SHINE: SERS-based Hepatotoxicity detection using Inference from Nanoscale Extracellular vesicle content
Parlatan, U.; boudreau, L.; Torun, H.; Fan, L.; Aygun, U.; Gokaltun, A. A.; Akin, D.; Usta, O. B.; Demirci, U.
Show abstract
Extracellular vesicles (EV) are becoming crucial tools in liquid biopsy, diagnostics, and therapeutic applications, yet their nanoscale characterization remains challenging. In this context, the detection of drug-induced liver injury, i.e., hepatotoxicity, through extracellular vesicle molecular content remains an unexplored frontier. To this end, we present a label-free surface-enhanced Raman (SERS) spectroscopy approach, which provides rapid EV content analysis under ten minutes and requires only 1.3 microliters of sample. Using hepatic cultures as a model, our platform captures distinct and reproducible EV molecular changes in response to acetaminophen-induced hepatoxicity. Our platform achieves exceptional accuracy with root mean squared error values as low as 3.80%, establishing strong correlations between EV spectra and conventional toxicity biomarkers. Unlike previous EV-SERS studies limited to vesicle identification and disease markers, this approach reveals EV drug-response signatures strongly correlated with conventional toxicity markers. These findings establish EVs as dynamic reporters of cellular drug responses and demonstrate use of SERS-based EV detection of hepatotoxicity.
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