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dc.creatorRuíz, José Javieres
dc.creatorMarro, Mónicaes
dc.creatorGalván, Mónicaes
dc.creatorBernabeu Wittel, Josées
dc.creatorConejo-Mir Sánchez, Juliánes
dc.creatorZulueta Dorado, Teresaes
dc.creatorGuisado Gil, Ana Belénes
dc.creatorLoza Álvarez, Pabloes
dc.date.accessioned2022-10-10T13:07:26Z
dc.date.available2022-10-10T13:07:26Z
dc.date.issued2022
dc.identifier.citationRuíz, J.J., Marro, M., Galván, M., Bernabeu Wittel, J., Conejo-Mir Sánchez, J., Zulueta Dorado, T.,...,Loza Álvarez, P. (2022). Novel non-invasive quantification and imaging of Eumelanin and DHICA subunit in skin lesions by raman spectroscopy and MCR algorithm: improving dysplastic Nevi diagnosis. Cancers, 14 (4), 1235-14. https://doi.org/10.3390/cancers14041056.
dc.identifier.issn2072-6694es
dc.identifier.urihttps://hdl.handle.net/11441/137760
dc.description.abstract: Malignant melanoma (MM) is the most aggressive form of skin cancer, and around 30% of them may develop from pre-existing dysplastic nevi (DN). Diagnosis of DN is a relevant clinical challenge, as these are intermediate lesions between benign and malignant tumors, and, up to date, few studies have focused on their diagnosis. In this study, the accuracy of Raman spectroscopy (RS) is assessed, together with multivariate analysis (MA), to classify 44 biopsies of MM, DN and compound nevus (CN) tumors. For this, we implement a novel methodology to non-invasively quantify and localize the eumelanin pigment, considered as a tumoral biomarker, by means of RS imaging coupled with the Multivariate Curve Resolution-Alternative Least Squares (MCR-ALS) algorithm. This represents a step forward with respect to the currently established technique for melanin analysis, High-Performance Liquid Chromatography (HPLC), which is invasive and cannot provide information about the spatial distribution of molecules. For the first time, we show that the 5, 6-dihydroxyindole (DHI) to 5,6-dihydroxyindole-2-carboxylic acid (DHICA) ratio is higher in DN than in MM and CN lesions. These differences in chemical composition are used by the Partial Least Squares-Discriminant Analysis (PLS-DA) algorithm to identify DN lesions in an efficient, non-invasive, fast, objective and cost-effective method, with sensitivity and specificity of 100% and 94.1%, respectively.es
dc.formatapplication/pdfes
dc.format.extent14 p.es
dc.language.isoenges
dc.publisherMDPIes
dc.relation.ispartofCancers, 14 (4), 1235-14.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectSkin neoplasmses
dc.subjectMelanomaes
dc.subjectDysplastic nevus syndromees
dc.subjectEumelanines
dc.subjectRaman spectroscopy analysises
dc.subjectMultivariate analysises
dc.subjectReactive oxygen specieses
dc.titleNovel non-invasive quantification and imaging of Eumelanin and DHICA subunit in skin lesions by raman spectroscopy and MCR algorithm: improving dysplastic Nevi diagnosises
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Medicinaes
dc.relation.publisherversionhttps://www.mdpi.com/2072-6694/14/4/1056es
dc.identifier.doi10.3390/cancers14041056es
dc.journaltitleCancerses
dc.publication.volumen14es
dc.publication.issue4es
dc.publication.initialPage1235es
dc.publication.endPage14es

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