Literature DB >> 12576322

Clinical and biologic implications of recurrent genomic aberrations in myeloma.

Rafael Fonseca1, Emily Blood, Montserrat Rue, David Harrington, Martin M Oken, Robert A Kyle, Gordon W Dewald, Brian Van Ness, Scott A Van Wier, Kimberly J Henderson, Richard J Bailey, Philip R Greipp.   

Abstract

Nonrandom recurrent chromosomal abnormalities are ubiquitous in multiple myeloma (MM) and include, among others, translocations of the immunoglobulin heavy chain locus (IgH). IgH translocations in MM result in the up-regulation of oncogenes, and include more commonly t(11;14)(q13;q32), t(4;14)(p16;q32), and t(14;16)(q32;q23). Based on the recurrent nature of these translocations and their finding since the early stages of the plasma cell (PC) disorders, we hypothesized that they would confer biologic and clinical variability. In addition, deletions of 13q14 and 17p13 have also been associated with a shortened survival. We used cytoplasmic Ig-enhanced interphase fluorescent in situ hybridization to detect deletions (13q14 and 17p13.1), and translocations involving IgH in 351 patients treated with conventional chemotherapy entered into the Eastern Cooperative Oncology Group clinical trial E9486/9487. Translocations were frequently unbalanced with loss of one of the derivative chromosomes. The presence of t(4; 14)(p16;q32) (n = 42; 26 vs 45 months, P <.001), t(14;16)(q32;q23) (n = 15; 16 vs 41 months, P =.003), - 17p13 (n = 37; 23 vs 44 months, P =.005), and - 13q14 (n = 176; 35 vs 51 months, P =.028) were associated with shorter survival. A stratification of patients into 3 distinct categories allowed for prognostication: poor prognosis group (t(4;14)(p16;q32), t(14; 16)(q32;q23), and - 17p13), intermediate prognosis (- 13q14), and good prognosis group (all others), with median survivals of 24.7, 42.3, and 50.5 months, respectively (P <.001). This molecular cytogenetic classification identifies patients into poor, intermediate, and good risk categories. More importantly it provides further compelling evidence that MM is composed of subgroups of patients categorized according to their underlying genomic aberrations.

Entities:  

Mesh:

Substances:

Year:  2003        PMID: 12576322     DOI: 10.1182/blood-2002-10-3017

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


  183 in total

1.  Suppressing miRNA-15a/-16 expression by interleukin-6 enhances drug-resistance in myeloma cells.

Authors:  Mu Hao; Li Zhang; Gang An; Weiwei Sui; Zhen Yu; Dehui Zou; Yan Xu; Hong Chang; Lugui Qiu
Journal:  J Hematol Oncol       Date:  2011-09-22       Impact factor: 17.388

2.  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

3.  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

4.  Synchronous Thyroid Involvement in Plasma Cell Leukemia Masquerading as Hashimoto's Thyroiditis: Role of Ancillary Cytology Techniques in Diagnostic Workup.

Authors:  Ashwani Tandon; T Roshni Paul; Rekha Singh; A M V R Narendra
Journal:  Endocr Pathol       Date:  2015-12       Impact factor: 3.943

Review 5.  The use of molecular-based risk stratification and pharmacogenomics for outcome prediction and personalized therapeutic management of multiple myeloma.

Authors:  Sarah K Johnson; Christoph J Heuck; Anthony P Albino; Pingping Qu; Qing Zhang; Bart Barlogie; John D Shaughnessy
Journal:  Int J Hematol       Date:  2011-10-15       Impact factor: 2.490

6.  Combining fluorescent in situ hybridization data with ISS staging improves risk assessment in myeloma: an International Myeloma Working Group collaborative project.

Authors:  H Avet-Loiseau; B G M Durie; M Cavo; M Attal; N Gutierrez; J Haessler; H Goldschmidt; R Hajek; J H Lee; O Sezer; B Barlogie; J Crowley; R Fonseca; N Testoni; F Ross; S V Rajkumar; P Sonneveld; J Lahuerta; P Moreau; G Morgan
Journal:  Leukemia       Date:  2012-10-03       Impact factor: 11.528

7.  Influence of body mass index on survival in veterans with multiple myeloma.

Authors:  Tracey S Beason; Su-Hsin Chang; Kristen M Sanfilippo; Suhong Luo; Graham A Colditz; Ravi Vij; Michael H Tomasson; John F Dipersio; Keith Stockerl-Goldstein; Arun Ganti; Tanya Wildes; Kenneth R Carson
Journal:  Oncologist       Date:  2013-09-18

8.  Histone deacetylase inhibitor panobinostat induces calcineurin degradation in multiple myeloma.

Authors:  Yoichi Imai; Eri Ohta; Shu Takeda; Satoko Sunamura; Mariko Ishibashi; Hideto Tamura; Yan-Hua Wang; Atsuko Deguchi; Junji Tanaka; Yoshiro Maru; Toshiko Motoji
Journal:  JCI Insight       Date:  2016-04-21

Review 9.  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

Review 10.  Novel therapies in multiple myeloma for newly diagnosed nontransplant candidates.

Authors:  Sigurdur Yngvi Kristinsson; Ola Landgren; Vincent S Rajkumar
Journal:  Cancer J       Date:  2009 Nov-Dec       Impact factor: 3.360

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.