Applying Evolutionary Principles to Cancer Therapy

Disseminated cancers often initially respond to systemic therapy but almost inevitably relapse due to emergence of resistant clones. The sequence of response followed by adaptation and progression indicates emergence of resistant phenotypes is governed by Darwinian dynamics generated by the strong selection pressure imposed by anti-cancer drugs. Thus, evolution of resistance to treatment eventually leads to death of virtually all metastatic cancer patients and this will likely remain so even with targeted, personalized therapy. Leslie Orgel famously observed that “evolution is cleverer than you.” Nevertheless, cancers, like all evolving systems, can only adapt to current and local environmental conditions—they can never anticipate future Darwinian dynamics. Importantly, we can and this is perhaps our greatest advantage in cancer treatment. Here we present therapeutic approaches that exploit evolutionary dynamics to maintain tumor control. We also examine strategies to overcome the practical limitations to the application of evolutionary principles in clinical settings. How do we generate the necessary and sufficient data to capture spatial and temporal heterogeneity and how do we use these data to predict optimal therapeutic strategies?