Mathematical Modeling of Tumor-Immune Interactions: Methods, Applications, and Future Perspectives (CSIAM Transactions on Life Sciences, 2025)
Mathematical oncology is a rapidly evolving interdisciplinary field that usesmathematical models to enhance our understanding of cancer dynamics, including tumor growth, metastasis, and treatment response. Tumor-immune interactions playa crucial role in cancer biology, influencing tumor progression and the effectivenessof immunotherapy and targeted treatments. However, studying tumor dynamics inisolation often fails to capture the complex interplay between cancer cells and the immune system, which is critical to disease progression and therapeutic efficacy. Mathematical models that incorporate tumor-immune interactions offer valuable insightsinto these processes, providing a framework for analyzing immune escape, treatmentresponse, and resistance mechanisms. In this review, we provide an overview of mathematical models that describe tumor-immune dynamics, highlighting their applications in understanding tumor growth, evaluating treatment strategies, and predictingimmune responses. We also discuss the strengths and limitations of current modelingapproaches and propose future directions for the development of more comprehensiveand predictive models of tumor-immune interactions. We aim to offer a comprehensive guide to the state of mathematical modeling in tumor immunology, emphasizingits potential to inform clinical decision-making and improve cancer therapies.
Keywords: Tumor immunology; mathematical oncology; tumor-immune interaction; mathematical model; computational simulation.