E2 stimulation (Figure 1E and F, Figure 1—figure supplement 1I ). This was associated with the reduced adhesion to collagens and cell motility (Figure 1G and H, Figure 1—figure supplement 1H). It is noteworthy that T47D cells differed from MCF7 cells in response to E2 treatment for 14 days, especially in acquired cell morphology. Amoeboid-like morphology was dominant among the scattered MCF7 cells, while mesenchymal-like morphology was dominant in T47D cells (Figure 1E and F, Figure 1—figure supplement 2D and E). Also, adhesion to collagens was not affected by E2 in T47D cells (Figure 1—figure supplement 2F). Nevertheless, E2 treatment enhanced migration of HSF1-proficient but not HSF1-deficient T47D cells (Figure 1—figure supplement 2G). Transcriptional response to estrogen is inhibited in HSF1-deficient cells In a search for the mechanism responsible for a distinct response to estrogen in ER-positive cells with different levels of HSF1, we analyzed global gene expression profiles by RNA-seq in all MCF7 cell variants. At control conditions (no E2 stimulation), we found relatively few genes differentially expressed in HSF1-proficient and HSF1-deficient cells that were common for different models of HSF1 downregulation. These included mainly known HSF1 targets (e.g., HSPH1, HSPE1, HSPD1, HSP90AA1) slightly repressed in HSF1-deficient cells. Analyzing the response to E2, we initially compared cell variants from different models: with the normal level of HSF1 (WT, SCR, and MIX) and HSF1-deficient cells (shHSF1, KO#1, and KO#2) (Supplementary file 1, sheet 1). We found 50 genes similarly regulated by E2 (47 upregulated and 3 downregulated) in all HSF1-proficient MCF7 cell variants (Figure 2—figure supplement 1A and B). On the other hand, only 13 genes were similarly upregulated after E2 stimulation in HSF1-deficient MCF7 cell variants (Figure 2—figure supplement 1A and C). The gene set enrichment analyses indicated that HSF1 deficiency negatively affected the processes activated by estrogen (the early and late estrogen response; Figure 2—figure supplement 1E). Moreover, though almost all genes upregulated by E2 in HSF1-proficient cells were also upregulated in HSF1-deficient cells (except NAPRT), the degree of their activation (measured as a fold change E2 versus Ctr) was usually weaker in the latter cells (Figure 2—figure supplement 1F), which indicated that the transcriptional response to estrogen was inhibited in the lack of HSF1. Interestingly, however, several E2-dependent genes revealed slightly higher basal expression (without E2 stimulation) in HSF1-deficient cells (Figure 2—figure supplement 1G), which suggested that in the absence of E2, HSF1 could be involved in the suppression of these genes. Considering differences between KO#1 and KO#2 HSF1 knockout clones derived from individual cells (Figure 2—figure supplement 1D), we performed an additional transcriptomic analysis using a putatively more representative MCF7 cell model obtained by DNA-free CRISPR/Cas9 method (heterogeneous populations of HSF1+ and HSF1− cells) (Supplementary file 1, sheet 2). The analysis showed that 3715 genes significantly changed the expression (2336 upregulated and 1479 downregulated) in HSF1+ cells after E2 stimulation. On the other hand, only 2969 genes (1818 upregulated and 1151 downregulated) changed the expression in HSF1− cells (Figure 2A). Thus, approximately 20% of genes responding to E2 treatment in HSF1+ cells did not respond similarly in HSF1− cells. Moreover, among genes up- or downregulated in both cell variants, approximately 68% or 81%, respectively, responded less effectively (fold change E2 versus Ctr) in HSF1− cells than HSF1+ cells (Figure 2A, bottom panel). The gene set enrichment analyses revealed the slight differences in the early and late estrogen response pathways (Hallmark gene sets M5906 and M5907) but also in genes defining epithelial-mesenchymal transition (M5930). Interestingly, the expression of genes from these pathways already differentiated untreated HSF1− and HSF1+ cells. Genes encoding cell cycle-related targets of E2F transcription factors (M5925), involved in the G2/M checkpoint (M5901) as well as ECM proteoglycans (M27219) and collagen formation (M631), also discriminated HSF1− and HSF1+ cells (Figure 2—figure supplement 2A). The analysis confirmed that the transcriptional response to estrogen was inhibited in the lack of HSF1. In addition, signaling pathways related to proliferation, migration, and collagen adhesion were identified as primarily affected, which was consistent with the results of functional tests. Among E2-responding genes that were common