Chemical manipulation of estrogen receptor alpha ligand binding domain structural mobility tunes receptor lifetime and influences breast cancer therapeutic activities. Selective estrogen receptor modulators (SERMs) extend estrogen receptor alpha (ERα) cellular lifetime/accumulation. They are antagonists in the breast but agonists in the uterine epithelium and/or in bone. Selective estrogen receptor degraders/downregulators (SERDs) reduce ERα cellular lifetime/accumulation and are pure antagonists. Activating somatic ESR1 mutations Y537S and D538G enable resistance to first-line endocrine therapies. SERDs have shown significant activities in ESR1 mutant setting while few SERMs have been studied. To understand whether chemical manipulation of ERα cellular lifetime and accumulation influences antagonistic activity, we studied a series of methylpyrollidine lasofoxifene (Laso) derivatives that maintained the drug’s antagonistic activities while uniquely tuning ERα cellular accumulation. These molecules were examined alongside a panel of antiestrogens in live cell assays of ERα cellular accumulation, lifetime, SUMOylation, and transcriptional antagonism. High-resolution x-ray crystal structures of WT and Y537S ERα ligand binding domain in complex with the methylated Laso derivatives or representative SERMs and SERDs show that molecules that favor a highly buried helix 12 antagonist conformation achieve the greatest transcriptional suppression activities in breast cancer cells harboring WT/Y537S ESR1. Together these results show that chemical reduction of ERα cellular lifetime is not necessarily the most crucial parameter for transcriptional antagonism in ESR1 mutated breast cancer cells. Importantly, our studies show how small chemical differences within a scaffold series can provide compounds with similar antagonistic activities, but with greatly different effects of the cellular lifetime of the ERα, which is crucial for achieving desired SERM or SERD profiles.
This work elegantly provides novel insights into the molecular mechanisms of selective Estrogen Receptor modulator and downregulator activities on Estrogen Receptor function.https://doi.org/10.7554/eLife.72512.sa0
The pro-oncogenic cellular activities of estrogen receptor alpha (ERα) drive breast cancer pathogenesis. ERα is overexpressed in approximately 70% of breast cancers and targeted endocrine therapies are given to prevent primary disease metastasis. Post-menopausal patients primarily receive aromatase inhibitors, which indirectly inhibits ERα by ablating endogenous estrogens, and may be given in combination with a CDK 4/6 inhibitor (Burstein et al., 2019). Pre-menopausal patients receive tamoxifen, a selective estrogen receptor modulator (SERM), which directly binds to the receptor and reprograms transcription to induce cellular quiescence (Maximov et al., 2018). Together, these therapeutic paradigms significantly reduce the 5 years risk of recurrence and continually show improved disease outcomes (Early Breast Cancer Trialists Collaborative Group, 2005; Mouridsen et al., 2003).
Acquired resistance to endocrine therapies remains a major source of breast cancer mortality. Approximately 50% of patients present acquired or de novo resistance to endocrine therapies after an average of 5-years (Anurag et al., 2018). Deep genomic sequencing of endocrine-resistant, ER+, and metastatic breast cancers revealed the presence of ESR1 ligand binding domain mutations (ESR1muts) at a rate of approximately 25% (Toy et al., 2013; Jeselsohn et al., 2014; Robinson et al., 2013). Y537S (14%) and D538G (36%) are the two most prevalent mutations and account for nearly 50% of those identified. Both mutations, especially Y537S, enable hormone-free transcriptional activity, resistance to inhibition by 4-hydroxytamoxifen (4OHT, the active metabolite of tamoxifen), and are associated with a more aggressive disease phenotype (Chandarlapaty et al., 2016). ESR1muts have also been identified in cultured breast cancer cells and become enriched as they become resistant to endocrine therapies, suggesting a latent and selectable mechanism of acquired drug resistance (Martin et al., 2017). In addition to mimicking the genomic actions of E2 stimulation, ESR1muts bind to unique cistromes and promote allele-specific transcriptional programs compared to E2-stimulated WT receptor (Jeselsohn et al., 2018). Mutation-induced molecular alterations enable resistance to clinically approved antiestrogens and a more aggressive metastatic progressive disease.
Biochemical studies and x-ray crystal structures have shown that both mutations favor an E2-like agonist conformation in the absence of hormone (Fanning et al., 2016; Nettles et al., 2008). This favored agonist conformation reduces the binding affinity of ERα ligands and alters the therapeutically important antagonist receptor conformation of the SERM 4OHT (Fanning et al., 2016). Competitive antiestrogens with selective estrogen receptor degrader/downregulator (SERD) activities with improved potencies show superior therapeutic antagonistic activities compared to 4OHT in breast cancer cells harboring Y537S or D538G ESR1 (Fanning et al., 2018b). The SERD fulvestrant, contrary to 4OHT, completely ablated Y537S ERα transcriptional activity in breast cancer cells (Toy et al., 2013). Fulvestrant’s antiestrogenicity stems from its ability to antagonize ERα transcription and reduce its cellular lifetime (degrade/downregulate receptor) by inducing post-translational modifications including SUMOylation and ubiquitination by increasing proteasomal degradation (Wijayaratne and McDonnell, 2001; Traboulsi et al., 2019; Hilmi et al., 2012). Tamoxifen and other SERMs also antagonize transcription but induce a stable antagonist conformation that enhances ERα nuclear lifetime (Fanning et al., 2018b). SERMs show partial agonist activities in the uterine endometrium and/or in bone while SERDs are pure antagonists (Fanning and Greene, 2019). Due to unfavorable pharmacological properties of fulvestrant, large-scale efforts brought about the development and clinical evaluation of improved SERDs (Guan et al., 2019; Wardell et al., 2015b; Hamilton, 2018; Tria et al., 2018; Dickler, 2018; Bardia et al., 2019; Wardell et al., 2017; Metcalfe et al., 2019; Fanning et al., 2018a). These molecules possess functional groups including carboxylic acids, azeditines, and pyrrolidines that favor the H12 antagonist conformation and induce proteasomal degradation by increasing its conformational mobility, although their impact on receptor post-translational modifications remains uncharacterized (Fanning and Greene, 2019; Guan et al., 2019; Fanning et al., 2018a; De Savi et al., 2015). Interestingly, recent studies suggest that ERα degrading activities may not be required for therapeutic efficacy in breast cancer cells with recurring hotspot ESR1 mutations (Fanning et al., 2018b; Lainé et al., 2021; Wardell et al., 2015a; Andreano et al., 2020). In light of this recent work, the role of ERα modification by ubiquitin and SUMO, cellular lifetime, and accumulation in anti-cancer therapeutic activities, especially with the ESR1muts, remains unclear.
In this study, we developed a series of novel lasofoxifene (Laso) derivatives that affect ERα cellular accumulation similar to either SERMs or SERDs, providing a comparable chemical scaffold to study the role of receptor stability on transcriptional antagonistic and antiproliferative activities. We evaluated these molecules against a panel of SERMs and SERDs (Figure 1) representing a comprehensive spectrum of clinical and preclinical antiestrogenic small molecules. As part of these studies, we developed a novel high-throughput live-cell approach to quantify and observe the kinetics of ERα cellular accumulation within living breast cancer cells upon treatment with SERMs or SERDs. Because fulvestrant-induced SUMOylation of WT ERα correlates with shortened kinetics of interaction with DNA, lowered accessibility of estrogen response elements, and more efficient repression of ERα target genes in the presence of fulvestrant (Traboulsi et al., 2019; Hilmi et al., 2012), bioluminescence resonance energy transfer (BRET) was used to examine differences between SERM and SERD-induced SUMOylation for WT, Y537S, and D538G ERα. Reporter gene assays quantifying the impact of SERM or SERD treatment on WT transcriptional antagonism in WT or heterozygous Y537S/WT and D538G/WT MCF7 breast cancer cells revealed that antiestrogen efficacy at suppressing transcription did not necessarily correlate with reduced receptor accumulation. Further, cellular proliferation studies in MCF7 with heterozygous WT/Y537S ESR1, which possesses the greatest degree of antiestrogen-resistance, show that manipulating ERα stability did not enhance anti-proliferative activities in cultured cells. Comparison of Y537S ERα LBD x-ray crystal structures in complex with SERMs and SERDs reveal a ligand-dependent H12 conformational pose that corresponds to increased transcriptional antagonistic efficacies.
We developed a live cell-based assay to quantify differences in ERα expression and cellular lifetime based on ligand or mutation. T47D breast cancer cells were engineered to express a doxycycline (dox) inducible halo-tagged (HT) ERα, allowing the cells to be treated with a permeable HT-specific fluorophore (halo-618) and levels of ERα expression quantified following the addition of dox. To determine ERα accumulation, cells were distributed into 96-well plates in estrogen depleted medium. Using a range of dox concentrations, we found that 1 μg/mL was the lowest dose needed to achieve maximal signal-to-noise ratio (Figure 2—figure supplement 1). To uncover whether ligands and activating somatic mutations influenced the cellular lifetime of ERα, we simultaneously induced halo-ERα expression, treated with 1 μM ligand, and measured fluorescence normalized to cell count every 4 hr for 100 hr. Figure 2 shows representative curves plotting the mean fluorescence counts of two biological replicates (± SD) after normalization to cell count by phase contrast. For WT cells, ERα reached a maximum at approximately 24 hr then fell to baseline by 80 hr (Figure 2A). Treatment with E2 lead to a reduced expression but the signal converged with vehicle by around 30 hr and had fully returned to baseline around 80 hr. Treatment with SERDs further reduced the signal and led to a rapid return to baseline, at around 45 hr for fulvestrant (Figure 2A). Treatment with SERMs greatly enhanced ERα levels over vehicle and extended the time to baseline to past 80 hr (Figure 2D). Interestingly, veh-treated WT and Y537S cells showed similar profiles, but the Y537S mutant took slightly longer to reach baseline (Figure 2B). Unlike the E2-treated WT cells, E2-treated Y537S cells showed an identical pattern to veh-treated Y537S cells (Figure 2B). Surprisingly, the Y537S mutant extended the ERα lifetime in the presence of fulvestrant, past 60 hr compared to 45 hr for WT (Figure 2B). Unexpectedly, the D538G mutant not only reduced the magnitude of ERα expression, but also the kinetics of its cellular turnover with a greater time to baseline for each SERD (Figure 2C). For SERMs, each molecule showed similar profiles of enhancing ERα lifetime in the WT T47D cells (Figure 2D). In the 537 S cells, they further enhanced stability compared to WT (Figure 2E). Surprisingly, RU39411 was the only SERM to elicit any kind of difference on D538G by showing a slight increase in stability; however, it was still approximately 2.5-fold less than in the Y537S (Figure 2F). These data suggest that, in addition to hormone independent transcriptional activities, both Y537S and D538G mutations uniquely affect ERα cellular lifetime within T47D cells.
To quantitate ERα stabilization or degradation/downregulation by different ligands, cells were simultaneously treated by dox, halo-618 and hormone (E2), SERMs, SERM/SERDs, or SERDs at concentrations varying between 0.1 nM and 5 μM for 24 hr. Figure 2—source data 1 shows IC50, R (Maximov et al., 2018) of fit, and fluorescence levels normalized to cell count at maximum dose (5 μM) for each ligand and ERα mutant. As expected, treatment with SERMs resulted in increased maximal signals, while SERDs induced a significant decrease (Fanning et al., 2018b). SERMs, such as 4OHT, show a normalized fluorescence greater than 1 at 5 μM, whereas Laso was neutral (between 0.8 and 1), and SERDs reduced fluorescence levels to less than 0.8. As expected, the hormone E2 induced ERα degradation, which at 0.68 ± 0.05 was approximately 2–3-fold less than for the SERDs with the greatest reduction, at 0.2 ± 0.03, 0.29 ± 0.04, and 0.33 ± 0.04 for RU58668, fulvestrant (ICI182,780), and GDC-0927 respectively. The SERMs 4OHT and RU39411 significantly increased ERα signal with a normalized fluorescence of 2.23 ± 0.24 and 2.11 ± 0.36 at 5 μM treatment respectively. Overall, GDC-0927, fulvestrant, and pipendoxifene (PIP) showed the most potent IC50 values at 0.13 ± 0.03, 0.4 ± 0.02, and 0.77 ± 0.03 nM. Notably, many oral SERDs were not significantly different from PIP. To validate our data, we treated normal T47D cells with increasing doses of fulvestrant then used a capillary-based western blotting technique to observe differences in ERα levels after 24 hr normalized to β-actin. We derived an IC50 value of 0.34 ± 0.10 with an R (Maximov et al., 2018) of 0.94 using this method, which is in close agreement with the results from the engineered HT-ERα expressing cells (Figure 2—figure supplement 2). We also used an in-cell western approach to validate these data for endogenous ERα in T47D cells and observed similar trends in receptor levels after 24 hr (Zhao et al., 2017; Figure 2—figure supplement 3).
