TY - JOUR
T1 - Mathematical Modeling of Tumor-Immune Interactions: Methods, Applications, and Future Perspectives
AU - Li , Chenghang
AU - Lei , Jinzhi
JO - CSIAM Transactions  on Life Sciences
VL - 2
SP - 200
EP - 257
PY - 2025
DA - 2025/06
SN - 1
DO - http://doi.org/10.4208/csiam-ls.SO-2024-0008
UR - https://global-sci.org/intro/article_detail/csiam-ls/24161.html
KW - Tumor immunology, mathematical oncology, tumor-immune interaction, mathematical model, computational simulation.
AB - <p style="text-align: justify;">Mathematical oncology is a rapidly evolving interdisciplinary field that uses
mathematical models to enhance our understanding of cancer dynamics, including tumor growth, metastasis, and treatment response. Tumor-immune interactions play
a crucial role in cancer biology, influencing tumor progression and the effectiveness
of immunotherapy and targeted treatments. However, studying tumor dynamics in
isolation 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 insights
into these processes, providing a framework for analyzing immune escape, treatment
response, 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 predicting
immune responses. We also discuss the strengths and limitations of current modeling
approaches and propose future directions for the development of more comprehensive
and predictive models of tumor-immune interactions. We aim to offer a comprehensive guide to the state of mathematical modeling in tumor immunology, emphasizing
its potential to inform clinical decision-making and improve cancer therapies.</p>