Abstract
Mathematical models of cancer–immune interactions help explain how tumors evolve under different immune systems. In this study, we analyze a nonlinear system describing tumor and immune cell dynamics. We focus on how changes in the immune suppression parameter κ, representing immune checkpoint-mediated medicine, leads to different long-term outcomes. Using simulations and phase plane analysis, we mathematically explicate two regimes: immune limited and immune escape. We also simulate treatment strategies such as surgery and immunotherapy, showing how parameter changes can shift the system between these outcomes.