Abstract
Abstract Introduction: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal common malignancies, with little improvement in patient outcomes over the past decades. We have developed a novel methodology to culture organoids from both human healthy pancreatic ductal epithelial tissues and PDAC. A collection of patient-derived organoids (PDO), grown using this protocol, numbers over 100 models to date. The 100% neoplastic purity of the organoid cultures facilitates molecular characterization that has been traditionally challenging in the pauci-cellular state of primary pancreatic tumors. These PDO open new opportunities for deep genomic and transcriptomic studies of the disease, and for individualized drug screens. Here we demonstrate that accurate predictive models of response to pharmacological treatments of PDAC can be developed using data from such screens alongside molecular profiles of the PDO. Methods: Molecular analysis of the PDO library yielded genomic and transcriptional profiles of the cultures, including those of copy number variation (CNV), mutations in the exome and mRNA expression. From these, we drew features for prediction of drug responses. Using molecular features drawn from these profiles, we developed a panel of predictive models for response to standard-of-care cytotoxic agents and a number of targeted treatments. We employed Random Forest (RF) regression as a machine-learning tool for this purpose. Results: PDO are faithful models of PDAC, whose molecular features closely resemble those of PDAC tumor specimens. Using a subset of these features, we were able to accurately learn PDO responses to cytotoxic agents: for each of the five agents considered, the predicted drug response correlated strongly (p < 10-7) with the observed value. A similar accuracy of prediction was achieved for a number of targeted agents. Conclusion: PDOs are a valuable resource for molecular and pharmacological characterization of PDAC, with a potential to guide clinical decisions with regard to treatment. Citation Format: Astrid Deschênes, Pascal Belleau, Dennis Plenker, Amber Habowski, Hardik Patel, Youngkyu Park, Hervé Tiriac, Lindsey A. Baker, Alexander Krasnitz, David A. Tuveson. Genomic and pharmaco-genomic profiling of pancreatic cancer using patient-derived organoids [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 4042.
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