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Plasma Cell Dyscrasias

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Attention for Chapter 3: Genomic Aberrations in Multiple Myeloma
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Chapter title
Genomic Aberrations in Multiple Myeloma
Chapter number 3
Book title
Plasma Cell Dyscrasias
Published in
Cancer treatment and research, January 2016
DOI 10.1007/978-3-319-40320-5_3
Pubmed ID
Book ISBNs
978-3-31-940318-2, 978-3-31-940320-5
Authors

Salomon Manier, Karma Salem, Siobhan V. Glavey, Aldo M. Roccaro, Irene M. Ghobrial, Manier, Salomon, Salem, Karma, Glavey, Siobhan V., Roccaro, Aldo M., Ghobrial, Irene M.

Abstract

Multiple myeloma (MM) is a genetically complex disease. The past few years have seen an evolution in cancer research with the emergence of next-generation sequencing (NGS), enabling high throughput sequencing of tumors-including whole exome, whole genome, RNA, and single-cell sequencing as well as genome-wide association study (GWAS). A few inherited variants have been described, counting for some cases of familial disease. Hierarchically, primary events in MM can be divided into hyperdiploid (HDR) and nonhyperdiploid subtypes. HRD tumors are characterized by trisomy of chromosomes 3, 5, 7, 9, 11, 15, 19, and/or 21. Non-HRD tumors harbor IGH translocations, mainly t(4;14), t(6;14), t(11;14), t(14;16), and t(14;20). Secondary events participate to the tumor progression and consist in secondary translocation involving MYC, copy number variations (CNV) and somatic mutations (such as mutations in KRAS, NRAS, BRAF, P53). Moreover, the dissection of clonal heterogeneity helps to understand the evolution of the disease. The following review provides a comprehensive review of the genomic landscape in MM.

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The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 23%
Other 4 11%
Student > Bachelor 3 9%
Student > Ph. D. Student 3 9%
Student > Master 3 9%
Other 3 9%
Unknown 11 31%
Readers by discipline Count As %
Medicine and Dentistry 14 40%
Biochemistry, Genetics and Molecular Biology 3 9%
Agricultural and Biological Sciences 3 9%
Computer Science 1 3%
Nursing and Health Professions 1 3%
Other 0 0%
Unknown 13 37%