Purpose: High-grade serous ovarian cancer (HGSOC) is an aggressive disease with few available targeted therapies. Despite high expression of estrogen receptor-alpha (ERα) in approximately 80% of HGSOC and some small but promising clinical trials of endocrine therapy, ERα has been understudied as a target in this disease. We sought to identify hormone-responsive, ERα-dependent HGSOC.

Experimental Design: We characterized endocrine response in HGSOC cells across culture conditions [ two-dimensional (2D), three-dimensional (3D), forced suspension] and in patient-derived xenograft (PDX) explants, assessing proliferation and gene expression. Estrogen-regulated transcriptome data were overlapped with public datasets to develop a comprehensive panel of ERα target genes. Expression of this panel and ERα H-score were assessed in HGSOC samples from patients who received endocrine therapy. Time on endocrine therapy was used as a surrogate for clinical response.

Results: Proliferation is ERα-regulated in HGSOC cells in vitro and in vivo, and is partly dependent on 3D context. Transcriptomic studies identified genes shared by cell lines and PDX explants as ERα targets. The selective ERα downregulator (SERD) fulvestrant is more effective than tamoxifen in blocking ERα action. ERα H-score is predictive of efficacy of endocrine therapy, and this prediction is further improved by inclusion of target gene expression, particularly IGFBP3.

Conclusions: Laboratory models corroborate intertumor heterogeneity of endocrine response in HGSOC but identify features associated with functional ERα and endocrine responsiveness. Assessing ERα function (e.g., IGFBP3 expression) in conjunction with H-score may help select patients who would benefit from endocrine therapy. Preclinical data suggest that SERDs might be more effective than tamoxifen. Clin Cancer Res; 23(14); 3802–12. ©2017 AACR.

Translational Relevance

High-grade serous ovarian cancer (HGSOC) is a malignancy with extremely poor prognosis and limited therapeutic options. Targeting estrogen receptor-alpha (ERα) has shown promise in laboratory models and in clinical trials, but identification of the appropriate patient subset has remained elusive. We characterized endocrine response in cell line and patient-derived HGSOC models to identify features associated with estrogen-responsive HGSOC. In these studies, we observed that a subset of HGSOC models require estrogen for growth and survival. Furthermore, we identified genes (e.g., the ER-α target IGBP3) which were associated with clinical endocrine response. We also determined that fulvestrant may be more effective than tamoxifen at blocking cell proliferation in HGSOC. Our data may enable the identification of patients with ovarian cancer who would benefit from endocrine therapy.

High-grade serous ovarian cancer (HGSOC) is an aggressive and often lethal disease with limited options for therapy. HGSOC typically responds to surgical debulking and platinum-based chemotherapy as first-line treatment but the majority of patients relapse and ultimately succumb to the disease (1). Identifying targeted, individualized treatment strategies for ovarian cancer will be essential for improving patient survival.

One promising but understudied therapeutic target for HGSOC is estrogen receptor-alpha (ERα). ERα is expressed in approximately 80% of HGSOC (2–4), and estrogen exposure (e.g., oral contraceptive use, hormone replacement therapy) affects the risk of ovarian cancer (4–6). Preclinical studies have shown that estrogen can promote proliferation and migration of HGSOC cell lines and mouse models and, in part, these effects are blocked by antiestrogens (7–12).

Several clinical trials have evaluated endocrine therapy in ovarian cancer. Trials were small (n = 14–105 patients), patients were heavily pretreated with chemotherapy, and ERα status was infrequently used as an inclusion criterion (4). Nevertheless, in each trial, a subset of patients benefited from tamoxifen (∼20% of patients; refs. 13–20), aromatase inhibitors (∼17%; refs. 21–24), or fulvestrant (∼40%; ref. 25). Although consistent inclusion of ERα status may improve response rates, superior biomarkers for ERα function and endocrine responsiveness are needed.

We sought to identify HGSOC likely to be ERα-dependent and endocrine responsive. Therefore, we comprehensively characterized estrogen and antiestrogen response with regards to growth, survival, and gene expression in HGSOC cell lines and patient-derived xenograft (PDX) explants. On the basis of these data, we built an assay for endocrine response and profiled tumors from patients with ovarian cancer who received endocrine therapy to identify genes associated with clinical response. Here we show that ERα H-score with expression of other biomarkers (e.g., IGFBP3) can identify patients with HGSOC who benefit from endocrine therapy.

Antibodies and reagents

Chemicals.

Estradiol (E2; Sigma-Aldrich), 4-hydroxytamoxifen (4OHT; Sigma-Aldrich), ICI 182,780 (fulvestrant; Tocris Bioscience), staurosporine (STS; Tocris Bioscience), and Z-VAD (Tocris Bioscience). E2, 4OHT, and fulvestrant were solubilized in 200-proof ethanol prior to use. STS and Z-VAD were solubilized in sterile DMSO.

Antibodies.

ERα 6F11 clone (Leica Biosystems), ER (SP1 Clone, Biocare Medical), bromodeoxyuridine (BrdUrd; Bu20a clone, Cell Signaling Technology), Ki67 (M1B clone, Dako), Tubulin (Sigma-Aldrich), and β-actin (Sigma-Aldrich).

Cell lines and culture conditions

PEO1, PEO4, OVSAHO, and MCF-7 cells were maintained in DMEM (Invitrogen) + 10% FBS (Gibco). OVCA432 cells were maintained in RPMI1640 + 10% FBS. Cell line identity was verified by short tandem repeat (STR) profiling. PEO1 and PEO4 cells were derived from the same patient (26), PEO1 after her first recurrence and PEO4 after the tumor became platinum-resistant.

Hormone deprivation was performed as described previously (27) using IMEM + 10% charcoal-stripped serum (CSS) for PEO1, PEO4, and OVCA432 or 5% CSS for MCF-7 and OVSAHO. Unless otherwise specified, hormones were used at the following concentrations: 1 nmol/L E2, 1 μmol/L fulvestrant, and 1 μmol/L 4OHT.

