Highly sensitive detection of extracellular vesicles on ZnO nanorods integrated microarray chips with cascade signal amplification and portable glucometer readout

Extracellular vesicle (EV) has become a type of potential biomarker for cancer diagnosis in liquid biopsy. However, the accurate detection of EVs for large-scale cancer scanning is still challenge due to the low sensi-tivity, high cost, and requirement of large instruments, which impedes their wide applications in clinical trials, especially in resource limited areas. Herein, we report a ZnO nanorods integrated microarray chip (ZnO-chip) for effective capture and sensitive detection of EVs. The ZnO-chip provides abundant binding sites for EVs capture. Meanwhile, the high-ordered hybridization chain reaction and non-ordered enzyme catalytic reaction are collaborated for cascade signal amplification. The oxidized product, glucose, can be read out directly by portable glucometer to realize accurate quantitation of EVs with a linear range of 1.0 x 104 to 8.4 x 107 particles/mu L and a minimal detectable concentration of 3.3 x 103 particles/mu L. Our approach could distinguish cancer patients from healthy individuals, proving the statistically increase of EVs in serums of cancer patients. Finally, we verify that the captured EVs can be released for downstream molecular assays by dissolving ZnO nanorods under slightly acidic condition. We believe our approach has remarkable possibility for the routine screening of cancer patients in clinical trials.

Automated summary

Researchers have developed a ZnO nanorods integrated microarray chip (ZnO-chip) for effective capture and sensitive detection of extracellular vesicles (EVs), which have potential as biomarkers for cancer diagnosis in liquid biopsy. The chip provides abundant binding sites for EVs capture and utilizes cascade signal amplification for accurate quantitation. The method has the ability to distinguish cancer patients from healthy individuals and could be applied for routine screening in clinical trials.