2. Academic Validation
  3. Accurate determination of CRISPR-mediated gene fitness in transplantable tumours

Accurate determination of CRISPR-mediated gene fitness in transplantable tumours

  • Nat Commun. 2022 Aug 4;13(1):4534. doi: 10.1038/s41467-022-31830-2.
Peter Eirew 1,  Ciara O'Flanagan 1,  Jerome Ting 1,  Sohrab Salehi 1,  Jazmine Brimhall 1 2,  Beixi Wang 1,  Justina Biele 1 2,  Teresa Algara 1,  So Ra Lee 1,  Corey Hoang 1 3,  Damian Yap 1,  Steven McKinney 1,  Cherie Bates 1,  Esther Kong 1,  Daniel Lai 1,  Sean Beatty 1,  Mirela Andronescu 1,  Elena Zaikova 1,  Tyler Funnell 4,  Nicholas Ceglia 4,  Stephen Chia 5,  Karen Gelmon 5,  Colin Mar 6,  Sohrab Shah 4,  Andrew Roth 1 7 8,  Alexandre Bouchard-Côté 9,  Samuel Aparicio 10 11
Affiliations

Affiliations

  • 1 Department of Molecular Oncology, BC Cancer, Vancouver, BC, Canada.
  • 2 AbCellera Biologics Inc., Vancouver, BC, Canada.
  • 3 British Columbia Institute of Technology, Vancouver, BC, Canada.
  • 4 Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA.
  • 5 Department of Medical Oncology, BC Cancer, Vancouver, BC, Canada.
  • 6 Department of Diagnostic Radiology, BC Cancer, Vancouver, BC, Canada.
  • 7 Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada.
  • 8 Department of Computer Science, University of British Columbia, Vancouver, BC, Canada.
  • 9 Department of Statistics, University of British Columbia, Vancouver, BC, Canada. [email protected].
  • 10 Department of Molecular Oncology, BC Cancer, Vancouver, BC, Canada. [email protected].
  • 11 Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada. [email protected].
PMID: 35927228 DOI: 10.1038/s41467-022-31830-2
Abstract

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.

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