Naslov
MicroRNA expression in multiple myeloma is associated with genetic subtype, isotype and survival

Autori
Chi, Jianxiang ; Ballabio, Erica ; Chen, Xiao-He ; Kušec, Rajko ; Taylor, Steve ; Hay, Deborah ; Tramonti, Daniela ; Saunders, Nigel ; Littlewood, Timothy ; Pezzella, Francesco ; Boultwood, Jacqueline ; Wainscoat, James ; Hatton, Christian ; Lawrie, Charles

Izvornik
Biology direct (1745-6150) 6 (2011), 23;

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
micro-RNA; multiple myeloma; oncogenesis

Sažetak
BACKGROUND: MicroRNAs are small RNA species that regulate gene expression post-transcriptionally and are aberrantly expressed in many cancers including hematological malignancies. However, the role of microRNAs in the pathogenesis of multiple myeloma (MM) is only poorly understood. We therefore used microarray analysis to elucidate the complete miRNome (miRBase version 13.0) of purified tumor (CD138+) cells from 33 patients with MM, 5 patients with monoclonal gammopathy of undetermined significance (MGUS) and 9 controls. RESULTS: Unsupervised cluster analysis revealed that MM and MGUS samples have a distinct microRNA expression profile from control CD138+ cells. The majority of microRNAs aberrantly expressed in MM (109/129) were up-regulated. A comparison of these microRNAs with those aberrantly expressed in other B-cell and T-cell malignancies revealed a surprising degree of similarity (~40%) suggesting the existence of a common lymphoma microRNA signature. We identified 39 microRNAs associated with the pre-malignant condition MGUS. Twenty-three (59%) of these were also aberrantly expressed in MM suggesting common microRNA expression events in MM progression. MM is characterized by multiple chromosomal abnormalities of varying prognostic significance. We identified specific microRNA signatures associated with the most common IgH translocations (t(4 ; 14) and t(11 ; 14)) and del(13q). Expression levels of these microRNAs were distinct between the genetic subtypes (by cluster analysis) and correctly predicted these abnormalities in > 85% of cases using the support vector machine algorithm. Additionally, we identified microRNAs associated with light chain only myeloma, as well as IgG and IgA-type MM. Finally, we identified 32 microRNAs associated with event-free survival (EFS) in MM, ten of which were significant by univariate (logrank) survival analysis. CONCLUSIONS: In summary, this work has identified aberrantly expressed microRNAs associated with the diagnosis, pathogenesis and prognosis of MM, data which will prove an invaluable resource for understanding the role of microRNAs in this devastating disease.

Izvorni jezik
Engleski

Znanstvena područja
Kliničke medicinske znanosti

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