Assistant professor Texas A&M University, United States
Introduction:: Understanding the complex relationship between tumor immune evasion and T cell exhaustion is crucial for understanding the extent of immunoediting on cancer progression and for developing optimized treatment strategies. The extracellular matrix (ECM) is one of the most important components of the tumor microenvironment (TME) and plays a critical role in regulating the activity of both tumor cells and cytotoxic T cells. Research has shown that changes in ECM topology that occur during tumor progression affect both tumor cells and T cells mobility. However, the influence of ECM topology on the spatiotemporal progression of cancer, together with its impact on cytotoxic T cell infiltration, recognition of tumor-associated antigens, and immunosurveillance, is not well understood. The primary objective of this research is to enhance our understanding of the interplay between ECM geometry remodeling and the bidirectional interaction between tumor and T cells.
Materials and Methods:: Our research has devised a novel dual-agent-based model (ABM) to explore the intricate interplay between T cell recognition of tumor-associated antigens, spatiotemporal tumor growth, and the geometry of the ECM fibers. Specifically, we have focused on comparing two common ECM geometries observed in human solid tumors - circumferentially packed ECM fibers and radially packed fibers - which have been linked to patient survival outcomes. We have also integrated immune microenvironmental factors, such as hypoxia and nutrient concentration, into our model to capture their impact on T-cell dysfunction.
Results, Conclusions, and Discussions:: Our study incorporates the inherent impact of ECM topology on immune surveillance and tumor evasion processes. Our model demonstrates that the geometry of the ECM plays a significant role in determining the spatial distribution and release of tumor-associated antigens. This, in turn, affects the evolution of the cancer population, which may produce evasive subclones randomly, resulting in transient protection against effector T cells and altering the T cell recognition process. By accounting for these factors, our model provides a more accurate prediction of the tumor-immune evolution process.
Our research delves into the intricate relationship between T cell accessibility, tumor recognition, and antigen loss, and how these factors are affected by immune microenvironmental conditions, shedding light on the underlying mechanisms of T-cell dysfunction in cancer progression. Through computational modeling, we have gained a deeper understanding of the complex, ECM-regulated interactions between tumor cells and immune cells. Our model serves as a valuable computational framework that incorporates ECM geometry and microenvironmental parameters, allowing for accurate prediction of tumor-immune evolution outcomes in a variety of contexts.
