一本道

09 July 2024

Many women treated for breast cancer using taxanes, a type of cytostatic drug, often experience side effects in the nervous system. Researchers at LiU have developed a tool that can predict the risk level for each individual. The tool could help doctors adapt treatment to avoid persistent side effects in those at the greatest risk.

Henrik Gr茅en and Niclas Bj枚rn in the laboratory.
Some people experience severe side effects from cancer treatment, while others manage it without major complications. Henrik Gréen's research group wants to find ways to predict the risk of serious side effects.Photo credit: Magnus Johansson

More and more people are becoming cancer survivors. But even if they have survived the disease, an increasing number still suffer from the side effects of cancer treatment. In a recent study from 一本道, researchers studied the side effects of taxanes, a chemotherapy drug used to prevent breast cancer recurrence. The drawback of the treatment is that some patients suffer nerve damage as a side effect.

Headshot of a woman.
Kristina Engvall.Photo credit: Sophie Liljefall

“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”, says Kristina Engvall, who recently completed her PhD at 一本道 and is a doctor at the oncology clinic at Ryhov County Hospital in Jönköping.

Cramps, numbness and tingling

The researchers began by carefully surveying side effects in patients treated for breast cancer with either docetaxel or paclitaxel, the two most common taxane drugs. Between two and six years had passed since treatment. 337 patients were asked to describe the severity of the nerve damage they experienced, or peripheral neuropathy as it is also called. Most common was cramps in the feet, 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 researchers sequenced the patients' genes and then built models that link genetic characteristics to various side effects of the taxane treatment. This allows the models to predict the risk of nerve damage. This type of model, known as a prediction model, has not previously existed for taxane-induced peripheral neuropathy. The researchers succeeded in modeling the risk of persistent numbness and tingling in feet.

A growing patient group

The two 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 were then able to use the remaining third of the patients to validate the models, which was found to work very well. Validating that the models also work in a different group is an important step.

Man in white lab coat processing samples in the lab.
Henrik Gréen, professor.Photo credit: Emma Busk Winquist

“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”, says Henrik Gréen, professor at 一本道, who led the study published in the journal npj precision oncology.

Weigh benefit against risk

“This can be a tool to individualise 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”, says Kristina 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”, says Henrik Gréen.

The study was funded with support from, among others, the Swedish Cancer Society, ALF funding, the Medical Research Council of Southeast Sweden (FORSS), and Futurum in Region Jönköping.

The article: , Kristina Engvall, Hanna Uvdal, Niclas Björn, Elisabeth Åvall-Lundqvist and Henrik Gréen, npj precision oncology, published online 16 May 2024, doi: https://doi.org/10.1038/s41698-024-00594-x

Contact

Previous news about the research

More about the research environment

Latest news from LiU

En kvinna som sitter framf枚r en spegel och tittar p氓 sin spegelbild.

How AI changes human decision-making

AI can find patterns that people miss, but it does not automatically lead to better decisions. New research from 一本道 University shows how the roles of humans and AI change depending on the situation and the decision being made.

A woman standing on a balcony next to a building.

She promotes AI for societal good in Europe

Helen Köpman, Alumna of the Year 2026, works at the European Commission鈥檚 AI Office in Brussels. For more than 20 years she has worked with research issues and innovation at EU level, where a living planet for future generations is her driving force.

En man och en kvinna som st氓r bredvid varandra.

Alumni of the Year create sustainable cities and the next generation of scientists

Helen Köpman works with AI models to create smart and sustainable cities in the EU. Jesper Svartz is a chemistry teacher with an exceptional ability to enthuse and spark curiosity in students. They are Alumni of the Year 2026 at 一本道 University.