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Clonal fitness inferred from time-series modelling of single-cell cancer genomes

2021; Nature Portfolio; Volume: 595; Issue: 7868 Linguagem: Inglês

10.1038/s41586-021-03648-3

1476-4687

Sohrab Salehi, Farhia Kabeer, Nicholas Ceglia, Mirela Andronescu, Marc Williams, Kieran R. Campbell, Tehmina Masud, Beixi Wang, Justina Biele, Jazmine Brimhall, David Gee, Hakwoo Lee, Jerome Ting, Allen W. Zhang, Hoa Tran, Ciara H. O’Flanagan, Fatemeh Dorri, Nicole Rusk, Teresa Ruiz de Algara, So Ra Lee, Brian Yu Chieh Cheng, Peter Eirew, Takako Kono, Jenifer Pham, Diljot Grewal, Daniel Lai, Richard A. Moore, Andrew J. Mungall, Marco A. Marra, Gregory J. Hannon, Giorgia Battistoni, Dario Bressan, Ian G. Cannell, Hannah Casbolt, Atefeh Fatemi, Cristina Jauset, Tatjana Kovačević, Claire M. Mulvey, Fiona Nugent, Marta Ribes, Isabella Pearsall, Fatime Qosaj, Kirsty Sawicka, Sophia A. Wild, Elena Williams, Emma Laks, Yangguang Li, Ciara H. O’Flanagan, Austin Smith, Teresa Ruíz, Daniel Lai, Andrew Roth, Shankar Balasubramanian, Maximillian Lee, Bernd Bodenmiller, Marcel Burger, Laura Kuett, Sandra Tietscher, Jonas Windhager, Edward S. Boyden, Shahar Alon, Yi Cui, Amauche Emenari, Dan Goodwin, Emmanouil D. Karagiannis, Anubhav Sinha, Asmamaw T. Wassie, Carlos Caldas, Alejandra Bruna, Maurizio Callari, Wendy Greenwood, Giulia Lerda, Yaniv Eyal-Lubling, Oscar M. Rueda, Abigail Shea, Owen Harris, Robby Becker, Flaminia Grimaldi, Suvi Harris, Sara Lisa Vogl, Joanna Weselak, Johanna A. Joyce, Spencer S. Watson, Ignacio Vázquez-Garćıa, Simon Tavaré, Khanh N. Dinh, Eyal Fisher, Russell Kunes, N. A. Walton, Mohammad Al Sa’d, Nick Chornay, A. Dariush, E. A. González-Solares, Carlos González‐Fernández, A. Yoldaş, Neil S. Millar, Tristan Whitmarsh, Xiaowei Zhuang, Jean Fan, Hsuan Lee, Leonardo A. Sepúlveda, Chenglong Xia, Pu Zheng, Andrew McPherson, Alexandre Bouchard‐Côté, Samuel Aparício, Sohrab P. Shah,

Single-cell and spatial transcriptomics

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. Whole-genome sequencing of human cancer cells in patient-derived mouse xenograft models indicates a key role for TP53 in determining the fitness landscape of polyclonal cancer cell populations.