HMN 2026: How Genetic test forecasts chemo response in breast cancer

A new study from Karolinska Institutet shows that gene analysis of breast cancer tumors can identify patients who do not benefit from chemotherapy given before surgery. The findings, published in the journal Nature Communications, could in the long term contribute to more personalized treatment.

The study included 179 patients with hormone dependent, HER2 negative breast cancer who took part in the Swedish PREDIX LumB trial. Before surgery, all patients received both treatments, but in different sequences. They were given either chemotherapy followed by hormone blocking therapy together with the drug palbociclib, which slows the division of cancer cells, or the reverse sequence.

When the researchers analyzed the results, they found that the treatments led to similar reductions in tumor size overall. Survival was also similar regardless of whether treatment started with chemotherapy or with palbociclib and hormone blocking therapy.

Not all tumors responded to chemotherapy

At the same time, the analyses showed that there was a subgroup of tumors with a poorer response to chemotherapy but a better response to palbociclib in combination with hormone-blocking therapy.

To understand why some tumors did not respond to chemotherapy, the researchers analyzed tumor gene expression, how active different genes are in the tumor, in tissue samples taken before treatment started. Based on these analyses, they developed a model called CDKPredX, which can identify tumors that respond poorly to chemotherapy but better to palbociclib combined with hormone blocking therapy.

“Today, we lack reliable ways to determine in advance which patients will actually benefit from chemotherapy before surgery. Our results show that tumor gene expression can provide important information in this respect,” says first author Alexios Matikas, docent at the Department of Oncology-Pathology, Karolinska Institutet.

The model is based on patterns of gene expression in the tumor, including genes involved in cell division, hormone signaling and the immune system. When the researchers tested the model in other patient groups, they observed similar patterns.

“In the longer term, this type of analysis could help patients avoid treatments that do not benefit them, such as chemotherapy, and instead receive treatment that has a better chance of working. At the same time, further studies are needed before the method can be used in clinical practice,” says senior author Theodoros Foukakis, professor at the same department.

The researchers emphasize that the study is exploratory and that the genetic analysis is not yet ready for clinical use. Nevertheless, the results provide new insights into why different tumors respond differently to treatment.