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A multiple myeloma classification system that associates normal B-cell subset phenotypes with prognosis

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  • Julie Støve Bødker, Aalborg Universitet
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  • Rasmus Froberg Brøndum, Aalborg Universitet
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  • Alexander Schmitz
  • Anna Amanda Schönherz
  • Ditte Starberg Jespersen, Aalborg Universitet
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  • Mads Sønderkær, Aalborg Universitet
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  • Charles Vesteghem, Aalborg Universitet
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  • Hanne Due, Aalborg Universitet
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  • Caroline Holm Nørgaard, Aalborg Universitet
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  • Martin Perez-Andres, Molecular Medicine Unit, Department of Medicine and Biomedical Research Institute of Salamanca (IBSAL), University Hospital of Salamanca, University of Salamanca - CSIC, Salamanca, Spain.
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  • Mehmet Kemal Samur, Dana-Farber Cancer Institute
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  • Faith Davies, UAMS Myeloma Institute, University of Arkansas for Medical Sciences, Little Rock, AR.
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  • Brian Walker, UAMS Myeloma Institute, University of Arkansas for Medical Sciences, Little Rock, AR.
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  • Charlotte Pawlyn, Division of Molecular Pathology, Institute of Cancer Research, London, United Kingdom.
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  • Martin Kaiser, Division of Molecular Pathology, Institute of Cancer Research, London, United Kingdom.
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  • David Johnson, Division of Molecular Pathology, Institute of Cancer Research, London, United Kingdom.
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  • Uta Bertsch, German Cancer Research Center (DKFZ), Heidelberg, Germany / Department of Radiation Oncology, University Heidelberg German Consortium for Translational Oncology (DKTK), Germany / National Center for Tumor Diseases (NCT), Heidelberg, Germany
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  • Annemiek Broyl, Department of Haematology, Erasmus Medical Center, Rotterdam, the Netherlands
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  • Mark van Duin, Department of Haematology, Erasmus Medical Center, Rotterdam, the Netherlands
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  • Rajen Shah, Centre for Mathematical Sciences, University of Cambridge, Cambridge, United Kingdom; and.
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  • Preben Johansen, Department of Haematopathology.
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  • Martin Agge Nørgaard, Department of Cardiothoracic and Vascular Surgery.
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  • Richard J Samworth, Centre for Mathematical Sciences, University of Cambridge, Cambridge, United Kingdom; and.
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  • Pieter Sonneveld, Department of Haematology, Erasmus Medical Center, Rotterdam, the Netherlands
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  • Hartmut Goldschmidt, German Cancer Research Center (DKFZ), Heidelberg, Germany / Department of Radiation Oncology, University Heidelberg German Consortium for Translational Oncology (DKTK), Germany / National Center for Tumor Diseases (NCT), Heidelberg, Germany
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  • Gareth J Morgan, UAMS Myeloma Institute, University of Arkansas for Medical Sciences, Little Rock, AR.
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  • Alberto Orfao, Molecular Medicine Unit, Department of Medicine and Biomedical Research Institute of Salamanca (IBSAL), University Hospital of Salamanca, University of Salamanca - CSIC, Salamanca, Spain.
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  • Nikhil Munshi, Dana-Farber Cancer Institute
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  • Hans Erik Johnson, Aalborg Universitet
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  • Tarec El-Galaly, Aalborg Universitet
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  • Karen Dybkær, Aalborg Universitet
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  • Martin Bøgsted

Despite the recent progress in treatment of multiple myeloma (MM), it is still an incurable malignant disease, and we are therefore in need of new risk stratification tools that can help us to understand the disease and optimize therapy. Here we propose a new subtyping of myeloma plasma cells (PCs) from diagnostic samples, assigned by normal B-cell subset associated gene signatures (BAGS). For this purpose, we combined fluorescence-activated cell sorting and gene expression profiles from normal bone marrow (BM) Pre-BI, Pre-BII, immature, naïve, memory, and PC subsets to generate BAGS for assignment of normal BM subtypes in diagnostic samples. The impact of the subtypes was analyzed in 8 available data sets from 1772 patients' myeloma PC samples. The resulting tumor assignments in available clinical data sets exhibited similar BAGS subtype frequencies in 4 cohorts from de novo MM patients across 1296 individual cases. The BAGS subtypes were significantly associated with progression-free and overall survival in a meta-analysis of 916 patients from 3 prospective clinical trials. The major impact was observed within the Pre-BII and memory subtypes, which had a significantly inferior prognosis compared with other subtypes. A multiple Cox proportional hazard analysis documented that BAGS subtypes added significant, independent prognostic information to the translocations and cyclin D classification. BAGS subtype analysis of patient cases identified transcriptional differences, including a number of differentially spliced genes. We identified subtype differences in myeloma at diagnosis, with prognostic impact and predictive potential, supporting an acquired B-cell trait and phenotypic plasticity as a pathogenetic hallmark of MM.

OriginalsprogEngelsk
TidsskriftBlood Advances
Vol/bind2
Nummer18
Sider (fra-til)2400-2411
Antal sider12
ISSN2473-9529
DOI
StatusUdgivet - 25 sep. 2018
Eksternt udgivetJa

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© 2018 by The American Society of Hematology.

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