For standard (two-dimensional; 2D) proliferation assays, growth was analyzed using the FluoReporter dsDNA quantitation kit (Molecular Probes) as described previously (27). Cells (2,000–4,000/well) were seeded in 96-well plates (Thermo Fisher Scientific). After cells adhered (16–24 hours), drug was added directly to the wells. For ultra-low attachment (ULA) assays, cells (5,000–10,000/well) were treated at the time of seeding in ULA (Corning). Viability was measured using the CellTiter-Glo assay and apoptosis with the CaspaseGlo-3/7 assay (Promega). For three-dimensional (3D) assays, dishes were coated with phenol red–free Matrigel (BD Biosciences). Cells were seeded on top of the Matrigel in media + 2% Matrigel.

Cell line gene expression analyses

Hormone-deprived cells were treated in biological quadruplicate with vehicle, E2, 4OHT ± E2, or fulvestrant ± E2 as described previously (27). RNA was isolated using the Illustra RNAspin Mini Kit (GE Healthcare). Gene expression was measured on Affymetrix U133A 2.0 arrays. Data were RMA normalized using the affy() package in R (command “rma()”, http://www.bioconductor.org/). Differentially expressed genes were identified with limma. When genes were represented by multiple probes, the probe with greatest variation (largest dynamic range) across samples was chosen for downstream analysis. Heatmaps were generated using the Multiple Experiment Viewer (MeV, http://www.tm4.org/). E2-regulated genes were considered “blocked” by fulvestrant or 4OHT whether E2 produced significant (P < 0.001) changes in expression compared with vehicle but fulvestrant + E2 or 4OHT + E2 did not. To determine overlap with E2-regulated genes in breast cancer, MCF-7 data were obtained from the GEMS database. Significantly E2-regulated genes were defined as those with q < 0.05. Because the treatment for our microarray studies was 3 hours, we used only the “early” (3- to 4-hour E2 treatment) GEMS dataset.

cDNA conversion and qRT-PCR were performed using iScript and Universal SYBR RT Supermix (Bio-Rad). Primer sequences are in Table 1.

Table 1.

Primer sequences for qPCR

GeneFwdRev
RPLP0 TAAACCCTGCGTGGCAATC TTGTCTGCTCCCACAATGAAA 
GREB1 GGTTCTTGCCAGATGACAATGG CTTGGGTTGAGTGGTCAGTTTC 
ESR1 GAGTATGATCCTACCAGACCCTTC CCTGATCATGGAGGGTCAAATC 
IGFBP3 CACAGATACCCAGAACTTCTCC CAGGTGATTCAGTGTGTCTTCC 
CCNG2 GTTTGGATCGTTTCAAGGCG CCTCTCCACAACTCATATCTTCAC 
PGR TCGCCTTAGAAAGTGCTGTC GCTTGGCTTTCATTTGGAACG 
MYC GCTGCTTAGACGCTGGATTT GAGTCGTAGTCGAGGTCATAGT 
GeneFwdRev
RPLP0 TAAACCCTGCGTGGCAATC TTGTCTGCTCCCACAATGAAA 
GREB1 GGTTCTTGCCAGATGACAATGG CTTGGGTTGAGTGGTCAGTTTC 
ESR1 GAGTATGATCCTACCAGACCCTTC CCTGATCATGGAGGGTCAAATC 
IGFBP3 CACAGATACCCAGAACTTCTCC CAGGTGATTCAGTGTGTCTTCC 
CCNG2 GTTTGGATCGTTTCAAGGCG CCTCTCCACAACTCATATCTTCAC 
PGR TCGCCTTAGAAAGTGCTGTC GCTTGGCTTTCATTTGGAACG 
MYC GCTGCTTAGACGCTGGATTT GAGTCGTAGTCGAGGTCATAGT 

Immunoblotting

Cells were lysed in RIPA buffer + Halt Phosphatase/Protease Inhibitor Cocktail (Pierce). Protein (20 μg) was run on a 10% SDS polyacrylamide gel and transferred to a polyvinylidene difluoride membrane. Membranes were incubated with primary antibody overnight at 4°C. Blots were imaged on the Olympus LI-COR system. Antibody dilutions were as follows: ER 6F11, 1:500; Tubulin, 1:10,000.

Xenograft studies

All animal studies were approved by the University of Pittsburgh Institutional Animal Care and Use Committee. C.B.17/IcrHsd-PrkdcscidLystbg-J (SCID/Beige, Harlan Laboratories) mice were used for all studies. For PEO4 xenografts, mice underwent ovariectomy followed by subcutaneous pellet implantation (placebo or 0.03 mg E2, Innovative Research of America). Each group had n = 5 mice. Two weeks after surgery, 106 PEO4 cells in 1:1 RPMI + Matrigel were injected intraperitoneally (i.p.). Mice were monitored for 11 weeks after injection and then sacrificed. Tumors were harvested immediately after euthanasia. Tissue was either flash frozen in liquid nitrogen or fixed in 10% NBF. Patient-derived xenografts (PDX) were provided by Dr. Paul Haluska and processed as described previously (28). Tissue was collected at necropsy in the same manner as the PEO4 xenografts.

Explants

PDXs were passaged <5 times prior to use. PDXs were cultured ex vivo using an established protocol for primary tumors (29). Briefly, fresh PDX tissue was harvested and dissected into approximately 1-mm3 fragments. Fragments were cultured on VetSPON sponges (Henry Schein) partially submerged in media (IMEM + 5% FBS + 10 μg/mL insulin + 10 μg/mL hydrocortisone) + vehicle, fulvestrant, or 4OHT. Three tissue fragments were placed on each sponge. After three days, explants were pulsed with 30 μg/mL BrdUrd (Invitrogen) for 4–6 hours. Tissue was either fixed in 10% neutral-buffered formalin (NBF) for IHC or snap-frozen in liquid nitrogen. Snap-frozen tissue was processed using the RNEasy Mini Kit (Qiagen). qRT-PCR was performed as described above. IHC details are provided below. For PH045, PH053, and PH070, two sponges per treatment group (6 explant pieces total) were used for each assay type (i.e., two sponges for RNA collection and two for fixation/IHC). For PH242, only one sponge (three fragments) was used per treatment group although several time points (day 1–3) were assessed. Each tissue fragment was treated as a unique biological replicate.

