Spatial structure governs the mode of tumour evolution
Noble, Robert; Burri, Dominik; Le Sueur, Cécile; Lemant, Jeanne; Viossat, Yannick; Kather, Jakob Nikolas; Beerenwinkel, N. (2022), Spatial structure governs the mode of tumour evolution, Nature ecology & evolution, 6, p. 207–217. 10.1038/s41559-021-01615-9
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Article accepté pour publication ou publiéExternal document link
520Date
2022Journal name
Nature ecology & evolutionVolume
6Publisher
Springer
Pages
207–217
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Show full item recordAuthor(s)
Noble, RobertSwiss Institute of Bioinformatics [SIB/ISB]
Department of Biosystems Science and Engineering [ETH Zürich] [D-BSSE]
Burri, Dominik
Department of Biosystems Science and Engineering [ETH Zürich] [D-BSSE]
Le Sueur, Cécile
Department of Biosystems Science and Engineering [ETH Zürich] [D-BSSE]
Lemant, Jeanne
Department of Biosystems Science and Engineering [ETH Zürich] [D-BSSE]
Viossat, Yannick
CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
Kather, Jakob Nikolas
German Cancer Consortium (DKTK) Core Center Heidelberg, Heidelberg, Germany
RWTH Aachen University, Department of Internal Medicine III, Aachen, Germany
Beerenwinkel, N.
Swiss Institute of Bioinformatics [SIB/ISB]
Department of Biosystems Science and Engineering [ETH Zürich] [D-BSSE]
Abstract (EN)
Abstract Characterizing the mode—the way, manner or pattern—of evolution in tumours is important for clinical forecasting and optimizing cancer treatment. Sequencing studies have inferred various modes, including branching, punctuated and neutral evolution, but it is unclear why a particular pattern predominates in any given tumour. Here we propose that tumour architecture is key to explaining the variety of observed genetic patterns. We examine this hypothesis using spatially explicit population genetics models and demonstrate that, within biologically relevant parameter ranges, different spatial structures can generate four tumour evolutionary modes: rapid clonal expansion, progressive diversification, branching evolution and effectively almost neutral evolution. Quantitative indices for describing and classifying these evolutionary modes are presented. Using these indices, we show that our model predictions are consistent with empirical observations for cancer types with corresponding spatial structures. The manner of cell dispersal and the range of cell–cell interactions are found to be essential factors in accurately characterizing, forecasting and controlling tumour evolution.Related items
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