Controllable Cascade Aggregation Ion Programmed Nanomachines and Simple Isolation Enable Tumor-Derived Small Extracellular Vesicles Detection for Enhanced Breast Cancer Assessment.

Small extracellular vesicles (sEVs) carry biomolecules that reflect their cellular origin, making them attractive biomarkers for breast cancer assessment and human epidermal growth factor receptor 2 (HER2)-status discrimination. However, existing methods involve lengthy isolation procedures and exhibit poor detection performance due to severe interference from excessive impurities. In this study, we constructed a dual-target electrochemical (EC) sensing platform based on cascade aggregation effects. Combined with a facile filter-based isolation strategy, this enables rapid and convenient dual-marker (epithelial cell adhesion molecule (EpCAM) and HER2) analysis of breast cancer-derived sEVs. This mechanism relies on the target-triggered disassembly of DNA nanospheres to release Ag+/Hg2+ for EC signaling. Subsequently, colistin specifically binds to G-quadruplexes on unreacted nanospheres and induces their aggregation, sequestering background signal sources and preventing ion leakage. This noise-silencing strategy improved matrix tolerance and reduced background leakage under a standardized diluted-plasma workflow, enabling reliable detection of sEVs-associated signals in filtration-derived clinical samples. A proof-of-concept clinical study involving 63 breast cancer patients and 22 nonmalignant controls successfully demonstrated the platform's capability to distinguish cancer patients from controls. Furthermore, the platform achieved a 88.9% accuracy in differentiating HER2 status within this cohort. Overall, this streamlined "filtration-to-detection" platform offers a promising strategy for analyzing breast cancer-specific sEVs signals and conducting exploratory HER2-status assessments.