University of California, Irvine researchers have identified a critical factor in why PD-1 blockade immunotherapy, a treatment for advanced melanoma, frequently loses its efficacy after initial success. Their work, published in Cancer Research, utilized a mathematical model to predict a mechanism of resistance, which was then experimentally validated.
PD-1 blockade immunotherapy has transformed outcomes for some patients with advanced melanoma, an aggressive form of skin cancer, converting terminal diagnoses into long-term survival for responders. However, approximately 7 out of 10 melanoma patients treated with this immunotherapy experience disease recurrence, even if the treatment initially appeared effective. Historically, determining why immunotherapy fails and identifying solutions has been a challenging and resource-intensive process, typically involving slow, incremental experimental testing of one hypothesis at a time.
A research team at UC Irvine adopted a different approach. Instead of sequential laboratory experiments, they first constructed a mathematical model capturing interactions between tumor and immune cells. This model was used to identify the most probable mechanism of resistance. Francesco Marangoni, a cancer immunologist and assistant professor, collaborated with John Lowengrub, a Distinguished Professor of mathematics, biomedical engineering and systems biology, and Rachel Sousa, a graduate student researcher and the study’s first author, on the project.
Within a tumor, effector T cells are key in destroying cancer cells, while regulatory T cells, or Tregs, can protect the tumor by suppressing these effector cells. Tumor cells also defend themselves by displaying PD-L1 protein, which binds to PD-1 on effector T cells, inhibiting their activity. PD-1 blockade immunotherapy works by thwarting this interaction, reactivating effector T cells. However, this treatment can also unintentionally strengthen Treg activity, helping restore the tumor-protective environment it aimed to overcome.
The researchers translated these cellular interactions into mathematical equations, then validated the model against experimental data from mice with melanoma. After refinement, the team used the model to simulate 342 "virtual mice" with melanoma, each reflecting natural biological variation. By comparing virtual mice that responded favorably to those that experienced recurrence after simulated PD-1 blockade immunotherapy, the team found one consistent distinguishing factor: the speed at which Tregs were entering the tumor. Rachel Sousa stated that the mathematical analysis "indicated that the rate of Treg infiltration into the tumor was the critical factor."
To validate this finding, the team engineered mice where Tregs inefficiently migrated into tumors, then treated these animals with PD-1 blockade immunotherapy. This combined approach significantly improved outcomes, nearly doubling survival duration and slowing tumor growth compared to PD-1 blockade alone. John Lowengrub noted the "agreement between the model prediction and experiments is exciting because it points toward a promising new strategy."
This study does not represent a treatment immediately available to patients. However, it provides a faster, more cost-efficient framework for determining which therapeutic strategies merit further development. For melanoma specifically, this research reinforces interest in targeting Treg infiltration of the tumor simultaneously with PD-1 blockade immunotherapy. The mathematical model itself is also a reusable platform for testing other treatments and exploring additional mechanisms of therapy resistance.
