The prevalence of prostate cancer worldwide means that finding effective treatments is critical. A new UK study uses mathematics to investigate the effectiveness of several currently available prostate cancer treatments.
Prostate cancer is the second most common cancer in men worldwide and the fourth most common cancer overall. Treatment may include everything from observation, immunotherapy, and radiation therapy to chemotherapy and surgery, depending on when the cancer was discovered and at what stage.
A commonly used treatment is androgen deprivation therapy (ADT). This includes surgery or drug therapy to lower the amount of androgens produced by the testicles. Androgens are sex hormones that promote the growth of normal and cancerous prostate cells, and ADT deprives cancers of these hormones, halting their growth. However, some patients may be resistant to treatment.
A nonsteroidal antiandrogen called enzalutamide (Xtandi) has been used since 2012, often in combination with ADT, to treat men with advanced prostate cancer or who have stopped responding to chemotherapy. However, like ADT, patients are known to develop tolerance to this drug.
In recent decades, the use of mathematical models to determine cancer growth has gained popularity as a way for researchers to understand cancer evolution and provide insight into the efficacy of drug treatments. increase. Generally speaking, mathematical modeling is the process of creating mathematical representations of real-world scenarios and using them to make predictions or provide better insights.
Researchers at the University of Portsmouth, UK, have developed a new mathematical model with the goal of optimizing prostate cancer treatment over the short and long term. They used enzalutamide or one of the chemotherapy drugs everolimus and cabazitaxel to simulate the use of enzalutamide in combination with everolimus or cabazitaxel for 12, 18, or 52 weeks.
“In our recent study, we looked at slices of the prostate microscopically and looked computer-assisted at how cancer cell growth was affected by the addition of specific drugs,” said one of the co-authors of the study. One, Dr. Marianna Cerasuolo, said:
In this study, 12-week and 18-week short-term simulations showed cabazitaxel to be the most effective monotherapy with low numbers of tumor cells. Alternating therapy, ie, replacing enzalutamide with one of his two chemotherapy drugs, was more effective than monotherapy.
However, simulations showed that alternation therapy using a combination of enzalutamide and cabazitaxel was the most effective and could significantly improve cancer treatment. verified by comparing with
“We are confident that our mathematical simulations are reasonable predictors of short- and long-term tumor behavior,” said Cerasuolo. “However, this mathematical model is based on mouse cancer, and further work is needed to obtain a mathematical modeling framework that can support human studies and clinical trials.”
The study was published in a journal Mathematical Life Science.
Source: University of Portsmouth
