Cancer treatment scheduling and dynamic heterogeneity in social dilemmas of tumour acidity and vasculature.
BACKGROUND
Tumours are diverse ecosystems with persistent heterogeneity in various cancer hallmarks like self-sufficiency of growth factor production for angiogenesis and reprogramming of energy metabolism for aerobic glycolysis. This heterogeneity has consequences for diagnosis, treatment and disease progression.


METHODS
We introduce the double goods game to study the dynamics of these traits using evolutionary game theory. We model glycolytic acid production as a public good for all tumour cells and oxygen from vascularisation via vascular endothelial growth factor production as a club good benefiting non-glycolytic tumour cells. This results in three viable phenotypic strategies: glycolytic, angiogenic and aerobic non-angiogenic.


RESULTS
We classify the dynamics into three qualitatively distinct regimes: (1) fully glycolytic; (2) fully angiogenic; or (3) polyclonal in all three cell types. The third regime allows for dynamic heterogeneity even with linear goods, something that was not possible in prior public good models that considered glycolysis or growth factor production in isolation.


CONCLUSIONS
The cyclic dynamics of the polyclonal regime stress the importance of timing for anti-glycolysis treatments like lonidamine. The existence of qualitatively different dynamic regimes highlights the order effects of treatments. In particular, we consider the potential of vascular normalisation as a neoadjuvant therapy before follow-up with interventions like buffer therapy.
Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
Artem
A
Kaznatcheev
Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA.
Robert
R
Vander Velde
Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.|Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford OX2 6GG, UK.
Jacob G
JG
Scott
Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
David
D
Basanta
D049109:Cell Proliferation; D018450:Disease Progression; D004734:Energy Metabolism; D005716:Game Theory; D006019:Glycolysis / Q000502:physiology*; D006801:Humans; D006863:Hydrogen-Ion Concentration; D019344:Lactic Acid / Q000378:metabolism*; D008962:Models, Theoretical; D009369:Neoplasms / Q000098:blood supply / Q000145:classification / Q000378:metabolism* / Q000473:pathology; D009389:Neovascularization, Pathologic; D010100:Oxygen / Q000378:metabolism; D042461:Vascular Endothelial Growth Factor A / Q000378:metabolism
C467484:VEGFA protein, human; D042461:Vascular Endothelial Growth Factor A; D019344:Lactic Acid; D010100:Oxygen