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Variables that influence BRAF mutation probability: A next-generation sequencing, non-interventional investigation of BRAFV600 mutation status in melanoma

BACKGROUND: The incidence of melanoma, particularly in older patients, has steadily increased over the past few decades. Activating mutations of BRAF, the majority occurring in BRAFV600, are frequently detected in melanoma; however, the prognostic significance remains unclear. This study aimed to de...

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Autores principales: Gaiser, Maria Rita, Skorokhod, Alexander, Gransheier, Diana, Weide, Benjamin, Koch, Winfried, Schif, Birgit, Enk, Alexander, Garbe, Claus, Bauer, Jürgen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5703505/
https://www.ncbi.nlm.nih.gov/pubmed/29176861
http://dx.doi.org/10.1371/journal.pone.0188602
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author Gaiser, Maria Rita
Skorokhod, Alexander
Gransheier, Diana
Weide, Benjamin
Koch, Winfried
Schif, Birgit
Enk, Alexander
Garbe, Claus
Bauer, Jürgen
author_facet Gaiser, Maria Rita
Skorokhod, Alexander
Gransheier, Diana
Weide, Benjamin
Koch, Winfried
Schif, Birgit
Enk, Alexander
Garbe, Claus
Bauer, Jürgen
author_sort Gaiser, Maria Rita
collection PubMed
description BACKGROUND: The incidence of melanoma, particularly in older patients, has steadily increased over the past few decades. Activating mutations of BRAF, the majority occurring in BRAFV600, are frequently detected in melanoma; however, the prognostic significance remains unclear. This study aimed to define the probability and distribution of BRAFV600 mutations, and the clinico-pathological factors that may affect BRAF mutation status, in patients with advanced melanoma using next-generation sequencing. MATERIALS AND METHODS: This was a non-interventional, retrospective study of BRAF mutation testing at two German centers, in Heidelberg and Tübingen. Archival tumor samples from patients with histologically confirmed melanoma (stage IIIB, IIIC, IV) were analyzed using PCR amplification and deep sequencing. Clinical, histological, and mutation data were collected. The statistical influence of patient- and tumor-related characteristics on BRAFV600 mutation status was assessed using multiple logistic regression (MLR) and a prediction profiler. RESULTS: BRAFV600 mutation status was assessed in 453 samples. Mutations were detected in 57.6% of patients (n = 261), with 48.1% (n = 102) at the Heidelberg site and 66.0% (n = 159) at the Tübingen site. The decreasing influence of increasing age on mutation probability was quantified. A main effects MLR model identified age (p = 0.0001), center (p = 0.0004), and melanoma subtype (p = 0.014) as significantly influencing BRAFV600 mutation probability; ultraviolet (UV) exposure showed a statistical trend (p = 0.1419). An interaction model of age versus other variables showed that center (p<0.0001) and melanoma subtype (p = 0.0038) significantly influenced BRAF mutation probability; age had a statistically significant effect only as part of an interaction with both UV exposure (p = 0.0110) and melanoma subtype (p = 0.0134). CONCLUSIONS: This exploratory study highlights that testing center, melanoma subtype, and age in combination with UV exposure and melanoma subtype significantly influence BRAFV600 mutation probability in patients with melanoma. Further validation of this model, in terms of reproducibility and broader relevance, is required.
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spelling pubmed-57035052017-12-08 Variables that influence BRAF mutation probability: A next-generation sequencing, non-interventional investigation of BRAFV600 mutation status in melanoma Gaiser, Maria Rita Skorokhod, Alexander Gransheier, Diana Weide, Benjamin Koch, Winfried Schif, Birgit Enk, Alexander Garbe, Claus Bauer, Jürgen PLoS One Research Article BACKGROUND: The incidence of melanoma, particularly in older patients, has steadily increased over the past few decades. Activating mutations of BRAF, the majority occurring in BRAFV600, are frequently detected in melanoma; however, the prognostic significance remains unclear. This study aimed to define the probability and distribution of BRAFV600 mutations, and the clinico-pathological factors that may affect BRAF mutation status, in patients with advanced melanoma using next-generation sequencing. MATERIALS AND METHODS: This was a non-interventional, retrospective study of BRAF mutation testing at two German centers, in Heidelberg and Tübingen. Archival tumor samples from patients with histologically confirmed melanoma (stage IIIB, IIIC, IV) were analyzed using PCR amplification and deep sequencing. Clinical, histological, and mutation data were collected. The statistical influence of patient- and tumor-related characteristics on BRAFV600 mutation status was assessed using multiple logistic regression (MLR) and a prediction profiler. RESULTS: BRAFV600 mutation status was assessed in 453 samples. Mutations were detected in 57.6% of patients (n = 261), with 48.1% (n = 102) at the Heidelberg site and 66.0% (n = 159) at the Tübingen site. The decreasing influence of increasing age on mutation probability was quantified. A main effects MLR model identified age (p = 0.0001), center (p = 0.0004), and melanoma subtype (p = 0.014) as significantly influencing BRAFV600 mutation probability; ultraviolet (UV) exposure showed a statistical trend (p = 0.1419). An interaction model of age versus other variables showed that center (p<0.0001) and melanoma subtype (p = 0.0038) significantly influenced BRAF mutation probability; age had a statistically significant effect only as part of an interaction with both UV exposure (p = 0.0110) and melanoma subtype (p = 0.0134). CONCLUSIONS: This exploratory study highlights that testing center, melanoma subtype, and age in combination with UV exposure and melanoma subtype significantly influence BRAFV600 mutation probability in patients with melanoma. Further validation of this model, in terms of reproducibility and broader relevance, is required. Public Library of Science 2017-11-27 /pmc/articles/PMC5703505/ /pubmed/29176861 http://dx.doi.org/10.1371/journal.pone.0188602 Text en © 2017 Gaiser et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Gaiser, Maria Rita
Skorokhod, Alexander
Gransheier, Diana
Weide, Benjamin
Koch, Winfried
Schif, Birgit
Enk, Alexander
Garbe, Claus
Bauer, Jürgen
Variables that influence BRAF mutation probability: A next-generation sequencing, non-interventional investigation of BRAFV600 mutation status in melanoma
title Variables that influence BRAF mutation probability: A next-generation sequencing, non-interventional investigation of BRAFV600 mutation status in melanoma
title_full Variables that influence BRAF mutation probability: A next-generation sequencing, non-interventional investigation of BRAFV600 mutation status in melanoma
title_fullStr Variables that influence BRAF mutation probability: A next-generation sequencing, non-interventional investigation of BRAFV600 mutation status in melanoma
title_full_unstemmed Variables that influence BRAF mutation probability: A next-generation sequencing, non-interventional investigation of BRAFV600 mutation status in melanoma
title_short Variables that influence BRAF mutation probability: A next-generation sequencing, non-interventional investigation of BRAFV600 mutation status in melanoma
title_sort variables that influence braf mutation probability: a next-generation sequencing, non-interventional investigation of brafv600 mutation status in melanoma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5703505/
https://www.ncbi.nlm.nih.gov/pubmed/29176861
http://dx.doi.org/10.1371/journal.pone.0188602
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