Characterization of Inkjet-Printed Stacked MIM Thin-film Solid-State Flexible Super-Capacitor
Abstract
Single vesicle molecular profiling has the potential to transform cancer detection and monitoring by precisely probing cancer-associated extracellular vesicles (EVs) in the presence of normal EVs in body fluids, but it is challenging due to the small EV size, low abundance of antigens on individual vesicles, and a complex biological matrix. Here, we report a facile dual imaging single vesicle technology (DISVT) for surface protein profiling of individual EVs and quantification of target-specific EV subtypes based on direct molecular capture of EVs from diluted biofluids, dual EV-protein fluorescence-light scattering imaging, and fast image analysis using Bash scripts, Python, and ImageJ. Plasmonic gold nanoparticles (AuNPs) were used to label and detect targeted surface protein markers on individual EVs with dark-field light scattering imaging at the single particle level. Monte Carlo calculations estimated that the AuNPs could detect EVs down to 40 nm in diameter. Using the DISVT, we profiled surface protein markers of interest across individual EVs derived from several breast cancer cell lines, which reflected the parental cells. Studies with plasma EVs from healthy donors and breast cancer patients revealed that the DISVT, but not the traditional bulk enzyme-linked immunosorbent assay, detected human epidermal growth factor receptor 2 (HER2)-positive breast cancer at an early stage. The DISVT also precisely differentiated HER2-positive breast cancer from HER2-negative breast cancer. We additionally showed that the amount of tumor-associated EVs was tripled in locally advanced patients compared to that in early-stage patients. These studies suggest that single EV surface protein profiling with DISVT can provide a facile and high-sensitivity method for early cancer detection and quantitative monitoring.
Publication Title
IEEE International Conference on Electro Information Technology
Recommended Citation
Amrhein, K., Taylor, M., Wilson, R., Gallops, C., Annamer, A., Vinduska, V., Kwizera, E., Zhang, H., Wang, Y., Hoang, T., & Huang, X. (2023). Characterization of Inkjet-Printed Stacked MIM Thin-film Solid-State Flexible Super-Capacitor. IEEE International Conference on Electro Information Technology, 2023-May, 509-513. https://doi.org/10.1109/eIT57321.2023.10187294