To understand how Y537S and D538G ERα mutations impact the stabilizing or degrading activities of antiestrogens, we generated stable T47D breast cancer cells that possess dox-inducible HT Y537S and D538G ERα. SERM-like molecules appeared to retain their abilities to increase receptor nuclear lifetime in the Y537S, but did so with approximately 10-fold reduced IC50 values (Figure 2H and Figure 2—source data 1). Laso, which was essentially neutral to slightly SERD-like in the WT cells, showed a SERM-like profile with Y537S (1.48 ± 0.22 at 5 μM). Interestingly, SERD molecules that possessed carboxylic acids (AZD9496, LSZ102, and GDC0801) all showed more SERM-like profiles with their normalized fluorescence above 1 at 5 μM. Fulvestrant, RU58668, GDC-0927, and PIP were the only molecules that did not show statistically significant differences to their maximal normalized fluorescence with Y537S. However, they did show about a 10-fold decreased IC50 compared to WT. Surprisingly, introduction of the D538G mutation mostly abolished ligand-dependent control on receptor levels (Figure 2I). Nearly every tested SERM and SERD had decreased IC50 values and the greatly increased maximum dosages to achieve an effect on ERα levels (Figure 2—source data 1). GDC-0927 was the only SERD that attained maximal effect on normalized fluorescence with an IC50 <10 nM at 1.88 ±0.04 nM.
A major goal of this study was to understand whether chemical manipulation of WT and mutant ERα cellular lifetime enhanced transcriptional antagonistic activities. Laso did not significantly affect ERα signal compared to vehicle across all concentrations. Notably, Laso possesses a pyrrolidine moiety, similar to OP-1074, which induces ERα degradation through a 3R-methylpyrrolidine (Fanning et al., 2018a). Hence, we synthesized a series of Laso derivatives with stereospecific methyl groups at the 2 and 3 positions on the pyrrolidine (Figure 3A). We first examined the abilities of the molecules to influence WT halo-ERα lifetime in our engineered T47D cells (Figure 3B). LA-3 possesses a 3 R methylpyrrolidine (similar to OP1074) and showed a SERD-like profile with an IC50 of 26.94 ± 0.4 nM and maximum normalized fluorescence of 0.48 ± 0.07 at 5 μM. LA-5 possesses a 2 S methylpyrrolidine and showed a SERM-like profile with an IC50 of 15.68+0.27 nM and a normalized fluorescence of 1.706 ± 0.09 at 5 μM. LA2 and LA4 appeared similar to Laso in that they did not affect receptor lifetime.
LA3 and LA5 were synthesized as racemic mixtures. To understand whether one chiral species accounted for the activity, we performed chiral separation and were able to resolve two major peaks (Figure 3—figure supplement 1). Both LA3 and LA5 showed significantly improved IC50 values for the second peak versus the first peak (Figure 3C). For LA3 peak 1 (LA3-1) and LA3-2 the IC50 was 112.9 ± 0.23 nM and 2.58 ± 0.13 nM respectively. The normalized fluorescent signals at 5 μM were somewhat decreased for LA3-1 versus LA3-2 at 0.57 ± 0.02 and 0.49 ± 0.02 respectively. They were also slightly decreased at 1.75 ± 0.02 and 1.66 ± 0.04 for LA5-1 and LA5-2 respectively. As such, chiral separation substantially improved the IC50 but not the fluorescence at maximum dose. LA3-2 and LA5-2 are subsequently referred to as LA-Deg and LA-Stab for Laso degrader and stabilizer respectively. We used an in-cell western approach to validate these data for endogenous ERα and observed similar trends in receptor levels after 24 hr (Figure 3—figure supplement 2).
We next examined the abilities of LA-Deg and LA-Stab to affect the cellular lifetime of Y537S and D538G halo-ERα in T47D breast cancer cells. In Y537S cells, LA-Stab demonstrated a slightly improved IC50 over 4OHT at 10.62 ± 0.12 and 12.42 ± 0.15 nM respectively. LA-Stab also increased Y537S levels to a slightly greater extent than 4OHT at maximum dose at a signal of 2.47 ± 0.06 and 2.27 ± 0.07 respectively (Figure 3D). Interestingly, the Y537S essentially neutralized the SERD activities of LA-Deg with a normalized fluorescence of 1.01 ± 0.04 at 5 μM. Laso showed a more SERM-like profile with a normalized fluorescence of 1.38 ± 0.03 at 5 μM. As with other molecules, the D538G mutant completely neutralized the LA-Deg and LA-Stab with normalized fluorescent signals around 1 at 5 μM treatment. In the kinetics/lifetime assays, the methylated Laso derivatives showed similar profiles compared to other antagonists (Figure 3F,H). Summary data for IC50 and normalized fluorescence at maximum dose are shown for all antagonists in Figure 3I. Overall, these data show that the methylated Laso derivatives have different impacts on WT ERα accumulation and lifetime but are affected by Y537S and D538G mutations similar to other antiestrogens with comparable properties.
The activating somatic mutations Y537S and D538G differentially influenced how ligands affect ERα cellular lifetime. Fulvestrant induces both ubiquitination and SUMOylation of ERα in breast cancer cells, impacting its stability and activity (Hilmi et al., 2012). SUMOylation of ERα can be measured in HEK293T cells using BRET between Renilla Luciferase (RLucII) tagged ERα and YFP tagged SUMO3 (Hilmi et al., 2012; Cotnoir-White et al., 2018). Figure 4 shows representative SUMO BRET response curves for WT, Y537S, and D538G ERα with a panel of antiestrogens. Figure 4—source data 1 shows IC50 values and maximum BRET ratios for the SUMOylation experiments. In both WT and Y537S cells, fulvestrant induces the greatest degree of SUMO3 recruitment, but the IC50 values and maximum BRET ratios are decreased with the Y537S mutant. GDC0927 is the next most efficacious antiestrogen and its potency trends similarly to fulvestrant with the Y537S mutant. LA-Deg induces SUMOylation but to a lesser maximum than fulvestrant and GDC0927 in WT and is further reduced in Y537S, while LA-Stab did not induce SUMOylation with either receptor. Interestingly, RAL, which showed weak SERD-like activity in WT but not mutant ERα in our cellular lifetime and accumulation assays, also induced low levels of SUMOylation in the WT but not the Y537S cells. Overall, these assays show a correlation between a molecule’s ERα-degrading activities and induction of SUMOylation. However, the acrylic acid SERD AZD9496 did not induce SUMOylation with any ERα construct.
As in our cellular lifetime studies, the D538G mutant showed the greatest alterations in induced SUMOylation compared to WT and Y537S ERα in the BRET assay. Fulvestrant induced about 25% of the SUMOylation for D538G compared to WT ERα. GDC0927 was less affected in its capacity to induce SUMOylation by D538G, albeit its potency was reduced, consistent with our lifetime/accumulation experiments. Surprisingly, LA-Stab and LA-Deg displayed similar activity, contrary to observations with WT and Y537S ERα. Interestingly, 4OHT also induced low levels of SUMOylation in the D538G mutant that were not observed for WT and Y537S. These gains in SUMOylation for LA-Stab and 4OHT correlate with their loss of stabilization activity observed in T47D cells. Because fulvestrant showed significant differences in SUMOylation for the D538G mutant, we examined whether addition of E2 further affected its efficacy for induction of this post-translational modification (Figure 4—figure supplement 1). Both the efficacy and potency of fulvestrant for SUMOylation were markedly reduced, similar to our previous studies in which they were significantly reduced for the D538G mutant. Together, these studies show that the D538G activating somatic ESR1 mutation uniquely affects receptor SUMOylation in response to SERDs, in agreement with our measured differences in cellular lifetime.
Ligand-dependent transcriptional activities depend on the association of coactivator proteins with ERα to form functional complexes (Liao et al., 2002). SERMs and SERDs elicit a structural rearrangement of the ERα LBD to sterically preclude binding of coactivators in the activating function-2 cleft (Fanning and Greene, 2019). Mutations affect the ligand-dependence, antagonistic efficacies and potencies of SERMs and SERDs, and specific coactivator proteins that associate with ERα (Jeselsohn et al., 2018; Fanning et al., 2016; Fanning et al., 2018b). As such, we used BRET to understand whether SERD molecules showed improved abilities to inhibit the binding of the receptor-interacting domain (RID) of the coactivator SRC1 with WT and mutant ERα in cells. RLucII tagged ERα and YFP tagged SRC1 RID were used to measure differences in association in HEK293T cells. Figure 4D shows representative curves for WT and mutant ERα-SRC1 RID binding. Figure 4—source data 1 shows IC50 values and maximum BRET ratios for the coactivator binding experiments. Overall, enhanced basal BRET ratios are observed for the mutants compared to WT ERα. The mutations also decreased the potencies of all SERMs and SERDs to inhibit coactivator binding, consistent with earlier findings for 4OHT and bazedoxifene (BZA) using purified recombinant proteins in vitro (Fanning et al., 2018b). Interestingly, all molecules showed similar efficacies in inhibiting this interaction at the greatest concentrations. AZD9496 showed the greatest potency for all ERα species, but is approximately 10-fold reduced in the mutants. Fulvestrant was the next most potent. Raloxifene, 4OHT, LA-Deg, and LA-Stab showed similar potencies in cells with WT and mutant ERα. GDC0927 showed the least potent inhibition of coactivator association in the WT and mutant ERα assays. Because SERDs showed varied potencies in prohibiting coactivator association with the ERα mutants and did not display greater efficacies, we conclude that induction of ERα SUMOylation does not correlate with repression of SRC1 RID recruitment in cells. Importantly, the mutants uniquely affect which coactivator proteins associate with ERα (Jeselsohn et al., 2018). Therefore, additional studies will be needed to identify preferred antiestrogens to target mutant-specific cofactor interactions.
We used reporter gene assays to measure transcriptional antagonistic potencies of antiestrogens in breast cancer cells harboring WT, Y537S, or D538G ESR1. A 3x-estrogen response element DNA sequence upstream of a GFP reporter was stably incorporated into MCF7 cells harboring WT, heterozygous WT/Y537S, or heterozygous WT/D538G ESR1 (donated by Dr. Ben Ho Park). Cells with stable incorporation of the gene cassette were selected for and enriched using flow sorting. Cells were placed in serum-starved media for 48 hr then treated with increasing concentrations of ligand. ERα transcription was determined by quantitating the total integrated green fluorescence of these cells 24 hr later (Figure 5, Figure 5—source data 1). For WT cells: GDC0927, RAL, and OP1074 showed the most potent transcriptional inhibition at IC50 = 0.03 ± 0.08, 0.11 ± 0.08, and 0.14 ± 0.05 nM respectively, compared to 0.35 ± 0.06 nM for fulvestrant (Figure 5D and G). At the 5 μM maximum dose, RU39411, RAL, and BZA showed the greatest reduction in transcription at 0.14 ± 0.02, 0.16 ± 0.02, and 0.17 ± 0.01. In the WT/Y537S heterozygous cells GDC0927, RAL, and Laso showed the most potent inhibition at IC50 = 0.95 ± 0.51, 2.16 ± 0.67, and 2.88 ± 0.34 nM respectively. At the maximum dose: RU39411, BZA, and PIP showed the greatest reduction in transcription at 0.33 ± 0.02, 0.32 ± 0.05, and 0.32 ± 0.04 respectively. As previously reported, no antiestrogen completely reduced transcriptional activity in cells that possessed Y537S ERα (Toy et al., 2013). In the WT/D538G heterozygous cells RU39411, fulvestrant, and OP-1074 showed the best IC50 values at 0.26 ± 0.53, 0.57 ± 0.69, and 0.52 ± 0.63 nM respectively. At the maximum dose: OP1154, PIP, fulvestrant, and OP1074 showed the greatest transcriptional inhibition at normalized fluorescence of 0.25 ± 0.03, 0.29 ± 0.07, 0.32 ± 0.03, and 0.37±0.05 respectively. Only these four molecules returned the D538G transcriptional activity back to their respective WT values. Together, these data suggest that neither the potency nor the efficacy of induced ERα degradation correlate with improved transcriptional inhibition for the Y537S and D538G mutant receptors in this assay.