for all MCF7 cell models, 46 were upregulated and 2 were downregulated (Figure 2B). Though a fraction of genes with higher basal expression in HSF1− cells than in HSF1+ cells (potentially repressed by HSF1) was smaller compared to other models of HSF1 deficiency (Figure 2—figure supplement 1), it remained relevant (Figure 2C). Figure 2 with 2 supplements see all Download asset Open asset The deficiency of HSF1 reduces a transcriptional response to estrogen (E2) in ER-positive MCF7 cells. (A) Overlap of genes stimulated or repressed after the E2 treatment (RNA-seq analyses) in HSF1+ and HSF1− cells (model created as described in Figure 1). The bottom panel compares the degree of response to E2 of overlapping genes. (B) Heatmap with hierarchical clustering of normalized read counts from RNA-seq (row z-score) for selected genes (identified as similarly responding in all MCF7 cell models; see Figure 2—figure supplement 1) stimulated or repressed after the E2 treatment. (C) The response to E2 stimulation presented as a mean fold change E2 versus Ctr (dots; scale on the top) as well as changes in the expression level between Ctr and E2 (arrows begin at the level of mean expression in untreated cells and end at the level of mean expression in treated cells; normalized RNA-seq read counts with a scale on the bottom). Genes are sorted according to the hierarchical clustering shown in the heatmap. Upregulation, fold change >1.0; downregulation, fold change <1.0. Statistically significant differences between untreated HSF1+ and HSF1− cells are marked: ***p<0.0001, **p<0.001, *p<0.05. (D) Nascent RNA gene expression analyses by RT-qPCR in wild-type (WT), HSF1+, and HSF1− cells. The upper panel shows E2-stimulated changes (E2 versus Ctr fold change; E2 treatment: 10 nM, 4 hr), bottom panel shows basal expression level represented as fold differences between untreated wild-type control (WT), HSF1+, and HSF1− cells. Corresponding total RNA analyses are shown in Figure 2—figure supplement 2B. ***p<0.0001, **p<0.001, *p<0.05 (significance of differences versus the corresponding control – above the bar, or between cell variants). (E) Analyses at the protein level (western blot) after 48 hr treatment with E2. HSPA8 was used as a protein loading control. The graph below shows the results of densitometric analyses (n = 3). To validate the RNA-seq results, we selected 13 estrogen-induced genes for RT-qPCR analyses using nascent RNA (Figure 2D). In the case of nine genes, the degree of activation was substantially lower in HSF1− than in HSF1+ cells. When the basal expression in E2-untreated cells was compared, there were 12 genes expressed at a higher level in untreated HSF1− cells in comparison to HSF1+ cells (Figure 2D). Additional RT-qPCR analyses using total RNA showed that of the 15 genes tested 12 were less activated after E2 treatment in HSF1− than in HSF1+ cells. When the basal expression in E2-untreated cells was compared, six genes were expressed at a significantly higher level and one at a lower level in HSF1− than HSF1+ cells (Figure 2—figure supplement 2B). Therefore, although the response to E2 was highly variable (differences were observed between cell models), RT-qPCR-based validation generally confirmed differences between HSF1-proficient and HSF1-deficient MCF7 cells revealed by the RNA-seq. These changes at the transcriptional level might have direct functional consequences in HSF1− cells (reduced level of E2-stimulated lcnRNAs, e.g., LINC01016) but also were connected with the reduced protein level of E2-stimulated genes (HSPB8, PHLDA1, and EGR3 are shown as examples; Figure 2E). HSF1 influences the binding of ERα to chromatin To further study the influence of HSF1 on estrogen signaling, we analyzed ERα binding to chromatin in HSF1-proficient and HSF1-deficient MCF7 cells. We performed ChIP-seq analyses using the first functional knockout model (KO#2 and MIX cells) and validation by ChIP-qPCR using the model obtained by the DNA-free CRISPR/Cas9 system. A list of all ERα-binding sites detected by ChIP-seq in unstimulated cells and after 30 or 60 min of E2 treatment is presented in Supplementary file 2. These analyses revealed that in unstimulated cells ERα binding was more efficient (more binding sites and increased number of tags per peak) in HSF1-deficient cell variant (KO#2) than in the corresponding HSF1-proficient control (MIX cells) (Figure 3A and B) (it is worth noting that the MIX cell variant was also different from wild-type cells, indicating that the genome organization was affected by the CRISPR/Cas9 procedure itself, possibly due to off-targets). ERα target sequences