Synergizing chemotherapy with immune and evolutionary tradeoffs: Searching for Goldilocks

A mainstay treatment for many cancers is chemotherapy, for which the dosing strategy is primarily limited by patient toxicity. While this Maximum Tolerated Dose (MTD) approach builds upon the intuitively appealing principle that maximum therapeutic benefit is achieved by killing the largest possible number of cancer cells, there is increasing evidence that moderation may be better. The increasing use of immune therapies which seek to use the patient’s own immune system therapeutically, bring the effectiveness of MTD into question. In some cases, there may exist a ‘Goldilocks Window’ of sub-maximal chemotherapy that yields improved overall outcomes. This window reflects the complex interplay of cancer cell death, changes in immune function, emergence of chemoresistance, and the potential for metastatic dissemination. Importantly, the many changes induced by chemotherapy have tradeoffs that depend on the specific agents being used, as well as their dosing levels and scheduling. We present experimental and clinical observations across cancer types that support the idea that MTD may not always be the best approach. Our mathematical model driven results indicate which patient states would benefit most from a Goldilocks chemotherapy dosing schedule. Implementation of such a personalized treatment regime, that incorporates insights from eco-evolutionary dynamics, will require the integration of predictive mathematical models of tumor-immune responses to therapy with appropriate patient specific clinical data.