Literature DB >> 17367409

Upregulation of translational machinery and distinct genetic subgroups characterise hyperdiploidy in multiple myeloma.

Luca Agnelli1, Sonia Fabris, Silvio Bicciato, Dario Basso, Luca Baldini, Fortunato Morabito, Donata Verdelli, Katia Todoerti, Giorgio Lambertenghi-Deliliers, Luigia Lombardi, Antonino Neri.   

Abstract

Karyotypic instability, including numerical and structural chromosomal aberrations, represents a distinct feature of multiple myeloma (MM). About 40-50% of patients display hyperdiploidy, defined by recurrent trisomies of non-random chromosomes. To molecularly characterise hyperdiploid (H) and nonhyperdiploid (NH) MM, we analysed the gene expression profiles of 66 primary tumours, and used fluorescence in situ hybridisation to investigate the major chromosomal alterations. The differential expression of 225 genes mainly involved in protein biosynthesis, transcriptional machinery and oxidative phosphorylation distinguished the 28 H-MM from the 38 NH-MM cases. The 204 upregulated genes in H-MM mapped mainly to the chromosomes involved in hyperdiploidy, and the 29% upregulated genes in NH-MM mapped to 16q. The identified transcriptional fingerprint was robustly validated on a publicly available gene expression dataset of 64 MM cases; and the global expression modulation of regions on the chromosomes involved in hyperdiploidy was verified using a self-developed non-parametric statistical method. H-MM could be further divided into two distinct molecular and transcriptional entities, characterised by the presence of trisomy 11 and 1q-extracopies/chromosome 13 deletion respectively. These data reinforce the importance of combining molecular cytogenetics and gene expression profiling to define a genomic framework for the study of MM pathogenesis and clinical management.

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Year:  2007        PMID: 17367409     DOI: 10.1111/j.1365-2141.2006.06467.x

Source DB:  PubMed          Journal:  Br J Haematol        ISSN: 0007-1048            Impact factor:   6.998


  26 in total

1.  Secretome of human bone marrow mesenchymal stem cells: an emerging player in lung cancer progression and mechanisms of translation initiation.

Authors:  Oshrat Attar-Schneider; Victoria Zismanov; Liat Drucker; Maya Gottfried
Journal:  Tumour Biol       Date:  2015-10-30

2.  Multiple myeloma with 1q21 amplification is highly sensitive to MCL-1 targeting.

Authors:  Anne Slomp; Laura M Moesbergen; Jia-Nan Gong; Marta Cuenca; Peter A von dem Borne; Pieter Sonneveld; David C S Huang; Monique C Minnema; Victor Peperzak
Journal:  Blood Adv       Date:  2019-12-23

3.  MicroRNA-532 exerts oncogenic functions in t(4;14) multiple myeloma by targeting CAMK2N1.

Authors:  Kaihong Xu; Xuezhen Hu; Laifang Sun; Qingyue Liang; Guifang Ouyang; Yanli Zhang; Qitian Mu; Xiao Yan
Journal:  Hum Cell       Date:  2019-08-26       Impact factor: 4.174

Review 4.  Staging and prognostication of multiple myeloma.

Authors:  Rafael Fonseca; Jorge Monge; Meletios A Dimopoulos
Journal:  Expert Rev Hematol       Date:  2014-02       Impact factor: 2.929

5.  Unique Pattern of Overexpression of Raf-1 Kinase Inhibitory Protein in Its Inactivated Phosphorylated Form in Human Multiple Myeloma.

Authors:  Stavroula Baritaki; Sara Huerta-Yepez; Ma da Lourdas Cabrava-Haimandez; Marialuisa Sensi; Silvana Canevari; Massimo Libra; Manuel Penichet; Haiming Chen; James R Berenson; Benjamin Bonavida
Journal:  For Immunopathol Dis Therap       Date:  2011-04-01

6.  Uncovering the biology of multiple myeloma among African Americans: a comprehensive genomics approach.

Authors:  Angela Baker; Esteban Braggio; Susanna Jacobus; Sungwon Jung; Dirk Larson; Terry Therneau; Angela Dispenzieri; Scott A Van Wier; Gregory Ahmann; Joan Levy; Louise Perkins; Seungchan Kim; Kimberly Henderson; David Vesole; S Vincent Rajkumar; Diane F Jelinek; John Carpten; Rafael Fonseca
Journal:  Blood       Date:  2013-02-19       Impact factor: 22.113

7.  Migration and epithelial-to-mesenchymal transition of lung cancer can be targeted via translation initiation factors eIF4E and eIF4GI.

Authors:  Oshrat Attar-Schneider; Liat Drucker; Maya Gottfried
Journal:  Lab Invest       Date:  2016-08-08       Impact factor: 5.662

Review 8.  The molecular characterization and clinical management of multiple myeloma in the post-genome era.

Authors:  Y Zhou; B Barlogie; J D Shaughnessy
Journal:  Leukemia       Date:  2009-08-06       Impact factor: 11.528

9.  The expression pattern of small nucleolar and small Cajal body-specific RNAs characterizes distinct molecular subtypes of multiple myeloma.

Authors:  D Ronchetti; K Todoerti; G Tuana; L Agnelli; L Mosca; M Lionetti; S Fabris; P Colapietro; M Miozzo; M Ferrarini; P Tassone; A Neri
Journal:  Blood Cancer J       Date:  2012-11-23       Impact factor: 11.037

10.  Classify hyperdiploidy status of multiple myeloma patients using gene expression profiles.

Authors:  Yingxiang Li; Xujun Wang; Haiyang Zheng; Chengyang Wang; Stéphane Minvielle; Florence Magrangeas; Hervé Avet-Loiseau; Parantu K Shah; Yong Zhang; Nikhil C Munshi; Cheng Li
Journal:  PLoS One       Date:  2013-03-15       Impact factor: 3.240

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