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Automated Universal BRAF State Detection within the Activation Segment in Skin Metastases by Pyrosequencing-Based Assay U-BRAF(V600)

Malignant melanoma is a highly-aggressive type of malignancy with considerable metastatic potential and frequent resistance to cytotoxic agents. BRAF mutant protein was recently recognized as therapeutic target in metastatic melanoma. We present a newly-developed U-BRAF(V600) approach – a universal...

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Autores principales: Skorokhod, Alexander, Helmbold, Peter, Brors, Benedikt, Schirmacher, Peter, Enk, Alexander, Penzel, Roland
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3608589/
https://www.ncbi.nlm.nih.gov/pubmed/23555633
http://dx.doi.org/10.1371/journal.pone.0059221
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author Skorokhod, Alexander
Helmbold, Peter
Brors, Benedikt
Schirmacher, Peter
Enk, Alexander
Penzel, Roland
author_facet Skorokhod, Alexander
Helmbold, Peter
Brors, Benedikt
Schirmacher, Peter
Enk, Alexander
Penzel, Roland
author_sort Skorokhod, Alexander
collection PubMed
description Malignant melanoma is a highly-aggressive type of malignancy with considerable metastatic potential and frequent resistance to cytotoxic agents. BRAF mutant protein was recently recognized as therapeutic target in metastatic melanoma. We present a newly-developed U-BRAF(V600) approach – a universal pyrosequencing-based assay for mutation detection within activation segment in exon 15 of human braf. We identified 5 different BRAF mutations in a single assay analyzing 75 different formalin-fixed paraffin-embedded (FFPE) samples of cutaneous melanoma metastases from 29 patients. We found BRAF mutations in 21 of 29 metastases. All mutant variants were quantitatively detectable by the newly-developed U-BRAF(V600) assay. These results were confirmed by ultra-deep-sequencing validation ((∼)60,000-fold coverage). In contrast to all other BRAF state detection methods, the U-BRAF(V600) assay is capable of automated quantitative identification of at least 36 previously-published BRAF mutations. Under the precaution of a minimum of 3% mutated cells in front of a background of wild type cells, U-BRAFV600 assay design completely excludes false wild-type results. The corresponding algorithm for classification of BRAF-mutated variants is provided. The single-reaction assay and data analysis automation makes our approach suitable for the assessment of large clinical sample sizes. Therefore, we suggest U-BRAF(V600) assay as a most powerful sequencing-based diagnostic tool to automatically identify BRAF state as a prerequisite to targeted therapy.
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spelling pubmed-36085892013-04-03 Automated Universal BRAF State Detection within the Activation Segment in Skin Metastases by Pyrosequencing-Based Assay U-BRAF(V600) Skorokhod, Alexander Helmbold, Peter Brors, Benedikt Schirmacher, Peter Enk, Alexander Penzel, Roland PLoS One Research Article Malignant melanoma is a highly-aggressive type of malignancy with considerable metastatic potential and frequent resistance to cytotoxic agents. BRAF mutant protein was recently recognized as therapeutic target in metastatic melanoma. We present a newly-developed U-BRAF(V600) approach – a universal pyrosequencing-based assay for mutation detection within activation segment in exon 15 of human braf. We identified 5 different BRAF mutations in a single assay analyzing 75 different formalin-fixed paraffin-embedded (FFPE) samples of cutaneous melanoma metastases from 29 patients. We found BRAF mutations in 21 of 29 metastases. All mutant variants were quantitatively detectable by the newly-developed U-BRAF(V600) assay. These results were confirmed by ultra-deep-sequencing validation ((∼)60,000-fold coverage). In contrast to all other BRAF state detection methods, the U-BRAF(V600) assay is capable of automated quantitative identification of at least 36 previously-published BRAF mutations. Under the precaution of a minimum of 3% mutated cells in front of a background of wild type cells, U-BRAFV600 assay design completely excludes false wild-type results. The corresponding algorithm for classification of BRAF-mutated variants is provided. The single-reaction assay and data analysis automation makes our approach suitable for the assessment of large clinical sample sizes. Therefore, we suggest U-BRAF(V600) assay as a most powerful sequencing-based diagnostic tool to automatically identify BRAF state as a prerequisite to targeted therapy. Public Library of Science 2013-03-26 /pmc/articles/PMC3608589/ /pubmed/23555633 http://dx.doi.org/10.1371/journal.pone.0059221 Text en © 2013 Skorokhod 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Skorokhod, Alexander
Helmbold, Peter
Brors, Benedikt
Schirmacher, Peter
Enk, Alexander
Penzel, Roland
Automated Universal BRAF State Detection within the Activation Segment in Skin Metastases by Pyrosequencing-Based Assay U-BRAF(V600)
title Automated Universal BRAF State Detection within the Activation Segment in Skin Metastases by Pyrosequencing-Based Assay U-BRAF(V600)
title_full Automated Universal BRAF State Detection within the Activation Segment in Skin Metastases by Pyrosequencing-Based Assay U-BRAF(V600)
title_fullStr Automated Universal BRAF State Detection within the Activation Segment in Skin Metastases by Pyrosequencing-Based Assay U-BRAF(V600)
title_full_unstemmed Automated Universal BRAF State Detection within the Activation Segment in Skin Metastases by Pyrosequencing-Based Assay U-BRAF(V600)
title_short Automated Universal BRAF State Detection within the Activation Segment in Skin Metastases by Pyrosequencing-Based Assay U-BRAF(V600)
title_sort automated universal braf state detection within the activation segment in skin metastases by pyrosequencing-based assay u-braf(v600)
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3608589/
https://www.ncbi.nlm.nih.gov/pubmed/23555633
http://dx.doi.org/10.1371/journal.pone.0059221
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