Induction of alkaline phosphatase is an in vitro assay that correlates with ERα-mediated uterine stimulation, (Holinka et al., 1986) a hallmark of tissue-specific SERM partial agonist activities. We measured the abilities of E2, 4OHT, Z-endoxifen, ICI, Laso, LA-Stab, and LA-Deg to induce alkaline phosphatase in Ishikawa uterine epithelial cells using previously published methods (Fanning et al., 2018a). Figure 6 shows the measured AP assay dose-response curves. 1 nM E2 induced the greatest AP response followed by LA-Stab, 4OHT, Z-endoxifen, and Laso. LA-Deg showed a slightly increase induction compared to ICI and Veh, but it was significantly lower than Laso. Figure 6—source data 1 shows a table of the EC50 and maximum absorbance for these assays. Together, these data suggest that the SERM-like effects on ERα accumulation observed for LA-Stab correlate to an increased stimulation of ERα-activities in uterine cells, while, modest ERα-degradation by LA-Deg was sufficient to prevent uterine stimulation.
We used label-free cell counting to determine whether induction of ERα degradation improved anti-proliferative outcomes in MCF7 cells with heterozygous WT/Y537S ESR1. This model was chosen because it shows the greatest resistance to inhibition by antiestrogens (Toy et al., 2013). Cells were treated with 4OHT, fulvestrant, Laso, LA-Stab, or LA-Deg at 1 nM, 50 nM, and 1 μM in the presence of 1 nM E2 alongside vehicle (DMSO) and 1 nM E2-only controls. Subsequently, cells were counted every 6 hr for 84 hr. The experiment was halted when cells in the E2-treated well reached 100% confluence. All treatments were performed with three biological replicates and a total of 9 technical replicates per ligand per concentration. Figure 7 shows the proliferation data and a summary of results. As expected, addition of 1 nM E2 enhanced cell proliferation. No compound completely abrogated proliferation, even at the highest dose. Every compound shows similar efficacies at the maximum 1 μM dose, although LA-Deg and LA-Stab appear slightly improved and closest to veh levels. However, differences were not statistically significant compared to the other molecules at the maximal dose. Fulvestrant and Laso on the other hand show improved efficacies at the 1 nM and 50 nM doses compared to the other molecules. Together, these data show that induction of ERα degradation does not by itself predict the anti-proliferative activities of an antiestrogen in this cell model.
We solved x-ray crystal structures of antiestrogens in complex with Y537S and WT ERα ligand binding domain (LBD) to understand the structural basis of differential transcriptional antagonistic efficacies. We solved x-ray crystal structures for BZA, RAL, 4OHT, LA-Deg, LA-Stab, RU39411 and LSZ102 in complex with the Y537S mutant. We also solved structures with the WT LBD for those molecules with no existing structures (LA-Deg, LA-Stab, RU39411) or were able to solve to improved resolution (RAL). We were unable to solve x-ray crystal structures for antagonists in complex with the D538G mutant, despite earlier success with 4OHT (Jeselsohn et al., 2018). Overall, these structures present canonical ERα LBD homodimers with 2–4 monomers in the asymmetric unit. As with other ERα LBD structures, these show significant crystal contact influences at H12 of one monomer but not the other, namely a contact at or near 538 that affects the positioning of 537 (Figure 8—figure supplement 1). For analysis purposes, we have named the monomer free of H12 free of crystal contacts ‘Chain A’.
Enforcing WT Antagonist Conformation Enables Efficacious Transcriptional Inhibition of Y537S ERα. RAL, BZA, and RU39411 showed the greatest efficacy of transcriptional inhibition in MCF7 cells with WT/Y537S ESR1. Laso, LA-Stab, and LA-Deg showed significant but reduced efficacy. 4OHT and LSZ102 were the least effective. Figure 8 shows a structural analysis for RAL and 4OHT, which are representative of the most and least effective molecules in WT/Y537S ESR1 MCF7 cells. In the most effective molecules (BZA, RAL, and RU39411), superposition of all monomers of WT and Y537S structures, based on alpha carbon positions, shows that H12 maintains a conserved AF-2 antagonist conformation that is well ordered in the AF2 cleft regardless of mutation (Figure 8A/B). In addition, a new hydrogen bond is observed between S537 and E380 (Figure 8C), which was previously computationally predicted for the Y537S-BZA structure (Fanning et al., 2018b). This hydrogen bond is not observed in monomers where crystal packing forms a hydrogen bond between D538 and a symmetry mate arginine, pulling 537 S away from E380 (Figure 8—figure supplement 1). Laso, LA-Stab, and LA-Deg showed intermediate efficacy. In these Y537S structures, H12 is slightly more dynamic and the S537-E380 hydrogen bond is no longer observed. 4OHT and LSZ102 were the least effective molecules. Both show significant Y537S H12 conformational changes, are significantly less ordered in the AF2 cleft, and no S537-E380 hydrogen bond is observed (Figure 8D–F).
Reduced Y537S efficacy correlates with decreased H12 surface area burial in the AF-2 Cleft. As H12 showed improved AF-2 cleft packing in the Y537S structures with the most effective molecules, we performed B-factor analysis to understand whether higher B-factors correlated with reduced anti-transcriptional efficacy. Indeed, the least effective molecules (4OHT and LSZ102) possess greater main-chain H12 B-factors (normalized to all main chain atoms) indicating a relatively poor packing in the AF-2 cleft compared to more effective molecules (Figure 8—figure supplement 2). We further calculated H12 buried surface area (BSA) Y537S LBD using proteins, interfaces, structures, and assemblies (Krissinel and Henrick, 2005) and found it correlates with transcriptional antagonism. BZA, RAL, and RU39411 show the greatest burial at 379.75, 377.87, and 325.21 Å (Maximov et al., 2018) respectively. Molecules with reduced potencies showed reduced BSA at 245.57, 56.13, 27.62, and 14.69 Å (Maximov et al., 2018) for LA-Stab, LSZ-102, LA-Deg, and 4OHT respectively. Together these structures show that SERMs, SERM/SERDs, or SERDs that favor H12 packing in the AF-2 cleft and promote an S537-E380 hydrogen bond and achieve the greatest anti-transcriptional efficacies in MCF7 breast cancer cells that harbor WT/Y537S ERα.
We show here how chemical manipulation of ERα H12 conformation and mobility can be used to tune receptor lifetime in live cells. SERMs extend ERα lifetime, increase receptor accumulation, and are antagonists in the breast and agonists in the bone and uterine epithelium (Fanning and Greene, 2019). Tissue-specific partial agonist activities stem from SERM inhibition of Activating Function-2 (AF-2) but not AF-1 genomic activities (Shang and Brown, 2002). SERDs decrease the quantity and lifetime of ERα in the cell and are pure antagonists by effectively prohibiting ERα transcriptional activities. Activating somatic mutations near ERα helix 12, Y537S and D538G, enable hormone therapy resistance in metastatic ER +breast cancers (Toy et al., 2013; Jeselsohn et al., 2014). Antiestrogens with improved potencies including bazedoxifene, fulvestrant, OP-1074 and GDC-0945 possess variable degrees of ERα degrading/downregulating activities but show significant potencies and efficacies in mutant ESR1 breast cancer cells (Toy et al., 2013; Metcalfe et al., 2019; Fanning et al., 2018a). Initial studies suggested that SERD activity was necessary for therapeutic potency (Toy et al., 2013); however, Lainé et al. showed that the SERM Laso induced marked anti-cancer activities in xenografts of Y537S ESR1 breast cancer cells without fulvestrant-level ERα degradation (Lainé et al., 2021). In addition, Wardell et al., 2020 concluded that antagonism rather than ERα degradation/downregulation drives most of fulvestrant efficacy in suppressing primary tumor growth in xenograft assays, based on observations that a dose of fulvestrant affording a non-significant reduction in ER levels led to significant growth suppression of a long-term estrogen-deprived breast cancer cell model over 4 weeks (). This is supported by observation in cell lines that fulvestrant retains transcriptional inhibition properties upon increases in ERα concentrations that lead to saturation of degradation. (Lupien et al., 2007) Based on this work, we examined the contribution of SERD activity to the potency and efficacy of transcriptional suppression by antiestrogens in breast cancer cells harboring Y537S or D538G ESR1. To understand whether chemical manipulation of ERα cellular lifetime correlates with improved antagonistic activities, we synthesized methylated derivatives of Laso that uniquely influence receptor cellular lifetime and accumulation. We compared these molecules to a comprehensive panel of SERMs, SERM/SERDs and SERDs for their effects on WT and mutant ERα cellular stability and transcriptional activity in breast cancer cells.
To quantify the influence of antiestrogens on ERα cellular lifetime, we developed a high-throughput system to observe WT, Y537S, or D538G ERα expression in living T47D breast cancer cells. Because induction of ERα modifications may take place even when degradation is absent, we also quantified differences in ERα SUMOylation, a post-translational modification that is induced by fulvestrant together with ubiquitination and that influences interaction with DNA and transcriptional activity in ER +MCF7 cells (Traboulsi et al., 2019). We discovered that addition of a 3R-methyl group on Laso’s pyrrolidine induced both ERα SUMOylation and degrading activities, while addition of a 2S-methyl on the pyrrolidine leads to an accumulation of ERα in the breast cancer cells.
This approach also revealed an unexpected effect of each mutant on ERα expression and cellular lifetime. Most SERD molecules exhibited diminished capacities to affect Y537S ERα levels compared to WT. Two carboxylic acid-containing SERD molecules AZD9496 and LSZ102 unexpectedly switched to stabilizing Y537S, similar to 4OHT. Of note, AZD9496 did not induce SUMOylation with WT ERα, in keeping with a different conformation of the receptor observed in carboxylic acid-containing antiestrogens. Apart from this discrepancy, the general good degree of correlation between the impact of antiestrogens on SUMOylation of WT or mutant ER and their impact on receptor lifetime suggests either a cross-talk between SUMOylation and ubiquitination, possibly mediated by SUMO targeted ubiquitin ligases (STUbLs) such as RNF4, or similar structural determinants for addition of either marks by their respective enzymatic complexes. It will therefore be of interest in the future to explore whether carboxylic acid-containing antiestrogens selectively induce increased receptor ubiquitination, or lead to degradation by other mechanisms.
We were surprised that the Y537S mutant showed nearly identical unliganded/apo and E2-treated profiles, with enhanced cellular expression in the presence hormone to similar levels as WT in the absence of hormone. In addition to constitutive transcriptional activities and resistance to inhibition by tamoxifen, the Y537S also likely contributes to breast cancer pathology through increasing the quantity of active receptor in the cell. The D538G mutant was also surprising because it dampened the influence of SERDs on ERα SUMOylation, accumulation, and lifetime. It suppressed the stabilizing effects of SERMs on WT ERα, correlating with induction of weak SUMOylation of the D538G mutant but not WT receptor. The D538G ESR1 mutant occurs with the greatest frequency in patients (Chandarlapaty et al., 2016) but its selective advantage has remained unclear. Our studies suggest that the diminished ability of cells to degrade D538G ERα coupled with its low-level constitutive transcriptional activities contributes a pathological advantage within the tumor in the presence of first-line endocrine therapies. Further studies will reveal whether these alterations to ERα lifetime influence breast cancer pathological endpoints and therapeutic response.
