The evolution of carrying capacity in constrained and expanding tumour cell populations.
Cancer cells are known to modify their micro-environment such that it can sustain a larger population, or, in ecological terms, they construct a niche which increases the carrying capacity of the population. It has however been argued that niche construction, which benefits all cells in the tumour, would be selected against since cheaters could reap the benefits without paying the cost. We have investigated the impact of niche specificity on tumour evolution using an individual based model of breast tumour growth, in which the carrying capacity of each cell consists of two components: an intrinsic, subclone-specific part and a contribution from all neighbouring cells. Analysis of the model shows that the ability of a mutant to invade a resident population depends strongly on the specificity. When specificity is low selection is mostly on growth rate, while high specificity shifts selection towards increased carrying capacity. Further, we show that the long-term evolution of the system can be predicted using adaptive dynamics. By comparing the results from a spatially structured versus well-mixed population we show that spatial structure restores selection for carrying capacity even at zero specificity, which poses a solution to the niche construction dilemma. Lastly, we show that an expanding population exhibits spatially variable selection pressure, where cells at the leading edge exhibit higher growth rate and lower carrying capacity than those at the centre of the tumour.
Mathematical Sciences, Chalmers University of Technology and Göteborg University, Chalmers Tvärgata, 412 96 Göteborg, Sweden.
Philip
P
Gerlee
Alexander R A
AR
Anderson
D000220:Adaptation, Biological; D001940:Breast / Q000166:cytology* / Q000378:metabolism / Q000473:pathology*; D001943:Breast Neoplasms / Q000235:genetics / Q000473:pathology*; D049109:Cell Proliferation; D003198:Computer Simulation; D005260:Female; D006801:Humans; D008954:Models, Biological; D009154:Mutation; D059016:Tumor Microenvironment