Abstract 2750: Multiplexed Plate-Reader Based Drug Screening of 3D-Tumoroid Models

Cancer drug development is an extremely challenging and resource-consuming process with a dismal success rate of 5%. The high failure rate is partly due to the inadequacy of traditional 2D cell culture model to predict drug efficacy and toxicity. A highly accurate and representative system is therefore urgently needed to improve cancer drug discovery and development process. The emerging 3D cancer models can better recapitulate the in vivo tumor microenvironment and have shown closer gene expression profiles to clinical samples compared to 2D models. Another crucial element of in vitro cancer models is the source of cancer cells: patient-derived models have shown advantages to better capture tumor heterogeneity and clinically relevant genetic alterations of the tissue origin compared to traditional cancer cell lines. Several studies showed that response of patient-derived models to treatment reflects the response of patients from which the organoids are derived, suggesting they are great platform for studies of personalized medicine. Hereby, we performed a proof-of-concept high throughput multiplexed plate-reader based drug screening assay on 3D patient-derived tumoroids. Methods: Patient-derived tumoroids were sequenced for cancer relevant mutations, copy number variants, and altered gene expression using multi-biomarker targeted next generation sequencing (NGS) and RNA-seq. 3D tumoroid lines derived from three different colorectal cancer patient samples, together with a colorectal cancer cell line were treated with chemotherapy, and targeted therapy agents. The same tumoroid and cell lines were cultured and treated in 2D as experimental control. Drug response readout was multiplexed using three different plate reader-based assays, measuring the reducing power, ATP, and the release of lactate dehydrogenase from treated cells. Results: Comparable drug responses were observed from three different viability cytotoxicity assays. Different patient-derived tumoroids demonstrated differential drug sensitivity that correlates with their clinical cancer stages. Both patient-derived and cancer cell lines cultured in 3D models showed markedly increased drug resistance compared 2D adherent culture. Differential response was also observed between cancer cell lines vs patient-derived lines. Conclusion: Taken together, these findings suggest the potential advantages of 3D patient-derived tumoroid models over 2D culture and cancer cell lines for accurate prediction of drug response. Through targeted NGS and RNA-seq, patient-specific drug targets could be identified for personalized drug screening. Selected drug candidates could be further subjected to in vivo drug validation using patient-derived xenograft model generated from the same donor. In combination with other derived models or large donor banks, this workflow provides a platform for large-scale drug discovery workflows and precision medicine. Citation Format: Xiaoyu Yang, Andrew Tsao, Garrett Wong, Chris Yankaskas, Colin Paul, Brittany Balhouse, Amber Bullock, Anthony Chatman, Shyanne Salen, Sybelle Djikeng, Matt Dallas, David Kuninger. Multiplexed plate-reader based drug screening of 3D-tumoroid models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2750.