Transcriptional reporter gene assays in MCF7 cells harboring WT, WT/Y537S, or WT/D538G ESR1 were used to understand whether the degrees of ERα degradation and/or SUMOylation correlated with transcriptional inhibitory activities. We identified antiestrogens across the SERM-SERD spectrum that demonstrated significantly improved transcriptional repressive activity over 4OHT in these cells. Interestingly, RU39411, which significantly enriched ERα levels (SERM-like), showed enhanced transcriptional inhibition compared to most molecules. Despite their unique influences on WT ERα cellular stability, the methylated Laso derivatives showed identical transcriptional antagonistic efficacies in the WT and mutant cell lines compared to unmodified Laso in our assay.
Alkaline phosphatase activities in Ishikawa uterine cell lines were used to understand whether observed SERM or SERD influences on ERα degradation correlated with receptor-dependent uterotrophic activities. Here, the SERM-like LA-Stab showed a robust induction of AP activity, but not to the extent of 4OHT or Z-endoxifen. Laso showed a modest induction and LA-Deg showed no induction of AP activity. Surprisingly, 4OHT was more uterotrophic than Z-endoxifen, another tamoxifen metabolite. These results suggest that Z-endoxifen is less SERM-like that 4OHT and may explain its improved efficacy in letrazole-resistant models of ER +breast cancer (Jayaraman et al., 2020).
Cellular proliferation assays in MCF7 cells with WT/Y537S ESR1 were used to reveal the role of ERα degradation in anti-proliferative activities. We showed that 4OHT, fulvestrant, Laso, LA-Deg, and LA-Stab can reduce E2-stimulated proliferation. Fulvestrant and Laso show improved efficacies at lower concentrations, while LA-Stab and LA-Deg did not show improved anti-proliferative activities. However, no molecule completely repressed the proliferation of these cells. Our BRET, transcription, and proliferation data are consistent with our observations that SERMs have similar efficacies at suppressing cofactor recruitment in WT and ESR1mut cells. Together, these data suggest that SERM or SERD influences on ERα cellular lifetime may not directly correlate with transcriptional antagonistic and anti-proliferative activities of ESR1 mutant breast cancer cells. Rather, engineered chemical reduction of ERα cellular accumulation is critical for tuning tissue- and gene-specific agonistic/partial agonistic activities (Fanning and Greene, 2019) and preventing AF-1 dependent mechanisms of endocrine resistance (Massarweh et al., 2008).
X-ray crystal structures of WT and Y537S ERα LBD in complex with SERMs, SERM/SERDs, and a SERD showed that the most efficacious molecules enforced H12 burial within the AF-2 cleft. We previously showed that BZA resisted the impact of the Y537S mutation on its antagonist H12 conformation, which was perturbed for the less effective 4OHT (Fanning et al., 2018b). Of the structures, RU39411 (SERM), RAL (SERM/SERD), and BZA (SERM/SERD) demonstrated the greatest transcriptional inhibitory efficacies in WT/Y537S ESR1 MCF7 cells. These molecules engaged a new S537-E380 hydrogen bond that enforced a well-ordered antagonistic H12 conformation that corresponded to significant surface area burial within the AF-2 cleft. Conversely, molecules with diminished Y537S transcriptional potencies poorly enforced this conformation as H12 showed variable conformations and reduced surface area burial in the AF-2 cleft.
Overall, our studies show how minor chemical modifications lead to switches in ERα stabilizing or degrading activities onto an antiestrogen scaffold, likely via modulation of ERα post-translational modification. While these activities may not confer an antagonistic benefit in breast cancer cells, they are important drivers of AF-1 mediated tissue-specific activities (Shang and Brown, 2002). ERα proteolysis is critical to normal activity and E2 binding induces phosphorylation at position Y537, which recruits E3 ubiquitin ligases (Sun et al., 2012). Therefore, further understanding of the role played by Y537 phosphorylation in ERα SERM or SERD antagonism in breast cancer cells requires further study. Importantly, we showed that SERMs and SERDs differentially affect Y537S H12 binding in the AF-2 cleft. SERDs, like fulvestrant, increase H12 conformational mobility (Fanning et al., 2018b; Pike et al., 2001) and enhance binding of corepressor proteins such as NCOR (Webb et al., 2003) that are important contributors to anti-cancer activities. Therefore, it is likely that SERMs and SERDs differentially affect the repertoire of coregulator proteins that associate with Y537S ERα and contribute to anti-cancer activities. Revealing these changes will be critical for developing new competitive antiestrogens that maintain activities in the presence of Y537S and D538G ESR1 mutations.
MCF-7 and T47D cells were purchased directly from ATCC. MCF7 WT/Y537S cells were generously donated by Dr Ben Ho Park. MCF-7 cells were cultured in DMEM supplemented with 10% FBS and 1% penicillin-streptomycin. T47D cells were cultured in RPMI supplemented with 10% FBS and 1% penicillin-streptomycin. Cells were STR profiled to confirm identify and routinely subjected to mycoplasma testing.
T47D cells with stable TetON HT WT, Y537S, or D538G ERα were plated in a 6 well dish at a density of 15,000 and 30,000 cells, respectively. These cells were cultured for 48 hr in phenol-free media supplemented with charcoal-stripped FBS in puromycin. Following this incubation, 1 µg/mL dox and 1 µM G618 were added to each well. Cells were then treated with increasing concentrations of our compounds of interest (0.00512, 0.0256, 0.128, 0.64, 3.2, 16, 80, 400, 2000, and 5000 nM) for 24 hr. After treatment, the cells were imaged using an Incucyte S3. ER degradation was quantified by using the red channel integrated intensity per image normalized to the phase channel confluence area. Assays were performed twice with three technical replicates each.
was prepared starting from 4-bromophenol in four steps according to a literature procedure with slightly modification (Simpson et al., 1987).
Figure 9 shows the synthetic route used to generate the Laso analogs. A mixture of 4-bromophenol (40.0 g, 231 mmol), ethylene carbonate (38.0 g, 432 mmol) and K2CO3 (68.0 g, 492 mmol) in DMF (200 mL) was heated for 36 hr at 100 °C and then cooled. The reaction mixture was poured into water (500 mL), extracted with ether (3 × 400 mL) and the combined organic layers was washed with 5% NaOH (250 mL), brine and dried over Na2SO4. The solid was filtered off and the solvent was removed by rotary evaporator under reduced pressure to give 2-(4-bromophenoxy)ethanol (2) as colorless solid (49.5 g, 99% yield). 1H NMR (CDCl3/TMS) δ7.37 (m, 2 H), 6.79 (m, 2 H), 4.04 (m, 2 H), 3.96 (m, 2 H), 2.14 (t, 1 H, J = 6.0 Hz); 13C NMR (CDCl3) δ157.9, 132.5, 116.5, 113.4, 69.5, 61.5 ppm.
Under argon to the solution of 2 (48.8 g, 225 mmol) in dry DMF (650 mL), NaH (95%, 8.53 g, 338 mmol) was added at 0 °C. After stirred at rt for 30 min, tetra-n-butylammonium iodide (872 mg, 2.36 mmol) and benzyl chloride (29.9 g, 236 mmol) was added. The reaction mixture was stirred at rt overnight and then quenched with saturated aqueous ammonium chloride (150 mL). The product was extracted with dichloromethane (4 × 100 mL). The combined organic layers were washed with brine and dried over Na2SO4. The solvent was removed and the residue was purified by silica gel chromatography, eluting with 10% ethyl acetate to give 4-[2-(benzyloxy) ethoxy] bromobenzene (3) (57.7 g, 74% yield). 1H NMR (CDCl3/TMS) δ7.37–7.28 (m, 7 H), 6.81 (m,2H), 4.63 (s, 2 H), 4.11 (m, 2 H), 3.82 (m, 2 H); 13C NMR (CDCl3) δ158.1, 138.1, 132.4, 128.6, 127.9, 116.6, 113.2, 73.6, 68.5, 67.8 ppm.
Under argon a mixture of 3 (28 g, 91.2 mmol) and magnesium turnings (2.32 g, 95.8 mmol) in THF (300 mL) was heated under reflux for 24 h with the addition of several iodine particles to initiate the reaction. The solution was cooled to rt and 6-methoxy-3,4-dihydronaphthalen-1(2 H)-one (11.7 g, 66.4 mmol) in THF (100 mL) was added dropwise. After the reaction mixture was stirred at rt for 20 hr, the reaction was quenched with 5% HCl (100 mL). The product was extracted with ether, dried over Na2SO4. The solvent was removed, the residue was isolated by silica gel chromatography, eluting with 10% ethyl acetate in hexane to give 1-[4-(2-benzyloxy)ethoxy]phenyl-6-methoxy-3,4-dihydronaphthalene (4) as light-yellow oil (13.9 g, 54% yield). 1H NMR (CDCl3/TMS) δ7.40–7.20 (m, 7 H), 7.00–6.90 (m, 3 H), 6.76 (d, 1 H, J = 2.4 Hz), 6.63 (dd, 1 H, J = 8.6, 2.6 Hz), 5.91 (t, 1 H, J = 4.4 Hz), 4.65 (s, 2 H), 4.18 (m, 2 H), 3.85 (m, 2 H), 3.79 (s, 3 H), 2.81 (t, 2 H, J = 8.0 Hz), 2.36 (m, 2 H); 13C NMR (CDCl3) δ158.6, 158.1, 139.0, 138.8, 138.2, 133.7, 129.8, 128.6, 127.92, 127.85, 126.7, 124.6, 114.5, 113.9, 110.8, 73.5, 68.7, 67.6, 55.4, 29.0, 23.6 ppm.
Bromine (2.0 mL, 39.5 mmol) was added slowly to the solution of 4 (13.87 g, 35.9 mmol) in THF (120 mL) at 0 °C. After 5 min, triethylamine (5.5 mL, 39.5 mmol) was added while the mixture was stirred vigorously. The reaction mixture was stirred at rt for 10 min. The reaction mixture was washed with 5% Na2S2O3, extracted with ether, washed with brine and dried over Na2SO4. The solvent was removed and the residue was isolated by silica gel chromatography, eluting with 10% ethyl acetate in hexane to give 1-[4-(2-benzyloxy)ethoxy]phenyl-2-bromo-6-methoxy-3,4-dihydronaphthalene (5) as brown solid (15.6 g, 94% yield). 1H NMR (CDCl3/TMS) δ7.40–7.24 (m, 5 H), 7.15–7.10 (m, 2 H), 7.00–6.94 (m, 2 H), 6.70 (d, 1 H, J = 2.4 Hz), 6.60–6.50 (m, 2 H), 4.66 (s, 2 H), 4.20 (m, 2 H), 3.87 (m, 2 H), 3.77 (s, 3 H), 2.95 (m, 4 H); 13C NMR (CDCl3) δ158.8, 158.1, 138.2, 137.6, 136.2, 132.4, 131.0, 129.4, 128.6, 127.92, 127.85, 127.5, 120.7, 114.5, 113.7, 110.0, 73.5, 68.7, 67.5, 55.4, 35.2, 30.1 ppm.
Under argon a mixture of 4 (3.84 g, 8.25 mmol), phenylboronic acid (1.11 g, 9.1 mmol), Pd(PPh3)4 (286 mg, 0.247 mmol) and potassium carbonate (2.28 g, 16.5 mmol) in dry THF (100 mL) was stirred at reflux for 24 h. After the mixture was cooled down, water (30 mL) was added. The organic layer was separated. The aqueous layer was extracted with ether, washed with brine. The organic layers were combined and dried over Na2SO4. The solvent was removed, the residue was isolated by silica gel chromatography, eluting with 10% ethyl acetate in hexane to give 6 (3.55 g, 93% yield). 1H NMR (CDCl3/TMS) δ7.40–7.20 (m, 6 H), 7.15–6.90 (m, 6 H), 6.82–6.78 (m, 3 H), 6.74 (d, 1 H, J = 8.8 Hz), 6.60 (dd, 1 H, J = 8.8, 2.8 Hz), 4.66 (s, 2 H), 4.13 (m, 2 H), 3.83 (m, 2 H), 3.82 (s, 3 H), 2.95 (m, 2 H), 2.79 (m, 2 H); 13C NMR (CDCl3) δ158.5, 157.5, 143.4, 138.2, 137.8, 134.9, 134.4, 132.4, 132.2, 130.6, 128.5, 128.4, 127.9, 127.8, 127.7, 127.6, 125.8, 114.2, 113.3, 110.9, 73.5, 68.6, 67.4, 55.4, 30.9, 29.1 ppm.
