Diagnostic Algorithm to Subclassify Atypical Spitzoid Tumors in Low and High Risk According to Their Methylation Status

Current diagnostic algorithms are insufficient for the optimal clinical and therapeutic management of cutaneous spitzoid tumors, particularly atypical spitzoid tumors (AST). Therefore, it is crucial to identify new markers that allow for reliable and reproducible diagnostic assessment and can also b...

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Detalles Bibliográficos
Autores: González-Muñoz, JF, Sánchez-Sendra, B, Monteagudo, C
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:INCLIVA
Repositorio:r-INCLIVA. Repositorio Institucional de Producción Científica de INCLIVA
OAI Identifier:oai:incliva.fundanetsuite.com:p17936
Acceso en línea:https://incliva.portalinvestigacion.com/publicaciones/17936
Access Level:acceso abierto
Palabra clave:Spitzoid melanocytic tumors
Spitz
melanoma
methylation
algorithm
novel biomarkers
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spelling Diagnostic Algorithm to Subclassify Atypical Spitzoid Tumors in Low and High Risk According to Their Methylation StatusGonzález-Muñoz, JFSánchez-Sendra, BMonteagudo, CSpitzoid melanocytic tumorsSpitzmelanomamethylationalgorithmnovel biomarkersCurrent diagnostic algorithms are insufficient for the optimal clinical and therapeutic management of cutaneous spitzoid tumors, particularly atypical spitzoid tumors (AST). Therefore, it is crucial to identify new markers that allow for reliable and reproducible diagnostic assessment and can also be used as a predictive tool to anticipate the individual malignant potential of each patient, leading to tailored individual therapy. Using Reduced Representation Bisulfite Sequencing (RRBS), we studied genome-wide methylation profiles of a series of Spitz nevi (SN), spitzoid melanoma (SM), and AST. We established a diagnostic algorithm based on the methylation status of seven cg sites located in TETK4P2 (Tektin 4 Pseudogene 2), MYO1D (Myosin ID), and PMF1-BGLAP (PMF1-BGLAP Readthrough), which allows the distinction between SN and SM but is also capable of subclassifying AST according to their similarity to the methylation levels of Spitz nevi or spitzoid melanoma. Thus, our epigenetic algorithm can predict the risk level of AST and predict its potential clinical outcomes.MDPI2024info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://incliva.portalinvestigacion.com/publicaciones/17936INTERNATIONAL JOURNAL OF MOLECULAR SCIENCESISSN: 16616596ISSNe: 14220067reponame:r-INCLIVA. Repositorio Institucional de Producción Científica de INCLIVAinstname:INCLIVAInglésinfo:eu-repo/semantics/openAccessoai:incliva.fundanetsuite.com:p179362026-06-07T16:35:31Z
dc.title.none.fl_str_mv Diagnostic Algorithm to Subclassify Atypical Spitzoid Tumors in Low and High Risk According to Their Methylation Status
title Diagnostic Algorithm to Subclassify Atypical Spitzoid Tumors in Low and High Risk According to Their Methylation Status
spellingShingle Diagnostic Algorithm to Subclassify Atypical Spitzoid Tumors in Low and High Risk According to Their Methylation Status
González-Muñoz, JF
Spitzoid melanocytic tumors
Spitz
melanoma
methylation
algorithm
novel biomarkers
title_short Diagnostic Algorithm to Subclassify Atypical Spitzoid Tumors in Low and High Risk According to Their Methylation Status
title_full Diagnostic Algorithm to Subclassify Atypical Spitzoid Tumors in Low and High Risk According to Their Methylation Status
title_fullStr Diagnostic Algorithm to Subclassify Atypical Spitzoid Tumors in Low and High Risk According to Their Methylation Status
title_full_unstemmed Diagnostic Algorithm to Subclassify Atypical Spitzoid Tumors in Low and High Risk According to Their Methylation Status
title_sort Diagnostic Algorithm to Subclassify Atypical Spitzoid Tumors in Low and High Risk According to Their Methylation Status
dc.creator.none.fl_str_mv González-Muñoz, JF
Sánchez-Sendra, B
Monteagudo, C
author González-Muñoz, JF
author_facet González-Muñoz, JF
Sánchez-Sendra, B
Monteagudo, C
author_role author
author2 Sánchez-Sendra, B
Monteagudo, C
author2_role author
author
dc.subject.none.fl_str_mv Spitzoid melanocytic tumors
Spitz
melanoma
methylation
algorithm
novel biomarkers
topic Spitzoid melanocytic tumors
Spitz
melanoma
methylation
algorithm
novel biomarkers
description Current diagnostic algorithms are insufficient for the optimal clinical and therapeutic management of cutaneous spitzoid tumors, particularly atypical spitzoid tumors (AST). Therefore, it is crucial to identify new markers that allow for reliable and reproducible diagnostic assessment and can also be used as a predictive tool to anticipate the individual malignant potential of each patient, leading to tailored individual therapy. Using Reduced Representation Bisulfite Sequencing (RRBS), we studied genome-wide methylation profiles of a series of Spitz nevi (SN), spitzoid melanoma (SM), and AST. We established a diagnostic algorithm based on the methylation status of seven cg sites located in TETK4P2 (Tektin 4 Pseudogene 2), MYO1D (Myosin ID), and PMF1-BGLAP (PMF1-BGLAP Readthrough), which allows the distinction between SN and SM but is also capable of subclassifying AST according to their similarity to the methylation levels of Spitz nevi or spitzoid melanoma. Thus, our epigenetic algorithm can predict the risk level of AST and predict its potential clinical outcomes.
publishDate 2024
dc.date.none.fl_str_mv 2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://incliva.portalinvestigacion.com/publicaciones/17936
url https://incliva.portalinvestigacion.com/publicaciones/17936
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
ISSN: 16616596
ISSNe: 14220067
reponame:r-INCLIVA. Repositorio Institucional de Producción Científica de INCLIVA
instname:INCLIVA
instname_str INCLIVA
reponame_str r-INCLIVA. Repositorio Institucional de Producción Científica de INCLIVA
collection r-INCLIVA. Repositorio Institucional de Producción Científica de INCLIVA
repository.name.fl_str_mv
repository.mail.fl_str_mv
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