Prostate Cancer Lab #9: An Evolutionary Treatment Strategy (Bob Gatenby)

Bob Gatenby, MD, Moffitt Cancer Center, Co-Director, Center of Excellence for Evolutionary Therapy, and Department Chair, Diagnostic Imaging, shared his novel strategies for advanced cancer treatment based on evolutionary and game theory and experimental models. The strategies include combining therapies, low doses, sequencing treatments, and using mathematical simulation models, in contrast with the predominant treatment strategy of maximum tolerable dose until resistance. An incidental theme is his concern about limitations in the clinical gold standard of evidence – double-blind randomized trials, which he argues have some benefits, but also some drawbacks, which are more apparent as we move away from maximum tolerated dose treatments to personalized cancer care with molecular targets.

Bob advocates using “adaptive therapy”, rather than continuously applying the maximum tolerable dose until resistance: you treat enough to knock the tumor back a little bit, and then pull the treatment away, allowing the tumor to grow. But since the sensitive cells do not have the burden of the resistance mechanisms that the resistant cells have, the sensitive cells have a fitness advantage, and outcompete the resistant cells. The strategy is to use the sensitive cells that you can control to control the resistant cells that you cannot control.

Bob shared a study using an androgen suppressing drug (abiraterone) in this adaptive therapy on-off mode, monitoring disease progression through PSA tests. 17 patients completed the trial and were compared to 16 demographically similar patients who had the same 50% PSA decline with the initial abiraterone dose, but who then got standard of care dosing. The difference in median time to progression was 14.3 months on the standard of care, compared to 33.5 months on adaptive therapy. Overall survival in the standard of care cohort was 30.4 months vs. 58.5 months in the adaptive therapy group. 4 of the 17 adaptive therapy patients are still alive and on treatment, over six years since their treatment began. The patients on the adaptive therapy did not get treatment about half of the time, which resulted in a cost reduction of an average of $70,000 per patient per year.

Bob shared several key principles of advanced cancer treatment strategy that he has learned:

• Low dose: Hit the tumors with enough treatment to perturb their system, but not so much to kill the sensitive cells and leave the resistant cells to proliferate. The cancer group is heterogeneous and the resistant cells can be controlled by keeping the sensitive cells around.
• Combinations (first strike second strike): Lacking magic bullets, metastatic cancers can be cured through a strategic combination of pretty good bullets. None of these bullets could by themselves cure the cancer, but the combination could.
• Sequencing (not a combination cocktail): If you have a combination cocktail, especially as a first strike, you’re applying the therapy to the largest possible population. The heterogeneity is such that almost certainly you will find tumor cells that can be resistant to the combination. It is better to hit the cancer with therapies in sequence, as each knocks the population down and can drive it to an extinction.
• Mathematical models: Having a hypothesis and a simulation of what should happen based on evolutionary theory helps in understanding why and enables insights from much smaller trial cohorts.

To apply this strategy in real life we asked Bob to give his off-the-cuff thoughts on the case of advanced cancer patient Brian McCloskey, who is currently on abiraterone, the drug that Bob used in his study. Bob felt that because Brian currently has a low tumor volume that he is a candidate for an attempt at extinction, to hit his cancer with a ladder of 3 different drugs to successively knock down the population, with the hope that it could be nudged down the vortex.

Requests

• Do you have any feedback on Bob’s principles for treatment strategy?
• This adaptive strategy seems intuitive, yet it’s not widely practiced. What are the barriers or objections to it?