Spatial structure governs the mode of tumour evolution

Nature Ecology & Evolution, vol. 6, pp. 207–217

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.

Authors 7

1. Robert Noble corresponding

   University of London · SIB Swiss Institute of Bioinformatics · City, University of London · University of Zurich · ETH Zurich

   Affiliation as printed

   Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland. robert.noble@city.ac.uk

   Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland. robert.noble@city.ac.uk

   Department of Mathematics, City, University of London, London, UK. robert.noble@city.ac.uk

   SIB Swiss Institute of Bioinformatics, Basel, Switzerland. robert.noble@city.ac.uk

   Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland

2. Dominik Bürri

   University of Basel · ETH Zurich

   Affiliation as printed

   Biozentrum, University of Basel, Basel, Switzerland

   Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland

3. Cécile Le Sueur

   ETH Zurich

   Affiliation as printed

   Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland

4. Jeanne Lemant

   ETH Zurich

   Affiliation as printed

   Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland

5. Yannick Viossat

   Centre de Recherche en Mathématiques de la Décision · Université Paris Dauphine-PSL

   Affiliation as printed

   Ceremade, Université Paris Dauphine-PSL, Paris, France

6. Jakob Nikolas Kather Aachen Internal Medicine III

   German Cancer Research Center · Universitätsklinikum Aachen · Deutsches Konsortium für Translationale Krebsforschung · RWTH Aachen University

   Affiliation as printed

   Applied Tumor Immunity, German Cancer Research Center (DKFZ), Heidelberg, Germany

   German Cancer Consortium (DKTK), Heidelberg, Germany

   Internal Medicine III, University Hospital RWTH Aachen, Aachen, Germany

7. Niko Beerenwinkel corresponding

   SIB Swiss Institute of Bioinformatics · ETH Zurich

   Affiliation as printed

   Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland. niko.beerenwinkel@bsse.ethz.ch

   SIB Swiss Institute of Bioinformatics, Basel, Switzerland. niko.beerenwinkel@bsse.ethz.ch

   SIB Swiss Institute of Bioinformatics, Basel, Switzerland