To the solution of 6 (3.47 g, 7.5 mmol) in a mixed solvent of ethanol/ethyl acetate (2/1, v/v, 150 mL), palladium hydroxide on carbon (20% wt., 263 mg, 0.375 mmol) was added. After exchange the air with argon, the mixture was then stirred under a hydrogen balloon overnight. TLC showed no starting material left. The catalyst was filtered off. The solvent was removed and the residue was isolated by silica gel chromatography, eluting with 20% ethyl acetate in hexane to give 7 as a white foam (2.105 g, 75% yield). 1H NMR (CDCl3/TMS) δ7.15–7.05 (m, 3 H), 6.85–6.70 (m, 4 H), 6.63 (dd, 1 H, J = 8.4, 2.8 Hz), 6.49 (d, 2 H, J = 8.8 Hz), 6.30 (d, 2 H, J = 8.4 Hz), 4,21 (d, 1 H, J = 6.0 Hz), 3.83 (m, 2 H), 3.79 (m, 2 H), 3.73 (s, 3 H), 3.32 (m, 1 H), 3.02 (m, 2 H), 2.89 (brs, 1 H), 2.14 (m, 1 H), 1.78 (m, 1 H); 13C NMR (CDCl3) δ157.7, 156.6, 144.2, 137.6, 134.9, 132.1, 131.4, 131.3, 128.1, 127.6, 125.9, 112.84, 112.82, 112.5, 68.9, 61.1, 55.0, 50.1, 45.3, 30.0, 21.8 ppm. HRMS calcd for C25H30NO3 [MNH4+] 392.2226, found 392.2222.
Triethylamine (0.63 mL, 4.52 mmol) was added to a solution of 7 (848 mg, 2.26 mmol) and MsCl (0.35 mL, 4.52 mmol) in THF (25 mL) at 0 °C. The reaction mixture was stirred at rt for 1 hr. The reaction was quenched with water, extracted with ethyl acetate, and dried over MgSO4. The solvent was removed and the residue was purified by silica gel chromatography, eluting with 20% ethyl acetate in hexane to give the mesylate 8 (0.90 g, 94% yield). 1H NMR (CDCl3/TMS) δ7.18–7.10 (m, 3 H), 6.85–6.70 (m, 4 H), 6.66 (dd, 1 H, J = 8.4, 2.4 Hz), 6.50 (d, 2 H, J = 8.4 Hz), 6.33 (d, 2 H, J = 8.4 Hz), 4,44 (m, 2 H), 4.23 (d, 1 H, J = 4.8 Hz), 4.05 (m, 2 H), 3.78 (s, 3 H), 3.36 (m, 1 H), 3.06 (m, 2 H), 2.99 (s, 3 H), 2.16 (m, 1 H), 1.82 (m, 1 H); 13C NMR (CDCl3) δ157.9, 156.0, 144.2, 137.8, 135.7, 132.0, 131.50, 131.45, 128.1, 127.8, 126.0, 113.0, 112.9, 112.6, 68.3, 65.6, 55.2, 50.2, 45.3, 37.6, 30.1, 21.9 ppm. HRMS calcd for C26H28O5SNa [MNa+] 475.1555, found 475.1550.
The synthesis of 9 a is representative: To the solution of 8 (85 mg, 0.20 mmol) in anhydrous DMF (5 mL), (3 R)–3-methylpyrrolidine-HCl salt (242 mg, 2.0 mmol) and i-Pr2NEt (700 uL, 4.0 mmol) were added. After the mixture was stirred at 80 °C for 24 h, TLC showed the reaction was completed. The solvent was removed, and the residue was dissolved into ether, washed with saturated NaHCO3, brine, and dried over Na2SO4. After filtration, the solvent was removed, the residue was dried under vacuum overnight, and then redissolved into dry dichloromethane (10 mL). Under argon the dichloromethane solution was cooled to –78 °C. BBr3 (1.0 M in CH2Cl2, 2.0 mL, 2.0 mmol) was added. After the reaction mixture was warmed and stirred at 0 °C for 2 h, the reaction was quenched with Na2S2O3 solution at 0 °C. The mixture was basified with 2 N NaOH. extracted with CH2Cl2, washed with brine and dried over MgSO4. The solvent was removed, the residue was purified by silica gel chromatography, eluting with 4% methanol in dichloromethane containing 1% triethylamine to give product 9 a (31 mg, 36% yield). (Burstein et al., 2019) H NMR (CDCl3/TMS) δ7.15 (m, 3 H), 6.80–6.62 (m, 4 H), 6.58 (dd, 1 H, J = 8.4, 2.4 Hz), 6.42 (m, 2 H), 6.26 (m, 2 H), 4.19 (d, 1 H, J = 5.2 Hz), 3.98 (m, 2 H), 3.35 (m, 1 H), 3.15–2.55 (m, 7 H), 2.45–2.25 (m, 1 H), 2.25–2.05 (m, 3 H), 1.76 (m, 1 H), 1.42 (m, 1 H), 1.05 (d, 3 H, J = 6.8 Hz); 13C NMR (CDCl3) δ156.7, 155.4, 144.6, 137.6, 135.0, 131.5, 131.3, 130.8, 128.30, 127.8, 126.0, 115.15, 115.12, 114.2, 112.8, 65.8, 62.5, 62.3, 55.5, 54.6, 54.4, 50.3, 45.5, 32.43, 32.39, 31.9, 31.8, 30.0, 22.0, 19.9 ppm; HRMS calcd for C29H34NO2 [MH+] 428.2590 found 428.2590. HPLC analysis and purification with Chiral pack IBN-3 column, 0.75 mL/min, mobile phase: 0.1% Et2NH in MeOH. UV 279 nm, 9 a-1, retention time 8.05 min, 9 a-2, retention time 9.62 min.
9b (30 mg, 35% yield) was prepared from 8 (85 mg, 0.20 mmol), (3 S)–3-methylpyrrolidine-HCl salt (121 mg, 1.0 mmol) and i-Pr2NEt (348 μL, 2.0 mmol) according to the typical procedure: (Burstein et al., 2019) H NMR (CDCl3/TMS) δ7.14 (m, 3 H), 6.80–6.62 (m, 4 H), 6.55 (dd, 1 H, J = 8.4, 2.8 Hz), 6.37 (d, 2 H, J = 8.8 Hz), 6.26 (d, 2 H, J = 7.6 Hz), 4.19 (d, 1 H, J = 4.8 Hz), 3.96 (m, 2 H), 3.35 (m, 1 H), 3.15–2.75 (m, 6 H), 2.60 (m, 1 H), 2.40–2.25 (m, 1 H), 2.20–2.00 (m, 3 H), 1.75 (m, 1 H), 1.40 (m, 1 H), 1.05 (d, 3 H, J = 6.8 Hz); 13C NMR (CDCl3) δ156.8, 155.5, 144.7, 137.6, 134.9, 131.6, 131.4, 130.7, 128.4, 127.8, 126.0, 115.23, 115.18, 114.3, 112.8, 65.9, 62.6, 62.4, 55.63, 55.60, 54.6, 54.4, 50.3, 45.6, 32.51, 32.45, 31.9, 31.8, 30.1, 22.0, 20.1, 20.0 ppm; HRMS calcd for C29H34NO2 [MH+] 428.2590 found 428.2589. HPLC analysis with Chiral pack IBN-3 column, 0.75 mL/min, mobile phase: 0.1% Et2NH in EtOH. UV 279 nm, 9b-1, retention time 5.87 min, 9b-2, retention time 6.67 min.
9 c (52 mg, 53% yield) was prepared from 8 (100 mg, 0.23 mmol), (2 R)–2-methylpyrrolidine-HCl salt (280 mg, 2.3 mmol) and i-Pr2NEt (800 uL, 4.6 mmol) according to the typical procedure: 1H NMR (CDCl3/TMS) δ7.15 (m, 3 H), 6.80–6.62 (m, 4 H), 6.55 (m, 1 H), 6.46 (d, 1 H, J = 8.4 Hz), 6.41 (d, 1 H, J = 8.8 Hz), 6.27 (m, 2 H), 4.19 (d, 1 H, J = 4.8 Hz), 3.98 (m, 2 H), 3.35–3.15 (m, 3 H), 3.02–2.90 (m, 2 H), 2.50–2.40 (m, 2 H), 2.29 (m,1H), 2.20–2.00 (m, 1 H), 2.00–1.90 (m, 1 H), 1.90–1.60 (m, 3 H), 1.55–1.40 (m, 1 H), 1.19 (m, 3 H); 13C NMR (CDCl3) δ156.8, 155.3, 155.2, 144.63, 144.60, 137.7, 135.0, 134.9, 131.6, 131.5, 131.4, 131.0, 130.8, 128.32, 128.29, 127.8, 126.0, 115.3, 115.2, 114.4, 114.2, 112.9, 112.8, 66.4, 66.2, 61.1, 60.9, 54.5, 54.4, 53.0, 50.3, 45.6, 32.33, 32.26, 30.1, 22.0, 21.8, 21.7, 18.5, 18.4 ppm.; HRMS calcd for C29H34NO2 [MH+] 428.2590 found 428.2591. HPLC analysis with Chiral pack IBN-3 column, 0.75 mL/min, mobile phase: 0.1% Et2NH in EtOH. UV 279 nm, 9 c-1, retention time 5.88 min, 9 c-2, retention time 6.57 min.
9d (59 mg, 60% yield) was prepared from 8 (100 mg, 0.23 mmol), (2 S)–2-methylpyrrolidine-HCl salt (280 mg, 2.3 mmol) and i-Pr2NEt (800 μL, 4.6 mmol) according to the typical procedure: (Burstein et al., 2019) H NMR (CDCl3/TMS) δ7.15 (m, 3 H), 6.80–6.62 (m, 4 H), 6.55 (m, 1 H), 6.47 (d, 1 H, J = 8.8 Hz), 6.42 (d, 1 H, J = 8.8 Hz), 6.28 (m, 2 H), 4.19 (d, 1 H, J = 4.8 Hz), 3.98 (m, 2 H), 3.40–3.15 (m, 3 H), 3.02–2.90 (m, 2 H), 2.50–2.40 (m, 2 H), 2.26 (m, 1H), 2.20–2.15 (m, 1 H), 2.00–1.87 (m, 1 H), 1.87–1.60 (m, 3 H), 1.55–1.40 (m, 1 H), 1.16 (m, 3 H); 13C NMR (CDCl3) δ156.8, 155.31, 155.26, 144.62, 144.60, 137.71, 137.69, 135.0, 134.9, 131.6, 131.5, 131.3, 130.9, 130.8, 128.30, 128.28, 127.8, 126.0, 115.3, 115.2, 114.4, 114.3, 112.9, 112.8, 66.5, 66.3, 61.0, 60.8, 54.6, 54.4, 53.0, 50.3, 45.6, 32.34, 32.28, 30.1, 22.0, 21.8, 21.7, 18.6, 18.4 ppm; HRMS calcd for C29H34NO2 [MH+] 428.2590 found 428.2591. HPLC analysis and purification with Chiral pack IBN-3 column, 0.75 mL/min, mobile phase: 0.1% Et2NH in MeOH. UV 279 nm, 9d-1, retention time 7.94 min, 9d-2, retention time 9.11 min.
HEK293 HTS cells were maintained at 37 degree celsius in Dulbecco’s modified Eagle’s medium (DMEM) (Wisent) supplemented with 10% fetal bovine serum (FBS) (Sigma), 2% L-glutamine (Wisent) and 1% penicillin-streptomycin (Wisent). Two days prior to transfection, HEK293 HTS cells were washed twice in PBS and seeded in 15 cm petri dishes at a density of 5×106 in phenol red-free DMEM supplemented with 1charcoal-stripped FBS (Sigma) and 1% penicillin-streptomycin. Forty-eight hr later, cells were co-transfected with expression plasmids for WT, Y537S, or D538G ERα fused to RlucII and YFP-SUMO3 (Hilmi et al., 2012; Cotnoir-White et al., 2018) or SRC1/NCOA1 RID-Topaz YFP (Liao et al., 2002). Transfections were performed using linear polyethylenimine (Polysciences Inc) at a ratio of 3 μg of PEI to 1 μg of DNA per 1.25×106 cells and aliquoted at 125,000 cells per well in white 96 well assay plates (Corning). BRET assays were carried out 48 h post-transfection by replacing cell media by 1 x HBSS (Wisent) supplemented with 4.5 g/L dextrose and either compounds or vehicle and incubating for 2–3 h at 37 degree celsius. For dose-response experiments, compounds were serially diluted 1:3 in 1 x HBSS from a maximum concentration of 9 μM. Coelenterazine H (Nanolight Technologies) was added to a final concentration of 5 μM and readings were taken following a 5 min incubation at room temperature using a Mithras LB 940 microplate reader (Berthold Technologies). Net BRET ratios were calculated as described previously (Hilmi et al., 2012). All experiments were performed with three to five biological replicates comprised of three technical replicates each. Best-fit EC50 and BRETMax values were determined with Prism. Curves represent average values +/-SEM.
