Plasmonic Nano-aperture Label-free Imaging of Single Small Extracellular Vesicles for Cancer Detection

Background: Small extracellular vesicle (sEV) analysis can potentially improve cancer detection and diagnostics. However, this potential has been constrained by insufficient sensitivity, dynamic range, and the need for complex labeling.

Methods: In this study, we demonstrate the combination of PANORAMA and fluorescence imaging for single sEV analysis. The co-acquisition of PANORAMA and fluorescence images enables label-free visualization, enumeration, size determination, and enables detection of cargo microRNAs (miRs).

Results: An increased sEV count is observed in human plasma samples from patients with cancer, regardless of cancer type. The cargo miR-21 provides molecular specificity within the same sEV population at the single unit level, which pinpoints the sEVs subset of cancer origin. Using cancer cells-implanted animals, cancer-specific sEVs from 20 µl of plasma can be detected before tumors were palpable. The level plateaus between 5-15 absolute sEV count (ASC) per µl with tumors ≥8 mm. In healthy human individuals (N = 106), the levels are on average 1.5 ASC/µl (+/- 0.95) without miR-21 expression. However, for stage I-III cancer patients (N = 205), nearly all (204 out of 205) have levels exceeding 3.5 ASC/µl with an average of 12.2 ASC/µl (±9.6), and a variable proportion of miR-21 labeling among different tumor types with 100% cancer specificity. Using a threshold of 3.5 ASC/µl to test a separate sample set in a blinded fashion yields accurate classification of healthy individuals from cancer patients.

Conclusions: Our techniques and findings can impact the understanding of cancer biology and the development of new cancer detection and diagnostic technologies.