Interpreting the Evolutionary Games Played in the NSCLC Microenvironment

eSMB2020 eSMB2020 Follow 2:30 - 3:30pm EDT, Monday - Wednesday
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Ranjini Bhattacharya

Moffitt Cancer Center
"Interpreting the Evolutionary Games Played in the NSCLC Microenvironment"
Lung cancer is the second most common type of cancer and non- small cell lung cancer (NSCLC) accounts for 84% of lung cancer diagnoses. Like other cancers, NSCLC is driven by somatic selection of fitter cells that can cheat the host. While there are treatments available to these patients, tumor heterogeneity enables selection of resistant cells. The tumor microenvironment can promote drug resistance and relapse by aiding tumor growth, angiogenesis, metastasis etc. Evolutionary Game Theory (EGT) can be used as a framework to map out the dynamics of different cellular strategies in a given tumor context to study cancer evolution. In our work we employ EGT to study the evolution of resistance to EML4- ALK positive NSCLC, with a focus on three cellular strategies- producers of hepatocyte growth factor (HGF), resistant cells, and sensitive cells. Tyrosine kinase inhibitors have been developed to block the oncogenic tyrosine kinase activity of ALK and inhibit cancer progression. progression. Resistance to TKIs has been attributed to expression of HGF which activates the alternative MET pathway, enabling cancer progression. We set up in vitro game assays to study the pairwise interactions between the three phenotypic strategies in control and drug (Alectinib) exposed environments. We find that HGF producers are the fittest and that they extend a protective effect on sensitive cells thus, enhancing their fitness. Curiously, this protection depends on the frequency of producers and undergoes saturation after a frequency of 0.4. Resistant cells do not show any significant interactions with the other two types. We then try to extrapolate the predictions from the pairwise games to predict outcomes of the three-player game involving all three phenotypes. Our study can give novel insights into possible therapeutic interventions targeting NSCLC and provides a framework for studying evolution of other cancers.
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Virtual conference of the Society for Mathematical Biology, 2020.