Controllable Cascade Aggregation Ion Programmed Nanomachines and Simple Isolation Enable Tumor‐Derived Small Extracellular Vesicles Detection for Enhanced Breast Cancer Assessment
- 1Department of Laboratory Medicine Med+X Center for Manufacturing Department of General Surgery State Key Laboratory of Biotherapy Department of Medical Oncology State Key Laboratory of Respiratory Health and Multimorbidity West China Hospital Sichuan University Chengdu Sichuan China
- 2Breast Disease Center West China Hospital Sichuan University Chengdu Sichuan China
Abstract
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.
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BibTeX
@article{zhang2026controllable,
title = {{Controllable Cascade Aggregation Ion Programmed Nanomachines and Simple Isolation Enable Tumor‐Derived Small Extracellular Vesicles Detection for Enhanced Breast Cancer Assessment}},
author = {Zhihao Zhang and Zijing Liu and Xiangyue Meng and Pengjun Jiang and Jie Qu and Yu Jiang and Binxu Qiu and Jie Chen and Piaopiao Chen},
journal = {Advanced Science},
year = {2026},
month = aug,
doi = {10.1002/advs.77177},
url = {https://doi.org/10.1002/advs.77177},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Controllable Cascade Aggregation Ion Programmed Nanomachines and Simple Isolation Enable Tumor‐Derived Small Extracellular Vesicles Detection for Enhanced Breast Cancer Assessment
AU - Zhihao Zhang
AU - Zijing Liu
AU - Xiangyue Meng
AU - Pengjun Jiang
AU - Jie Qu
AU - Yu Jiang
AU - Binxu Qiu
AU - Jie Chen
AU - Piaopiao Chen
PY - 2026
DA - 2026/08/14
JO - Advanced Science
DO - 10.1002/advs.77177
UR - https://doi.org/10.1002/advs.77177
AB - 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.
SN - 2198-3844
ER -