Abstract 1890: Development of the drug efficacy testing in ex vivo 3D cultures (DETECT) platform and its application to functional precision medicine in ovarian cancer
Authors: Åkerlund Emma , Gudoityte Greta , Lamodiere Elisabeth Moussaud , Carlson Joseph , Wallin Emelie , Fernebro Josefin , Kallioniemi Olli , Östling Päivi , Joneborg Ulrika , Seashore-Ludlow Brinton 
Published: June 2022

Many ovarian cancer (OC) patients receiving chemotherapy relapse with acquired resistance, hence novel treatment allocation strategies are urgently needed. 3D cell culture models and organoid technologies have emerged as exciting tools to study cancer. Despite the advances, there is a need for protocols that can quickly generate patient-relevant 3D models for high-throughput drug screening and for diagnostic drug sensitivity testing. Ideally, such methods should be cost-effective, provide multi-parametric data to reveal distinct phenotypes, have single cell resolution to reveal heterogeneity and cell interactions, meet diagnostic timeframes and be miniaturized to allow the analysis of many drugs and combinations with small numbers of primary tumor cells. Here, we aimed to develop a robust technology for high-throughput ex vivo drug sensitivity testing for functional precision medicine using OC tissue and ascites samples (mostly high-grade serous carcinoma) from patients. We present a scalable drug screening platform: DETECT (Drug Efficacy Testing in Ex-vivo 3D Cultures), where tumor-derived patient cells can be rapidly screened within one week from sampling. Using this information patient-specific drug combinations are subsequently designed and tested with these data available within 9 days. This is much faster than with most screening protocols for organoids and PDC models where many weeks or months are required for establishment of the models and expansion of the required numbers of cells. We have currently tested the efficacy of 58 selected chemo- and targeted drugs in 5 doses using high content imaging and then a complete dose-matrix of 3 combinations at step 2. We report robust drug screening data in 15 out of 18 OC patient samples, which has resulted in a functional taxonomy of patient samples and a taxonomy of drugs based on their efficacy across patient samples. Some of the most common responses were seen for the BCL-XL inhibitor A-1331852 (9/15 patients), Topotecan (7), Dactinomycin (7), Omipalisib (6) and Omacetaxine (6). All but 2 drugs showed efficacy in at least one OC sample, suggesting heterogeneity and opportunities to make use of unique drug response patterns. Combination screening revealed that Carboplatin and A-1331852, a BCL-XL inhibitor, showed increased efficacy in 3 of the 5 tested patient samples. In conclusion, our 3D HT-drug testing assay DETECT with a combination screening capability could in the future be useful for guiding individualized treatment in a clinical setting as well as for identifying existing and emerging drugs and drug combinations for repurposing in OC.

Citation Format: Emma Åkerlund, Greta Gudoityte, Elisabeth Moussaud Lamodiere, Joseph Carlson, Emelie Wallin, Josefin Fernebro, Olli Kallioniemi, Päivi Östling, Ulrika Joneborg, Brinton Seashore-Ludlow. Development of the drug efficacy testing in ex vivo 3D cultures (DETECT) platform and its application to functional precision medicine in ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1890.