Controllable Cascade Aggregation Ion Programmed Nanomachines and Simple Isolation Enable Tumor-Derived Small...

Area of Science:

• Biomedical Engineering
• Nanotechnology
• Clinical Diagnostics

Background:

• Small extracellular vesicles (sEVs) are promising biomarkers for breast cancer detection and HER2-status assessment.
• Current sEV isolation and detection methods are often time-consuming and susceptible to interference from impurities.
• There is a need for rapid, sensitive, and specific platforms for analyzing breast cancer-derived sEVs.

Purpose of the Study:

• To develop a dual-target electrochemical (EC) sensing platform for rapid analysis of breast cancer-derived sEVs.
• To enable simultaneous detection of epithelial cell adhesion molecule (EpCAM) and HER2.
• To improve the accuracy and reliability of sEV biomarker detection in clinical samples.

Main Methods:

• A facile filter-based isolation strategy for sEVs.
• A dual-target EC sensing platform utilizing cascade aggregation effects.
• Target-triggered disassembly of DNA nanospheres releasing Ag+/Hg2+ for signaling, followed by colistin-induced aggregation for noise silencing.

Main Results:

• The platform successfully distinguished breast cancer patients (63) from nonmalignant controls (22) in a proof-of-concept clinical study.
• Achieved 88.9% accuracy in differentiating HER2 status within the patient cohort.
• Demonstrated improved matrix tolerance and reduced background leakage in diluted plasma samples.

Conclusions:

• The streamlined 'filtration-to-detection' platform offers a rapid and convenient method for breast cancer sEV analysis.
• The developed sensing platform shows potential for exploratory HER2-status assessment.
• This approach provides a promising strategy for advancing liquid biopsy techniques in oncology.