Preventing relapse is the major challenge to effective therapy in cancer. Within the tumour, stromal (ST) cells play an important role in cancer progression and the emergence of drug resistance. During cancer treatment, the fitness of cancer cells can be enhanced by ST cells because their molecular signalling interaction delays the drug-induced apoptosis of cancer cells. On the other hand, competition among cancer and ST cells for space or resources should not be ignored. We explore the population dynamics of multiple myeloma (MM) versus bone marrow ST cells by using an experimental microecology that we call the death galaxy, with a stable drug gradient and connected microhabitats. Evolutionary game theory is a quantitative way to capture the frequency-dependent nature of interactive populations. Therefore, we use evolutionary game theory to model the populations in the death galaxy with the gradients of pay-offs and successfully predict the future densities of MM and ST cells. We discuss the possible clinical use of such analysis for predicting cancer progression.
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| http://dx.doi.org/10.1098/rsfs.2014.0028 | DOI Listing |
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