MCF-7 cells with WT, WT/Y537S, and WT/D538G with a 3×-ERE-GFP reporter gene construct with a CMV promoter were plated in a 6 well dish at a density of 15,000 and 30,000 cells, respectively. Cells were cultured for 48 hr in media supplemented with charcoal-stripped FBS. Subsequently, cells were treated with increasing concentrations of compounds of interest (0.00512, 0.0256, 0.128, 0.64, 3.2, 16, 80, 400, 2000, and 5000 nM) for 48 hr. After treatment, the cells were imaged using an Incucyte S3. ERE transcriptional response was quantified by using the green channel integrated intensity per image normalized to the phase channel confluence area. Assays were performed twice with three technical replicates each.
This assay was performed with Ishikawa cells exactly as previously described (Fanning et al., 2018a). Briefly, approximately 15,000 Ishikawa cells were plated onto a 96-well plate in serum starved media. After 4 hr, cells were treated with vehicle, hormone, SERM, or SERD. Cells were incubated for 72 hr, media removed, and frozen at –80 °C for at least 12 hr. Thawed plates were incubated with p-nitrophenyl phosphate (NEB, #P0757L) for 1–3 hr at 37 °C. Absorbance was read at 405 nm on a BioTek Cytation 5 plate reader. These assays were performed three independent times with three technical replicates each.
A BioTek Cytation 5 with BioSpa was used for automatic cell counting experiments. MCF7 WT/Y537S cells were plated in 96-well plates at 750 cells per well in phenol-free medium. After 24 hr, cells placed in charcoal-stripped FBS and allowed to acclimate for 48 hr. Subsequently, cells were treated with 1, 50, and 1000 nM antiestrogen and 1 nM E2 then placed in the BioSpa. Cells were automatically imaged by bright-field and phase contrast every 6 hr for a total of 84 hr. Cell counts were analyzed using the label-free cell counting protocol on BioTek Gen5 software. These assays were performed three independent times with three technical replicates each.
A gene containing a hexa-His-TEV fusion of the ERα LBD, residues 300–550 with C381S, C417S, C530S, and L536S in pET21(a)+was used for all WT ERα LBD x-ray crystal structures, as this construct enables the adoption of a canonical antagonist conformation of the receptor (Fanning et al., 2018a). An identical construct with but with an intact 536 L and Y537S was generated using Q5 site-directed mutagenesis (Promega) and was used for all Y537S x-ray crystal structure determinations. E. coli BL21(DE3) were used for all recombinant protein expression. An overnight culture at 37 °C was inoculated with a single colony in 50 mL LB broth containing 100 μg/mL ampicillin. 5 mL of the overnight culture was used to inoculated each of 10 L of LB-ampicillin, which were allowed to grow at 37 °C with shaking until an OD600 = 0.6 was reached, indicating log-phase growth. Protein expression commenced upon the addition of 0.3 mM IPTG and continued overnight at 16 °C. Cells were harvested by centrifugation at 4000 g for 15 min. Cells were resuspended in 5 mL/g cell paste in 50 mM HEPES pH 8.0, 250 mM NaCl, 20 mM imidazole pH 8.0, 0.5 mM TCEP, and 5% glycerol with the addition of 1 EDTA-free cOmplete protease inhibitor cocktail tablet per 50 mL lysate (Roche). Cells were lysed by sonication on ice with stirring and the lysates were clarified by centrifugation at 20,000 g for 30 min at 4 °C. The clarified lysate was loaded onto 2.5 mL of pre-equilibrated Ni-NTA resin and washed with 5 column volumes of 50 mM HEPES pH 8.0, 250 mM NaCl, 20 mM imidazole pH 8.0, 0.5 mM TCEP, and 5% glycerol. Protein was eluted with 50 mM HEPES pH 8.0, 250 mM NaCl, 400 mM imidazole pH 8.0, 0.5 mM TCEP, and 5% glycerol. A 1:200 mol:mol ratio of hexa-His-TEV protease was added to the eluent and the solution was dialyzed in 4 L of 50 mM HEPES pH 8.0, 250 mM NaCl, 20 mM imidazole pH 8.0, 0.5 mM TCEP, and 5% glycerol overnight at 4° with stirring. ERα was separated from the hexa-His tag and His-TEV protease by passing it over pre-equilibrated Ni-NTA resin and collecting the flow-through. The protein was concentrated to 5 mL, but no higher than 15 mg/mL and placed over a Superdex 200 HiLoad 200 16/600 size exclusion column that was equilibrated with 25 mM HEPES pH 8.0, 150 mM NaCl, 0.5 mM TCEP, and 5% glycerol. A small precipitate peak was observed at the leading edge of the column followed by a well-resolved single peak corresponding to the correct molecular weight of approximately 30,000 Da for ERα LBD. Fractions corresponding to these proteins were concentrated to > 10 mg/mL, flash frozen, and stored at –80 °C for later use.
Purified LBD was incubated with 2 mM of each compound between 4 and 16 hr at 4 °C prior to crystal screens. The mixture was centrifuged at 20,000 g for 30 min at 4 °C to remove precipitated ligand/protein. Hanging drop vapor diffusion was used to generate all crystals. 2 μL protein at 5–15 mg/mL was mixed with 2 μL mother liquor using Hampton VDX plates (Hampton Research, HR3-140). All crystals were grown in 5%–20% PEG 3350 or PEG 8000, pH 6–8.0, 200 mM MgCl2. For each complex, clear crystals grew at room temperature. Crystals emerged between 16 hr and 2 weeks. For BZA, RAL, 4-OHT, Laso, 48–2, and LSZ102 complexes these crystals appeared as hexagonal pucks. For RU39411 and 49–2 complexes crystals were rhombohedral. Crystals were either directly frozen in mother liquor or incubated in mother liquor with the addition of 25% glycerol as cryo-protectants. All x-ray data sets were collected at the Advanced Photon Source, Argonne National Laboratories, Argonne, Illinois on the SBC 19-BM beamline (0.97 Å). Figure 8—figure supplement 3 shows representative 2mFo-DFc difference maps for ligands in the ligand binding pocket. Figure 8—source data 1 contains data collection and refinement statistics.
All protein crystal structures have been deposited in the PDB under accession codes: 6PSJ, 7KBS, 7UJC, 7UJ8, 7UJM, 7UJY, 7UJF, 7UJW, 7UJO, 7UJ7, 6V8T, and 6VPF.
RCSB Protein Data BankID 6PSJ. Bazedoxifene in Complex with Y537S Estrogen Receptor Alpha Ligand Binding Domain.
RCSB Protein Data BankID 7KBS. Estrogen Receptor Alpha Ligand Binding Domain in Complex with Raloxifene.
RCSB Protein Data BankID 7UJC. Estrogen Receptor Alpha Ligand Binding Domain Y537S Mutant in Complex with Raloxifene.
RCSB Protein Data BankID 7UJ8. Estrogen Receptor Alpha Ligand Binding Domain Y537S in Complex with 4-Hydroxytamoxifen.
RCSB Protein Data BankID 7UJM. Estrogen Receptor Alpha Ligand Binding Domain in Complex with a Methylated Lasofoxifene Derivative That Increases Receptor Resonance Time in the Nucleus of Breast Cancer Cells.
RCSB Protein Data BankID 7UJY. Estrogen Receptor Alpha Ligand Binding Domain Y537S Mutant in Complex with a Methylated Lasofoxifene Derivative that Enhances Estrogen Receptor Alpha Nuclear Resonance Time.
RCSB Protein Data BankID 7UJF. Estrogen Receptor Alpha Ligand Binding Domain in Complex with a Methylated Lasofoxifene Derivative with Selective Estrogen Receptor Degrader Properties.
RCSB Protein Data BankID 7UJW. Estrogen Receptor Alpha Ligand Binding Domain Y537S Mutant in Complex with a Methylated Lasofoxifene Derivative that Possesses Selective Estrogen Receptor Degrader Activities.
RCSB Protein Data BankID 7UJO. Estrogen Receptor Alpha Ligand Binding Domain in Complex with RU39411.
RCSB Protein Data BankID 7UJ7. Estrogen Receptor Alpha Ligand Binding Domain Y537S Mutant in Complex with RU39411.
RCSB Protein Data BankID 6V8T. Estrogen Receptor Alpha Ligand Binding Domain Y537S in Complex with LSZ102.
RCSB Protein Data BankID 6VPF. Estrogen Receptor Alpha Ligand Binding Domain in Complex with the Selective Estrogen Receptor Modulator Clomiphene.
The Dysregulated Pharmacology of Clinically Relevant ESR1 Mutants is Normalized by Ligand-activated WT ReceptorMolecular Cancer Therapeutics 19:1395–1405.https://doi.org/10.1158/1535-7163.MCT-19-1148
Optimization of a Novel Binding Motif to (E)-3-(3,5-Difluoro-4-((1R,3R)-2-(2-fluoro-2-methylpropyl)-3-methyl-2,3,4,9-tetrahydro-1H-pyrido[3,4-b]indol-1-yl)phenyl)acrylic Acid (AZD9496), a Potent and Orally Bioavailable Selective Estrogen Receptor Downregulator and AntagonistJournal of Medicinal Chemistry 58:8128–8140.https://doi.org/10.1021/acs.jmedchem.5b00984
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Structural insights into the mode of action of a pure antiestrogenStructure (London, England) 9:145–153.https://doi.org/10.1016/s0969-2126(01)00568-8
Activating ESR1 mutations in hormone-resistant metastatic breast cancerNature Genetics 45:1446–1451.https://doi.org/10.1038/ng.2823
Molecular determinants for the tissue specificity of SERMsScience (New York, N.Y.) 295:2465–2468.https://doi.org/10.1126/science.1068537
ERα phosphorylation at Y537 by Src triggers E6-AP-ERα binding, ERα ubiquitylation, promoter occupancy, and target gene expressionMolecular Endocrinology (Baltimore, Md.) 26:1567–1577.https://doi.org/10.1210/me.2012-1140
ESR1 ligand-binding domain mutations in hormone-resistant breast cancerNature Genetics 45:1439–1445.https://doi.org/10.1038/ng.2822
Evaluation of the pharmacological activities of RAD1901, a selective estrogen receptor degraderEndocrine-Related Cancer 22:713–724.https://doi.org/10.1530/ERC-15-0287
Pharmacokinetic and pharmacodynamic analysis of fulvestrant in preclinical models of breast cancer to assess the importance of its estrogen receptor-α degrader activity in antitumor efficacyBreast Cancer Research and Treatment 179:67–77.https://doi.org/10.1007/s10549-019-05454-y
Differential SERM effects on corepressor binding dictate ERalpha activity in vivoThe Journal of Biological Chemistry 278:6912–6920.https://doi.org/10.1074/jbc.M208501200
Wilbert ZwartReviewing Editor; Netherlands Cancer Institute, Netherlands
Anna AkhmanovaSenior Editor; Utrecht University, Netherlands
Kendall W NettlesReviewer; The Scripps Research Institute, United States
Our editorial process produces two outputs: (i) public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.
Decision letter after peer review:
Thank you for submitting your article "Stereo-specific Lasofoxifene Derivatives Reveal the Interplay between Estrogen Receptor Α Stability and Antagonistic Activity in ESR1 Mutant Breast Cancer Cells" for consideration by eLife. Your article has been reviewed by 2 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Anna Akhmanova as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Kendall W Nettles (Reviewer #2).
