Accurate determination of CRISPR-mediated gene fitness in transplantable tumours

Assessing tumour gene fitness in physiologically-relevant model systems is challenging due to biological features of in vivo tumour regeneration, including extreme variations in single cell lineage progeny. Here we develop a reproducible, quantitative approach to pooled genetic perturbation in patie...

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Bibliographic Details
Published in:Nature communications Vol. 13; no. 1; pp. 4534 - 19
Main Authors: Eirew, Peter, O’Flanagan, Ciara, Ting, Jerome, Salehi, Sohrab, Brimhall, Jazmine, Wang, Beixi, Biele, Justina, Algara, Teresa, Lee, So Ra, Hoang, Corey, Yap, Damian, McKinney, Steven, Bates, Cherie, Kong, Esther, Lai, Daniel, Beatty, Sean, Andronescu, Mirela, Zaikova, Elena, Funnell, Tyler, Ceglia, Nicholas, Chia, Stephen, Gelmon, Karen, Mar, Colin, Shah, Sohrab, Roth, Andrew, Bouchard-Côté, Alexandre, Aparicio, Samuel
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 04.08.2022
Nature Publishing Group
Nature Portfolio
Subjects:
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Animals
Bayes Theorem
Bayesian analysis
Breast cancer
Breast Neoplasms - genetics
Cell lineage
Clustered Regularly Interspaced Short Palindromic Repeats
CRISPR
Data analysis
Disease Models, Animal
Female
Fitness
Heterografts
Humanities and Social Sciences
Humans
In vivo methods and tests
Mathematical models
MDM2 protein
multidisciplinary
Outliers (statistics)
p53 Protein
Perturbation
Progeny
Reproductive fitness
Science
Science (multidisciplinary)
Transplants
Transplants & implants
Tumors
Uncertainty
Xenograft Model Antitumor Assays
Xenografts
Xenotransplantation
ISSN:2041-1723, 2041-1723
Online Access:Get full text
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Summary:Assessing tumour gene fitness in physiologically-relevant model systems is challenging due to biological features of in vivo tumour regeneration, including extreme variations in single cell lineage progeny. Here we develop a reproducible, quantitative approach to pooled genetic perturbation in patient-derived xenografts (PDXs), by encoding single cell output from transplanted CRISPR-transduced cells in combination with a Bayesian hierarchical model. We apply this to 181 PDX transplants from 21 breast cancer patients. We show that uncertainty in fitness estimates depends critically on the number of transplant cell clones and the variability in clone sizes. We use a pathway-directed allelic series to characterize Notch signaling, and quantify TP53 / MDM2 drug-gene conditional fitness in outlier patients. We show that fitness outlier identification can be mirrored by pharmacological perturbation. Overall, we demonstrate that the gene fitness landscape in breast PDXs is dominated by inter-patient differences. Gene fitness and essentiality analyses using in vivo cancer models are challenging due to multiple confounders. Here, the authors develop a quantitative approach to study CRISPR-transduced patient-derived xenografts, which they use to analyse in vivo gene fitness in breast cancers and the biological features that influence uncertainty in fitness estimation.
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ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-022-31830-2