IHC

Antigen retrieval was performed in citrate buffer (pH 6) for 30 minutes using a boiling water bath. Sections were then blocked in 5% BSA in PBS + 0.5% Tween-20 for 1 hour at room temperature. Sections were incubated in primary antibody overnight at 4°C. Staining was visualized with DAB. Slides were counterstained with hematoxylin. BrdUrd staining was quantified by determining %BrdUrd+ cells (# BrdUrd+ cells/total cells × 100%) for a given field of view. For each treatment group, 10 fields of view were counted, spanning multiple explant pieces.

IHC of clinical samples was performed by the research histology core at University of Pittsburgh Medical Center (Pittsburgh, PA). Antigen retrieval was performed in citrate buffer (pH 6) at 120°C. Staining was detected using Envision Dual Link+ HRP Polymer and DAB (Dako). Hematoxylin was used for counterstaining. Antibody dilutions were as follows: ER 6F11, 1:50; BrdUrd, 1:200; Ki67, 1:300, ER SP-1, predilute.

Clinical samples

Paraffin-embedded tumor samples from the University of Pittsburgh Medical Center, Fox Chase Cancer Center, Roswell Park Cancer Institute, and the University of Michigan were centrally reviewed by a pathologist (E. Elishaev) to confirm >50% tumor and >50% viable cells. RNA was isolated using the AllPrep FFPE kit (Qiagen). Expression of genes on the EndoRx panel (see Materials and Methods, Supplementary File S1) was measured on the NanoString nCounter as described previously (30). Data were normalized to internal controls and the geometric mean of four housekeeping genes. All work was approved by local Institutional Review Boards.

Design of the EndoRx assay

To develop a comprehensive assay for estrogen response, we overlapped our microarray results with publicly available preclinical studies of E2 response in breast, bone, ovarian, and endometrial cancer, and with genes differentially expressed between ERα-positive and ERα-negative breast and ovarian tumors and genes specific to “hormonally responsive” endometrial tumors from The Cancer Genome Atlas (TCGA; refs. 31–33). Ad hoc additions were made including mediators of ERα signaling (e.g., NCOAs), genes with known associations to endocrine resistance, immune response, or tumor–stromal interactions, and genes that correlated with response in clinical trials of endocrine therapy (34, 35).The final assay comprised 350 genes (Supplementary File S1).

Statistical analysis

Significance was determined at P = 0.05 unless otherwise specified. Unpaired, two-tailed t tests were used to compare two groups. For three or more groups, one-way ANOVA and Tukey post hoc test were used. Growth curves in ULA were fit with simple logarithmic regression [log(y)=log(y0)+k*x] and k was compared between groups using sum-of-squares F test. χ2 test was used to compute significance of overlap in E2-regulated genes between cell lines. On figures, asterisks indicate significance: ****, P < 0.0001; ***, P < 0.001; **, P < 0.01; *, P < 0.05.

Clinical specimens were dichotomized by time on endocrine therapy: “long” (≥120 days, n = 43) and “short” (<120 days. n = 25). Differentially expressed genes were identified with edgeR; significance was determined using a likelihood ratio test and Benjamini–Hochberg correction for multiple comparisons. To construct a prediction model for classifying patients by time on endocrine therapy, support vector machines (SVM) with linear kernel was used. SVM is a supervised machine learning algorithm used to solve classification problems. It is a generalization of the maximal margin classifier. Given a separation of the hyperplane and when data are separable, the maximal margin is defined as the minimum distance of the objects to the hyperplane. In addition, we applied an SVM-RFE (Recursive Feature Extraction) to return a ranking of the features of our classification problem by training an SVM with a linear kernel and removing the feature with the smallest ranking criterion. Model accuracy was assessed through leave-one-out cross-validation. Log-rank test was used to determine significance level of the survival curves. ANOVA was used to test differences of cohort means from major clinical variables. Differences in pre- and postendocrine therapy CA-125 levels were determined by paired t test.

Endocrine response in HGSOC cell lines

To determine whether estrogen regulates growth, we evaluated ERα expression and response to E2, fulvestrant, and 4OHT in four ERα+ HGSOC cell lines. PEO1, PEO4, and OVCA432 cells expressed high ERα but expression in OVSAHO cells was lower (Fig. 1A); all lines were ERβ-negative (data not shown). In 2D assays, E2 stimulated proliferation of PEO4 and PEO1 cells in a dose-dependent manner, which was abrogated by fulvestrant and 4OHT. In contrast, E2 had no effect on growth of OVCA432 and OVSAHO cells (Fig. 1B).

Figure 1.

Endocrine response in HGSOC cell lines grown in 2D. A, Expression of ERα mRNA (ESR1) and protein in HGSOC cell lines. The hormone-responsive breast cancer cell line MCF-7 was included as a positive control. B, Effect of E2, fulvestrant, and 4OHT on growth of HGSOC cells after six days. Hormone-deprived cells were treated with increasing doses of E2, fulvestrant, or 4OHT. Fulvestrant and 4OHT were added in the presence of 100 pmol/L E2. Data are shown as fold change (FC) versus vehicle. Points represent the mean of six biological replicates; error bars, SD. Graphs are representative of >2 independent experiments. Lines represent best fit nonlinear regressions. Curves could not be fit for OVCA432 nor OVSAHO. C, Heatmaps depicting gene expression changes (log2FC vs. vehicle) after 3-hour treatment with E2 ± 4OHT or fulvestrant in PEO4 and PEO1 cells. Genes shown are significantly regulated by E2 compared with vehicle (P < 0.001). Heatmaps were generated using MeV. D, Overlap of E2-regulated genes in PEO1 and PEO4 cells versus MCF7 breast cancer cells (GEMS early data). E, Mean log2(FC) (treatment vs. vehicle) of ERα target genes in HGSOC cells. Gene expression was measured by qRT-PCR after 8-hour treatment with Vhc, E2, E2 + fulvestrant, or E2 + 4OHT. Error bars, SD of three biological replicates.

