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Advanced filters: Author: Ingrid Garberis Clear advanced filters

Deep learning assessment of metastatic relapse risk from digitized breast cancer histological slides

Early breast cancer is often responsive to treatment, however, long-term prognosis is variable. Here, the authors utilise a deep learning model to predict metastasis free survival using digitised tumour slides.

I. Garberis
V. Gaury
M. Lacroix-Triki
ResearchOpen Access01 Jul 2025
Nature Communications

Volume: 16, P: 1-13
Trastuzumab deruxtecan in metastatic breast cancer with variable HER2 expression: the phase 2 DAISY trial

Trastuzumab deruxtecan, an anti-HER2–drug conjugate, exhibits the highest objective response rate in patients with HER2-overexpressing metastatic breast cancer, but clinical activity is also observed in patients with HER2-low or non-expressing tumors, potentially pointing to additional determinants of drug efficacy.

Fernanda Mosele
Elise Deluche
Fabrice André
ResearchOpen Access24 Jul 2023
Nature Medicine

Volume: 29, P: 2110-2120
Durvalumab compared to maintenance chemotherapy in metastatic breast cancer: the randomized phase II SAFIR02-BREAST IMMUNO trial

Exploratory analyses from the phase 2 randomized SAFIR02-IMMUNO trial identify biomarkers associated with improved outcomes to durvalumab as compared to maintenance chemotherapy in patients with triple-negative breast cancer.

Thomas Bachelot
Thomas Filleron
Fabrice Andre
Research18 Jan 2021
Nature Medicine

Volume: 27, P: 250-255

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