Modeling the impact of adiponectin on tumor-immune dynamics: Stability, bifurcations, and optimal control.

Obesity has emerged as a risk factor for several malignancies, primarily due to the dysregulation of adipokines, particularly adiponectin. We develop a nonlinear mathematical model to examine the effects of plasma adiponectin on interactions among tumor cells, healthy cells, and immune cells. Stability and bifurcation analysis reveal a Hopf bifurcation, indicating periodic dynamics in tumor cell behavior. The numerical simulations demonstrate the local stability of equilibrium points and confirm the presence of bifurcations. A two-stage parameter estimation method is used to estimate model parameters using experimental tumor-growth data associated with adiponectin-enhancing treatment. The global sensitivity analysis underscores the adiponectin production rate and tumor immune competition coefficient as the most sensitive parameters. The model suggests a potential threshold of 8.66 μg/mL for achieving tumor suppression. An independent data-driven analysis on clinical data from 2708 individuals yields an optimal threshold of 8.95 μg/mL, showing strong concordance with the model's prediction. We propose an optimal control model that combines immune stimulation and adiponectin-boosting therapy. The model suggests that starting with strong immune activation followed by sustained adiponectin treatment provides the most effective approach. These findings provide a scientific basis for developing cancer treatments that target adiponectin pathways, particularly for obesity-related cancers.