Figure 1.

Endocrine response in HGSOC cell lines grown in 2D. A, Expression of ERα mRNA (ESR1) and protein in HGSOC cell lines. The hormone-responsive breast cancer cell line MCF-7 was included as a positive control. B, Effect of E2, fulvestrant, and 4OHT on growth of HGSOC cells after six days. Hormone-deprived cells were treated with increasing doses of E2, fulvestrant, or 4OHT. Fulvestrant and 4OHT were added in the presence of 100 pmol/L E2. Data are shown as fold change (FC) versus vehicle. Points represent the mean of six biological replicates; error bars, SD. Graphs are representative of >2 independent experiments. Lines represent best fit nonlinear regressions. Curves could not be fit for OVCA432 nor OVSAHO. C, Heatmaps depicting gene expression changes (log2FC vs. vehicle) after 3-hour treatment with E2 ± 4OHT or fulvestrant in PEO4 and PEO1 cells. Genes shown are significantly regulated by E2 compared with vehicle (P < 0.001). Heatmaps were generated using MeV. D, Overlap of E2-regulated genes in PEO1 and PEO4 cells versus MCF7 breast cancer cells (GEMS early data). E, Mean log2(FC) (treatment vs. vehicle) of ERα target genes in HGSOC cells. Gene expression was measured by qRT-PCR after 8-hour treatment with Vhc, E2, E2 + fulvestrant, or E2 + 4OHT. Error bars, SD of three biological replicates.

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As ERα status alone did not predict E2 response in HGSOC cells, we examined markers of ERα function. Previous efforts to identify ERα target genes in HGSOC are limited (7, 9). To create a comprehensive picture of the ERα transcriptome, we performed whole-genome microarrays in PEO4 and PEO1 cells after treatment with E2 ± fulvestrant or 4OHT. E2 regulated the expression of 221 and 291 genes in PEO1 and PEO4, respectively (Fig. 1C; Supplementary File S2). Notably, fulvestrant was more effective than 4OHT at blocking E2 effects; 4OHT mitigated E2-mediated expression of 70% of genes in PEO4 cells and 89% in PEO1 cells, whereas fulvestrant mitigated 96% and 99.5%.

There was significant overlap among E2-regulated genes in HGSOC lines (n = 175/515, P < 0.001) versus MCF-7 cells (ref. 36; Fig. 1D), including canonical ERα targets GREB1, CCNG2, and MYC. We validated E2-regulation (and blockade by fulvestrant and 4OHT) of GREB1, CCNG2, and MYC by qRT-PCR in PEO1 and PEO4 cells (Fig. 1E). This suggests ERα targets in HGSOC cells comprise a largely classical E2 response.

We then evaluated endocrine response of HGSOC cells lines in models mimicking in vivo tumor growth, first via 3D growth in a Matrigel. Similar to growth in 2D, E2 increased spheroid formation in PEO4 cells (Fig. 2A) but not in OVCA432 cells. To model ascites, a common clinical manifestation in late-stage HGSOC, we grew cells in forced suspension using ultra-low attachment (ULA) plastics. Cells in ULA grow in aggregates (Supplementary Fig. S1A). E2 significantly increased PEO1 and PEO4 cell number; OVSAHO and OVCA432 cells gained E2 responsiveness, as E2 now increased cell number (Fig. 2B). ULA increased ERα mRNA and protein levels versus 2D conditions (Fig. 2C and D), which may mediate the novel E2 response. The effect of E2 on PEO1 appeared to be more through a decrease of cell death than increased proliferation. Survival in ULA/forced suspension typically requires resistance to anoikis (apoptosis due to detachment) but we observed no effect of E2 on caspase-3/7 activity (Supplementary Fig. S1B), suggesting E2 did not inhibit anoikis but may mediate other survival mechanisms. We then sought to directly assess estrogen response in vivo. Because PEO4 displayed hormone dependence across all three culture methods, we chose this cell line for our xenograft experiments. E2 treatment increased tumor burden versus placebo (Fig. 2E) and induced GREB1 and MYC expression, consistent with our in vitro results. Taken together, these data demonstrate that some HGSOC cells are E2-responsive but that response may be dependent on 3D context.

Figure 2.

Endocrine response in 3D, ULA, and cell line xenografts. A, PEO4 and OVCA432 cells were plated in Matrigel, treated as indicated, and allowed to grow for 10 days. Images are representative of two biological replicates. B, Hormone-deprived cells were plated in ULA ± E2. Data are presented as blank-corrected luminescence (mean of six replicates ± SD). Graphs are representative of three experiments. C and D, Cells were plated in 2D or ULA plates for 24 hours. ESR1 mRNA levels were measured by qRT-PCR (C) and ERα protein levels measured by immunoblot (D). Numbers below the band indicate ERα/tubulin ratio. E, PEO4 cells were injected intraperitoneally into mice after ovariectomy (OVX) plus placebo or E2 pellet supplementation. Tumor burden was measured after 11 weeks and calculated as (tumor weight/total body weight) × 100%. Each point represents an individual mouse. F, Gene expression in xenografts was measured by qRT-PCR. Each point represents an individual mouse. Differences were not statistically significant.

Figure 2.

Endocrine response in 3D, ULA, and cell line xenografts. A, PEO4 and OVCA432 cells were plated in Matrigel, treated as indicated, and allowed to grow for 10 days. Images are representative of two biological replicates. B, Hormone-deprived cells were plated in ULA ± E2. Data are presented as blank-corrected luminescence (mean of six replicates ± SD). Graphs are representative of three experiments. C and D, Cells were plated in 2D or ULA plates for 24 hours. ESR1 mRNA levels were measured by qRT-PCR (C) and ERα protein levels measured by immunoblot (D). Numbers below the band indicate ERα/tubulin ratio. E, PEO4 cells were injected intraperitoneally into mice after ovariectomy (OVX) plus placebo or E2 pellet supplementation. Tumor burden was measured after 11 weeks and calculated as (tumor weight/total body weight) × 100%. Each point represents an individual mouse. F, Gene expression in xenografts was measured by qRT-PCR. Each point represents an individual mouse. Differences were not statistically significant.

