斑马鱼
高含量筛选
表型
表型筛选
药品
内容(测量理论)
计算生物学
生物
病理
医学
药理学
遗传学
基因
数学
细胞
数学分析
作者
Caterina Sturtzel,Sarah Grissenberger,Polyxeni Bozatzi,Emil Scheuringer,Andrea Wenninger-Weinzierl,Živa Zajec,Jaka Dernovšek,Susana Pascoal,Virag Gehl,A. Kutsch,A. Granig,Fikret Rifatbegovic,Manon Carré,Alexandra Lang,I. Valtingojer,Jürgen Moll,Daniela Lötsch,Friedrich Erhart,Georg Widhalm,Didier Surdez
标识
DOI:10.1038/s41698-023-00386-9
摘要
Abstract Zebrafish xenotransplantation models are increasingly applied for phenotypic drug screening to identify small compounds for precision oncology. Larval zebrafish xenografts offer the opportunity to perform drug screens at high-throughput in a complex in vivo environment. However, the full potential of the larval zebrafish xenograft model has not yet been realized and several steps of the drug screening workflow still await automation to increase throughput. Here, we present a robust workflow for drug screening in zebrafish xenografts using high-content imaging. We established embedding methods for high-content imaging of xenografts in 96-well format over consecutive days. In addition, we provide strategies for automated imaging and analysis of zebrafish xenografts including automated tumor cell detection and tumor size analysis over time. We also compared commonly used injection sites and cell labeling dyes and show specific site requirements for tumor cells from different entities. We demonstrate that our setup allows us to investigate proliferation and response to small compounds in several zebrafish xenografts ranging from pediatric sarcomas and neuroblastoma to glioblastoma and leukemia. This fast and cost-efficient assay enables the quantification of anti-tumor efficacy of small compounds in large cohorts of a vertebrate model system in vivo. Our assay may aid in prioritizing compounds or compound combinations for further preclinical and clinical investigations.
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