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      Landscape of genetic lesions in 944 patients with myelodysplastic syndromes

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          Abstract

          High-throughput DNA sequencing significantly contributed to diagnosis and prognostication in patients with myelodysplastic syndromes (MDS). We determined the biological and prognostic significance of genetic aberrations in MDS. In total, 944 patients with various MDS subtypes were screened for known/putative mutations/deletions in 104 genes using targeted deep sequencing and array-based genomic hybridization. In total, 845/944 patients (89.5%) harbored at least one mutation (median, 3 per patient; range, 0–12). Forty-seven genes were significantly mutated with TET2, SF3B1, ASXL1, SRSF2, DNMT3A, and RUNX1 mutated in >10% of cases. Many mutations were associated with higher risk groups and/or blast elevation. Survival was investigated in 875 patients. By univariate analysis, 25/48 genes (resulting from 47 genes tested significantly plus PRPF8) affected survival ( P<0.05). The status of 14 genes combined with conventional factors revealed a novel prognostic model (‘Model-1') separating patients into four risk groups (‘low', ‘intermediate', ‘high', ‘very high risk') with 3-year survival of 95.2, 69.3, 32.8, and 5.3% ( P<0.001). Subsequently, a ‘gene-only model' (‘Model-2') was constructed based on 14 genes also yielding four significant risk groups ( P<0.001). Both models were reproducible in the validation cohort ( n=175 patients; P<0.001 each). Thus, large-scale genetic and molecular profiling of multiple target genes is invaluable for subclassification and prognostication in MDS patients.

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          Revised international prognostic scoring system for myelodysplastic syndromes.

          The International Prognostic Scoring System (IPSS) is an important standard for assessing prognosis of primary untreated adult patients with myelodysplastic syndromes (MDS). To refine the IPSS, MDS patient databases from international institutions were coalesced to assemble a much larger combined database (Revised-IPSS [IPSS-R], n = 7012, IPSS, n = 816) for analysis. Multiple statistically weighted clinical features were used to generate a prognostic categorization model. Bone marrow cytogenetics, marrow blast percentage, and cytopenias remained the basis of the new system. Novel components of the current analysis included: 5 rather than 3 cytogenetic prognostic subgroups with specific and new classifications of a number of less common cytogenetic subsets, splitting the low marrow blast percentage value, and depth of cytopenias. This model defined 5 rather than the 4 major prognostic categories that are present in the IPSS. Patient age, performance status, serum ferritin, and lactate dehydrogenase were significant additive features for survival but not for acute myeloid leukemia transformation. This system comprehensively integrated the numerous known clinical features into a method analyzing MDS patient prognosis more precisely than the initial IPSS. As such, this IPSS-R should prove beneficial for predicting the clinical outcomes of untreated MDS patients and aiding design and analysis of clinical trials in this disease.
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            International scoring system for evaluating prognosis in myelodysplastic syndromes.

            Despite multiple disparate prognostic risk analysis systems for evaluating clinical outcome for patients with myelodysplastic syndrome (MDS), imprecision persists with such analyses. To attempt to improve on these systems, an International MDS Risk Analysis Workshop combined cytogenetic, morphological, and clinical data from seven large previously reported risk-based studies that had generated prognostic systems. A global analysis was performed on these patients, and critical prognostic variables were re-evaluated to generate a consensus prognostic system, particularly using a more refined bone marrow (BM) cytogenetic classification. Univariate analysis indicated that the major variables having an impact on disease outcome for evolution to acute myeloid leukemia were cytogenetic abnormalities, percentage of BM myeloblasts, and number of cytopenias; for survival, in addition to the above, variables also included age and gender. Cytogenetic subgroups of outcome were as follows: "good" outcomes were normal, -Y alone, del(5q) alone, del(20q) alone; "poor" outcomes were complex (ie, > or = 3 abnormalities) or chromosome 7 anomalies; and "intermediate" outcomes were other abnormalities. Multivariate analysis combined these cytogenetic subgroups with percentage of BM blasts and number of cytopenias to generate a prognostic model. Weighting these variables by their statistical power separated patients into distinctive subgroups of risk for 25% of patients to undergo evolution to acute myeloid leukemia, with: low (31% of patients), 9.4 years; intermediate-1 (INT-1; 39%), 3.3 years; INT-2 (22%), 1.1 years; and high (8%), 0.2 year. These features also separated patients into similar distinctive risk groups for median survival: low, 5.7 years; INT-1, 3.5 years; INT-2, 1.2 years; and high, 0.4 year. Stratification for age further improved analysis of survival. Compared with prior risk-based classifications, this International Prognostic Scoring System provides an improved method for evaluating prognosis in MDS. This classification system should prove useful for more precise design and analysis of therapeutic trials in this disease.
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              Clinical effect of point mutations in myelodysplastic syndromes.

