Concentric gradient nanoplasmonic sensors for detecting tumor-derived extracellular vesicles

Quantification of tumor-derived extracellular vesicles (EVs) holds great promise for early cancer diagnosis and prognosis. Developing a rapid and straightforward EV detection platform is essential for timely and specific diagnostics. In this study, we present a novel concentric gradient nanoplasmonic (CGN) sensor to achieve sensitive and label-free EV quantification. The CGN sensor features wafer-scale gradient plasmonic nanostructures, converting resonance wavelength shift into a change in centimeter-scale transmission pattern. Through functionalization with smaller aptamers, a more sensitive area is reserved for EV surface proteins, facilitating the dynamic binding of EVs, which is recorded by a CCD camera to establish a correlation between pattern movement and EV attachment. We quantitatively characterized EVs derived from A549 and MCF-7 cancer cell lines by integrating the CGN sensor into a microfluidic device. With a high sensing performance of 9.23 x 10-5 RIU, we achieved real-time measurements of EV binding as low as 143 femtomolar. Furthermore, the CGN sensor exhibited excellent sensitivity in detecting EVs from cancer patient plasma. We also designed a compact imaging-based sensing device employing an LED and a CCD camera. This device combines the simplicity of large-area and real-time imaging with the robustness of spectroscopic approaches, making it highly promising for point-of-care diagnostics.

Automated summary

This study presents a novel concentric gradient nanoplasmonic sensor for sensitive and label-free quantification of tumor-derived extracellular vesicles (EVs). By functionalizing the sensor with smaller aptamers, a more sensitive area is reserved for EV surface proteins, enabling the dynamic binding of EVs. The sensor exhibits high sensitivity in detecting EV binding and shows great potential for diagnosing cancer patients.