Abstract 3861: 3D ex vivo PDX cell model screening to better predict in vivo outcome

Abstract

Abstract Patient-derived xenograft (PDX) models have been highly demanded in preclinical drug discovery and development due to several advantages over conventional 2D cell culture system: 1) reflection of the heterogeneity, molecular and histopathologic signatures of the original tumor than cell lines or genetically engineered mouse models, and 2) certain degree of correlation of their drug-response profiles with clinical response. Certain limitations of using PDX models, however, do exist, including low throughput in candidate drug screening, lack of dose-response curves, high cost and time-consuming studies, and progressive loss of human-derived stromal elements over passages. To overcome these disadvantages, we sought to develop ex vivo 3D assay format on cells isolated from early passage PDX models, and provide genetic mutation information to better interpret results. Moreover, we attempted to incorporate immunotherapy strategy into the 3D system as well. We have recently built up an ex vivo cell bank containing more than 300 frozen ex vivo tumor cells dissociated from freshly isolated PDX tumor tissues. We have collected five panels of such frozen ex vivo cells, each panel representing more than 50 models in a specific tumor type. SOC compounds corresponding to each unique tumor panel were tested, and will be discussed. Moreover, we have established a 3D immune cell and ex vivo somatic tumor cell co-culture system to evaluate drug efficacy of immune checkpoint inhibitors aPD1, aPDL1 and CTLA4 antibodies either as single agent or in combination with small-molecule inhibitors. The data will be presented. In summary, we have developed a robust and reproducible 3D ex vivo assay platform for medium-throughput compound screening with bioinformatics information for data interpretation. Citation Format: Xiaoxi Xu, Zhongliang Li, Yan Liu, Fanxiu Meng, Yu Lu, Songling Zhang, Chunlan Dong, Frank Xing, Qian Shi. 3D ex vivo PDX cell model screening to better predict in vivo outcome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3861.