Overcoming drug resistance to prostate cancer

Prostate cancer is the most common cancer in men, with one in eight receiving the diagnosis in their lifetime. Fortunately, a combination of hormonal treatments and chemotherapy can successfully manage the condition and the five-year survival rate is almost 100% for early-stage patients. However, late-stage diagnoses are far harder to treat. Around half of prostate cancer sufferers will develop metastases, meaning that tumours spread throughout the body and begin affecting other organs. Repeated treatments can help control tumour growth but currently there is no cure and existing medications become less effective over time. For oncology specialists, one of the biggest challenges is overcoming the drug resistance which emerges as these aggressive tumours are repeatedly exposed to the same treatments.

"The current approach to many cancer treatments is to apply the maximum tolerated dose," says Colette Christiansen, an applied mathematician at The Open University. "For many cancers, this is not only a high toxicity burden for the patient but also inevitably leads to resistance in the cancer itself."

Christiansen, alongside a close team of oncology experts and industry partners, is developing novel strategies for overcoming this problematic resistance as part of the Open University's Open Societal Challenges programme. Resistance is naturally present in a small number of cells but becomes a dominant characteristic when surrounding non-resistant cancer cells are killed by successful treatment. Without competition, the resistant cells thrive and, as the proportion of these cells grows, the tumour becomes harder and harder to treat and is ultimately incurable. Christiansen's team are exploring a subtler approach. By reducing the medication dose, they hope to suppress the emergence of resistant cancer cells by maintaining competition with carefully-controlled numbers of non-resistant tumour cells.

"If we consider the tumour as an ecosystem and adjust the timing of the treatment so that the resistant cells do not gain a significant growth advantage (due to large reductions in the populations of non-resistant cells), theoretically we can reduce the cancer, avoid resistance, and lower the toxicity of the treatment at the same time," explains Christiansen. "Our vision is to experimentally test this mechanism and mathematically optimise a treatment schedule that minimises resistance and materially improves the prognosis."

The team will focus their efforts on the most common first line treatment for late-stage prostate cancer, hormonal treatment; boosted by an epigenetic drug. The hormonal treatment enzalutamide starves the cancer cells of the testosterone they need to grow, while the booster drug tazemetostat may increase the sensitivity of resistant cells to the hormonal treatment. In the first stage, Christiansen will create a modelling framework to determine the optimal treatment schedule, moderating the doses of each drug as the tumour shrinks. This computation will be calibrated against experimental in vitro models of cancer cell cultures, allowing the team to determine how closely growth behaviour and resistance match the model. Refinements to this initial framework will then be tested on in vivo systems, enabling the team to make any final adjustments to ready the treatment plan for clinical trial approval.

"Ultimately, we hope to progress the prostate cancer optimised treatment to clinical trials and to potentially generalise the modelling to be suitable for use for other cancers," says Christiansen "This should lead to a better prognosis for prostate cancer and a robust framework for setting therapy schedules in preclinical and clinical trial stages for new treatments."