An evolutionary-game model of tumour-cell interactions: possible relevance to gene therapy.
Evolutionary games have been applied as simple mathematical models of populations where interactions between individuals control the dynamics. Recently, it has been proposed to use this type of model to describe the evolution of tumour cell populations with interactions between cells. We extent the analysis to allow for synergistic effects between cells. A mathematical model of a tumour cell population is presented in which population-level synergy is assumed to originate through the interaction of triplets of cells. A threshold of two cooperating cells is assumed to be required to produce a proliferative advantage. The mathematical behaviour of this model is explored. Even this simple synergism (minor clustering effect) is sufficient to generate qualitatively different cell-population dynamics from the models published previously. The most notable feature of the model is the existence of an unstable internal equilibrium separating two stable equilibria. Thus, cells of a malignant phenotype can exist in a stable polymorphism, but may be driven to extinction by relatively modest perturbations of their relative frequency. The proposed model has some features that may be of interest to biological interpretations of gene therapy. Two prototypical strategies for gene therapy are suggested, both of them leading to extinction of the malignant phenotype: one approach would be to reduce the relative proportion of the cooperating malignant cell type below a certain critical value. Another approach would be to increase the critical threshold value without reducing the relative frequency of cells of the malignant phenotype.
Bach
L A
LA
Department of Genetics and Ecology, Aarhus University, Aarhus, Denmark.
Bentzen
S M
SM
Alsner
J
J
Christiansen
F B
FB
D000465:Algorithms; D002450:Cell Communication / Q000502:physiology*; D002455:Cell Division; D019143:Evolution, Molecular; D005716:Game Theory; D015316:Genetic Therapy / Q000379:methods*; D006801:Humans; D008954:Models, Biological; D009369:Neoplasms / Q000473:pathology* / Q000628:therapy