Accurate determination of CRISPR-mediated gene fitness in transplantable tumours.

Peter Eirew, Ciara O'Flanagan, Jerome Ting, Sohrab Salehi, Jazmine Brimhall, Beixi Wang, Justina Biele, Teresa Algara, So Ra Lee, Corey Hoang, Damian Yap, Steven McKinney, Cherie Bates, Esther Kong, Daniel Lai, Sean Beatty, Mirela Andronescu, Elena Zaikova, Tyler Funnell, Nicholas Ceglia, Stephen Chia, Karen Gelmon, Colin Mar, Sohrab Shah, Andrew Roth, Alexandre Bouchard-Côté, Samuel Aparicio, Nature communications 13, 4534 (2022)


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.