in IGFBP4 or GREB1 are examples of such increased binding efficiency in unstimulated HSF1-deficient cells (Figure 3D). Estrogen treatment for 30 or 60 min resulted in enhanced ERα binding in all cell variants. However, fold enrichment (E2 versus Ctr) was lower in HSF1-deficient cells than in HSF1-proficient cells (Figure 3C). Moreover, the number of detected peaks in the E2-treated HSF1-deficient cells was only slightly higher than in unstimulated cells (Figure 3A) and enhanced ERα binding was primarily manifested in sites already existing in unstimulated cells (Figure 3C and D). We additionally searched for ERα- binding preferences in HSF1-proficient and HSF1-deficient cells. After estrogen treatment, ERβ (ESR2) and ERα (ESR1) motifs were centrally enriched in ERα-binding regions in all cell variants (Figure 3—figure supplement 1). Moreover, in untreated cells, the motif for PBX1 (not centrally enriched in peak regions), which is a pioneer factor known to bind to the chromatin before ERα recruitment (Magnani et al., 2011), was identified by MEME-ChIP analysis in all cell variants (not shown). This indicates that ERα chromatin-binding preferences were not substantially changed in HSF1-deficient cells. Figure 3 with 2 supplements see all Download asset Open asset HSF1 deficiency influences the binding of ERα to chromatin in ER-positive MCF7 cells. (A) Number of peaks and peak size distribution (number of tags per peak), (B) heatmap visualization of ERα ChIP-seq data (versus input), and (C) binding enrichment (fold enrichment E2 versus Ctr) after E2 stimulation (10 nM for 30 or 60 min) in HSF1-deficient cells (KO#2) and corresponding control (MIX, a combination of control clones arisen from single cells following CRISPR/Cas9 gene targeting). Heatmaps depict all ERα-binding events centered on the peak region within a 3 kb window around the peak. Peaks in each sample were ranked on intensity. (D) Examples of ERα peaks identified in ChIP-seq analyses, normalized by scaling factor using bamCoverage tool, and visualized by the IGV browser in unstimulated cells (Ctr) and after E2 treatment (10 nM, 30 min). The scale for each sample is shown in the left corner. Line plots show the E2/Ctr ratio obtained using the bamCoverage tool. (E) Comparison of ERα-binding efficiency (by ChIP-qPCR; % of input) in selected sequences in untreated (Ctr; upper panel) and after E2 stimulation (10 nM, 30 min; bottom panel) HSF1+ and HSF1− MCF7 cells (model created as described in Figure 1). ***p<0.0001, **p<0.001, *p<0.05 (significance of differences versus the corresponding control – above the bar, or between cell variants). (F) Western blot analysis of ERα level and its phosphorylated form (pS118) after E2 treatment (1, 10, and 100 nM for 30 or 60 min) in HSF1+ and HSF1− cells. Actin (ACTB) was used as a protein loading control. Graphs below show the results of densitometric analyses (n = 4). *p<0.05 (significance of differences versus the corresponding control – above the bar, or between cell variants, versus the same treatment). Validation of ChIP-seq results revealed that in the case of IGFBP4 and GREB1 (i.e., sequences highly enriched with ERα after E2 stimulation) the binding efficiency of ERα was higher in unstimulated HSF1− cells than in the corresponding HSF1+ cells. On the other hand, although estrogen treatment strongly induced ERα binding, this induction was considerably lower in HSF1− cells (Figure 3E). Therefore, we confirmed that in this experimental system the deficiency of HSF1 may result in enhanced binding of unliganded ERα (in particular at strongly responsive ERα-binding sites) and weaker subsequent enrichment of ERα binding upon estrogen stimulation. However, other patterns of the response to E2 treatment are also possible, especially in sequences that were weakly enriched in ERα after stimulation, as exemplified by AMZ1, SDK2, SMPD3, and SMTNL2 (Figure 3D and E). Observed differences in response to E2 between cells with different levels of HSF1 may result from altered expression of ERα in HSF1-deficient cells. We found that although the kinetics of ERα activation (as assessed by S118 phosphorylation) in response to E2 treatment was similar in HSF1+ and HSF1− MCF7 cells, ERα and pS118 ERα levels were lower in HSF1− cel" @default.
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• W4200319315 title "Author response: Heat shock factor 1 (HSF1) cooperates with estrogen receptor α (ERα) in the regulation of estrogen action in breast cancer cells" @default.
• W4200319315 doi "https://doi.org/10.7554/elife.69843.sa2" @default.
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