Drug screening of primary patient derived tumor xenografts in zebrafish

Meghan G. Haney, L. Henry Moore, Jessica S. Blackburn

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Patient derived xenograft models are critical in defining how different cancers respond to drug treatment in an in vivo system. Mouse models are the standard in the field, but zebrafish have emerged as an alternative model with several advantages, including the ability for high-throughput and low-cost drug screening. Zebrafish also allow for in vivo drug screening with large replicate numbers that were previously only obtainable with in vitro systems. The ability to rapidly perform large scale drug screens may open up the possibility for personalized medicine with rapid translation of results back to clinic. Zebrafish xenograft models could also be used to rapidly screen for actionable mutations based on tumor response to targeted therapies or to identify new anti-cancer compounds from large libraries. The current major limitation in the field has been quantifying and automating the process so that drug screens can be done on a larger scale and be less labor-intensive. We have developed a workflow for xenografting primary patient samples into zebrafish larvae and performing large scale drug screens using a fluorescence microscope equipped imaging unit and automated sampler unit. This method allows for standardization and quantification of engrafted tumor area and response to drug treatment across large numbers of zebrafish larvae. Overall, this method is advantageous over traditional cell culture drug screening as it allows for growth of tumor cells in an in vivo environment throughout drug treatment, and is more practical and cost-effective than mice for large scale in vivo drug screens.

Original languageEnglish
Article numbere60996
JournalJournal of Visualized Experiments
Volume2020
Issue number158
DOIs
StatePublished - Apr 2020

Bibliographical note

Funding Information:
This research was supported by a V Foundation V Scholar Award and NIH Grants DP2CA228043, R01CA227656 (to J.S. Blackburn) and NIH Training Grant T32CA165990 (to M.G. Haney).

Publisher Copyright:
© 2020 Journal of Visualized Experiments.

Keywords

  • Automated
  • Cancer research
  • Drug screen
  • High throughput
  • Issue 158
  • Leukemia
  • Patient-derived xenograft
  • Zebrafish

ASJC Scopus subject areas

  • Neuroscience (all)
  • Chemical Engineering (all)
  • Biochemistry, Genetics and Molecular Biology (all)
  • Immunology and Microbiology (all)

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