Proefschrift

CHAPTER 9. IMPACT While overall survival of early stage prostate cancer has increased due to early detection and improved therapy for local and regionally confined disease, metastatic prostate cancer, with few exceptions, remains incurable. The 5-year overall survival for metastatic prostate cancer patients has actually dropped by 3.1% (from 31.8% to 28.7%) since 1977. This is largely due to the ability of metastatic cancer cell populations to evolve resistance to all currently available therapies. Despite the increasing numbers of effective agents for treating metastatic cancers, evolution of resistance remains the fundamental barrier to achieving a cure. In the simplest sense, the ultimate goal of treating cancer is for the patient to remain alive. This is not synonymous with eradicating all tumor cells in the body. This thesis proposes, at its core, to abandon the idea of curing metastatic disease and presents multiple alternative approaches to current standard of care, developed using mathematical oncology, to reimagine metastatic disease as a chronic illness that is managed in the long term. As H.G. Wells once stated, “If we don’t end war, war will end us.” While the search for truly curative therapies continues, the work in this thesis provides evidence that patient outcomes can be improved by optimizing the dosing strategy of current standard of care therapies. By integrating evolutionary principles that aim to limit or delay the proliferation of resistant subpopulations into current treatment protocols, the time to progression of currently available therapies can be significantly lengthened. Delaying or preventing the evolution of resistance could prolong drug sensitivity and potentially allow for large increases in overall survival. Scientific Impact Chapter 1 provides a background of the main threads of this thesis: prostate cancer, evolutionary game theory, and agricultural pest management. Chapter 2 qualitatively formalizes a clinical paradigm for treatment of metastatic disease exploiting proven pest management techniques that could drastically reduce drug usage, delay or completely prevent evolution of resistance to available drugs, and lengthen the overall survival of patients. Chapter 3 presents details of the design, analysis, and implementation of an evolutionary game theoretic model of prostate cancer with abiraterone treatment. Chapter 4 reports the interim results of the first of its kind clinical trial at Moffitt Cancer Research Institute based on the mathematical model developed for this thesis (NCT02415621). The evolutionary based application of abiraterone, designed by work in this thesis, increased median time to progression of 16 men with metastatic prostate cancer from 14.3 months to 30.4 months. With the success of the trial, Chapter 5 uses optimal control theory to show that while the clinical trial provided significant patient benefit, small changes in the abiraterone dosing protocol could provide significant additional benefits. Chapter 6 proposes that an increasing dose titration protocol, a very common dosing protocol in other medical fields, though rarely used in clinical oncology, could potentially achieve tumor stabilization to drastically lengthen the overall survival of patients. All of the full scientific chapters in this thesis are published in international peer-reviewed journals. Chapter 2 is published in Nature Ecology & Evolution in 2019. Chapter 4 is published in Nature Communications in 2017 and has been accessed over 122