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Mutational landscape reflects the biological continuum of plasma cell dyscrasias
We subjected 90 patients covering a biological spectrum of plasma cell dyscrasias (monoclonal gammopathy of undetermined significance (MGUS), amyloid light-chain (AL) amyloidosis and multiple myeloma) to next-generation sequencing (NGS) gene panel analysis on unsorted bone marrow. A total of 64 diff...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5386334/ https://www.ncbi.nlm.nih.gov/pubmed/28234344 http://dx.doi.org/10.1038/bcj.2017.19 |
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author | Rossi, A Voigtlaender, M Janjetovic, S Thiele, B Alawi, M März, M Brandt, A Hansen, T Radloff, J Schön, G Hegenbart, U Schönland, S Langer, C Bokemeyer, C Binder, M |
author_facet | Rossi, A Voigtlaender, M Janjetovic, S Thiele, B Alawi, M März, M Brandt, A Hansen, T Radloff, J Schön, G Hegenbart, U Schönland, S Langer, C Bokemeyer, C Binder, M |
author_sort | Rossi, A |
collection | PubMed |
description | We subjected 90 patients covering a biological spectrum of plasma cell dyscrasias (monoclonal gammopathy of undetermined significance (MGUS), amyloid light-chain (AL) amyloidosis and multiple myeloma) to next-generation sequencing (NGS) gene panel analysis on unsorted bone marrow. A total of 64 different mutations in 8 genes were identified in this cohort. NRAS (28.1%), KRAS (21.3%), TP53 (19.5%), BRAF (19.1%) and CCND1 (8.9%) were the most commonly mutated genes in all patients. Patients with non-myeloma plasma cell dyscrasias showed a significantly lower mutational load than myeloma patients (0.91±0.30 vs 2.07±0.29 mutations per case, P=0.008). KRAS and NRAS exon 3 mutations were significantly associated with the myeloma cohort compared with non-myeloma plasma cell dyscrasias (odds ratio (OR) 9.87, 95% confidence interval (CI) 1.07–90.72, P=0.043 and OR 7.03, 95% CI 1.49–33.26, P=0.014). NRAS exon 3 and TP53 exon 6 mutations were significantly associated with del17p cytogenetics (OR 0.12, 95% CI 0.02–0.87, P=0.036 and OR 0.05, 95% CI 0.01–0.54, P=0.013). Our data show that the mutational landscape reflects the biological continuum of plasma cell dyscrasias from a low-complexity mutational pattern in MGUS and AL amyloidosis to a high-complexity pattern in multiple myeloma. Our targeted NGS approach allows resource-efficient, sensitive and scalable mutation analysis for prognostic, predictive or therapeutic purposes. |
format | Online Article Text |
id | pubmed-5386334 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-53863342017-04-26 Mutational landscape reflects the biological continuum of plasma cell dyscrasias Rossi, A Voigtlaender, M Janjetovic, S Thiele, B Alawi, M März, M Brandt, A Hansen, T Radloff, J Schön, G Hegenbart, U Schönland, S Langer, C Bokemeyer, C Binder, M Blood Cancer J Original Article We subjected 90 patients covering a biological spectrum of plasma cell dyscrasias (monoclonal gammopathy of undetermined significance (MGUS), amyloid light-chain (AL) amyloidosis and multiple myeloma) to next-generation sequencing (NGS) gene panel analysis on unsorted bone marrow. A total of 64 different mutations in 8 genes were identified in this cohort. NRAS (28.1%), KRAS (21.3%), TP53 (19.5%), BRAF (19.1%) and CCND1 (8.9%) were the most commonly mutated genes in all patients. Patients with non-myeloma plasma cell dyscrasias showed a significantly lower mutational load than myeloma patients (0.91±0.30 vs 2.07±0.29 mutations per case, P=0.008). KRAS and NRAS exon 3 mutations were significantly associated with the myeloma cohort compared with non-myeloma plasma cell dyscrasias (odds ratio (OR) 9.87, 95% confidence interval (CI) 1.07–90.72, P=0.043 and OR 7.03, 95% CI 1.49–33.26, P=0.014). NRAS exon 3 and TP53 exon 6 mutations were significantly associated with del17p cytogenetics (OR 0.12, 95% CI 0.02–0.87, P=0.036 and OR 0.05, 95% CI 0.01–0.54, P=0.013). Our data show that the mutational landscape reflects the biological continuum of plasma cell dyscrasias from a low-complexity mutational pattern in MGUS and AL amyloidosis to a high-complexity pattern in multiple myeloma. Our targeted NGS approach allows resource-efficient, sensitive and scalable mutation analysis for prognostic, predictive or therapeutic purposes. Nature Publishing Group 2017-02 2017-02-24 /pmc/articles/PMC5386334/ /pubmed/28234344 http://dx.doi.org/10.1038/bcj.2017.19 Text en Copyright © 2017 The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Original Article Rossi, A Voigtlaender, M Janjetovic, S Thiele, B Alawi, M März, M Brandt, A Hansen, T Radloff, J Schön, G Hegenbart, U Schönland, S Langer, C Bokemeyer, C Binder, M Mutational landscape reflects the biological continuum of plasma cell dyscrasias |
title | Mutational landscape reflects the biological continuum of plasma cell dyscrasias |
title_full | Mutational landscape reflects the biological continuum of plasma cell dyscrasias |
title_fullStr | Mutational landscape reflects the biological continuum of plasma cell dyscrasias |
title_full_unstemmed | Mutational landscape reflects the biological continuum of plasma cell dyscrasias |
title_short | Mutational landscape reflects the biological continuum of plasma cell dyscrasias |
title_sort | mutational landscape reflects the biological continuum of plasma cell dyscrasias |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5386334/ https://www.ncbi.nlm.nih.gov/pubmed/28234344 http://dx.doi.org/10.1038/bcj.2017.19 |
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