Evolutionary Game Theory

Cancer cells and stromal cells interact within a tumor to give both cooperative and competitive behaviors that have been attributed to various molecular signaling pathways. Evolutionary game theory (EGT), which studies the strategic interactions of biological agents based on frequency-dependent fitness functions, has been purported to provide a lens in which to understand cancer-stroma interactions as well as to interpret counter-intuitive cooperative behaviors amongst cells in the tumor microenviroment. Further, EGT has been employed clinically in the form of adaptive therapy to take advantage of competition between various cancer clones. 

EGT allows for a top-down approach to infer large-scale population dynamics of varying cell types, without necessarily requiring the dissection of specific signaling pathways. Thus, EGT has been adopted as a model to describe the interactions between cancer and stromal cells and as a means to predict future behavior. The power of this methodology lies in its ability to understand current population-level behavior through experimental fitting and simultaneously predicting future dynamics. Our work in EGT includes 1) understanding population behavior by applying these models to experimental data, and 2) studying more representative classes of models such as the interacting particle system (IPS) in describing cancer dynamics. 

 

Selected Publications: 

  • Zheng, Y., Sun, Y., Torga, G., Pienta, K. J., & Austin, R. H., “Game Theory Cancer Models of Cancer Cell-Stromal Cell Dynamics using Interacting Particle Systems”, Biophysical Reviews and Letters, 2020. In press.
  • Wu, A., Liao, D., Tlsty, T. D., Sturm, J. C., & Austin, R. H. (2014). Game theory in the death galaxy: interaction of cancer and stromal cells in tumour microenvironment. Interface Focus, 4(4), 20140028.
  • Lambert, G., Vyawahare, S., & Austin, R. H. (2014). Bacteria and game theory: the rise and fall of cooperation in spatially heterogeneous environments. Interface focus, 4(4), 20140029.
  • Wu, A., Liao, D., & Austin, R. (2015). Evolutionary game theory in cancer: first steps in prediction of metastatic cancer progression?. Future Oncology, 11(6), 881-883.
  • Wu, A., Liao, D., Kirilin, V., Lin, K. C., Torga, G., Qu, J., ... & Austin, R. (2018). Cancer dormancy and criticality from a game theory perspective. Cancer convergence, 2(1), 1.