  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 vascularization via VEGF
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.
  Conclusion: 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
renormalization as a neoadjuvant therapy before follow up with interventions
like buffer therapy.
