Abstract B14: Engineering a long-term in vitro model of breast cancer tumor resistance for high-throughput predictive drug screening

Solid tumors often show high levels of heterogeneity, making targeted therapeutics especially challenging. In breast cancer, for example, the primary cancer type may be eradicated with targeted therapy, but the minority subclones that are drug resistant can emerge as the new majority clones. Here, we present an in vitro model for long-term culture of ex vivo tumors (e.g., from biopsies) that maintain the tumor microenvironment such that tumors can be dramatically reduced with drugs yet maintained to observe long-term drug resistance. Our in vitro “avatars” (“ivitars”) utilize perfused 3D cultures in a high-throughput, robust, and easily maintained format. We demonstrate in vivo relevance with heterogeneous tumors composed of human breast cancer cell lines MCF-7 and LCC9, with sublines that are tamoxifen sensitive or resistant, in combination with stromal cells. Our results indicate that stromal cells, extracellular matrix components, and relevant biophysical stimuli such as fluid flow in the tumor microenvironment enhance tumor resistance to tamoxifen, even in tamoxifen-sensitive tumor cells. Together, our results suggest that the model can be used as a robust and high-throughput system for studying tumor resistance and will be further investigated for use in patient-specific testing. Citation Format: Rachel Weathered, Ruolan Zhou, Melody A. Swartz. Engineering a long-term in vitro model of breast cancer tumor resistance for high-throughput predictive drug screening [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr B14.