BIMSA > BIMSA Computational Math Seminar BIMSA Computational Math Seminar Mathematical model of tumor-macrophage interactions: Elucidating the tumor-driven macrophage phenotype reprogramming
Mathematical model of tumor-macrophage interactions: Elucidating the tumor-driven macrophage phenotype reprogramming
Organizers
Tahereh Eftekhari , Pipi Hu , Xin Liang , Zhiting Ma , Hamid Mofidi , Chunmei Su , Axel G.R. Turnquist , Li Wang , Fansheng Xiong , Shuo Yang , Wuyue Yang
Speaker
Haifeng Zhang
Time
Wednesday, June 17, 2026 1:30 PM - 2:30 PM
Venue
Online
Online
Zoom 518 868 7656 (BIMSA)
Abstract
The interplay between tumor cells and macrophages plays a central regulatory role in cancer progression. In this study, we developed a mathematical model that incorporates tumor cells, M1-type macrophages, M2-type macrophages, and an M3-type macrophage population characterized by dual phenotypic features. First, we analyzed the fundamental mathematical properties of the model and derived the conditions under which the system attains a tumor‑free equilibrium or a coexistence state of tumor and immune cells. Second, global sensitivity analysis revealed that key parameters governing macrophage polarization and intercellular communication vary dynamically during tumor development. Bifurcation analysis further identified the polarization rate of M1‑type macrophages and the baseline level of resting macrophages as critical determinants of the system's dynamical behavior. Notably, using approximate Bayesian computation for parameter inference and dynamic simulations, the model successfully recapitulated the evolutionary trajectories of eight tumor samples. The results demonstrate that lower tumor burden is significantly associated with higher M1‑type macrophage infiltration and delayed peak time of M3‑type macrophage activation. Moreover, survival analysis indicated that both enhanced M1‑type macrophage infiltration and delayed peak time of M3‑type macrophage activation are correlated with longer survival time. In summary, this study provides a theoretical framework for understanding the dynamic mechanisms underlying tumor-macrophage interactions and proposes two model-derived parameters as candidate prognostic markers: the level of M1-type macrophage infiltration and the peak time of M3-type macrophage activation. These predictions, while grounded in the model, require further experimental and clinical validation.
Speaker Intro
Haifeng Zhang obtained Ph.D. degree from Department of Mathematical Sciences at Tsinghua University, China in 2023. Currently, he is a lecturer in School of Mathematical Sciences, Jiangsu University. His current research interests include mathematical biology, differential equations, and control theory.