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dc.contributor.authorKoo, Kevin M
dc.contributor.authorWang, Jing
dc.contributor.authorRichards, Renee S
dc.contributor.authorFarrell, Aine
dc.contributor.authorYaxley, John W
dc.contributor.authorSamaratunga, Hema
dc.contributor.authorTeloken, Patrick E
dc.contributor.authorRoberts, Matthew J
dc.contributor.authorCoughlin, Geoffrey D
dc.contributor.authorLavin, Martin F
dc.contributor.authorMainwaring, Paul N
dc.contributor.authorWang, Yuling
dc.contributor.authorGardiner, Robert A
dc.contributor.authorTrau, Matt
dc.date.accessioned2019-08-20T01:20:19Z
dc.date.available2019-08-20T01:20:19Z
dc.date.issued2018
dc.identifier.issn1936-0851en_US
dc.identifier.doi10.1021/acsnano.8b03698en_US
dc.identifier.urihttp://hdl.handle.net/10072/382872
dc.description.abstractThe use of emerging nanotechnologies, such as plasmonic nanoparticles in diagnostic applications, potentially offers opportunities to revolutionize disease management and patient healthcare. Despite worldwide research efforts in this area, there is still a dearth of nanodiagnostics which have been successfully translated for real-world patient usage due to the predominant sole focus on assay analytical performance and lack of detailed investigations into clinical performance in human samples. In a bid to address this pressing need, we herein describe a comprehensive clinical verification of a prospective label-free surface-enhanced Raman scattering (SERS) nanodiagnostic assay for prostate cancer (PCa) risk stratification. This contribution depicts a roadmap of (1) designing a SERS assay for robust and accurate detection of clinically validated PCa RNA targets; (2) employing a relevant and proven PCa clinical biomarker model to test our nanodiagnostic assay; and (3) investigating the clinical performance on independent training (n = 80) and validation (n = 40) cohorts of PCa human patient samples. By relating the detection outcomes to gold-standard patient biopsy findings, we established a PCa risk scoring system which exhibited a clinical sensitivity and specificity of 0.87 and 0.90, respectively [area-under-curve of 0.84 (95% confidence interval: 0.81–0.87) for differentiating high- and low-risk PCa] in the validation cohort. We envision that our SERS nanodiagnostic design and clinical verification approach may aid in the individualized prediction of PCa presence and risk stratification and may overall serve as an archetypical strategy to encourage comprehensive clinical evaluation of nanodiagnostic innovations.en_US
dc.description.peerreviewedYesen_US
dc.languageEnglishen_US
dc.language.isoeng
dc.publisherAmerican Chemical Societyen_US
dc.relation.ispartofpagefrom8362en_US
dc.relation.ispartofpageto8371en_US
dc.relation.ispartofissue8en_US
dc.relation.ispartofjournalACS Nanoen_US
dc.relation.ispartofvolume12en_US
dc.subject.fieldofresearchMultidisciplinaryen_US
dc.subject.fieldofresearchcodeMDen_US
dc.titleDesign and Clinical Verification of Surface Enhanced Raman Spectroscopy Diagnostic Technology for Individual Cancer Risk Predictionen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Articlesen_US
dc.type.codeC - Journal Articlesen_US
dc.description.versionAccepted Manuscript (AM)en_US
gro.rights.copyrightThis document is the Accepted Manuscript version of a Published Work that appeared in final form in ACS Nano, © 2018 American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acsnano.8b03698en_US
gro.hasfulltextFull Text
gro.griffith.authorGardiner, Robert A.


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