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Spatial structure governs the mode of tumour evolution.


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.

SUBMITTER: Noble R 

PROVIDER: S-EPMC8825284 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Spatial structure governs the mode of tumour evolution.

Noble Robert R   Burri Dominik D   Le Sueur Cécile C   Lemant Jeanne J   Viossat Yannick Y   Kather Jakob Nikolas JN   Beerenwinkel Niko N  

Nature ecology & evolution 20211223 2


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 genetic  ...[more]

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