Literature DB >> 11877296

Oncogenesis of multiple myeloma: 14q32 and 13q chromosomal abnormalities are not randomly distributed, but correlate with natural history, immunological features, and clinical presentation.

Hervé Avet-Loiseau1, Thierry Facon, Bernard Grosbois, Florence Magrangeas, Marie-José Rapp, Jean-Luc Harousseau, Stéphane Minvielle, Régis Bataille.   

Abstract

Multiple myeloma (MM) is a plasma-cell malignancy characterized by marked epidemiological, biological, and clinical heterogeneity. The goal of this study was to find a genetic basis for this heterogeneity. Using fluorescence in situ hybridization, we analyzed a prospective cohort of 901 patients with various plasma-cell disorders--monoclonal gammopathies of undetermined significance, smoldering MM, MM, and primary plasma-cell leukemia--for genetic abnormalities involving the 13q14 and 14q32 chromosomal regions; the patients were consecutively enrolled in the Intergroupe Francophone du Myélome clinical trials, We performed statistical analyses comparing these chromosomal abnormalities in terms of immunological (ie, immunoglobulin types and light-chain subtypes) and clinical status and, to some extent, prognostic features. It was found that 14q32 translocations and del(13) are the most frequent chromosomal abnormalities, observed in 75% and 45% of the patients, respectively, and are not randomly distributed, but interconnected. Second, correlations between them allowed us to define 4 major genetic categories of patients: (1) patients lacking any 14q32 abnormality (25%) and generally also lacking del(13); (2) patients presenting either t(4;14) or t(14;16), almost always associated with a del(13) (15% of patients); (3) patients with other 14q32 abnormalities and presenting del(13) (25%); and (4) patients with other 14q32 abnormalities but not presenting del(13) (35%). Third, we show that this genetic stratification is highly correlated with immunological status and clinical presentation and with some major prognostic factors. For the first time, this study gives genetic support to the heterogeneity observed in patients with MM and demonstrates that the 14q32 and 13q chromosomal abnormalities are not randomly distributed. The strong correlations we found might be the basis for a novel genetic classification of MM, as has been previously demonstrated for leukemias and lymphomas. Furthermore, our study supports different models for MM oncogenesis.

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Year:  2002        PMID: 11877296     DOI: 10.1182/blood.v99.6.2185

Source DB:  PubMed          Journal:  Blood        ISSN: 0006-4971            Impact factor:   22.113


  78 in total

1.  Monosomy 13 in metaphase spreads is a predictor of poor long-term outcome after bortezomib plus dexamethasone treatment for relapsed/refractory multiple myeloma.

Authors:  Miki Kiyota; Tsutomu Kobayashi; Shinichi Fuchida; Mio Yamamoto-Sugitani; Muneo Ohshiro; Yuji Shimura; Shinsuke Mizutani; Hisao Nagoshi; Nana Sasaki; Ryuko Nakayama; Yoshiaki Chinen; Natsumi Sakamoto; Hitoji Uchiyama; Yosuke Matsumoto; Shigeo Horiike; Chihiro Shimazaki; Junya Kuroda; Masafumi Taniwaki
Journal:  Int J Hematol       Date:  2012-03-17       Impact factor: 2.490

2.  The t(14;20) is a poor prognostic factor in myeloma but is associated with long-term stable disease in monoclonal gammopathies of undetermined significance.

Authors:  Fiona M Ross; Laura Chiecchio; GianPaolo Dagrada; Rebecca K M Protheroe; David M Stockley; Christine J Harrison; Nicholas C P Cross; Alex J Szubert; Mark T Drayson; Gareth J Morgan
Journal:  Haematologica       Date:  2010-04-21       Impact factor: 9.941

3.  Dysregulation of miRNAs in AL amyloidosis.

Authors:  Liangping Weng; Brian H Spencer; Pamela T SoohHoo; Lawreen H Connors; Carl J O'Hara; David C Seldin
Journal:  Amyloid       Date:  2011-08-11       Impact factor: 7.141

4.  Complex IGH rearrangements in multiple myeloma: Frequent detection discrepancies among three different probe sets.

Authors:  Gina Y Kim; Ana Gabrea; Yulia N Demchenko; Leif Bergsagel; Anna V Roschke; W Michael Kuehl
Journal:  Genes Chromosomes Cancer       Date:  2014-03-03       Impact factor: 5.006

5.  NEK2 induces drug resistance mainly through activation of efflux drug pumps and is associated with poor prognosis in myeloma and other cancers.

Authors:  Wen Zhou; Ye Yang; Jiliang Xia; He Wang; Mohamed E Salama; Wei Xiong; Hongwei Xu; Shashirekha Shetty; Tiehua Chen; Zhaoyang Zeng; Lei Shi; Maurizio Zangari; Rodney Miles; David Bearss; Guido Tricot; Fenghuang Zhan
Journal:  Cancer Cell       Date:  2013-01-14       Impact factor: 31.743

6.  Transcriptome analysis reveals molecular profiles associated with evolving steps of monoclonal gammopathies.

Authors:  Lucía López-Corral; Luis Antonio Corchete; María Eugenia Sarasquete; María Victoria Mateos; Ramón García-Sanz; Encarna Fermiñán; Juan-José Lahuerta; Joan Bladé; Albert Oriol; Ana Isabel Teruel; María Luz Martino; José Hernández; Jesús María Hernández-Rivas; Francisco Javier Burguillo; Jesús F San Miguel; Norma C Gutiérrez
Journal:  Haematologica       Date:  2014-05-09       Impact factor: 9.941

7.  Cyclin D dysregulation: an early and unifying pathogenic event in multiple myeloma.

Authors:  P Leif Bergsagel; W Michael Kuehl; Fenghuang Zhan; Jeffrey Sawyer; Bart Barlogie; John Shaughnessy
Journal:  Blood       Date:  2005-03-08       Impact factor: 22.113

Review 8.  Global gene expression profiling in the study of multiple myeloma.

Authors:  John D Shaughnessy
Journal:  Int J Hematol       Date:  2003-04       Impact factor: 2.490

Review 9.  Multistep tumorigenesis of multiple myeloma: its molecular delineation.

Authors:  Shinsuke Iida; Ryuzo Ueda
Journal:  Int J Hematol       Date:  2003-04       Impact factor: 2.490

Review 10.  Monoclonal gammopathy of undetermined significance and smoldering multiple myeloma: a review of the current understanding of epidemiology, biology, risk stratification, and management of myeloma precursor disease.

Authors:  Amit Agarwal; Irene M Ghobrial
Journal:  Clin Cancer Res       Date:  2012-12-05       Impact factor: 12.531

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