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Prime editing GEMMs to model cancer mutations

Nature Reviews Cancer volume 24, page 2 (2024)Cite this article

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Preclinical models of cancer mutations are crucial for advancing precision oncology. Existing genetically engineered mouse models (GEMMs) represent only a minority of the various cancer alleles found in human tumours. CRISPR–Cas9 and base editors have accelerated the generation of new GEMMs, but these techniques have key limitations. CRISPR–Cas9 excels at gene disruption, but inefficiently installs templated single nucleotide variants (SNVs). SNVs comprise over 80% of somatic cancer mutations in clinical sequencing datasets, such as MSK-IMPACT. Base editors install SNVs efficiently; however, they require unique enzymes for a desired edit (for example, adenine base editors to convert A•T to G•C), generate bystander mutations, and cannot install most multinucleotide variants or insertions or deletions (indels).

Given these challenges, we explored the use of prime editing to model cancer-associated mutations. Prime editors — fusion enzymes of a Cas9 nickase with a reverse transcriptase — can mediate all transition and transversion mutations, as well as defined indels. Edits are installed by delivering prime-editing guide RNAs (pegRNAs) in which a protospacer directs the enzyme to the target locus and a 3′ extension sequence both primes reverse transcription and templates the edit of interest. Of the 96% of MSK-IMPACT mutations that can be modelled in silico with prime editing, most loci have close orthologues in the mouse genome.

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  1. David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA

    Nicolas Mathey-Andrews

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  1. Nicolas Mathey-Andrews
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Correspondence to Nicolas Mathey-Andrews.

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Mathey-Andrews, N. Prime editing GEMMs to model cancer mutations. Nat Rev Cancer 24, 2 (2024). https://doi.org/10.1038/s41568-023-00627-w

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  • DOI: https://doi.org/10.1038/s41568-023-00627-w

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