The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.
This is an impressive structural and molecular mechanistic study in the modes of action of a series of Estrogen Receptor inhibitor molecules. The study is also of high relevance in the context of the resistance acquiring ER537/538 mutations. Molecular understanding of the underlying mechanisms is lacking here and the authors make a valuable contribution.
1) The authors use a halo-tagged ERα construct to quantify differences in ERα expression and cellular lifetime. Appending large protein domains to ERα potentially influences the properties of the protein. What are the data that show that this is not the case? Is the singular experiment of T47D cells with increasing doses of fulvestrant enough? This would constitute more a qualitative comparison and actually 2-3 additionally SERMs would ideally be compared in this manner as well. (Especially because this halo-tagged ER is also central to studies with the ER mutants).
2) Figure4A-C. The dose response curves look more like step-functions (Hill slope is extremely steep), than a -to be expected- curvature over at least two log decades (as is the case for example in Figure 4D-F). What is going on there?
3) The description/discussion of the crystallography data (for example movement of Helix 12) is very qualitative. Especially with such rather small movements (and not all structures at very high resolution), it would be extremely valuable (I personally would say necessary), to provide a more quantitative and statistical analysis of the data (by adding elements such as the maximum-likelihood coordinate error). Many movements in the Helix 12 position appear to be in the 0.1-0.4 Å scale and with only the refined structure shown (and not the actual electron density), there is a potential danger of overinterpretation of the data.
4) I very much appreciate that the authors selected the protein with the fewest crystal contacts in the crystal structure, to limit the effect of those contacts on the H12 as much as possible. However, it remains somewhat unclear to the reader now, for which of the structures these crystal contacts might still have influence the positioning of H12 in the final structures.
5) An interesting aspect (for future studies, potentially to be shortly discussed in the outlook of the manuscript) would be the effect/interplay of these ER modulators with the Y537 phosphorylation, which is -in the opinion of this reviewer- a highly relevant but understudied mechanism regarding responsiveness to SERM therapy. Also, because the molecular effects described for this phosphorylation are quite similar to the effects of the point mutations e.g. (a more E2 like conformation without ligand).
6) It would be helpful to know if the new compounds show SERM agonist activity, such as seen with tamoxifen in luciferase assays in the HepG2, and to a lesser extent, Ishikawa cell lines.
7) Reference 5: 50% de novo or acquired resistance at 5 years. This reference doesn't show that. See instead PMID: 30555626
8) Figure 2 is confusing. It appears that they completed time course studies (Figure 2 D-I), and then picked a time for the dose response (A-C), which are then summarized in Figure 2J. This should be reordered. The legend doesn't describe what is being done (fluorescence of halo tagged ER was assayed after addition of halo dye, dox, and ER ligand). Please reexamine the figure legends to make sure the reader can assess what was done.
9) Figure 2 presents the laso derivatives before they are explained in the text. The reader doesn't know what LA-stab and LA-Deg are at this point. These data could be removed from Figure 2A-I and Figure 2J moved to Figure 3.
10) Please renumber the chains so the A chain is the relevant chain to look at in each structure to make it easier for the viewer to look at them and superpose them. Please add a supplemental table listing all the pdb codes that were analyzed and their respective ligands.
11) Figure 7. And the associated text need significant revision.
12) Structures of the ER LBD have typically shown helix 12 in the agonist conformation, or with helix 12 flipped into the coactivator binding site to block recruitment of coactivators, which has been called the antagonist conformation. However, there is a significant body of data that antagonism involves recruitment of transcriptional corepressor proteins, which require helix 12 to be in a third position, which is unstructured. This was seen with the structure of a compound that is similar to fulvestrant, ICI 164,384, and some more recent full antagonist structures such as pdb 7rs3, 6b0f, 5T92 and 5t97. Importantly, mutations or phosphorylation of Ser305 that stabilize helix 12 in the "antagonist" conformer block corepressor recruitment and enable SERM agonist activity. The current model is that the degree of helix 12 destabilization drives efficacy, and that the so called "antagonist conformation" is actually the SERM agonist conformer by blocking corepressors, and allowing the amino terminal coactivator binding domain to have some constitutive activity see PMID: 34452998, 17283072, 1250199, 12482846. See also Dr. Fanning's previous eLife paper showing that the efficacy of bazedoxifene is through pushing on the helix 11-12 loop to destabilize helix 12.
Given this background, the conclusion of the structural studies was suggested to support the opposite conclusion, that stabilizing helix 12 leads to greater efficacy. After examining the structures in detail there does not appear to be a clear SAR between luciferase activity and helix 12 position, and it was not clear that the luciferase data correlated with anti-proliferative maximal efficacy.
13) The authors should reexamine the structures to identify how Ser537 and Tyr537 elicit different effects on the helix 11-12 loop interaction with the ligand to drive different pharmacology.
14) in the Baz 537S structure, the loop position is due to crystal packing, which could pull helix 12 and this should be noted or these structures not discussed.
15) The positions of amino acids 537, 373, and 351 should be reexamined in the structures. There are obvious errors in 7bk5 that if real space refined show the H-bond between Tyr537 and His373
16) The discussion and introduction have some redundancy. It might be better to move the extensive analysis on why degradation is not important for efficacy to the discussion and just briefly mention in the intro that there is increasing evidence and give the references. Sentences on line 439 and 440 are not needed in the discussion.https://doi.org/10.7554/eLife.72512.sa1
The authors use a halo-tagged ERα construct to quantify differences in ERα expression and cellular lifetime. Appending large protein domains to ERα potentially influences the properties of the protein. What are the data that show that this is not the case? Is the singular experiment of T47D cells with increasing doses of fulvestrant enough? This would constitute more a qualitative comparison and actually 2-3 additionally SERMs would ideally be compared in this manner as well. (Especially because this halo-tagged ER is also central to studies with the ER mutants).
We have performed dose-response curves using an in-cell western blot in T47D breast cancer cell lines treated with 4-hydroxytamoxifen (4OHT), fulvestrant (ICI), lasofoxifene (laso), laso-degrader (LA-Deg), laso-stablizer (LA-Stab). This assay measures endogenous estrogen receptor within the T47D cells and is normalized to cell number. Overall, these data agree with the halo-tag assay. Given the validation with the earlier fulvestrant study and that our data agree with previously published results, these data show that the halo-tag assay accurately recapitulates endogenous ERα responses to hormone, SERM, and SERD treatment in breast cancer cells1,2.
The description/discussion of the crystallography data (for example movement of Helix 12) is very qualitative. Especially with such rather small movements (and not all structures at very high resolution), it would be extremely valuable (I personally would say necessary), to provide a more quantitative and statistical analysis of the data (by adding elements such as the maximum-likelihood coordinate error). Many movements in the Helix 12 position appear to be in the 0.1-0.4 Å scale and with only the refined structure shown (and not the actual electron density), there is a potential danger of overinterpretation of the data.
I very much appreciate that the authors selected the protein with the fewest crystal contacts in the crystal structure, to limit the effect of those contacts on the H12 as much as possible. However, it remains somewhat unclear to the reader now, for which of the structures these crystal contacts might still have influence the positioning of H12 in the final structures.
Please renumber the chains so the A chain is the relevant chain to look at in each structure to make it easier for the viewer to look at them and superpose them. Please add a supplemental table listing all the pdb codes that were analyzed and their respective ligands.
Figure 7. And the associated text need significant revision.
The authors should reexamine the structures to identify how Ser537 and Tyr537 elicit different effects on the helix 11-12 loop interaction with the ligand to drive different pharmacology.
We have reanalyzed the crystal structures and have made significant changes to the associated text and figures. Because they were relatively minor, we have removed the discussion of ligand-specific changes and have instead focused the section on the clear structural features that are observed in the most potent molecules. In terms of qualitative discussion, we originally calculated buried surface area for each helix 12 in the Y537S structures and observed a trend where the molecules that favored the most burial in the AF2 cleft also showed the greatest anti-transcriptional efficacies. In the revised manuscript, we have now also included B-factor analysis and show that the H12 in the Y537S structures that has the lowest B-factor (normalized to the average B-factor across the structure) are those that show the greatest anti-transcriptional potencies.
We made a new Figure 7. Instead of showing every structure, we now highlight the structural features of the most versus least effective molecules in the MCF7 WT/Y537S ESR1 cells. Specifically, we observe that the most effective molecules show little difference versus their WT counterpart, form a hydrogen bond between S537 and E380, and the 2mFo-DFc difference maps of H12 are rigid and well packed in the AF-2 cleft. The least effective molecules lack this hydrogen bond and are poorly packed.
Further descriptions of the crystal contact are included in the results. A supplemental figure has been included that highlights the crystal contact formed between D538 and a symmetry mate arginine affects H12 and disqualified those monomers from the analysis. We have also renamed the chains so that chain A is the chain of interest in these structures.
An interesting aspect (for future studies, potentially to be shortly discussed in the outlook of the manuscript) would be the effect/interplay of these ER modulators with the Y537 phosphorylation, which is -in the opinion of this reviewer- a highly relevant but understudied mechanism regarding responsiveness to SERM therapy. Also, because the molecular effects described for this phosphorylation are quite similar to the effects of the point mutations e.g. (a more E2 like conformation without ligand).
We agree and have added in some text in the discussion about the importance of Y537 phosphorylation as well as potential changes to which coregulators associate with mutant versus WT ERα in the presence of SERMs and SERDs.
It would be helpful to know if the new compounds show SERM agonist activity, such as seen with tamoxifen in luciferase assays in the HepG2, and to a lesser extent, Ishikawa cell lines.
We attempted to study SERM agonist activity using HepG2 cells either endogenously or by transfecting ERα and were unable to measure meaningful responses using a reporter gene system. We were able to obtain these data in Ishikawa cells purchased from Σ Aldrich as well as ECC1 cells that were donated by Olema Oncology. We also purchased Ishikawa cells from ATCC but had difficulty culturing them. We used an established alkaline phosphatase activity assay to measure ERα agonism in these cells.3 These results show that the SERM-like LA-Stab does show SERM-agonistic activities in these assays. Laso showed a slight induction, while LA-Deg (the SERD) did not induce activity. These experiments were performed alongside 4OHT, ICI, and Z-endoxifen. Interestingly, E2 showed different degrees of stimulation between the two cells lines. However, the trend in SERM-agonism was the same in both cell lines.
Reference 5: 50% de novo or acquired resistance at 5 years. This reference doesn't show that. See instead PMID: 30555626
Citation has been changed.
Figure 2 is confusing. It appears that they completed time course studies (Figure 2 D-I), and then picked a time for the dose response (A-C), which are then summarized in Figure 2J. This should be reordered. The legend doesn't describe what is being done (fluorescence of halo tagged ER was assayed after addition of halo dye, dox, and ER ligand). Please reexamine the figure legends to make sure the reader can assess what was done.
Figure 2 presents the laso derivatives before they are explained in the text. The reader doesn't know what LA-stab and LA-Deg are at this point. These data could be removed from Figure 2A-I and Figure 2J moved to Figure 3.
The text and figure 2 have been reordered to discuss the time-course studies first then the dose-response and have revised the legend to be more descriptive. All LA-Stab and LA-Deg time-course studies into Figure 3. The summary figure panel has also been moved to Figure 3.
Structures of the ER LBD have typically shown helix 12 in the agonist conformation, or with helix 12 flipped into the coactivator binding site to block recruitment of coactivators, which has been called the antagonist conformation. However, there is a significant body of data that antagonism involves recruitment of transcriptional corepressor proteins, which require helix 12 to be in a third position, which is unstructured. This was seen with the structure of a compound that is similar to fulvestrant, ICI 164,384, and some more recent full antagonist structures such as pdb 7rs3, 6b0f, 5T92 and 5t97. Importantly, mutations or phosphorylation of Ser305 that stabilize helix 12 in the "antagonist" conformer block corepressor recruitment and enable SERM agonist activity. The current model is that the degree of helix 12 destabilization drives efficacy, and that the so called "antagonist conformation" is actually the SERM agonist conformer by blocking corepressors, and allowing the amino terminal coactivator binding domain to have some constitutive activity see PMID: 34452998, 17283072, 1250199, 12482846. See also Dr. Fanning's previous eLife paper showing that the efficacy of bazedoxifene is through pushing on the helix 11-12 loop to destabilize helix 12.
