Computational modeling of the crosstalk between macrophage polarization and tumor cell plasticity in the tumor microenvironment

Abstract

Tumor 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 constructednetwork 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 steadystates 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.

Interplay between tumor microenvironment and partial EMT as the driver of tumor progression

“…Although TAMs and polarized phenotypes M1 and M2 have been extensively studied with respect to cancer progression, the experimental evidence of the role of TAMs in inducing pEMT remains to be explored. This association has been explored using in silico computational models, wherein polarized M1/M2 macrophages (Li et al, 2019b) through interaction networks but remains to be validated using experimental models.…”

Mathematical investigation of innate immune responses to lung cancer: The role of macrophages with mixed phenotypes

“…To address various questions related to tumour-macrophage interactions (as well as questions about the effect of different immuno-and chemo-therapies on tumour-macrophage interactions), the last few decades have seen the development of a large variety of mathematical models [17,18,19,20,21,22,23,24].…”

Gene expression profiles of inflammatory breast cancer reveal high heterogeneity across the epithelial-hybrid-mesenchymal spectrum

“…Moreover, single-cell analysis of primary tumors and CTCs of IBC shall help in identifying various immune cell subsets in IBC which may drive disease progression. The composition and/or spatial localization of immune cells is likely to yield better insights into immune ecology of highly aggressive disease such as IBC [37,38].…”