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Antiestrogen response in HGSOC explants

To examine antiestrogen response in models more closely mimicking clinical HGSOC, we utilized four PDXs that recapitulate classic ovarian cancer phenotypes. They were established from HGSOC tumors of advanced stage (III/IV) and grade (III/IV). Our models also capture the varying ERα expression of HGSOC, encompassing high (PH045), medium (PH053, PH242), and low expression (PH070; Fig. 3A); none expressed ERβ (data not shown). However, HGSOC PDXs often take months to form detectable tumors (28, 37), limiting the feasibility of large-scale in vivo studies. We therefore assessed proliferation (BrdUrd incorporation) and gene expression in PDX explants (29) following endocrine treatment (Fig. 3B).

Figure 3.

ERα expression and endocrine response in HGSOC PDX explants. A, PDX tissue was collected when mice became moribund (8–16 weeks after engraftment). ERα (ESR1) mRNA was measured by qRT-PCR. Protein was assessed by Western blot and IHC analyses. H-scores were calculated by a pathologist (E. Elishaev) by reviewing the slide shown. B, Workflow for explant studies. For each model, 3–6 explants were used for each experiment (i.e., 3 for proliferation and 3 for qRT-PCR). Each fragment was treated as a unique biological replicate. C and D, Effect of fulvestrant and 4OHT treatment on ERα levels and BrdUrd incorporation in PH045 explants. E, Effect of fulvestrant and 4OHT on gene expression of PH045 explants. F and H, Effects of fulvestrant and 4OHT treatment on PH053 explant proliferation (F–G) and gene expression (H). For graphs in D and G, each point represents a separate field of view and bars show the mean. For E and H, each dot represents an individual explant piece. Bars, mean.

Figure 3.

ERα expression and endocrine response in HGSOC PDX explants. A, PDX tissue was collected when mice became moribund (8–16 weeks after engraftment). ERα (ESR1) mRNA was measured by qRT-PCR. Protein was assessed by Western blot and IHC analyses. H-scores were calculated by a pathologist (E. Elishaev) by reviewing the slide shown. B, Workflow for explant studies. For each model, 3–6 explants were used for each experiment (i.e., 3 for proliferation and 3 for qRT-PCR). Each fragment was treated as a unique biological replicate. C and D, Effect of fulvestrant and 4OHT treatment on ERα levels and BrdUrd incorporation in PH045 explants. E, Effect of fulvestrant and 4OHT on gene expression of PH045 explants. F and H, Effects of fulvestrant and 4OHT treatment on PH053 explant proliferation (F–G) and gene expression (H). For graphs in D and G, each point represents a separate field of view and bars show the mean. For E and H, each dot represents an individual explant piece. Bars, mean.

Close modal

Treatment of PH045 explants with 4OHT significantly decreased proliferation (Fig. 3C and D; P = 0.014, median change of −50%); 4OHT also decreased GREB1 and PGR expression and induced the E2-repressed gene CCNG2 (Fig. 3E). 4OHT did not affect MYC expression as was observed in cell lines (data not shown). Fulvestrant produced similar but more pronounced effects; the median change in proliferation was −50% (P = 0.005) but the maximal decrease was greater (−95% vs. −58%). Fulvestrant decreased ERα protein (mean change −55%), consistent with its mechanism of action, and produced stronger effects on gene expression versus 4OHT. Similar observations were made in PH053 explants (Fig. 3F–H); fulvestrant significantly decreased proliferation (P = 0.0049) while effects of 4OHT on proliferation and gene expression were weaker. In contrast, fulvestrant did not affect PH070 and PH242 explants (Supplementary Fig. S2). Lack of fulvestrant response was expected for PH070 (low/absent ERα) but PH242 had ERα levels similar to PH053. The fulvestrant resistance in PH242 thus supports clinical observations that ERα itself is limited as a biomarker of endocrine response in HGSOC (25, 34, 38, 39). Therefore, though some HGSOC PDXs are endocrine responsive, additional biomarkers are necessary to differentiate response versus resistance.

Genes associated with clinical endocrine response

To identify novel biomarkers of endocrine response, tumor specimens were procured from 70 patients with ovarian cancer who received tamoxifen and/or an aromatase inhibitor (AI) at four medical centers (Table 2). Median age at diagnosis was 63 and the majority (85%) of patients presented at late stages (III/IV). No patient or tumor characteristics differed across centers except age; RPCI patients were significantly older (P = 0.0013). There were also no significant differences in overall survival (time from diagnosis to death) or duration of endocrine therapy across cohorts (Supplementary Fig. S3).

Table 2.

