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–1 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.