Molecular Characterization of Exosomes for Subtype-Based Diagnosis of Breast Cancer.

Breast cancer is very heterogeneous and the most frequently diagnosed cancer worldwide, and precise therapy targeting specific subtypes may improve the survival rates of breast cancer patients. In this study, we designed a biomimetic vesicle by camouflaging catalytic DNA machinery with a breast cancer cell membrane, which enabled the molecular classification of circulating exosomes for subtype-based diagnosis through homotypic recognition. In addition, the vesicles specifically targeted and fused with breast cancer exosomes with phenotypic homology and manipulated the DNA machinery to amplify electrochemical signaling using exosomal RNA as an endogenous trigger. The biomimetic vesicles prepared with MCF-7 cancer cell-derived membranes were shown to recognize estrogen receptor-positive breast cancer exosomes and exhibited a low detection limit of 557 particles mL with microRNA-375 used as the endogenous biomarker. Furthermore, the biomimetic vesicles prepared with MDA-MB-231 cancer cell-derived membranes displayed satisfactory performance in a homotypic analysis of triple-negative breast cancer exosomes with a potential therapeutic target, PD-L1 mRNA, used as the endogenous biomarker. Most importantly, cross-validation experiments confirmed the high accuracy and selectivity of this homotypic recognition-driven analysis for molecular subtyping of breast cancer. When applied to clinical samples of breast cancer patients, the vesicles demonstrated feasibility and reliability for evaluating the molecular features of cancer cell-derived exosomes and enabled stage-specific monitoring of breast cancer patients because the electrochemical signals showed a positive correlation with disease progression. Therefore, this work may provide new ideas for the precise diagnosis and personalized treatment of breast cancer patients throughout the whole disease process.