Molecular classification of hormone receptor-positive HER2-negative breast cancer
Menée à partir de l'analyse multi-omique d'échantillons tumoraux prélevés sur 579 patientes atteintes d'un cancer du sein HR+ HER2-, cette étude identifie quatre sous-types moléculaires et met en évidence l'intérêt de modèles, basés sur la technologie des réseaux de neurones convolutifs, pour distinguer ces sous-types
Hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2−) breast cancer is the most prevalent type of breast cancer, in which endocrine therapy resistance and distant relapse remain unmet challenges. Accurate molecular classification is urgently required for guiding precision treatment. We established a large-scale multi-omics cohort of 579 patients with HR+/HER2− breast cancer and identified the following four molecular subtypes: canonical luminal, immunogenic, proliferative and receptor tyrosine kinase (RTK)-driven. Tumors of these four subtypes showed distinct biological and clinical features, suggesting subtype-specific therapeutic strategies. The RTK-driven subtype was characterized by the activation of the RTK pathways and associated with poor outcomes. The immunogenic subtype had enriched immune cells and could benefit from immune checkpoint therapy. In addition, we developed convolutional neural network models to discriminate these subtypes based on digital pathology for potential clinical translation. The molecular classification provides insights into molecular heterogeneity and highlights the potential for precision treatment of HR+/HER2− breast cancer.
Nature Genetics , résumé, 2023