Abstract B80: Predictive treatment response models for epithelial ovarian cancer: Comparison of 2D, 3D, and in vivo models

Abstract

Abstract Introduction: Epithelial ovarian cancer (EOC) is still a deadly disease, with a 5-year overall survival of 45%. Current research focuses on the development of new targeted and personalized therapies to improve survival in these patients. The drug discovery pipeline is dependent on preclinical models, which have mostly focused on 2D systems because of time and cost efficiency. However, it is currently unclear whether they accurately reflect patient response and whether other in vitro models may better predict therapeutic response. Preliminary data from our laboratory suggest that the sensitivity to carboplatin chemotherapy varies between 2D and 3D in vitro models. We hypothesize that the 3D model will more closely reflect therapeutic response. The primary objective of this study is to characterize the sensitivity to carboplatin of our EOC cell lines in 2D monolayers and 3D spheroids and compare them to their in vivo response using our xenograft mouse models. Methods: We are injecting NOD-RAG mice with 7 EOC cell lines (TOV112D, TOV21G, OV4485, OV4453, OV1946, OV90, OV3133). At 200mm3, weekly carboplatin treatments (group1 = control, group 2= 25mg/kg, group 3= 50mg/kg, group 4= 75mg/kg) are given up to 6 cycles. Tumor volume and survival curves are used to categorize chemosensitivity between cell lines. Furthermore, the same cell lines are seeded in ultra-low attachment microplates to form spheroids over 48hr and are thereafter treated with 24hr of carboplatin. Flow cytometry analyses are done to classify cell lines. Results: The results for the 2D models using clonogenic assays (IC50) of the 7 cell lines have previously been published. Thus far, we have completed a first set of in vivo experiments for TOV21G showing a nonsignificant tumor growth suppression after 6 doses (no difference between the 3 treated and the nontreated group). Tumor growth suppression for OV90 was statistically significant with 50mg/kg and 75mg/kg of carboplatin after 6 doses. This demonstrates thus far that the most resistant cell line in 2D is more sensitive in an in vivo model. Conclusion: The results will help define the most reliable preclinical model with the highest translational potential to predict treatment response. Citation Format: Melica Nourmoussavi, Euridice Carmona, Anne-Marie Mes-Masson. Predictive treatment response models for epithelial ovarian cancer: Comparison of 2D, 3D, and in vivo models [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr B80.