A DNA target-enrichment approach to detect mutations, copy number changes and immunoglobulin translocations in multiple myeloma.
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Authors
Li, Y
Sathiaseelan, V
Raine, K
Jones, D
Ganly, P
Cocito, F
Bignell, G
Chapman, MA
Sperling, AS
Anderson, KC
Avet-Loiseau, H
Minvielle, S
Campbell, PJ
Munshi, NC
Publication Date
2016-09-02Journal Title
Blood Cancer J
ISSN
2044-5385
Publisher
Springer Science and Business Media LLC
Volume
6
Issue
9
Pages
e467
Language
eng
Type
Article
Physical Medium
Electronic
Metadata
Show full item recordCitation
Bolli, N., Li, Y., Sathiaseelan, V., Raine, K., Jones, D., Ganly, P., Cocito, F., et al. (2016). A DNA target-enrichment approach to detect mutations, copy number changes and immunoglobulin translocations in multiple myeloma.. Blood Cancer J, 6 (9), e467. https://doi.org/10.1038/bcj.2016.72
Abstract
Genomic lesions are not investigated during routine diagnostic workup for multiple myeloma (MM). Cytogenetic studies are performed to assess prognosis but with limited impact on therapeutic decisions. Recently, several recurrently mutated genes have been described, but their clinical value remains to be defined. Therefore, clinical-grade strategies to investigate the genomic landscape of myeloma samples are needed to integrate new and old prognostic markers. We developed a target-enrichment strategy followed by next-generation sequencing (NGS) to streamline simultaneous analysis of gene mutations, copy number changes and immunoglobulin heavy chain (IGH) translocations in MM in a high-throughput manner, and validated it in a panel of cell lines. We identified 548 likely oncogenic mutations in 182 genes. By integrating published data sets of NGS in MM, we retrieved a list of genes with significant relevance to myeloma and found that the mutational spectrum of primary samples and MM cell lines is partially overlapping. Gains and losses of chromosomes, chromosomal segments and gene loci were identified with accuracy comparable to conventional arrays, allowing identification of lesions with known prognostic significance. Furthermore, we identified IGH translocations with high positive and negative predictive value. Our approach could allow the identification of novel biomarkers with clinical relevance in myeloma.
Keywords
Alleles, Cell Line, Tumor, DNA Copy Number Variations, Gene Frequency, Gene Rearrangement, B-Lymphocyte, Heavy Chain, High-Throughput Nucleotide Sequencing, Humans, Immunoglobulin Heavy Chains, Loss of Heterozygosity, Multiple Myeloma, Mutation, Reproducibility of Results, Translocation, Genetic
Identifiers
External DOI: https://doi.org/10.1038/bcj.2016.72
This record's URL: https://www.repository.cam.ac.uk/handle/1810/285781
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