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J Clin Oncol ; 29(14): 1893-7, 2011 May 10.
Article in English | MEDLINE | ID: mdl-21482986

ABSTRACT

Multiple myeloma (MM) is characterized by a significant heterogeneity at the molecular level. The first level is the chromosomal one. Although cytogenetics is difficult to assess in MM, patients can be divided into two categories: hyperdiploidy and non-hyperdiploidy (about half in each group). Using molecular cytogenetic techniques, several subgroups of patients are identified, particularly on the basis of 14q32 translocations. This chromosomal heterogeneity is confirmed by genomic techniques (gene expression profiling or single nucleotide polymorphism/comparative genomic hybridization arrays). Unsupervised analyses of gene expression profiles identified several subgroups of patients, essentially on the basis of chromosomal abnormalities such as hyperdiploidy or 14q32 translocations. However, these analyses failed to separate MM into subentities, which could lead to specific therapeutic approaches, as is the case for non-Hodgkin's lymphomas. Nevertheless, these chromosomal/genomic data can be used for prognostication of patients. Specific chromosomal changes, such as loss of the short arm of chromosome 17, or specific gene expression profiles clearly identify patients with short survival. No molecular change so far has been associated with long survival or even cure, probably because of the short follow-up observed in all studies. So far, it is unclear how to use this massive amount of data to treat patients. Because of the complex and heterogeneous picture of the molecular profiles, it is unexpected that targeted therapies might play a role in MM. The only recognized indication is to propose bortezomib-based approaches for the treatment of patients displaying the translocation t(4;14).


Subject(s)
Multiple Myeloma/genetics , Chromosome Deletion , Gene Dosage , Humans , Multiple Myeloma/etiology , Multiple Myeloma/mortality , Multiple Myeloma/therapy , Polymorphism, Single Nucleotide , Prognosis , Translocation, Genetic
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