Abstract 94: Identifying biomarkers of estrogen response in models of serous ovarian cancer.

Abstract

Abstract Ovarian cancer is the fifth leading cause of cancer death among women in the United States. Despite advances in treatment for other cancers, ovarian cancer patient prognosis has not improved significantly since the advent of platinum-based chemotherapy. It is a highly heterogeneous disease with at least four distinct histological subtypes: serous, mucinous, endometrioid, and clear cell. However, no subtype- or biomarker-specific therapies are approved for ovarian cancer. Identifying targeted therapies is crucial to improving clinical outcomes. Specific therapies will likely vary based on tumor histology and biomarkers. Expression of estrogen receptor alpha (ER) is a well established biomarker of response to endocrine therapies in breast cancer. Despite the success of anti-estrogen therapies in treating breast cancer, little attention has been given to their potential in ovarian cancer. However, epidemiologic studies show that approximately 70% of epithelial ovarian tumors express ER, particularly serous and endometrioid subtypes, and that estrogen plays a role in ovarian cancer etiology. Further, clinical data suggest that a subset of ovarian cancer patients can be successfully treated with endocrine therapy. We hypothesize that some ovarian tumors require estrogen for growth and that predictive biomarkers will identify patients who will benefit from endocrine therapy. Using cell line models, we examined the response of ovarian cancer cells to estrogen (E2) and anti-estrogens with regard to gene expression and cell proliferation. E2 induces expression of canonical ER target genes (e.g. GREB1) in these cells, suggesting that they are estrogen-responsive. We observe that 4-hydroxytamoxifen and fulvestrant inhibit growth of ovarian cancer cells including the chemo-resistant line PEO4. Gene expression microarray studies identified additional E2-regulated genes in ovarian cancer cells that may be utilized as biomarkers of ER activity. We are expanding our studies to in vivo models (human primary tumor xenografts) to evaluate the role of E2 in driving tumor progression and determine the efficacy of anti-estrogens in treating serous ovarian cancer. There is a critical need for targeted therapies in ovarian cancer. Our studies will determine if endocrine responsiveness correlates with gene expression of specific biomarkers, which may lead to the identification of predictive clinical markers of response to endocrine therapy. Citation Format: Courtney L. Andersen, Matthew J. Sikora, Paul Haluska, Steffi Oesterreich. Identifying biomarkers of estrogen response in models of serous ovarian cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 94. doi:10.1158/1538-7445.AM2013-94