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Clonal fitness inferred from time-series modelling of single-cell cancer genomes
Name
nihms-1728080.pdf
Description
Accepted version
Size
4.69 MB
Format
Adobe PDF
Checksum (MD5)
cf90e8b220f76b954e20d05ee2813781
Author(s)
Boyden, Edward S.
Date Issued
2021
Journal
Nature
Publisher
Springer Science and Business Media LLC
Citation
Boyden, Edward S. 2021. "Clonal fitness inferred from time-series modelling of single-cell cancer genomes." Nature, 595 (7868).
Version
Author's final manuscript
Abstract
Progress in defining genomic fitness landscapes in cancer, especially those defined by copy number alterations (CNAs), has been impeded by lack of time-series single-cell sampling of polyclonal populations and temporal statistical models1-7. Here we generated 42,000 genomes from multi-year time-series single-cell whole-genome sequencing of breast epithelium and primary triple-negative breast cancer (TNBC) patient-derived xenografts (PDXs), revealing the nature of CNA-defined clonal fitness dynamics induced by TP53 mutation and cisplatin chemotherapy. Using a new Wright-Fisher population genetics model8,9 to infer clonal fitness, we found that TP53 mutation alters the fitness landscape, reproducibly distributing fitness over a larger number of clones associated with distinct CNAs. Furthermore, in TNBC PDX models with mutated TP53, inferred fitness coefficients from CNA-based genotypes accurately forecast experimentally enforced clonal competition dynamics. Drug treatment in three long-term serially passaged TNBC PDXs resulted in cisplatin-resistant clones emerging from low-fitness phylogenetic lineages in the untreated setting. Conversely, high-fitness clones from treatment-naive controls were eradicated, signalling an inversion of the fitness landscape. Finally, upon release of drug, selection pressure dynamics were reversed, indicating a fitness cost of treatment resistance. Together, our findings define clonal fitness linked to both CNA and therapeutic resistance in polyclonal tumours.
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
10.1038/S41586-021-03648-3
