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• W4200336760 abstract "<b>Introduction</b> The staggeringly high failure rate of clinical trials for oncology drugs can be attributed to many factors, including suboptimal <i>in vitro</i> and <i>in vivo</i> models that fail to recapitulate the complexity of the human tumor microenvironment (TME) or predict patient response. Translational human 3D cell culture models, such as patient-derived tumor organoids, have begun to bridge the gap between tissue culture systems and patients in the clinic. However, even in these advanced models, the endogenous cells of the TME, such as tumor infiltrating lymphocytes (TILs), fibroblasts, macrophages and other immune cells, are absent. These TME components have been shown to express important drug targets and play a critical role in both tumor progression and modulation of the response to drugs. Here we present a novel patient avatar platform that combines a short-term 3D <i>ex vivo</i> tumor culture system with high content image (HCI)-based analysis. Patient tumor tissues from pleural fluid, ascites, surgical resections or biopsy were tested <i>ex vivo</i> to preserve tumor heterogeneity and resident immune cells, removing the need for artificial co-culture systems. This study entailed a detailed quantification of tumor sensitivity to targeted therapies, standard of care, and novel (immune) drugs and drug combinations, tested on different cancer types. <b>Methods</b> Patient tumor tissues were obtained from ongoing clinical trials in the Netherlands as well as from commercial tissue providers, and processed within 24 hours to preserve the native tumor heterogeneity and TME. Freshly isolated tumor cells from ovarian, breast cancer and non small cell lung cancer (NSCLC) patients were embedded in a protein-rich hydrogel and exposed to panels of single and combination drug treatments at different concentrations in a 384-well format for 5-7 days. Effects of drugs and combination therapies on physiologically relevant morphological features, such as tumor cell killing, growth arrest, invasion and immune cell proliferation, were measured using our proprietary automated HCI analysis platform. <b>Results</b> Patient-specific drug sensitivity profiles were generated based on the response to a broad range of drugs including standard of care (e.g., platinum, paclitaxel, gemcitabine), targeted therapies (e.g., PARP and EGFR inhibitors), and activity of immunomodulatory drugs (e.g., ipilimumab, pembrolizumab and STING agonists). Accurate and reproducible response evaluation demonstrates the feasibility of preclinical drug testing on patient primary material within the platform. <b>Conclusion</b> Our platform successfully combined proven <i>ex vivo</i> drug testing protocols using fresh patient tumor tissue with preserved TME components and advanced 3D HCI analysis. Our approach offers a rapid, reliable and patient-relevant approach to test various candidate compounds (e.g., antibodies, antibody-drug conjugates and small molecules) for various cancer types. It has the potential to significantly improve the preclinical evaluation of drugs, and also to improve the success rate of clinical trials. <b>Citation Format:</b> Nataliia Beztsinna, Fanny Grillet, Niels Meesters, Donny van der Meer, Lidia Daszkiewicz, Kuan Yan, Emma Spanjaard, Willemijn Vader, Leo Price. Novel patient avatar platform for oncology drug testing using 3D <i>ex vivo</i> models derived from fresh patient tumor tissues [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2021 Oct 7-10. Philadelphia (PA): AACR; Mol Cancer Ther 2021;20(12 Suppl):Abstract nr P115." @default.
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• W4200336760 date "2021-12-01" @default.
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• W4200336760 title "Abstract P115: Novel patient avatar platform for oncology drug testing using 3D ex vivo models derived from fresh patient tumor tissues" @default.
• W4200336760 doi "https://doi.org/10.1158/1535-7163.targ-21-p115" @default.
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