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A comprehensive DNA panel next generation sequencing approach supporting diagnostics and therapy prediction in neurooncology
Recent updates in the classification of central nervous system (CNS) tumors have increased the need for molecular testing. Assessment of multiple alterations in parallel, complex combinations of gene sequence and chromosomal changes, as well as therapy prediction by identification of actionable muta...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7405456/ https://www.ncbi.nlm.nih.gov/pubmed/32758285 http://dx.doi.org/10.1186/s40478-020-01000-w |
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author | Lorenz, Julia Rothhammer-Hampl, Tanja Zoubaa, Saida Bumes, Elisabeth Pukrop, Tobias Kölbl, Oliver Corbacioglu, Selim Schmidt, Nils O. Proescholdt, Martin Hau, Peter Riemenschneider, Markus J. |
author_facet | Lorenz, Julia Rothhammer-Hampl, Tanja Zoubaa, Saida Bumes, Elisabeth Pukrop, Tobias Kölbl, Oliver Corbacioglu, Selim Schmidt, Nils O. Proescholdt, Martin Hau, Peter Riemenschneider, Markus J. |
author_sort | Lorenz, Julia |
collection | PubMed |
description | Recent updates in the classification of central nervous system (CNS) tumors have increased the need for molecular testing. Assessment of multiple alterations in parallel, complex combinations of gene sequence and chromosomal changes, as well as therapy prediction by identification of actionable mutations are the major challenges. We here report on a customized next generation sequencing (NGS)-based DNA panel assay that combines diagnostic and predictive testing and -as a comprehensive approach- allows for simultaneous single nucleotide variant (SNP) / small insertion/deletion (InDel), copy number variation (CNV) and loss of heterozygosity (LOH) detection. We analyzed formalin-fixed and paraffin-embedded (FFPE) DNA from a total of 104 patients with CNS tumors. After amplicon capture-based library preparation, sequencing was performed on the relatively cost-efficient Illiumina MiniSeq platform and evaluated with freely available bioinformatical tools. 57 genes for exonic SNP/InDel calling (19 of those in intronic regions for CNV analysis), 3 chromosomal arms and 4 entire chromosomes for CNV and LOH analysis were covered. Results were extensively validated. Our approach yielded high accuracy, sensitivity and specificity. It led to refined diagnoses in a relevant number of analyzed cases, reliably enabled complex subclassifications (e.g. for medulloblastomas) and identified actionable targets for clinical use. Thus, our single-platform approach is an efficient and powerful tool to comprehensively support molecular testing in neurooncology. Future functionality is guaranteed as novel upcoming biomarkers can be easily incorporated in a modular panel design. |
format | Online Article Text |
id | pubmed-7405456 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-74054562020-08-07 A comprehensive DNA panel next generation sequencing approach supporting diagnostics and therapy prediction in neurooncology Lorenz, Julia Rothhammer-Hampl, Tanja Zoubaa, Saida Bumes, Elisabeth Pukrop, Tobias Kölbl, Oliver Corbacioglu, Selim Schmidt, Nils O. Proescholdt, Martin Hau, Peter Riemenschneider, Markus J. Acta Neuropathol Commun Research Recent updates in the classification of central nervous system (CNS) tumors have increased the need for molecular testing. Assessment of multiple alterations in parallel, complex combinations of gene sequence and chromosomal changes, as well as therapy prediction by identification of actionable mutations are the major challenges. We here report on a customized next generation sequencing (NGS)-based DNA panel assay that combines diagnostic and predictive testing and -as a comprehensive approach- allows for simultaneous single nucleotide variant (SNP) / small insertion/deletion (InDel), copy number variation (CNV) and loss of heterozygosity (LOH) detection. We analyzed formalin-fixed and paraffin-embedded (FFPE) DNA from a total of 104 patients with CNS tumors. After amplicon capture-based library preparation, sequencing was performed on the relatively cost-efficient Illiumina MiniSeq platform and evaluated with freely available bioinformatical tools. 57 genes for exonic SNP/InDel calling (19 of those in intronic regions for CNV analysis), 3 chromosomal arms and 4 entire chromosomes for CNV and LOH analysis were covered. Results were extensively validated. Our approach yielded high accuracy, sensitivity and specificity. It led to refined diagnoses in a relevant number of analyzed cases, reliably enabled complex subclassifications (e.g. for medulloblastomas) and identified actionable targets for clinical use. Thus, our single-platform approach is an efficient and powerful tool to comprehensively support molecular testing in neurooncology. Future functionality is guaranteed as novel upcoming biomarkers can be easily incorporated in a modular panel design. BioMed Central 2020-08-05 /pmc/articles/PMC7405456/ /pubmed/32758285 http://dx.doi.org/10.1186/s40478-020-01000-w Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Lorenz, Julia Rothhammer-Hampl, Tanja Zoubaa, Saida Bumes, Elisabeth Pukrop, Tobias Kölbl, Oliver Corbacioglu, Selim Schmidt, Nils O. Proescholdt, Martin Hau, Peter Riemenschneider, Markus J. A comprehensive DNA panel next generation sequencing approach supporting diagnostics and therapy prediction in neurooncology |
title | A comprehensive DNA panel next generation sequencing approach supporting diagnostics and therapy prediction in neurooncology |
title_full | A comprehensive DNA panel next generation sequencing approach supporting diagnostics and therapy prediction in neurooncology |
title_fullStr | A comprehensive DNA panel next generation sequencing approach supporting diagnostics and therapy prediction in neurooncology |
title_full_unstemmed | A comprehensive DNA panel next generation sequencing approach supporting diagnostics and therapy prediction in neurooncology |
title_short | A comprehensive DNA panel next generation sequencing approach supporting diagnostics and therapy prediction in neurooncology |
title_sort | comprehensive dna panel next generation sequencing approach supporting diagnostics and therapy prediction in neurooncology |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7405456/ https://www.ncbi.nlm.nih.gov/pubmed/32758285 http://dx.doi.org/10.1186/s40478-020-01000-w |
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