A Next-Generation Sequencing Strategy for Evaluating the Most Common Genetic Abnormalities in Multiple Myeloma. - PubMed - NCBI
J Mol Diagn. 2016 Nov 15. pii: S1525-1578(16)30186-6. doi: 10.1016/j.jmoldx.2016.08.004. [Epub ahead of print]
A Next-Generation Sequencing Strategy for Evaluating the Most Common Genetic Abnormalities in Multiple Myeloma.
Jiménez C1,
Jara-Acevedo M2,
Corchete LA1,
Castillo D3,
Ordóñez GR3,
Sarasquete ME1,
Puig N1,
Martínez-López J4,
Prieto-Conde MI1,
García-Álvarez M1,
Chillón MC1,
Balanzategui A1,
Alcoceba M1,
Oriol A5,
Rosiñol L6,
Palomera L7,
Teruel AI8,
Lahuerta JJ4,
Bladé J6,
Mateos MV1,
Orfão A2,
San Miguel JF9,
González M10,
Gutiérrez NC1,
García-Sanz R1.
Abstract
Identification and characterization of genetic alterations are essential for diagnosis of multiple myeloma and may guide therapeutic decisions. Currently, genomic analysis of myeloma to cover the diverse range of alterations with prognostic impact requires fluorescence in situ hybridization (FISH), single nucleotide polymorphism arrays, and sequencing techniques, which are costly and labor intensive and require large numbers of plasma cells. To overcome these limitations, we designed a targeted-capture next-generation sequencing approach for one-step identification of IGH translocations, V(D)J clonal rearrangements, the IgH isotype, and somatic mutations to rapidly identify risk groups and specific targetable molecular lesions. Forty-eight newly diagnosed myeloma patients were tested with the panel, which included IGH and six genes that are recurrently mutated in myeloma: NRAS, KRAS, HRAS, TP53, MYC, and BRAF. We identified 14 of 17 IGH translocations previously detected by FISH and three confirmed translocations not detected by FISH, with the additional advantage of breakpoint identification, which can be used as a target for evaluating minimal residual disease. IgH subclass and V(D)J rearrangements were identified in 77% and 65% of patients, respectively. Mutation analysis revealed the presence of missense protein-coding alterations in at least one of the evaluating genes in 16 of 48 patients (33%). This method may represent a time- and cost-effective diagnostic method for the molecular characterization of multiple myeloma.
Copyright © 2016 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.
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