Browse by author
Lookup NU author(s): Dr David Hill,
Dr Bill Chaudhry
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Cancer metastasis is the most important prognostic factor determining patient survival, but currently there are very few drugs or therapies that specifically inhibit the invasion and metastasis of cancer cells. Currently, human cancer metastasis is largely studied using transgenic and immunocompromised mouse xenograft models, which are useful for analysing end-point tumour growth but are unable to accurately and reliably monitor in vivo invasion, intravasation, extravasation or secondary tumour formation of human cancer cells. Furthermore, limits in our ability to accurately monitor early stages of tumour growth and detect micro-metastases likely results in pain and suffering to the mice used for cancer xenograft experiments. Zebrafish ( Danio rerio) embryos, however, offer many advantages as a model system for studying the complex, multi-step processes involved during cancer metastasis. This article describes a detailed method for the analysis of human cancer cell invasion and metastasis in zebrafish embryos before they reach protected status at 5 days post fertilisation. Results demonstrate that human cancer cells actively invade within a zebrafish microenvironment, and form metastatic tumours at secondary tissue sites, suggesting that the mechanisms involved during the different stages of metastasis are conserved between humans and zebrafish, supporting the use of zebrafish embryos as a viable model of human cancer metastasis. We suggest that the embryonic zebrafish xenograft model of human cancer is a tractable laboratory model that can be used to understand cancer biology, and as a direct replacement of mice for the analysis of drugs that target cancer invasion and metastasis.
Author(s): Hill D, Chen L, Snaar-Jagalska E, Chaudhry B
Publication type: Article
Publication status: Published
Online publication date: 22/10/2018
Acceptance date: 02/04/2018
Date deposited: 13/12/2018
ISSN (electronic): 2046-1402
Publisher: Faculty of 1000 Ltd
PubMed id: 30473782
Altmetrics provided by Altmetric