Given this background, the conclusion of the structural studies was suggested to support the opposite conclusion, that stabilizing helix 12 leads to greater efficacy. After examining the structures in detail there does not appear to be a clear SAR between luciferase activity and helix 12 position, and it was not clear that the luciferase data correlated with anti-proliferative maximal efficacy.
SERM/SERD-induced AF-2 antagonism is complex and stems from multiple contributing context/tissue-dependent influences on estrogen receptor α. Helix 12 in the AF-2 cleft occludes co-activator (i.e. SRC3) binding, while recruitment of corepressor enzymes like NCOR or SMRT to ERα also contribute epigenetic silencing activities4. 4-hydroxtamoxifen (4OHT) can induce ERα-NCOR binding but fulvestrant and raloxifene do so more efficiently4. These studies suggest H12 instability enhances co-repressor recruitment, which improves anti-transcriptional activities. It is also established that H12 instability correlates with ERα-degrading activities. Therefore, SERD-induced ERα-degradation should predict co-repressor recruitment and enhanced anti-transcriptional therapeutic activities. However, studies from the McDonnell lab suggests that the fulvestrant therapeutic activities stem from ERα transcriptional antagonism to a greater degree than degradation5. Further, lasofoxifene, a relatively poor ERα degrader, demonstrates improved activities over fulvestrant in MCF7 cells with WT or Y537S ERα6. Together, these studies suggest that, in breast cancer cells, ERα transcriptional antagonism may not correlate strongly with the degree of receptor degradation. In our study, we synthesized the lasofoxifene derivatives in order to test this hypothesis. These molecules, along with a panel of SERMs, SERM/SERDs, and SERDs suggest that degradation does not predict transcriptional antagonistic potency in breast cancer cell lines harboring WT or WT/mutant ESR1 under our assay conditions. As discussed, it may play a role in partial agonist activity of antiestrogens in a tissue- or possibly gene-specific specific manner.
Another major area of this study is revealing the structural basis for differential SERM or SERD activities for Y537S ERα. Structural studies were performed in parallel with the biological studies and we sought to solve as many structures as possible to identify structural features that correlate with efficacy. Our previous bazedoxifene (BZA) study did suggest that mobilizing H12 improved activity for Y537S ERα compared to 4OHT. However, we were unable to solve a structure of the molecule in complex with the Y537S mutant. Rather, we used solution-phase protein dynamics studies using HDX-MS of BZA in complex with WT or Y537S ERα LBD. We also performed detailed atomistic molecular dynamics simulations of the BZA bound to Y537S ERα LBD. Both studies from that paper agree with our current structural analysis. The HDX-MS data showed that H12 is less dynamic in the Y537S-BZA structure versus WT. The MD-sim predicted the formation of the S537-E380 hydrogen bond.
In terms of the structures of ICI 164,380 and other pure antagonist SERDs. In the PDB, the ICI 164,380 structure is with rat ERβ and lacks an ordered H12. We recently solved a structure of the same ligand and derivatives thereof in complex with ERα LBD carrying the mutation L536S in collaboration with our co-author Dr. Sylvie Mader for a forthcoming paper. Here, ERα H12 is observed in the antagonistic conformation in the AF-2 cleft but it is less helical than what would be observed in a SERM structure (see Author response image 1). Modeling of fulvestrant binding with S536 or L536 LBDs also maintained H12 in antagonist conformations. As for the other ligands, we have evaluated the models and the maps and at least some difference density is observed in the AF-2 cleft in the monomers that lack a modeled H12. While it is not significant in all of the structures, it is readily apparent in the 5T92 and 5T97 (see Author response image 1). In our experience, additional rounds of refinement likely would have led to a better-observed H12 and would have enabled the modeling of at least the main-chain. These structures suggest that H12 is not completely in a new disordered conformation but may still pack into the AF-2 cleft.
We lack a complete understanding of how SERMs or SERDs induce ERα corepressor binding and the role these protein play in antagonistic activities across multiple hormone-responsive tissues. The NCOR-ERα binding study from the Kushner lab4 suggests that H12 must be absent from the AF2 cleft for full binding. They also show that the hinge region, in between the DNA-binding domain and LBD, is important for NCOR binding. Likewise, a decreased co-repressor recruitment is observed with phospho S305, which lies near the ERα hinge-region far from the AF-2 cleft7. Together, these studies suggest that co-repressors likely bind along multiple surfaces on ERα beyond just the AF-2 cleft. Recent, cryo-EM structures of ERα and AR from the O’Malley lab also show significant contacts between AF-2 co-activators and the respective LBDs8,9. Additionally, a recent study from the Nettles and Katzenellenbogen laboratories shows that ERα antagonists that affect helix 8, in addition to helix 12, alters the repertoire of associated coregulators and enhances anti-cancer activities10. Together, these studies show that coregulator binding occurs across multiple surfaces of ERα and more studies are needed to improve our understanding of these relationships.
14) in the Baz 537S structure, the loop position is due to crystal packing, which could pull helix 12 and this should be noted or these structures not discussed.
This is true for Chain B, which shows a potential crystal contact at L536 as well a hydrogen bond formed between D538 and R436 of a symmetry mate. We chose to analyze Chain A in this structure because there are no crystal contacts observed until the c-terminus of the protein. There is a symmetry mate that approaches the H11-12 loop around residues 530 to 532. However, there is no clear contact formed here and the closest it reaches is 3.8 Å, outside hydrogen bonding distance. Crystal contacts are frequent confounding factors in crystal structures that, in our opinion, are not discussed as often enough. We have included additional descriptions of the crystal contacts in the Results section.
15) The positions of amino acids 537, 373, and 351 should be reexamined in the structures. There are obvious errors in 7bk5 that if real space refined show the H-bond between Tyr537 and His373
We assume that the Reviewer is referring to 7KBS. Each of these structures have been extensively refined but we have reanalyzed the positioning of 537, 373, and 351. We have redeposited the coordinates as needed. As is the case with many ERα LBD structures, Y537 is not fully ordered in each chain, but is structured enough for us to have some confidence in its positioning. For 7KBS, we solved this structure because we wanted to improve upon the 2.6 Å of PDB: 1ERR. Indeed, we were able to solve the structure of RAL in complex with ERα LBD to 1.83 Å and in the same C2 spacegroup as 1ERR. In the 1ERR structure, Y537 is ordered in Chain A but not in Chain B and is poised for a hydrogen bond with H373. However, the density around H373 is poorly resolved in both monomers of 1ERR. In 7KBS, Y537 and H373 are better resolved in both chains. While Y537 is not fully resolved in Chain A, the curvature of the density suggests that we have modeled it in the most representative side-chain conformation. Neither monomer suggests the presence of an ideal hydrogen bond, given the roughly 90o angle between the phenol and imidazole. In sum, there is a potential hydrogen bond between Y537 and H373 in 1ERR but the sidechains are poorly resolved, while the sidechains better resolved in 7KBS and do not show the formation of a hydrogen bond.
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2. Fanning, S. W. et al. The SERM/SERD bazedoxifene disrupts ESR1 helix 12 to overcome acquired hormone resistance in breast cancer cells. eLife 7, e37161, doi:10.7554/eLife.37161 (2018).
3. Fanning, S. W. et al. Specific stereochemistry of OP-1074 disrupts estrogen receptor α helix 12 and confers pure antiestrogenic activity. Nature Communications 9, 2368, doi:10.1038/s41467-018-04413-3 (2018).
4. Webb, P., Nguyen, P. and Kushner, P. J. Differential SERM effects on corepressor binding dictate ERalpha activity in vivo. J Biol Chem 278, 6912-6920, doi:10.1074/jbc.M208501200 (2003).
5. Wardell, S. E. et al. Pharmacokinetic and pharmacodynamic analysis of fulvestrant in preclinical models of breast cancer to assess the importance of its estrogen receptor-α degrader activity in antitumor efficacy. Breast Cancer Res Treat 179, 67-77, doi:10.1007/s10549-019-05454-y (2020).
6. Lainé, M. et al. Lasofoxifene as a potential treatment for therapy-resistant ER-positive metastatic breast cancer. Breast Cancer Research 23, 54, doi:10.1186/s13058-021-01431-w (2021).
7. Houtman, R. et al. Serine-305 phosphorylation modulates estrogen receptor α binding to a coregulator peptide array, with potential application in predicting responses to tamoxifen. Mol Cancer Ther 11, 805-816, doi:10.1158/1535-7163.Mct-11-0855 (2012).
8. Yu, X. et al. Structural Insights of Transcriptionally Active, Full-Length Androgen Receptor Coactivator Complexes. Molecular Cell 79, 812-823.e814, doi:https://doi.org/10.1016/j.molcel.2020.06.031 (2020).
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10. Min, J. et al. Dual-mechanism estrogen receptor inhibitors. Proceedings of the National Academy of Sciences 118, e2101657118, doi:10.1073/pnas.2101657118 (2021).https://doi.org/10.7554/eLife.72512.sa2
- Sean W Fanning
- Geoffrey L Greene
- Sylvie C Mader
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Funding from Susan G Komen Foundation CCR19608597 (SWF), Ludwig Fund for Metastasis Research (GLG), and Canadian Institutes of Health Research (SM). Results shown in this report are derived from work performed at Argonne National Laboratory (ANL), Structural Biology Center (SBC) at the Advanced Photon Source (APS), under U.S. Department of Energy, Office of Biological and Environmental Research contract DE-AC02-06CH11257.
- Anna Akhmanova, Utrecht University, Netherlands
- Wilbert Zwart, Netherlands Cancer Institute, Netherlands
- Kendall W Nettles, The Scripps Research Institute, United States
© 2022, Hosfield et al.
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
Lactate oxidation with NAD+ as electron acceptor is a highly endergonic reaction. Some anaerobic bacteria overcome the energetic hurdle by flavin-based electron bifurcation/confurcation (FBEB/FBEC) using a lactate dehydrogenase (Ldh) in concert with the electron-transferring proteins EtfA and EtfB. The electron cryo-microscopically characterized (Ldh-EtfAB)2 complex of Acetobacterium woodii at 2.43 Å resolution consists of a mobile EtfAB shuttle domain located between the rigid central Ldh and the peripheral EtfAB base units. The FADs of Ldh and the EtfAB shuttle domain contact each other thereby forming the D (dehydrogenation-connected) state. The intermediary Glu37 and Glu139 may harmonize the redox potentials between the FADs and the pyruvate/lactate pair crucial for FBEC. By integrating Alphafold2 calculations a plausible novel B (bifurcation-connected) state was obtained allowing electron transfer between the EtfAB base and shuttle FADs. Kinetic analysis of enzyme variants suggests a correlation between NAD+ binding site and D-to-B-state transition implicating a 75° rotation of the EtfAB shuttle domain. The FBEC inactivity when truncating the ferredoxin domain of EtfA substantiates its role as redox relay. Lactate oxidation in Ldh is assisted by the catalytic base His423 and a metal center. On this basis, a comprehensive catalytic mechanism of the FBEC process was proposed.
Deubiquitinating enzymes (DUBs), ~100 of which are found in human cells, are proteases that remove ubiquitin conjugates from proteins, thereby regulating protein turnover. They are involved in a wide range of cellular activities and are emerging therapeutic targets for cancer and other diseases. Drugs targeting USP1 and USP30 are in clinical development for cancer and kidney disease respectively. However, the majority of substrates and pathways regulated by DUBs remain unknown, impeding efforts to prioritize specific enzymes for research and drug development. To assemble a knowledgebase of DUB activities, co-dependent genes, and substrates, we combined targeted experiments using CRISPR libraries and inhibitors with systematic mining of functional genomic databases. Analysis of the Dependency Map, Connectivity Map, Cancer Cell Line Encyclopedia, and multiple protein-protein interaction databases yielded specific hypotheses about DUB function, a subset of which were confirmed in follow-on experiments. The data in this paper are browsable online in a newly developed DUB Portal and promise to improve understanding of DUBs as a family as well as the activities of incompletely characterized DUBs (e.g. USPL1 and USP32) and those already targeted with investigational cancer therapeutics (e.g. USP14, UCHL5, and USP7).