Understanding breast cancer diversity to improve patient care
Breast cancer is not a single disease: different patients and tumours can behave very differently, even when they receive the same diagnosis. This biological diversity makes it challenging to predict how a tumour will develop and to identify the most appropriate treatment for each patient. This is particularly relevant for patients with intermediate-risk hormone receptor-positive breast cancer and for those with triple-negative breast cancer, an aggressive form of the disease for which effective targeted treatments remain limited.
This project aims to improve breast cancer classification and treatment by considering not only standard clinical and molecular features, but also the biological behaviour of tumour cells. We have developed two molecular signatures, called PetSign and StemPrintER, which capture different features of tumour biology, including changes in cellular metabolism and the acquisition of stem-like properties that can contribute to tumour growth and progression.
The project will investigate whether these signatures can improve the prediction of disease outcome and help identify groups of patients with different biological characteristics who may benefit from different therapeutic approaches. We will also test whether the biological features captured by these signatures can be used to identify novel drugs or existing drugs that could be repurposed for treating specific types of breast cancer.
We expect this research to provide new tools for more accurate patient stratification and to identify potential therapeutic opportunities, particularly for patients with limited treatment options. In the longer term, the project could contribute to a more personalised approach to breast cancer treatment, helping to select more effective therapies while reducing unnecessary treatments and their burden on patients and healthcare systems.
This project is funded by the Italian Ministry of University and Research (MUR) under the Fondo Italiano per la Scienza (FIS 3) programme.
Posted on October 2, 2026