The prevalence of prostate cancer around the world means that finding an effective treatment is critical. A new UK study has used mathematics to investigate the effectiveness of some currently available prostate cancer treatments.
Prostate cancer is the second most common cancer in men worldwide and the fourth most common cancer overall. Treatment includes everything from observation, immunotherapy and radiation therapy to chemotherapy and surgery, depending on when the cancer is detected and the stage it is at.
An often-used treatment is androgen deprivation therapy (ADT), which involves surgery or the use of medication to lower the amount of androgen produced by the testicles. Androgens are sex hormones that promote the growth of normal and cancerous prostate cells, and ADT deprives the cancer of these hormones, stopping it from growing. However, some patients can develop resistance to the treatment.
A non-steroidal antiandrogen drug called enzalutamide (Xtandi) has been used since 2012, often in combination with ADT, to treat men with advanced prostate cancer or those who stopped responding to chemotherapy. But, as with ADT, patients have been known to become resistant to the drug.
In recent decades, the use of mathematical models to determine cancer growth has gained popularity as a way of helping researchers understand cancer’s evolution and providing insights into the efficacy of drug treatments. In general terms, mathematical modeling is the process of creating a mathematical representation of a real-world scenario and using it to make a prediction or provide greater insights.
Researchers at the University of Portsmouth in the UK developed a novel mathematical model with the goal of optimizing prostate cancer treatment over the short and long term. They simulated using a single drug – enzalutamide, or one of the chemotherapy drugs everolimus and cabazitaxel – and using enzalutamide in combination with either everolimus or cabazitaxel for a 12-, 18-, or 52-week period.
“Our recent research looked at a slice of the prostate, as through a microscope, and then computationally observed how the growth of cancer cells is affected when you add certain drugs,” said Dr Marianna Cerasuolo, one of the study’s co-authors.
The study showed that, for the short-term simulations of 12 and 18 weeks, cabazitaxel was the most effective single-drug therapy, resulting in lower numbers of tumor cells. Alternating therapies, that is, swapping between enzalutamide and one of the two chemotherapy drugs, were more effective than single-drug therapies.
But the simulations showed that alternating therapies using a combination of enzalutamide and cabazitaxel worked best and could significantly improve cancer treatment. The results were verified by comparing them with data obtained from mice with cancer.
“We’re confident that our mathematical simulations are reasonable predictions of a tumor’s behavior in the short and long term,” Cerasuolo said. “However, this mathematical model is based on cancer in mice and further work would be needed to obtain a mathematical modeling framework able to support research in humans and clinical trials."
The study was published in the journal Mathematical Biosciences.
Source: University of Portsmouth
