dc.creator | Ruíz, José Javier | es |
dc.creator | Marro, Mónica | es |
dc.creator | Galván, Mónica | es |
dc.creator | Bernabeu Wittel, José | es |
dc.creator | Conejo-Mir Sánchez, Julián | es |
dc.creator | Zulueta Dorado, Teresa | es |
dc.creator | Guisado Gil, Ana Belén | es |
dc.creator | Loza Álvarez, Pablo | es |
dc.date.accessioned | 2022-10-10T13:07:26Z | |
dc.date.available | 2022-10-10T13:07:26Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Ruíz, 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.issn | 2072-6694 | es |
dc.identifier.uri | https://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.format | application/pdf | es |
dc.format.extent | 14 p. | es |
dc.language.iso | eng | es |
dc.publisher | MDPI | es |
dc.relation.ispartof | Cancers, 14 (4), 1235-14. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Skin neoplasms | es |
dc.subject | Melanoma | es |
dc.subject | Dysplastic nevus syndrome | es |
dc.subject | Eumelanin | es |
dc.subject | Raman spectroscopy analysis | es |
dc.subject | Multivariate analysis | es |
dc.subject | Reactive oxygen species | es |
dc.title | Novel non-invasive quantification and imaging of Eumelanin and DHICA subunit in skin lesions by raman spectroscopy and MCR algorithm: improving dysplastic Nevi diagnosis | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Medicina | es |
dc.relation.publisherversion | https://www.mdpi.com/2072-6694/14/4/1056 | es |
dc.identifier.doi | 10.3390/cancers14041056 | es |
dc.journaltitle | Cancers | es |
dc.publication.volumen | 14 | es |
dc.publication.issue | 4 | es |
dc.publication.initialPage | 1235 | es |
dc.publication.endPage | 14 | es |