Clinical features of the patient cohort

UPMC (n = 14)RPCI (n = 19)FCCC (n = 8)Mich (n = 26)
Age at dx 60.3 ± 10.5 72.4 ± 7.3 56.1 ± 7.7 58.9 ± 15.9 
Primary/Recur samples 14/0 17/2 5/3 26/0 
Grade     
 Low 
 High 12 19 23 
Stage     
 Early (1–2) 
 Late (3–4) 13 19 24 
Histology     
 Serous 10 17 15 
 Clear cell 
 Endometrioid 
Other 
Pre-rx CA-125a (# censored) 340.2 ± 544.0 (5) 392.4 ± 646.0 (1) 463.3 ± 785.0 (4) 105.0 ± 143.4 (0) 
Endo rx     
 Tamoxifen 11 18 14 
 AI 
 Both 
Days on endo rx 351 ± 358 419 ± 661 168 ± 115 260 ± 310 
 Min 38 22 31 30 
 Max 908 2850 396 1,470 
Survival after endo rx (days) 882 ± 564 717 ± 880 738 ± 653 834 ± 774 
Overall survival (days) 2,346 ±1,302 2,019 ± 1,372 2,129±1,104 1,880 ± 1,228 
UPMC (n = 14)RPCI (n = 19)FCCC (n = 8)Mich (n = 26)
Age at dx 60.3 ± 10.5 72.4 ± 7.3 56.1 ± 7.7 58.9 ± 15.9 
Primary/Recur samples 14/0 17/2 5/3 26/0 
Grade     
 Low 
 High 12 19 23 
Stage     
 Early (1–2) 
 Late (3–4) 13 19 24 
Histology     
 Serous 10 17 15 
 Clear cell 
 Endometrioid 
Other 
Pre-rx CA-125a (# censored) 340.2 ± 544.0 (5) 392.4 ± 646.0 (1) 463.3 ± 785.0 (4) 105.0 ± 143.4 (0) 
Endo rx     
 Tamoxifen 11 18 14 
 AI 
 Both 
Days on endo rx 351 ± 358 419 ± 661 168 ± 115 260 ± 310 
 Min 38 22 31 30 
 Max 908 2850 396 1,470 
Survival after endo rx (days) 882 ± 564 717 ± 880 738 ± 653 834 ± 774 
Overall survival (days) 2,346 ±1,302 2,019 ± 1,372 2,129±1,104 1,880 ± 1,228 

Abbreviations: dx, diagnosis; FCCC, Fox Chase Cancer Center; Mich, The University of Michigan; RPCI, Roswell Park Cancer Institute; rx, treatment; UPMC, University of Pittsburgh Medical Center.

aPre- and post-endocrine therapy CA-125 was available for 45 patients.

Endocrine therapy was given after chemotherapy, often in the setting of recurrent disease (Fig. 4A). While data on disease progression after endocrine therapy were limited, we have single values posttreatment CA-125 measurements for 45 of 70 patients and these were significantly higher than pretreatment levels (P = 0.031; Supplementary File S3). However, in light of the heterogeneity in our patient population (patients were placed on endocrine therapy at various points in their disease course and treated at different institutions) and to also capture patients who achieved disease stability, we chose to use time on endocrine therapy as a surrogate for clinical response.

Figure 4.

Identification of ERα targets associated with clinical response to endocrine therapy. A, Representative sample timeline of a patient in our cohort. After diagnosis (dx), treatment starts with debulking surgery and chemotherapy. Endocrine therapy is typically given after multiple rounds of chemotherapy if patients have a “biochemical” recurrence, determined by rising serum CA-125 levels. Endocrine therapy is continued until the disease progresses by CA-125 or other evidence of disease (e.g., imaging). B, Representative stains of ERα in our patient cohort (SP1 clone antibody) and distribution of H-scores. C, Patients with a higher H-score have better response to endocrine therapy. D,IGFBP3 expression in patients with short versus long duration of endocrine therapy. E, ERα-mediated repression of IGFBP3 in preclinical HGSOC models. E2 represses IGFBP3 expression in PEO1 and PEO4 cells and this is reversed by fulvestrant. Fulvestrant and 4OHT increase IGFBP3 expression in PH053 and PH045 explants. F, Kaplan–Meier analysis of association between IGFBP3 expression and time on endocrine therapy. G, Separation of ERαhigh and ERαlow groups by IGFBP3 expression. H, Separation of long and short treatment groups based on top 30 features identified by SVM.

Figure 4.

Identification of ERα targets associated with clinical response to endocrine therapy. A, Representative sample timeline of a patient in our cohort. After diagnosis (dx), treatment starts with debulking surgery and chemotherapy. Endocrine therapy is typically given after multiple rounds of chemotherapy if patients have a “biochemical” recurrence, determined by rising serum CA-125 levels. Endocrine therapy is continued until the disease progresses by CA-125 or other evidence of disease (e.g., imaging). B, Representative stains of ERα in our patient cohort (SP1 clone antibody) and distribution of H-scores. C, Patients with a higher H-score have better response to endocrine therapy. D,IGFBP3 expression in patients with short versus long duration of endocrine therapy. E, ERα-mediated repression of IGFBP3 in preclinical HGSOC models. E2 represses IGFBP3 expression in PEO1 and PEO4 cells and this is reversed by fulvestrant. Fulvestrant and 4OHT increase IGFBP3 expression in PH053 and PH045 explants. F, Kaplan–Meier analysis of association between IGFBP3 expression and time on endocrine therapy. G, Separation of ERαhigh and ERαlow groups by IGFBP3 expression. H, Separation of long and short treatment groups based on top 30 features identified by SVM.

Close modal

ERα status (positive vs. negative) was not associated with response (data not shown), so we examined whether ERα levels as a continuous variable or biomarkers of ERα function were predictive of time on endocrine therapy in our cohort. ERα H-scores ranged from 0 to 270 (median = 60; Fig. 4B). Patients with an H-score >60 stayed on endocrine therapy longer, suggesting a higher likelihood of response (P = 0.002; Fig. 4C). In parallel, we evaluated expression of ERα target genes (EndoRx panel, Supplementary Fig. S4A). This gene set (n = 350) includes ERα targets identified using public data on E2 treatment in hormone-responsive cancers (n = 207) and genes with known roles in antiestrogen resistance and ERα function (n = 77) or the tumor microenvironment (n = 66). The ERα target subset was validated in silico using public data from breast tumors [METABRIC (40) and Van't Veer and colleagues (41)], where it distinguished ERα-positive and -negative disease (Supplementary Fig. S5A), and in vitro using PEO4 and MCF-7 cells (Supplementary Fig. S5B).

