Personalized cancer treatments have greatly improved the lives of patients; however, many eventually develop resistance to these targeted drugs. Instead of simply using another targeted agent against a resistant tumor at a maximum tolerated dose, Moffitt Cancer Center researchers are approaching the problem of resistance from a different direction -; evolutionary science. In a new article published online ahead of print in Cancer Research, members of Moffitt's Center of Excellence for Evolutionary Therapy present a case study of an adaptive treatment approach based on evolutionary principles in prostate cancer and suggest that these strategies may provide a path toward improved multidrug adaptive therapies.
Patients with progressive prostate cancer are often treated continuously or intermittently with drugs that deprive their tumors of androgen. These drugs can work well initially, but eventually resistance develops and tumors regrow. Results from several clinical trials at Moffitt have revealed that adaptive therapy in prostate cancer patients is a promising alternative approach. In adaptive therapy, patient treatment is altered, stopped or reinitiated based on how the tumor responds to treatment.
The goal of adaptive therapy is to maintain a controllable stable tumor burden by allowing a significant population of treatment sensitive cells to survive. According to evolutionary principles, these remaining easy-to-treat sensitive cells block the growth of the resistant tumor cell populations that are difficult to treat. In this approach, it is possible that the tumor may never be completely eradicated; rather, the tumor may remain relatively stable, thereby limiting the development of uncontrollable drug resistance."
Alexander Anderson, Ph.D., chair of Moffitt's Department of Integrated Mathematical Oncology and director of the Center of Excellence for Evolutionary Therapy
Despite the promise of this strategy for prostate cancer, there are several challenges that physicians will need to address when designing the optimum adaptive treatment approach. This is particularly true for approaches that use multiple drugs, as it is unclear if the drugs should be given simultaneously or sequentially, or how often or how long breaks from drug treatments should be used. "Until now, there has not been a clear strategy to extend adaptive therapy to include additional treatments," said Jeffrey West, Ph.D., a Moffitt postdoctoral student and mathematician behind the research.
In order to address these challenges, Moffitt researchers used mathematical models based on evolutionary principles to present a case study of four androgen-deprivation resistant patients who participated in an adaptive treatment clinical trial at Moffitt. Through their analysis, the researchers revealed the importance of three concepts that are critical when designing multidrug adaptive therapies. "Our new strategy carefully selects each treatment to steer and trap the tumor into repeated cycles of evolution," said West.
The concept of "evolutionary cycling" allows the tumor to return to its original composition and reduces the growth of drug resistant populations. This new analysis helps guide the order and timing of currently available treatments based on the speed of evolution.
The researchers highlighted that including breaks from treatment is an important therapy option because it may slow tumor evolution. It is also important to ensure that changes in tumor growth are continuously monitored throughout adaptive treatment. The ideal monitoring approach involves both mathematical models combined with analysis of biomarkers that reveal when tumors are progressing, remaining stable or decreasing in size.
Designing treatments based on mathematical modeling and adaptive therapy is a novel approach that is gaining recognition throughout the oncology community as a potential treatment strategy. "Adaptive therapy is a promising step toward ecologically inspired personalized medicine. Optimizing multidrug adaptive therapy is not a straightforward task, but mathematical models are a powerful abstraction of clinical intuition, enabling the generation of new treatment schedules and comparisons to standard of care," said Anderson.
West, J., et al. (2020) Towards multi-drug adaptive therapy. Cancer Research. doi.org/10.1158/0008-5472.CAN-19-2669.