              Myelodysplastic syndromes are clinically heterogeneous disorders characterized by clonal hematopoiesis, impaired differentiation, peripheral-blood cytopenias, and a risk of progression to acute myeloid leukemia. Somatic mutations may influence the clinical phenotype but are not included in current prognostic scoring systems. We used a combination of genomic approaches, including next-generation sequencing and mass spectrometry-based genotyping, to identify mutations in samples of bone marrow aspirate from 439 patients with myelodysplastic syndromes. We then examined whether the mutation status for each gene was associated with clinical variables, including specific cytopenias, the proportion of blasts, and overall survival. We identified somatic mutations in 18 genes, including two, ETV6 and GNAS, that have not been reported to be mutated in patients with myelodysplastic syndromes. A total of 51% of all patients had at least one point mutation, including 52% of the patients with normal cytogenetics. Mutations in RUNX1, TP53, and NRAS were most strongly associated with severe thrombocytopenia (P<0.001 for all comparisons) and an increased proportion of bone marrow blasts (P<0.006 for all comparisons). In a multivariable Cox regression model, the presence of mutations in five genes retained independent prognostic significance: TP53 (hazard ratio for death from any cause, 2.48; 95% confidence interval [CI], 1.60 to 3.84), EZH2 (hazard ratio, 2.13; 95% CI, 1.36 to 3.33), ETV6 (hazard ratio, 2.04; 95% CI, 1.08 to 3.86), RUNX1 (hazard ratio, 1.47; 95% CI, 1.01 to 2.15), and ASXL1 (hazard ratio, 1.38; 95% CI, 1.00 to 1.89). Somatic point mutations are common in myelodysplastic syndromes and are associated with specific clinical features. Mutations in TP53, EZH2, ETV6, RUNX1, and ASXL1 are predictors of poor overall survival in patients with myelodysplastic syndromes, independently of established risk factors. (Funded by the National Institutes of Health and others.).
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                Author and article information

                Journal
                Leukemia
                Leukemia
                Leukemia
                Nature Publishing Group
                0887-6924
                1476-5551
                February 2014
                13 November 2013
                29 November 2013
                : 28
                : 2
                : 241-247
                Affiliations
                [1 ]Munich Leukemia Laboratory (MLL) , Munich, Germany
                [2 ]Cancer Genomics Project, Graduate School of Medicine, The University of Tokyo , Tokyo, Japan
                [3 ]Genome Science Division, Research Center for Advanced Science and Technology, The University of Tokyo , Tokyo, Japan
                [4 ]Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University , Kyoto, Japan
                [5 ]Laboratory of Sequence Data Analysis, Human Genome Center, Institute of Medical Science, The University of Tokyo , Tokyo, Japan
                [6 ]Laboratory of DNA Information Analysis, Institute of Medical Science, The University of Tokyo , Tokyo, Japan
                [7 ]Department of Hematology/Oncology, Cedars-Sinai Medical Center , Los Angeles, CA, USA
                [8 ]Cancer Science Institute of Singapore, National University of Singapore , Singapore, Singapore
                [9 ]Institute of Medical Informatics, University of Münster , Münster, Germany
                Author notes
                [* ]MLL Munich Leukemia Laboratory , Max-Lebsche-Platz 31, Munich 81377, GermanyE-mail: torsten.haferlach@ 123456mll.com
                [* ]Cancer Genomics Project, Graduate School of Medicine, The University of Tokyo , Bunkyo-ku, Tokyo, Japan. E-mail: sogawa-tky@ 123456umin.ac.jp
                [10]

                These authors contributed equally to this work. We dedicate the manuscript to Professor Helmut Löffler, a great mentor and friend.

                Article
                leu2013336
                10.1038/leu.2013.336
                3918868
                24220272
                dbde78e9-48cb-470e-899d-218c4949301d
                Copyright © 2014 Macmillan Publishers Limited

                This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/

                History
                : 19 September 2013
                : 21 October 2013
                : 30 October 2013
                Categories
                Leading Article

                Oncology & Radiotherapy
                next-generation sequencing,myelodysplastic syndromes,prognostic score,molecular markers

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