We compared expression of the EndoRx panel between patients with a long (≥4 months) or short (<4 months) duration of endocrine therapy. We specifically chose 4 months for a cutoff to allow adequate time to achieve disease stability or response with oral hormonal agents, which are often slower to affect tumor growth than cytotoxic therapies. Among the top 11 genes significantly associated >4 months endocrine therapy were ESR1 (ERα, P = 0.0005) and ERα targets IGFBP3 (P = 1,5 × 10−4), PGR (P = 0.008), and MYC (P = 0.0055). However, only IGFBP3 was significant after correction for multiple comparisons (q = 0.026; Fig. 4D). IGFBP3 was previously described as E2-repressed in ovarian cancer (42) and we observed similar ERα regulation in our hormone-responsive models (Fig. 4E). We did not see ERα regulation of IGFBP3 expression in OVCA432 cells (Supplementary Fig. S5). Using log-rank comparisons, the P value for the association with IGFBP3 and endocrine therapy was better than that of H-score (P = 0.00002 vs. P = 0.002; Fig. 4F). We then designated tumors as ERαhigh or ERαlow (H-score >60 or<60, respectively) and IGFBP3high or IGFBP3low (above or below third-quartile expression). The majority (30/33) of ERαhigh tumors were IGFBP3low (i.e., with ERα actively suppressing IGFBP3) and patients with these tumors remained on endocrine therapy longer than the rest of the cohort. Strikingly, patients with ERαlow/IGFBP3high tumors (i.e., no functional ERα) benefited less from endocrine therapy than their ERαlow/IGFBP3low counterparts (Fig. 4G; P = 0.023). Patients with ERαlow/IGFBP3low tumors had outcomes comparable with patients with ERαhigh/IGFBP3low tumors, suggesting some ERαlow tumors retain active ERα signaling.

In light of these data, we asked whether combining H-score with an aggregation of genes would provide stronger predictive power of time on endocrine therapy than a single gene. We used an SVM algorithm to identify features (genes and/or H-score) associated with duration of endocrine therapy. The top 30 features were significantly (P < 2 × 10−16) associated with endocrine response (Fig. 4H), including H-score and IGFBP3 (Table 3). The majority of features were known ERα targets, suggesting that assessing ERα function might be a stronger predictor of time on endocrine treatment than ERα alone.

Table 3.

Top 30 features associated with endocrine response from SVM analysis

Feature nameExpression long vs. short rx
IGFBP3 Higher in short rx 
RASGRP1 Lower in short rx 
KIAA1467 Lower in short rx 
RNF144A Higher in short rx 
BCAR3 Lower in short rx 
CDCA7 Lower in short rx 
PHLDA1 Lower in short rx 
SDHA Lower in short rx 
MUC1 Higher in short rx 
PTEN Lower in short rx 
PDGFRL Higher in short rx 
STAT3 Lower in short rx 
PIK3CA Higher in short rx 
CD8 Lower in short rx 
MYC Lower in short rx 
SMTNL2 Higher in short rx 
MYBL1 Higher in short rx 
SLC25A29 Higher in short rx 
MTUS1 Higher in short rx 
ID2 Higher in short rx 
DAAM1 Higher in short rx 
INPP4B Higher in short rx 
TNF Lower in short rx 
DNAJB4 Lower in short rx 
ARHGAP26 Lower in short rx 
SLC30A1 Higher in short rx 
RDX Lower in short rx 
YPEL2 Higher in short rx 
Hscore.nona Lower in short rx 
GATA3 Higher in short rx 
Feature nameExpression long vs. short rx
IGFBP3 Higher in short rx 
RASGRP1 Lower in short rx 
KIAA1467 Lower in short rx 
RNF144A Higher in short rx 
BCAR3 Lower in short rx 
CDCA7 Lower in short rx 
PHLDA1 Lower in short rx 
SDHA Lower in short rx 
MUC1 Higher in short rx 
PTEN Lower in short rx 
PDGFRL Higher in short rx 
STAT3 Lower in short rx 
PIK3CA Higher in short rx 
CD8 Lower in short rx 
MYC Lower in short rx 
SMTNL2 Higher in short rx 
MYBL1 Higher in short rx 
SLC25A29 Higher in short rx 
MTUS1 Higher in short rx 
ID2 Higher in short rx 
DAAM1 Higher in short rx 
INPP4B Higher in short rx 
TNF Lower in short rx 
DNAJB4 Lower in short rx 
ARHGAP26 Lower in short rx 
SLC30A1 Higher in short rx 
RDX Lower in short rx 
YPEL2 Higher in short rx 
Hscore.nona Lower in short rx 
GATA3 Higher in short rx 

Abbreviation: rx, treatment.

Clinical trials of endocrine therapy suggest a subset of patients with ovarian cancer benefit from endocrine therapy. However, unlike for breast cancer, tumor ERα status (positive vs. negative) is not sufficient to predict response in HGSOC. Furthermore, linking ERα immunoscore with endocrine response in ovarian cancer has produced mixed results (13, 34, 38). Implementing biomarkers that complement ERα will be critical to identifying appropriate patient populations for endocrine therapy.

Three studies have previously tried to identify biomarkers of endocrine response (34, 35, 43), all utilizing a small panel of IHC markers. We pursued a comprehensive profile of potential biomarkers by designing and evaluating the EndoRx panel. Our analysis indicated lower IGFBP3 was significantly associated with prolonged duration of endocrine therapy (Fig. 4), corroborating previous reports that IGFBP3 expression correlates with response to therapy (43, 44). IGFBP3 expression was more strongly associated with time on therapy than H-score (Fig. 4). Moreover, low IGFBP3 identified a subgroup of ERαlow patients who received longer endocrine therapy. Given that IGFBP3 is ERα-suppressed (Fig. 4) (35), our results suggest a direct output of ERα function better designates endocrine responsiveness than ERα itself. Further supporting this is the SVM analysis: while H-score was among the top features, it ranked 29th, indicating 28 genes, including ERα targets, carried stronger associations with endocrine response.

Except IGFBP3, we did not find strong associations between previously reported biomarkers of endocrine response and outcomes in our cohort (34, 35, 43). This could be attributable to different methodology (gene expression vs. IHC) or cohort size (ours is the largest to date). Although vimentin was shown to be associated with fulvestrant response (34), difference in therapy may account for this discrepancy; independent classes of endocrine therapy may require different predictive markers.

