Moffitt Cancer Center investigators, reporting in the journal Cell Systems, report the development of a new adaptive therapy approach to ovarian cancer poly-adenosine ribose polymerase (PARP) inhibitor treatments that promises a more personalized and less toxic treatment option for patients.
Toxicity and emerging drug resistance are challenges in providing PARP inhibitor maintenance therapy in ovarian cancer. Cancer treatments have largely consisted of providing the maximum tolerated dose to patients in the attempt to quickly kill as many cancer cells as possible.
Adaptive therapy approaches seek to address both issues. Using this approach, when a therapy shows it is acting against a patient’s cancer the patient and physician may pause treatment as soon as there is evidence the cancer is responding, instead of pursuing a traditional treatment strategy the uses the maximum tolerated dose of a drug until treatment failure. When tumor burden begins to increase again, the cancer is retreated with the same agent seeking an additional response, ideally before recurrence of symptoms or impacts to the quality of life of patients from treatment side effects.
“Adaptive therapy tailors treatment to the tumor’s dynamics, allowing us to adjust drug levels to match a patient’s specific disease characteristics,” said Alexander Anderson, PhD, study author and chair of the integrated mathematical oncology department at Moffitt. “Our findings suggest that modulation, rather than skipping doses, can halve the amount of drug used while maintaining its effectiveness. This approach reduces toxicity and can potentially delay the development of resistance.”
For this study, the Moffitt team used mathematical modeling and in vitro experiments seek the most effective adaptive dosing strategies. The investigators conducted time-lapse microscopy to observe cancer cell populations of each of the different treatment schedules studied. The model showed that dose modulation can both effectively manage a patient’s tumors and use less medication than traditional approaches. Follow on in vivo experiments confirmed the model’s results, showing the viability of this strategy.
While the rationale behind adaptive therapy is to delay resistance by promoting competition between sensitive and resistant tumor populations, the Moffitt researchers took a different route and instead focused only on the dynamics of cells sensitive to treatment. The team noted two reasons for taking this approach. “First, this is the dominant population at the start of treatment, and any (adaptive therapy) protocol will need to ensure that we can control this population before we can evaluate potential benefits in inhibiting resistance,” the researchers wrote. “Second, by integrating the tumor’s response dynamics into the decision-making process, (adaptive therapy) also allows patient-specific treatment tailoring that better reflects the amount of drug required to control a particular patient’s disease.”
This proof-of-principal marks the first mechanistic mathematical model of PARP inhibitor treatment in the literature, and it was systematically derived from, and validated with, in vitro experimental data, the investigators note.
While the results are promising, the team noted several remaining challenges that need to be addressed in future studies. The first was the delayed response to the PARP inhibitor, taking seven days after dosing for cancer cell populations to begin to recede. They also observed wide variability in the predicted treatment dynamics of adaptive therapy pointing to the need to further optimize the timing of when treatment decisions are made and the specific thresholds used to drive those decisions.
The investigators also believe their research could have implications beyond the treatment of ovarian cancer.
“With the growing use of PARP inhibitors in other cancers, such as prostate and breast cancer, we believe that our results may be of interest more broadly, and we encourage further exploration of adaptive scheduling as a means for patient-specific toxicity and resistance management,” the researchers concluded.
