Gene-Based Model Predicts Taxane Side Effects in Breast Cancer Treatment

Taxanes are often used as chemotherapy for breast cancer, but they can cause side effects in the nervous system, such as foot pain. Researchers at Linköping University in Sweden have now developed a statistical tool that uses sequencing and other data to predict individual risk level for such side effects. The tool, they said, could help doctors adapt treatment to avoid persistent side effects in those at the greatest risk.

The study was published in the journal nature precision oncology. Henrik Gréen, professor at Linköping University, was the senior author.

“This is the first time a prediction model has been developed that can predict the risk of nerve damage from taxane treatment. Women who have been treated with taxanes after breast cancer surgery make up a very large group in healthcare worldwide, so this is a major and clinically relevant problem,” said Gréen. 

“Side effects in the form of nerve damage are very common after treatment with taxanes for breast cancer, and they often persist for several years. For those affected it is extremely stressful, and it has a major impact on quality of life. So it is a major clinical problem, which has received more attention in recent years, but there has been no way to know which individuals are at greatest risk of side effects,” said Kristina Engvall, of the oncology clinic at Ryhov County Hospital in Jönköping.

The researchers began by surveying side effects in breast cancer patients treated with either docetaxel or paclitaxel, the two most common taxanes. Between two and six years after treatment, 337 patients were asked to describe the severity of the nerve damage, or neuropathy, they experienced. The most common symptom was foot cramps, which more than one in four patients had. Other side effects included difficulty opening a jar, numbness in feet, tingling in feet and difficulty climbing stairs.

The team then sequenced the patients’ genes and built models that link genetic characteristics to various side effects of the taxane reatment. This allows the models to predict the risk of nerve damage. They built two statistical prediction models for the risk of developing persistent foot numbness and tingling after taxane treatment.

The models were able to separate the patients into two clinically relevant groups: one with a high risk of persistent side effects, and one that corresponded to the frequency of peripheral neuropathy in the normal population. The researchers used two-thirds of the data to train the models through machine learning.They used the remaining third of the patients to validate the models.

“This can be a tool to individualize treatment, and not only to look at the benefits, but also to look at the risks for the individual patient. Today we are so good at treating breast cancer that we need to focus more on the risk of complications and side effects that affect the patient long after treatment,” said Engvall.

In the long term, the prediction model could be adopted as routine in healthcare. But first, research is needed in order to find out whether the prediction model also works well in other population groups than the Swedish population.

“It also emerged that three of the five symptoms we focused on are so biologically complex that we could not model them. These include, for example, difficulty opening cans. Opening a can involves both motor and sensory nerves, which makes it very difficult to predict which individuals are at greatest risk of developing that symptom,” said Gréen.