Spatial structure governs the mode of tumour evolution

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Robert Noble - , ETH Zurich (Author)
  • Dominik Burri - , ETH Zurich (Author)
  • Cécile Le Sueur - , ETH Zurich (Author)
  • Jeanne Lemant - , ETH Zurich (Author)
  • Yannick Viossat - , Ceremade (Author)
  • Jakob Nikolas Kather - , German Cancer Research Center (DKFZ), University Hospital Aachen (Author)
  • Niko Beerenwinkel - , ETH Zurich (Author)

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.

Details

Original languageEnglish
Pages (from-to)207-217
Number of pages11
JournalNature ecology & evolution
Volume6
Issue number2
Publication statusPublished - Feb 2022
Peer-reviewedYes
Externally publishedYes

External IDs

PubMedCentral PMC8825284
Scopus 85121629704

Keywords

Sustainable Development Goals

Keywords

  • Humans, Neoplasms/genetics

Library keywords