Abstract 500: Predicting patient response to immuno-oncology agents in vitro using 3D cultures

Immuno-oncology (I/O) based therapeutics, including cellular therapies and checkpoint inhibitors have surged in the last 2 years, but the technology to accurately test them in a pre-clinical setting is significantly lacking. While animal models have tried to provide accurate testing platforms, the ultimate goal of a matched patient tumor and immune system is not achievable in mice. To overcome this issue, we have developed two 3D tissue systems for in vitro testing that combine a patient’s tumor cells and autologous immune cells for accurate testing and prediction. We hypothesize that our 3D cell culture systems can recapitulate the patient’s tumor microenvironment to detect I/O response. Our spheroid-based system allows us to monitor how primary T-cells are affected by paired tumor cells and/or the PD-1 inhibitor pembrolizumab using flow cytometry. We have successfully detected pembrolizumab binding to T-cells in a dose dependent manner, clonal expansion of lymphocyte populations, as well as increased expression of activation markers on CD3+ cells following combination with tumor cells and exposure to pembrolizumab. This model also accurately detects CD3+CD8+ T-cell mediated tumor cell death and can be used to track changes in secreted cytokines and chemokines such as Granzyme B and IFN gamma. Our second model, a 3D microtumor platform, allows us to detect immune cell migration and infiltration and therapy related cell death. Our results show pembrolizumab can increase lymphocyte infiltration while simultaneously decreasing microtumor growth in matched patient samples whose tumor cells express PD-L1 and whose lymphocytes are CD8+. Cytokine secretion detected by multiplex technology from our microtumor model supports our observed enhanced T-cell activation in the presence of pembrolizumab. The data generated from our two complex 3D in vitro models can recapitulate in vivo biology in order to derive correlations to I/O drug response. These models can be utilized for preclinical testing of new I/O agents as well as for patient response predictions to I/O therapies. Citation Format: Kathryn M. Appleton, Qi Guo, Ashley Elrod, Alina Lotstein, Lillia Holmes, Teresa M. DesRochers. Predicting patient response to immuno-oncology agents in vitro using 3D cultures [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 500.