Spatial Dynamics of Myeloid-Tumor Cell Interactions During Early Non-Small Adenocarcinoma Development

Lung cancer yields the greatest mortality rate of all cancers in the United States. Among the types of lung cancer, non-small cell adenocarcinoma occurs most commonly in non-smokers. The immune system is the body’s first response to abnormal cell behavior. However, tumor progression often evades the immune system’s response and grows uncontrollably. This is a result of both tumor self-defense mechanisms inhibiting the maturation of myeloid cells in the environment, and/or natural spatial barriers of clumped tumor mass. We use a stochastic Cellular Automaton (CA) model to study the spatial dynamics of the immune cells (myeloid cells and T-cells) in response to tumor progression. This research explores how local effects of tumor defense mechanisms affect the spatial dynamics of tumor growth in terms of myeloid cell maturation and tumor proliferation. The mathematical analysis includes a mean-field approximation (MF) through a system of ordinary differential equations. The MF model is a non-spatial approximation to the spatially explicit Cellular Automaton model. We use numerical simulations to explore the control and growth of tumor progression. The results suggest that it is insufficient for mature myeloid cell quantities to surpass tumor cell quantities in order to eradicate tumor cells or vice versa.