Our EndoRx panel was designed on the basis of studies in models that recapitulate the varying endocrine response seen in clinical HGSOC. Consistent with previous reports that E2 promotes ovarian cancer cell growth (7, 8, 11), PEO1 and PEO4 cells were endocrine responsive in 2D, 3D, and ULA cultures. While PEO1 and PEO4 cells were isolated from the same patient (9), they exhibited different E2-response phenotypes. We believe that this is attributable to the differences in cell line biology because the lines were isolated at different points in the patient's disease course. The PEO1 cells were isolated from her first recurrence, whereas the PEO4 cells were isolated from a later recurrence after the tumor became platinum-refractory.

In contrast to the E2-responsive PEO1 and PEO4 cells, OVCA432 and OVSAHO were E2-independent in 2D and 3D but became E2-responsive in ULA. None of our models expressed ERβ, suggesting these effects are ERα-mediated and that ERα has unique roles throughout HGSOC progression. Elevated ERα protein in ULA supports the association between ERα levels and clinical endocrine response. Moreover, this alludes to a functional link between ERα protein levels and transcriptional activity. It is, however, also possible that a different E2-binding receptor is mediating these effects. Assessing the potential of other receptors as well as the tie between ERα function and ERα protein levels is an important direction for future investigation as it may provide insight into the efficacy of fulvestrant versus 4OHT. This also emphasizes the necessity of translational models such as PDXs and explants to fully understand ERα action in HGSOC.

We provide the first evidence of endocrine response in patient-derived HGSOC models. Fulvestrant produced stronger effects on explant proliferation and gene expression than 4OHT, suggesting modality of endocrine therapy will be an important consideration in HGSOC treatment. Selective ERα modulators (e.g., 4OHT) exhibit partial agonism in certain tissues and cancers (27) whereas selective ER degraders (e.g., fulvestrant) are pure antagonists. Potential tamoxifen agonism in HGSOC has not been explored but tamoxifen exposure was reported to promote fallopian tube and ovarian lesions (45, 46). Further comparisons of fulvestrant and 4OHT with other antiestrogens will be necessary to understand any differential class effects in HGSOC.

Our explant studies also suggest heterogeneous endocrine response across regions of HGSOC tumors: 4OHT and fulvestrant response varied in terms of both proliferation and gene expression between explants from the same PDX (Fig. 3). It is possible that interactions between different regions would facilitate response of the bulk tumor. However, strategies for combination therapy should also be considered. Two such possibilities are MAPK and Src, which are known to crosstalk with ERα and drive endocrine resistance in ovarian cancer (47, 48). Cotargeting PGR is also promising given its interaction with ERα (49) and recent reports demonstrating PGR agonists induce senescence in ovarian cancer cells (50).

We focused our study on HGSOC as it is the most common clinical subtype of ovarian cancer. However, there is likely potential for endocrine therapy in endometrioid ovarian cancer as well, which is also frequently ERα-positive. Evaluating the role of ERα and IGFBP3 in this subtype is an important area for future investigation.

Our clinical analysis is somewhat limited by its retrospective nature. Modality of endocrine therapy and number of previous therapies vary across patients and inconsistent posttreatment data necessitate the use of surrogates for clinical responsiveness. Prospective studies with posttreatment specimen collection, standardized timing of endocrine therapy, and sufficient power to compare different endocrine agents will be necessary to solidify the utility of any biomarkers. In addition, the mechanistic role of these markers (e.g., IGFBP3) in ovarian cancer should be followed up in preclinical studies.

In summary, ERα modulates growth, survival, and gene expression in a subset of HGSOC and targeting ERα can be effective clinically. Inhibiting ERα with fulvestrant and 4OHT modulates expression of MYC, PGR, and IGFBP3 in HGSOC models. Moreover, expression of these genes reflects clinical endocrine response. Our findings may enable selection of HGSOC patients who would benefit from endocrine therapy.

P. Haluska holds ownership interest (including patents) in the Mayo Ovarian Avatar Program. No potential conflicts of interest were disclosed by the other authors.

Conception and design: C.L. Andersen, M.J. Sikora, G. Mantia-Smaldone, A.V. Lee, R.P. Edwards, S. Oesterreich

Development of methodology: C.L. Andersen, M.J. Sikora, R.P. Edwards, S. Oesterreich

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): C.L. Andersen, M.M. Boisen, A. Christie, P. Haluska, G. Mantia-Smaldone, K. Odunsi, K. McLean, R.P. Edwards, S. Oesterreich

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): C.L. Andersen, M.J. Sikora, M.M. Boisen, T. Ma, G. Tseng, Y.S. Park, S. Luthra, U. Chandran, A.V. Lee, R.P. Edwards, S. Oesterreich

Writing, review, and/or revision of the manuscript: C.L. Andersen, M.J. Sikora, M.M. Boisen, T. Ma, Y.S. Park, S. Luthra, U. Chandran, G. Mantia-Smaldone, K. Odunsi, A.V. Lee, R.P. Edwards, S. Oesterreich

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): C.L. Andersen, M.M. Boisen, P. Haluska, K. McLean, R.P. Edwards, S. Oesterreich

Study supervision: C.L. Andersen, R.P. Edwards, S. Oesterreich

Other (pathology tissue analysis of HandE and all immunostains): E. Elishaev

We thank Dr. Marc Becker for guidance on establishing PDX models and Dr. Brian Szender for assistance in procuring RPCI specimens.

This work was supported by the NIH (F31CA186736 and T32GM008424 to C.L. Andersen; K99CA193734 to M.J. Sikora; and R01CA184502 to P. Haluska), the Magee-Womens Research Foundation (to S. Oesterreich), the University of Pittsburgh Cancer Institute (UPCI), and the ARCS Foundation (to C.L. Andersen). Additional support was provided by the Department of Defense (CDMRP W81XWH-13-1-0205 to S. Oesterreich; Ovarian Cancer Academy Early Career Investigator Award W81XWH-15-0194 to K. McLean), the RPCI-UPCI SPORE (5P50CA159981-03 to R.P. Edwards and K. Odunsi), and the Mayo Clinic SPORE (2P50CA136393 to P. Haluska). This project used the UPCI Cancer Biomarkers Core Facility, which is supported by NIHP30CA047904.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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