Modeling human tumor evolution in mice

Cancer develops through an evolutionary process driven by mutation and selective pressures imposed by the microenvironment. To be translationally relevant, experimental models must recapitulate these clinical complexities. In this Primer, we consider how different mouse-modeling strategies can be aligned with human tumor evolution, focusing on mutation order, the emergence and competition of initially rare mutant clones within genetically mosaic tissues, and microenvironmental context. By comparing conventional genetically engineered mouse models (GEMMs), transplant-based models, and emerging tools such as somatic editing and the tandem arrayed regulator (TAR) allele system, we offer a guide for selecting the most appropriate mouse model to address specific evolutionary questions.

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Publication Details

Journal
STAR Protocols
Published
2026-10-03
DOI
https://doi.org/10.1016/j.xpro.2026.104872
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
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article

Modeling human tumor evolution in mice

Dale M. Watt, Daniel J. Murphy, S. Leah Etheridge, Karen Blyth et al.
STAR Protocols
Cancer Genomics and Diagnostics
article

Modeling human tumor evolution in mice

Dale M. Watt, Daniel J. Murphy, S. Leah Etheridge, Karen Blyth, Louise E. Mitchell, Philip D.; id_orcid 0000-0001-9160-283X Dunne
article en

Abstract

Cancer develops through an evolutionary process driven by mutation and selective pressures imposed by the microenvironment. To be translationally relevant, experimental models must recapitulate these clinical complexities. In this Primer, we consider how different mouse-modeling strategies can be aligned with human tumor evolution, focusing on mutation order, the emergence and competition of initially rare mutant clones within genetically mosaic tissues, and microenvironmental context. By comparing conventional genetically engineered mouse models (GEMMs), transplant-based models, and emerging tools such as somatic editing and the tandem arrayed regulator (TAR) allele system, we offer a guide for selecting the most appropriate mouse model to address specific evolutionary questions.

STAR ProtocolsVol. 7(4)
Queen's University Belfast (GB), Cancer Research UK Scotland Institute (GB), University of York (GB), University of Glasgow (GB)
Openalex Percentile: Top 16%
Cancer Genomics and Diagnostics
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Modeling human tumor evolution in mice — Dale M. Watt, Daniel J. Murphy, et al. · STAR Protocols (2026) | TGRS Research Map | TGRS