Potential role of antiestrogens in treating ovarian cancer

Ovarian cancer is the deadliest of all gynecologic malignancies and remains the fifth leading cause of cancer related deaths among women (1). High-grade serous ovarian cancer (HGSOC) is the most predominant and lethal subtype accounting for about 70% of ovarian cancer cases (2). The standard of care involves platinum and taxol based cytotoxic chemotherapy which has remained unchanged for the past 3 decades (3,4). Development of individualized targeted therapies catering to the specific tumor characteristics is needed. Andersen and colleagues report the presence of a subset of estrogen dependent HGSOC and have identified estrogen responsive features, which can be used to determine patient cohorts who can benefit from endocrine therapy. Endocrine based therapies have been found to be effective when targeting estrogen receptor (ER) in ER positive metastatic breast cancer (5). Inhibition of ER is considered as an alternative in recurrent ovarian cancer patients who are resistant to the carbo-taxol based standard chemotherapy (6). However, changes in expression of ER have been reported between matched primary and recurrent ovarian cancer (7). Therefore, it is essential to take this into account while planning therapies involving ER inhibition. In their article Andersen and colleagues suggest that many OC patients exhibit high expression of ERα and have identified an ER dependent gene expression signature (8). They further report that the selective ER-alpha down-regulator (SERD) fulvestrant is more effective than the selective ER modulator (SERM) 4-Hydroxytamoxifen (4OHT) in inhibiting the growth of ERα expressing ovarian cancer.

Despite high expression of ER-alpha in ~80% of HGSOC, the ERα gene amplification is relatively rare, occurring in about 2% of cases. Though some small but promising clinical trials of endocrine therapy having been conducted, ER-alpha has been understudied as a target in this disease. Targeting ER-alpha has shown promise in laboratory models and in clinical trials but identification of the appropriate patient subset has remained elusive. A low percentage of ER positive ovarian cancer patients respond to initial anti-estrogen therapy based on blocking ER compared to 50% responders in case of ER-positive breast cancer (9). Moreover, there are conflicting reports in the prognosis of ovarian cancer patients with high ER expression (10). Microarray analysis of gene expression of ERα regulated genes in PEO1 ovarian cancer cells revealed a signature of 1,200 cancer related genes (11). On the other hand, ERβ did not play a role in the cellular response to 17beta-estradiol treatment (11). Andersen et al. (8) have attempted to identify features associated with estrogen-responsive HGSOC cell line and patient derived HGSOC models. They report a subset of HGSOC xenograft models, which require estrogen for growth and survival. Estrogen-regulated transcriptome data were overlapped with public datasets to develop a comprehensive panel of ERα target genes. Prolonged endocrine therapy resulted in a significant decrease in IGFBP3. This indicated that effects of ERα activation were a superior indicator of endocrine therapy effectiveness since IGFBP3 is suppressed by ERα. Previous studies have attempted to identify markers of tumor endocrine response and only their IGFBP3 expression results agreed with those studies. The authors reason that this could possibly be due to the differences in the detection methods used and the sample size. To determine if estrogen regulates growth, four ERα positive HGSOC cell lines were treated with E₂ and fulvestrant or 4OHT an active metabolite of tamoxifen, which binds ERs and estrogen-related receptors. Interestingly, estrogen is metabolized differentially in ovarian cancer cells as compared to the ovarian surface epithelium. Steroid sulphatase induced by tumor micro environmental cytokines and the suppression of estrogen sulfotransferase result in an increase in E₂ (12).

Andersen and colleagues demonstrate that some HGSOC cells are E₂ responsive but the response depended on ERα and the 3D context (8). PEO1, PEO4, and OVCA432 cells expressed high levels of ERα and OVSAHO had a low expression while all of them are ERβ negative. The effects of E₂ on these cells were assayed both in 2D as well as in 3D cultures. 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. Whole-genome microarray analysis was performed in PEO4 and PEO1 cells after treatment with E₂ along with fulvestrant or 4OHT. E₂ was found to regulate the expression of 221 and 291 genes in PEO1 and PEO4, respectively. Notably, fulvestrant was more effective than 4OHT at blocking E₂ effects; and mitigated expression of 96% and 99.5% E₂ mediated gene expression in PEO1 and PEO4. Similar to growth in 2D, E₂ treatment increased spheroid formation in PEO4 cells but not in OVCA432 cells. Seeding on ultra low attachment plates increased ERα mRNA and protein levels versus 2-D conditions, which may mediate a novel E₂ response. The effect of E₂ on PEO1 appeared to be more through a decrease of cell death rather than increased proliferation. Survival in forced suspension typically requires induction of anoikis resistance. However, E₂ did not have any effect on caspase-3/7 activity, suggesting that E₂ may mediate its effects through other survival mechanisms. Consistent with the in vitro results, E₂ treatment was found to increase tumor growth in mice through the induction of GREB1 and MYC expression.

