Abstract B48: Design of effective combination therapies for high-grade serous ovarian cancer using patient-derived xenograft models.
Authors: Iavarone Claudia , Zervantonakis Ioannis , Chen Hsing-Yu , Palakurthi Sangeetha S. , Liu Joyce Fu , Matulonis Ursula A. , Drapkin Ronny I. , Mills Gordon B. , Leverson Joel D. , Sampath Deepak , Brugge Joan S. 
Published: May 2016

Abstract
Despite advances in understanding the genetics and molecular biology of high grade serous ovarian cancer, there have not been any significant improvements in the outcome of patients treated with approved therapies to date. The overall aim of our studies is to identify synergistic drug combinations for the treatment of high-grade serous ovarian (HGS-Ov) cancer and the biomarkers that predict sensitivity for future translation in clinical trials. In particular, this study focuses on the vulnerabilities of patient-derived ovarian cancer cells to inhibition of anti-apoptotic proteins and the design of novel combination therapies to overcome drug resistance and improve the response of selected patients to a particular set of targeted therapies.
Previous studies from our lab provided evidence that inhibition of BCL-2/XL can significantly enhance the sensitivity of tumor cells to targeted therapies in ovarian and breast cancer cell line models (Muranen T, et al. Cancer Cell 2012). In this study, we evaluated the efficacy of this combination treatment in ascites cells derived from 15 high-grade serous patient-derived ovarian cancer xenografts (PDXs). We found that inhibitors of PI3K/mTOR (GNE-493) and BCL-2/XL (ABT-737) act synergistically ex vivo, with an ~15 fold variability among the 15 patient-derived samples. A large scale in vivo experiment is ongoing to evaluate the efficacy of this combined treatment in six PDX models.
To identify biomarkers that predict drug sensitivity we performed proteomic Reverse Phase Protein Array (RPPA) and immunoblot analyses. We found that baseline levels of the pro-apoptotic protein BIM correlate with sensitivity to BCL-2/XL inhibition. This motivated us to examine the basis for low BIM expression. In three of the least sensitive PDX models, we found that low levels of BIM correlated with ERK activation based on increased ERK phosphorylation and that inhibition of MEK by PD-0325901 in these models caused upregulation of BIM, as predicted from previous published reports which demonstrated that phosphorylation of BIM by ERK causes its degradation (Ley R, et al. Biol Chem 2003). We then examined the sensitivity of these PDX models to ABT-737 and PD-0325901, MEK162, or CI-1040 ex vivo and observed strong synergy resulting in reduction of cell viability and increased cell death. These results suggest that low BIM/high phosphoERK is a potential biomarker for sensitivity of ovarian tumors to combined MEK and BCL-2/XL inhibition. We now plan to examine the efficacy of drug combinations that target MEK and BCL-2/XL in these PDX models in vivo.
Our studies promise to lead to the identification of new drug combination therapies for HGS-Ov cancer treatment and predictive biomarkers to stratify patients that can benefit from these targeted therapies.
Citation Format: Claudia Iavarone, Ioannis Zervantonakis, Hsing-Yu Chen, Sangeetha S. Palakurthi, Joyce Fu Liu, Ursula A. Matulonis, Ronny I. Drapkin, Gordon B. Mills, Joel D. Leverson, Deepak Sampath, Joan S. Brugge. Design of effective combination therapies for high-grade serous ovarian cancer using patient-derived xenograft models. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: Exploiting Vulnerabilities; Oct 17-20, 2015; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(2 Suppl):Abstract nr B48.