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Cancer research

Predicting Response to Immunotherapy in HER2-Negative Breast Cancer

Strategic Insights

— 1 min read

Researchers from the University of Milan have made significant progress in understanding how to predict the response to immunotherapy in HER2-negative breast cancer patients. By developing an algorithmic strategy called ARIADNE, which analyzes gene expression data from bioptic samples based on epithelial-mesenchymal phenotypes, the team was able to predict the response to immunotherapy in a subset of patients. The study used data from the I-SPY 2 trial and found that the ARIADNE algorithm was able to predict differential response to immunotherapy, with a pathological complete response rate of 26% in the high-risk group compared to 62% in the low-risk group.

Key Takeaways:

  • The ARIADNE algorithm was able to predict the response to immunotherapy in HER2-negative breast cancer patients, with a pathological complete response rate of 26% in the high-risk group and 62% in the low-risk group.
  • The algorithm was based on gene expression data from bioptic samples and analyzed according to epithelial-mesenchymal phenotypes.
  • The study used data from the I-SPY 2 trial, which included 248 patients treated with pembrolizumab and chemotherapy.
  • The ARIADNE algorithm was not able to predict the response to chemotherapy in HER2-negative breast cancer patients.
  • The study highlights the potential of ARIADNE as a tool for predicting response to immunotherapy in HER2-negative breast cancer patients.
  • The research was led by Caterina A. M. La Porta and included contributions from Ornella Garrone, Marco Merlano, and Stefano Zapperi.

Statistics:

  • 248 patients were included in the study, with 69 receiving pembrolizumab and chemotherapy and 179 receiving chemotherapy alone.
  • The pathological complete response rate was higher in the low-risk group (62%) compared to the high-risk group (26%).
  • The odds ratio for the relationship between ARIADNE score and pathological complete response was 4.7 (95% CI 1.68-11.32).

Sources:

  • "Predicting the response to immunotherapy from gene expression data in HER2-negative breast cancer." Communications Medicine, 2025;5(1):415.
  • NewsRx. Researchers from University of Milan Report New Studies and Findings in the Area of Breast Cancer (Predicting the response to immunotherapy from gene expression data in HER2-negative breast cancer). Immunotherapy Weekly. October 15, 2025; p 1064.

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