New Mathematical Model Offers Novel Insights Into Cancer Therapy

Cancer responses to treatment can be hard to predict. Besides chemotherapeutic drugs, cancers can also be targeted by T cells and molecular agents called cytokines from the immune system. Mathematicians and physicians from the University of Bonn recently developed a computational model to simulate these stochastic or random interactions to predict the outcome in melanoma tumors undergoing treatment. This model was created using a mathematical concept called adaptive dynamics developed for cancer research applications. It does not only take into account the back-and-forth interactions between the cancer cells and immune system players (e.g., T cells and cytokines), but also reveals how the cells change in phenotype or appearance during the course of therapeutic interventions. Unexpectedly, the model revealed that tumor evolution and treatment outcomes were dependent on the random fluctuations of the size of interacting cell populations. It also suggested that under some circumstances treatment may lead to outgrowth of drug-resistant cancer cells and accelerate the development of aggressive cancer cells. Although this model needs to be further tested experimentally (e.g., human cancer cell culture studies) and advanced to better account for the complexities of the full biological system, it is a promising tool to help physicians determine optimal cancer therapeutic strategies.