Abstract
Abstract New anticancer drug development is an expensive and time consuming process, which typically can take more than 10 years and cost over a billion dollars. Although a majority of late discovery drug candidates demonstrate potency in preclinical models, most will ultimately fail to achieve efficacy in clinical trials. While recent strides have been made to improve preclinical models, the continued widespread use of traditional models creates translational challenges during clinical development. An intrinsic challenge for drug developers is to close the gap between preclinical modeling and translational efficiency for patients. Accurately modeling core attributes of the human tumor microenvironment (TME) in preclinical models is key for identifying novel targets, lowering toxicity and improving translational success. Even for advanced patient-derived xenograft (PDX) in vivo models, the cytokines generated by murine stromal cells fail to replicate many important paracrine networks, which can mislead preclinical pharmacology outcome data. To address this gap, we have begun to establish and characterize nearly 1,000 novel patient tumor samples, spanning over a dozen cancer indications, into robust human TME-restored 3D cell culture models and humanized patient derived xenograft models. Our goal is to improve overall patient-derived tumor model initiation success rates and subsequent translational pharmacology. Citation Format: Jing Zhang, Dabing Yang, Huilin Wang, Qiong Song, Hui Li, JP Shaw, Tianjing Deng. Novel tumor microenvironment (TME) restored 3D cell culture model and humanized patient-derived xenograft model for cancer research and drug evaluation. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4261.
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