In addition, using HGSOC patient derived xenograft (PDX) models, Andersen and colleagues demonstrated that fulvestrant was more effective than 4OHT (8). Traditionally approaches to inhibit ER pathways have been using SERMs like 4OHT or its precursor tamoxifen and subsequently SERDS like fulvestrant were introduced. Aromatase inhibitors, which interfere with ER ligand synthesis, have also been tried. Based on the evidence provided by Andersen and colleagues, fulvestrant would be a potentially superior mode of endocrine therapy to be considered in the clinic. Aromatase inhibitors have not been compared and should potentially be tested in the future in a direct comparison of the effects on tumor as well as the effects on the gene signature.

Recently, the Conejo-Garcia group has reported the cancer cell independent role of estrogen signaling in cancer progression (13), which points towards the role of estrogen signaling in the tumor microenvironment. They demonstrate that the estrogen insensitive tumors were still helped by estrogen signaling through the enhancement of the intrinsic immunosuppressive activity as well as the mobilization of myeloid-derived suppressor cells. Similarly, stromal fibroblasts expressing ERα promote tumor growth in prostrate cancer (14). This opens up the possibility of targeting endocrine-based therapies to the tumor microenvironment.

There are several questions for the field including whether we have a reliable gene expression signature that will enable us to target a subset of HGSOC tumors with effective endocrine therapy? Future prospective longitudinal studies comparing pre- and post-treatment samples using larger cohorts and uniform assay techniques would result in a more robust functional signature of ERα effects. Can a similar signature be derived for the tumor microenvironment compartment? Are the tumor cell intrinsic and extrinsic effects mutually exclusive? Can patients who do not express the tumor ERα gene signature still benefit from the effects of targeting the tumor microenvironment? Addressing these questions in future studies will potentially direct the development of effective endocrine therapies to treat HGSOC.

Acknowledgments

Funding: SM is supported by a Biomedical Research Grant from Indiana University School of Medicine. AKM is supported by DoD Ovarian Cancer Academy and Colleen’s Dream Foundation.

Footnote

Provenance and Peer Review: This article was commissioned and reviewed by the Section Editor Zheng Li (Department of Gynecologic Oncology, The Third Affiliated Hospital of Kunming Medical University, Kunming, China).

Conflicts of Interest: Both authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/tcr.2017.05.30). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin 2016;66:7-30. [Crossref] [PubMed]
2. Haley J, Tomar S, Pulliam N, et al. Functional characterization of a panel of high-grade serous ovarian cancer cell lines as representative experimental models of the disease. Oncotarget 2016;7:32810-20. [PubMed]
3. Vaughan S, Coward JI, Bast RC Jr, et al. Rethinking ovarian cancer: recommendations for improving outcomes. Nat Rev Cancer 2011;11:719-25. [Crossref] [PubMed]
4. Mitra AK. Ovarian Cancer Metastasis: A Unique Mechanism of Dissemination. Available online: https://www.intechopen.com/books/tumor-metastasis/ovarian-cancer-metastasis-a-unique-mechanism-of-dissemination
5. Osborne CK, Schiff R. Mechanisms of endocrine resistance in breast cancer. Annu Rev Med 2011;62:233-47. [Crossref] [PubMed]
6. Tropé C, Marth C, Kaern J. Tamoxifen in the treatment of recurrent ovarian carcinoma. Eur J Cancer 2000;36:S59-61. [Crossref] [PubMed]
7. Feng Z, Wen H, Ju X, et al. Hormone receptor expression profiles differ between primary and recurrent high-grade serous ovarian cancers. Oncotarget 2017; [Epub ahead of print]. [PubMed]
8. Andersen CL, Sikora MJ, Boisen MM, et al. Active Estrogen Receptor-alpha Signaling in Ovarian Cancer Models and Clinical Specimens. Clin Cancer Res 2017; [Epub ahead of print]. [Crossref] [PubMed]
9. Halon A, Materna V, Drag-Zalesinska M, et al. Estrogen receptor alpha expression in ovarian cancer predicts longer overall survival. Pathol Oncol Res 2011;17:511-8. [Crossref] [PubMed]
10. Aust S, Bachmayr-Heyda A, Pateisky P, et al. Role of TRAP1 and estrogen receptor alpha in patients with ovarian cancer -a study of the OVCAD consortium. Mol Cancer 2012;11:69. [Crossref] [PubMed]
11. O’Donnell AJ, Macleod KG, Burns DJ, et al. Estrogen receptor-alpha mediates gene expression changes and growth response in ovarian cancer cells exposed to estrogen. Endocr Relat Cancer 2005;12:851-66. [Crossref] [PubMed]
12. Ren X, Wu X, Hillier SG, et al. Local estrogen metabolism in epithelial ovarian cancer suggests novel targets for therapy. J Steroid Biochem Mol Biol 2015;150:54-63. [Crossref] [PubMed]
13. Svoronos N, Perales-Puchalt A, Allegrezza MJ, et al. Tumor Cell-Independent Estrogen Signaling Drives Disease Progression through Mobilization of Myeloid-Derived Suppressor Cells. Cancer Discov 2017;7:72-85. [Crossref] [PubMed]
14. Da J, Lu M, Wang Z. Estrogen Receptor Alpha (ERα)-Associated Fibroblasts Promote Cell Growth in Prostate Cancer. Cell Biochem Biophys 2015;73:793-8. [Crossref] [PubMed]