Publication:
SPECTRA-based detection of drug-induced hepatotoxicity through extracellular vesicle analysis

dc.contributor.coauthorParlatan, Ugur
dc.contributor.coauthorBoudreau, Luke
dc.contributor.coauthorTorun, Hulya
dc.contributor.coauthorFan, Letao
dc.contributor.coauthorGokaltun, Ayse Aslihan
dc.contributor.coauthorAkin, Demir
dc.contributor.coauthorUsta, O. Berk
dc.contributor.coauthorDemirci, Utkan
dc.contributor.departmentGraduate School of Sciences and Engineering
dc.contributor.kuauthorAygün, Uğur
dc.contributor.schoolcollegeinstituteGRADUATE SCHOOL OF SCIENCES AND ENGINEERING
dc.date.accessioned2026-07-02T07:04:29Z
dc.date.available2026-03-27
dc.date.issued2026
dc.description.abstractExtracellular vesicles (EV) are becoming crucial targets 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 EV molecular content remains unexplored. To this end, we present the SPECTRA - Surface Plasmonic Enhancement with Combined Transformative RAman and Interferometric Microscopy approach, which provides rapid, label-free EV content analysis under 30 min and requires only 1.3 microliters of EV sample. Using hepatic cultures as a model, our platform captures distinct and reproducible EV molecular changes in response to acetaminophen-induced hepatotoxicity. Across independent culture sets, a Gaussian Process Regression model predicted Acetaminophen (APAP) dose with median absolute error of 1.50 mM and minimal bias (Bland-Altman bias similar to 0.03 mM); cross-validated RMSE was 3.145 mM. These findings establish EVs as dynamic reporters of cellular drug responses and demonstrate use of SPECTRA for EV detection of hepatotoxicity.
dc.description.fulltextNo
dc.description.harvestedfromManual
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.publisherscopeInternational
dc.description.readpublishN/A
dc.description.sponsoredbyTubitakEuEU
dc.description.sponsorshipU.D. acknowledges the support of a seed award from Stanford University's PhIND Center. We also acknowledge funding from the National Institutes of Health under project numbers R21GM140656 (L.B. and O. B.U.) , (A.G. and O.B.U.) , and R21GM136002 (A.G. and O.B.U.) . U.A. acknowledges funding from the European Union's Horizon Europe research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 101066038 [75]
dc.description.versionPublished Version
dc.identifier.WoSQuartileQ1
dc.identifier.doi10.1016/j.snb.2026.139520
dc.identifier.eissn0925-4005
dc.identifier.embargoNo
dc.identifier.grantno101066038 [75]
dc.identifier.scopus2-s2.0-105029771077
dc.identifier.urihttps://doi.org10.1111/all.70210
dc.identifier.urihttps://hdl.handle.net/20.500.14288/32902
dc.identifier.volume455
dc.identifier.wos001691669600001
dc.keywordsSurface-enhanced Raman spectroscopy
dc.keywordsExtracellular vesicles
dc.keywordsHepatotoxicity
dc.keywordsDrug-induced liver injury
dc.keywordsLabel-free biosensor
dc.keywordsMachine learning
dc.languageeng
dc.publisherElsevier
dc.relation.affiliationKoç University
dc.relation.collectionKoç University Institutional Repository
dc.relation.ispartofSensors and Actuators B-chemical
dc.relation.openaccessN/A
dc.rightsN/A
dc.rights.uriN/A
dc.subjectChemistry
dc.subjectElectrochemistry
dc.subjectInstruments and instrumentation
dc.titleSPECTRA-based detection of drug-induced hepatotoxicity through extracellular vesicle analysis
dc.typeJournal Article
dspace.entity.typePublication
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