Moffitt Cancer Center researchers, in collaboration with Oxford University, published in Cancer Research their study on using mathematical modeling to show that cell turnover impacts drug resistance and is an important factor that governs the success of adaptive therapy, according to a news release from the cancer center.
Cancer treatment options have increased substantially over the past few decades; however, many patients eventually develop drug resistance. Physicians strive to overcome resistance by either trying to target cancer cells through an alternative approach or targeting the resistance mechanism itself, but success with these approaches is often limited, as additional resistance mechanisms can arise.
Moffitt researchers believe an alternative treatment strategy called adaptive therapy may be a better approach to kill cancer cells and minimize the development of drug resistance.
The research team at Moffitt used mathematical modeling to determine how the cost of resistance is associated with adaptive therapy. They modeled the growth of drug sensitive and resistant cell populations under both continuous therapy and adaptive therapy conditions and compared their time to disease progression in the presence and absence of a cost of resistance.
The researchers showed that tumors with higher cell density and those with smaller levels of pre-existing resistance did better under adaptive therapy conditions. They also showed that cell turnover is a key factor that impacts the cost of resistance and outcomes to adaptive therapy by increasing competition between sensitive and resistance cells. To do so, they made use of phase plane techniques, which provide a visual way to dissect the dynamics of mathematical models.
Previous laboratory studies have shown that adaptive therapy can prolong the time to cancer progression for several different tumor types, including ovarian, breast and melanoma. Additionally, a clinical trial in prostate cancer patients at Moffitt has shown that compared to standard treatment, adaptive therapy increased the time to cancer progression by approximately 10 months and reduced the cumulative drug usage by 53 percent.
Despite the encouraging results, it is unclear which tumor types will respond best to adaptive therapy in the clinic. Recent studies have shown that the success of adaptive therapy is dependent on different factors, including levels of spatial constraint, the fitness of the resistant cell population, the initial number of resistant cells and the mechanisms of resistance. However, it is unclear how the cost of resistance factors into a tumor’s response to adaptive therapy.
The cost of resistance refers to the idea that cells that become resistant have a fitness advantage over non-resistant cells when a drug is present, but this may come at a cost, such as a slower growth rate. However, drug resistance is not always associated with a cost and it is unclear whether a cost of resistance is necessary for the success of adaptive therapy.
While more studies are needed to understand how adaptive therapies may benefit patients, researchers are hopeful their data will lead to better indicators of which tumors will respond to adaptive therapy.
