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A mathematical dissection of the adaptation of cell populations to fluctuating oxygen levels

Research output: Contribution to journalArticlepeer-review

Author(s)

Aleksandra Ardaševa, Robert A. Gatenby, Alexander R.A. Anderson, Helen M. Byrne, Philip K. Maini, Tommaso Lorenzi

School/Research organisations

Abstract

The disordered network of blood vessels that arises from tumour angiogenesis results in variations in the delivery of oxygen into the tumour tissue. This brings about regions of chronic hypoxia (i.e. sustained low oxygen levels) and regions with alternating periods of low and relatively higher oxygen levels, and makes it necessary for cancer cells to adapt to fluctuating environmental conditions. We use a phenotype-structured model to dissect the evolutionary dynamics of cell populations exposed to fluctuating oxygen levels. In this model, the phenotypic state of every cell is described by a continuous variable that provides a simple representation of its metabolic phenotype, ranging from fully oxidative to fully glycolytic, and cells are grouped into two competing populations that undergo heritable, spontaneous phenotypic variations at different rates. Model simulations indicate that, depending on the rate at which oxygen is consumed by the cells, dynamic nonlinear interactions between cells and oxygen can stimulate chronic hypoxia and cycling hypoxia. Moreover, the model supports the idea that under chronic-hypoxic conditions lower rates of phenotypic variation lead to a competitive advantage, whereas higher rates of phenotypic variation can confer a competitive advantage under cycling-hypoxic conditions. In the latter case, the numerical results obtained show that bet-hedging evolutionary strategies, whereby cells switch between oxidative and glycolytic phenotypes, can spontaneously emerge. We explain how these results can shed light on the evolutionary process that may underpin the emergence of phenotypic heterogeneity in vascularised tumours.

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Details

Original languageEnglish
Article number81
JournalBulletin of Mathematical Biology
Volume82
Issue number6
DOIs
Publication statusPublished - 1 Jun 2020

    Research areas

  • Adaptive dynamics, Bet-hedging, Cell populations, Fluctuating oxygen levels, Phenotype-structured models

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