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

Autor:	Bødker JS; Department of Haematology, Aalborg University Hospital, Aalborg, Denmark., Brøndum RF; Department of Haematology, Aalborg University Hospital, Aalborg, Denmark., Schmitz A; Department of Haematology, Aalborg University Hospital, Aalborg, Denmark., Schönherz AA; Department of Clinical Medicine, Aalborg University, Denmark., Jespersen DS; Department of Haematology, Aalborg University Hospital, Aalborg, Denmark., Sønderkær M; Department of Haematology, Aalborg University Hospital, Aalborg, Denmark., Vesteghem C; Department of Clinical Medicine, Aalborg University, Denmark., Due H; Department of Haematology, Aalborg University Hospital, Aalborg, Denmark., Nørgaard CH; Department of Haematology, Aalborg University Hospital, Aalborg, Denmark., Perez-Andres M; Department of Haematology, Aalborg University Hospital, Aalborg, Denmark.; Institute of Biomedical Research of Salamanca, University of Salamanca, Salamanca, Spain., Samur MK; Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA., Davies F; UAMS Myeloma Institute, University of Arkansas for Medical Sciences, Little Rock, AR., Walker B; UAMS Myeloma Institute, University of Arkansas for Medical Sciences, Little Rock, AR., Pawlyn C; Division of Molecular Pathology, Institute of Cancer Research, London, United Kingdom., Kaiser M; Division of Molecular Pathology, Institute of Cancer Research, London, United Kingdom., Johnson D; Division of Molecular Pathology, Institute of Cancer Research, London, United Kingdom., Bertsch U; National Center for Tumor Diseases, University of Heidelberg, Heidelberg, Germany., Broyl A; Department of Haematology, Erasmus Medical Center, Rotterdam, The Netherlands., van Duin M; Department of Haematology, Erasmus Medical Center, Rotterdam, The Netherlands., Shah R; Centre for Mathematical Sciences, University of Cambridge, Cambridge, United Kingdom; and., Johansen P; Department of Haematopathology., Nørgaard MA; Department of Cardiothoracic Surgery, and., Samworth RJ; Centre for Mathematical Sciences, University of Cambridge, Cambridge, United Kingdom; and., Sonneveld P; Department of Haematology, Erasmus Medical Center, Rotterdam, The Netherlands., Goldschmidt H; National Center for Tumor Diseases, University of Heidelberg, Heidelberg, Germany., Morgan GJ; UAMS Myeloma Institute, University of Arkansas for Medical Sciences, Little Rock, AR., Orfao A; Institute of Biomedical Research of Salamanca, University of Salamanca, Salamanca, Spain., Munshi N; Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA., Johnson HE; Department of Haematology, Aalborg University Hospital, Aalborg, Denmark.; Department of Clinical Medicine, Aalborg University, Denmark.; Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark., El-Galaly T; Department of Haematology, Aalborg University Hospital, Aalborg, Denmark.; Department of Clinical Medicine, Aalborg University, Denmark.; Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark., Dybkær K; Department of Haematology, Aalborg University Hospital, Aalborg, Denmark.; Department of Clinical Medicine, Aalborg University, Denmark.; Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark., Bøgsted M; Department of Haematology, Aalborg University Hospital, Aalborg, Denmark.; Department of Clinical Medicine, Aalborg University, Denmark.; Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark.
Jazyk:	angličtina
Zdroj:	Blood advances [Blood Adv] 2018 Sep 25; Vol. 2 (18), pp. 2400-2411.
DOI:	10.1182/bloodadvances.2018018564
Abstrakt:	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 g ene 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. (© 2018 by The American Society of Hematology.)
Databáze:	MEDLINE
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