Mathematical Modeling and Solution Landscape Reveal Cancer Progression Dynamics in Tumor Ecological Microenvironment
Shun Wang, Tengfei Wang, Shuonan Wu, Lei Zhang, Xiufen Zou
Source abstract
Abstract. The cancer microenvironment is increasingly being viewed as an ecosystem, in which tumor cells interact with surrounding cells through diverse ecological relationships. However, the ecological principles governing the dynamics of cancer development and progression remain a mystery, hindering efforts to develop better treatment strategies. Here, we propose a novel ecological network of “predation-mutualism-amensalism” among tumor cells, immune cells, and mutualist cells. We found that this ecological model can accurately recapitulate the dynamic states and their transitions during cancer immunoediting by integrating mathematical modeling, stability and bifurcation analysis, and validation using experiment data. In contrast, two current models that only described predation and amensalism interactions failed to achieve it, suggesting the essential contribution of mutualism to the evolution of cancer immunoediting. Further, the immune barrier as a quantitative index was exploited to investigate the interlinkages between ecological relationships and cancer progression. Surprisingly, we found that the mutualism-mediated and amensalism-mediated inhibition of antitumor immune response only affects the transition from dormancy to escape phase, while the predation-mediated antitumor immune response affects all the phase transition dynamics of cancer progression. Moreover, by constructing the solution landscape of cancer progression dynamics, we revealed that tumor cell migration enables cancer progression to enter the dormancy phase by evading immunosurveillance, while mutualist cell migration facilitates the tumor’s evasion from dormancy to escape phase. The discovery of these ecological principles and the understanding of cell motility within the cancer microenvironment provide a potential for improved intervention of ecological interactions that could impact cancer progression and treatment.
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