Game Theory Helping to Predict Cancer Progress

Researchers at Johns Hopkins Medicine are borrowing ideas from evolutionary game theory to learn how cells cooperate within a tumor to gather energy. Their experiments, they say, could identify the ideal time to disrupt metastatic cancer cell cooperation and make a tumor more vulnerable to anti-cancer drugs.

Game theory is a mathematical study of strategic decision-making, and has been widely used to predict conflict and cooperation between individuals and even nations, but increasingly is applied to forecasting cell-to-cell interactions in biology with an ecological perspective.

In their research, the Johns Hopkins scientists used mathematical and computer tools to set up game parameters based on biological interactions between two types of tumor cells, one oxygen-rich and the other oxygen-poor. Cells within a tumor engage in different types of energy metabolism depending on how close they are to an oxygen-rich blood supply. Tumor cells in oxygen-poor areas use the sugar glucose to produce energy and, as part of the process, release a compound called lactate. Oxygen-rich cells use this lactate in a different type of energy metabolism process and, as a result, release glucose that can be used by oxygen-poor cells to burn for their own energy.

Applying game theory calculations that accounted for the tumor cells’ mutation rates and potential glucose and lactate levels, the scientists found that within certain ranges of mutation rates, there are critical transitions when a tumor suddenly switches between different types of energy metabolic strategies. This switch in the playbook of energy production tactics may happen when tumors progress and spread.

The scientists think tumors might be especially vulnerable within this window of strategy-switching, making it a potentially ideal time for clinicians to disrupt the tumor’s environment and wreck the partnership among its cells.