Abstract
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 × 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.
Published Version
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