Abstract
Abstract Breast cancer (BC) is the most common malignancy in women worldwide and metastasis is the principal cause of death. As BC is a highly heterogeneous disease, different drugs must be used according to each BC subtype. However, highly individual differences in treatment outcome exist even within subtypes, and the mechanisms underlying treatment response variability between BC patients is poorly understood. The use of cell lines in vitro or in vivo generally does not recapitulate the patient-specific differences in progression and treatment outcome. Analyses of patient-derived xenograft (PDX) models grown in mice solve this problem, but these techniques are resource-intensive and optimized for studying the effects on primary tumor growth rather than metastatic dissemination. Hence, there is a great and unmet need for alternative in vivo models that give accurate insights into metastatic properties of the PDX models, and which are better suited for screening libraries of drug candidates in many PDX models within a short period of time. Here we report the development of a zebrafish tumor xenograft (ZTX) platform for screening anti-tumor and anti-metastatic drug efficacy in a panel of 20 BC PDX models and comparing these to treatment outcome in mouse-PDX models and disease-stage of the patients. ZTX models have recently gained enormous popularity as an exciting new tool in the preclinical oncology research toolbox but have not yet been exploited as a platform for analyzing PDX models in general including BC PDX models. We show that of 20 PDX models tested, 19 models implanted effectively in zebrafish larvae (95% implantation success) exhibiting an average growth rate of 49% during the three-day assay period. Increased dissemination of implanted tumor cells in the zebrafish larvae correlated with clinical data on advancing tumor stage from stage 1 to stage 3 disease. Interestingly, response to docetaxel and trastuzumab in the ZTX platform was identical in 14 of 18 cases to that in the mouse PDX models showing prediction of positive treatment outcome in 11 of 14 sensitive models and prediction of resistance in 3 of 4 resistant models. In conclusion, ZTX models established from BC PDX material closely recapitulate the dissemination phenotypes of the patients from where the PDX models is generated, and treatment outcomes in the corresponding mouse-PDX models. The ZTX platform provides new opportunities for fast and accurate drug or PDX screens of anti-tumor and anti-metastatic efficacy. Citation Format: Gabriela Vazquez Rodriguez, Zaheer Ali, Anna Erkstam, Julia Schueler, Anna Fahlgren, Lasse D. Jensen. Zebrafish tumor-derived xenografts established from breast cancer pdx models predict treatment outcome and dissemination risk with superior sensitivity and specificity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2995.
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