The DOI matches its Crossref record; 116 of the 116 references it cites were found in a registry or an index.
Zebrafish patient avatars in cancer biology and precision cancer therapy
Open accessAbstract
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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Cites
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Cited by
Zebrafish disease models in drug discovery: from preclinical modelling to clinical trials
Patton, E. E., Zon, L. I., & Langenau, D. M. (2021) · Nature Reviews Drug Discovery · doi:10.1038/s41573-021-00210-8 · Cited by 567
Self-citationLongevity leap: mind the healthspan gap
Garmany, A., Yamada, S., & Terzic, A. (2021) · npj Regenerative Medicine · doi:10.1038/s41536-021-00169-5 · Cited by 252
Metadata
- Authors
- Fazio, M., Ablain, J., Chuan, Y., Langenau, D. M., & Zon, L. I.
- Venue
- Nature Reviews Cancer
- Published
- 2020-04-06
- Volume
- 20
- Issue
- 5
- Pages
- 263-273
- ISSN
- 1474-175X (ISSN-L)
- 1474-1768
- OpenAlex
- W3014569644
- Cited by
- 257
- References
- 116
- FWCI
- 4.27
- Type
- journal article
- Language
- en
- Open access
- green
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- Fazio, M., Ablain, J., Chuan, Y., Langenau, D. M., & Zon, L. I. (2020). Zebrafish patient avatars in cancer biology and precision cancer therapy. Nature Reviews Cancer. https://doi.org/10.1038/s41568-020-0252-3
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