Computational modeling of the crosstalk between macrophage polarization and tumor cell plasticity in the tumor microenvironment Institutional Repository Document uri icon

abstract

  • AbstractTumor microenvironments contain multiple cell types interacting among one another via different signaling pathways. Furthermore, both cancer cells and different immune cells can display phenotypic plasticity in response to these communicating signals, thereby leading to complex spatiotemporal patterns that can impact therapeutic response. Here, we investigate the crosstalk between cancer cells and macrophages in a tumor microenvironment through in silico (computational) co-culture models. In particular, we investigate how macrophages of different polarization (M1 vs. M2) can interact with epithelial-mesenchymal plasticity of cancer cells, and conversely, how cancer cells exhibiting different phenotypes (epithelial vs. mesenchymal) can influence the polarization of macrophages. Based on interactions documented in the literature, an interaction network of cancer cells and macrophages is constructed. The steady states of the network are then analyzed. Various interactions were removed or added into the constructed-network to test the functions of those interactions. Also, parameters in the mathematical models were varied to explore their effects on the steady states of the network. In general, the interactions between cancer cells and macrophages can give rise to multiple stable steady-states for a given set of parameters and each steady state is stable against perturbations. Importantly, we show that the system can often reach one type of stable steady states where cancer cells go extinct. Our results may help inform efficient therapeutic strategies.

altmetric score

  • 7.58

author list (cited authors)

  • Li, X., Jolly, M. K., George, J. T., Pienta, K. J., & Levine, H.

citation count

  • 1

complete list of authors

  • Li, Xuefei||Jolly, Mohit Kumar||George, Jason T||Pienta, Kenneth J||Levine, Herbert

Book Title

  • bioRxiv

publication date

  • October 2018