The PI of this project has developed a unique in vitro technology which can provide a realistic tumor-like environment to study the interactions between different cells. One can study both different cancer cells and cancer cells interacting with other cells in the organ. However, without a strong quantitative model capable of guiding our understanding of how these cell population change with time, we cannot quantitatively understand the progression of the cell populations nor make predictions of the cancer evolution. The PI will use sophisticated evolutionary game theory models to capture the complex dynamics observed in the experiments. Currently the path from diagnosis through estimation of hazards to emergence of the end of dormancy cannot be predicted and this project will develop understanding of how to follow different stages of cancer. Combining the PI?s technology with new micro-imaging modalities that have been developed by physicists, this project can be used to monitor the duration of dormancy in tumors, prescribe time-dependent therapies, and predict cancer emergence from dormancy.
This EAGER project will tackle the difficult problem of combining sophisticated, realistic game theory in patchy, locally interacting and stochastic systems and apply it to a micro-fabricated technology designed to mimic the actual tumor environment. The singularities in the ordinary differential equations that gave rise to dormancy are in principle removed by this modeling, and the PI will test the modeling with experimental re-emergence of cancer cell viability under stress.
This project is being jointly supported by the Physics of Living Systems program in the Division of Physics and the Molecular Biophysics Cluster in the Division of Molecular and Cellular Biosciences.
