斑马鱼
异种移植
计算生物学
精密医学
清脆的
生物
个性化医疗
基因组编辑
移植
转基因
癌症
医学
生物信息学
遗传学
基因
内科学
作者
Maurizio Fazio,Julien Ablain,Chuan Yan,David M. Langenau,Leonard I. Zon
出处
期刊:Nature Reviews Cancer
[Springer Nature]
日期:2020-04-06
卷期号:20 (5): 263-273
被引量:203
标识
DOI:10.1038/s41568-020-0252-3
摘要
In precision oncology, two major strategies are being pursued for predicting clinically relevant tumour behaviours, such as treatment response and emergence of drug resistance: inference based on genomic, transcriptomic, epigenomic and/or proteomic analysis of patient samples, and phenotypic assays in personalized cancer avatars. The latter approach has historically relied on in vivo mouse xenografts and in vitro organoids or 2D cell cultures. Recent progress in rapid combinatorial genetic modelling, the development of a genetically immunocompromised strain for xenotransplantation of human patient samples in adult zebrafish and the first clinical trial using xenotransplantation in zebrafish larvae for phenotypic testing of drug response bring this tiny vertebrate to the forefront of the precision medicine arena. In this Review, we discuss advances in transgenic and transplantation-based zebrafish cancer avatars, and how these models compare with and complement mouse xenografts and human organoids. We also outline the unique opportunities that these different models present for prediction studies and current challenges they face for future clinical deployment. This Review outlines the recent advances in the creation of both combinatorial transgenic cancer models in zebrafish and zebrafish patient-derived xenograft models, and argues that these models have potential to be used as avatars for precision oncology.
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