[SS22] Understanding complex dynamics of cancer progression and treatment response

[SS22-06] Mathematical Modeling of Cancer-Associated Fibroblast Heterogeneity in Cancer Progression

*Junho Lee¹, Eunjung Kim¹ (1. Korea Institute of Science and Technology (KIST) (Korea))

Keywords:

Fibroblast phenotypic heterogeneity,Mathematical model,Targeted therapy,Immunotherapy,Model-guided treatment choice,Agent-based model

The heterogeneity of cancer-associated fibroblasts (CAFs) within the tumor microenvironment (TME) plays a pivotal role in the progression and treatment of cancer. Understanding the distinct behaviors and effects of various CAF phenotypes is crucial for the development of more effective cancer treatment strategies. This study is driven by the purpose of elucidating the heterogeneity of CAFs within the TME and evaluating how different CAF phenotypes influence tumor progression and immune response dynamics. However, the exact role and mechanism of CAFs within the TME remains to be elucidated. This study highlights the need to dissect the complex roles of different CAF phenotypes that affect cancer progression and immune regulation and proposes mathematical models to explore these interactions. Utilizing method that combine an agent-based model with differential equations, we simulate the complex interactions between CAFs and T cells and analyze spatial effect. The agent-based modeling allows for the simulation of individual cellular behaviors within their microenvironments. This method provides nuanced insights into how cells interact with and influence their surroundings, which is critical for understanding the complexity of the TME. The results of our simulations indicate that the anti-immune CAF phenotype contributes to the inhibition of T cell activation, thereby enhancing tumor survival, while the prophylactic immune phenotype may support T cell activity and thus disrupt tumor growth. The conclusion of our study suggests that strategic manipulation of the CAF population may significantly alter the immune environment of TME, suggesting new avenues for treatment of target cancer. Adjusting CAF phenotypes can improve the effectiveness of immunotherapy strategies and lead to more personalized approaches in cancer treatment.