AbstractThe standard approach of using one-size-fits-all endocrine therapy for hormone receptor (HR)–positive and human epidermal growth factor receptor 2 (HER2)-negative breast cancers has faced significant challenges because of variations in treatment response among individuals. To overcome this challenge, we conducted a comprehensive study that integrated data from both “bench” (multiomics sequencing and functional drug response testing) and “bedside” (multicenter real-world and clinical trial cohorts) studies. Classification of HR+/HER2− breast cancer into four subtypes enabled effective subtyping-directed precision treatment strategies: endocrine therapy alone for the canonical luminal subtype, the addition of cyclin-dependent kinase 4/6 and poly (ADP-ribose) polymerase (PARP) inhibitors for the proliferative subtype, immunotherapy for the immunogenic subtype, and tyrosine kinase inhibitors for the receptor tyrosine kinase–driven subtype. The development of clinically applicable deep learning–based digital pathology classification demonstrated that matched treatment guided by subtyping-directed precision treatment strategies outperformed unmatched approaches in a real-world cohort and the I-SPY2 trial. Overall, this study emphasizes the superiority of subtyping-directed precision treatment strategies for HR+/HER2− breast cancer.Significance:A comprehensive understanding of subtypes of HR+/HER2− breast cancer facilitates development of a multipronged precision medicine approach that can be translated from bench to bedside.
Zhu et al. (Wed,) studied this question.