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 Blood, 30 July 2009, Vol. 114, No. 5, pp. 1063-1072.
Prepublished online as a Blood First Edition Paper on May 14, 2009; DOI 10.1182/blood-2008-10-187203.

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MYELOID NEOPLASIA

Microarray-based classifiers and prognosis models identify subgroups with distinct clinical outcomes and high risk of AML transformation of myelodysplastic syndrome

Ken I. Mills13, Alexander Kohlmann4,5, P. Mickey Williams4, Lothar Wieczorek4, Wei-min Liu4, Rachel Li4, Wen Wei4, David T. Bowen6, Helmut Loeffler7, Jesus M. Hernandez3,8, Wolf-Karsten Hofmann3,9,10, and Torsten Haferlach3,5

1 Centre for Cancer Research and Cell Biology, Queen's University Belfast, Belfast, United Kingdom; 2 Department of Haematology, Cardiff University, Cardiff, United Kingdom; 3 MILE Study (WP13), on behalf of the European LeukemiaNet, Mannheim, Germany; 4 Genomics and Oncology, Roche Molecular Systems Inc, Pleasanton, CA; 5 MLL, Munich Leukemia Laboratory, Munich, Germany; 6 Department of Haematology, St James's Institute of Oncology, Leeds, United Kingdom; 7 St Peter, Germany; 8 Servicio de Hematologia, Hospital Universitario de Salamanca and Instituto de Biologia Molecular y Celular del Cancer, Centro de Investigación del Cáncer, Universidad de Salamanca-CSIC, Salamanca, Spain; 9 Charité, University Hospital Benjamin Franklin, Berlin, Germany; and 10 Medizinischen Klinik III, Hämatologie und Onkologie, Universitätsmedizin Mannheim, Mannheim, Germany

The diagnosis of myelodysplastic syndrome (MDS) currently relies primarily on the morphologic assessment of the patient's bone marrow and peripheral blood cells. Moreover, prognostic scoring systems rely on observer-dependent assessments of blast percentage and dysplasia. Gene expression profiling could enhance current diagnostic and prognostic systems by providing a set of standardized, objective gene signatures. Within the Microarray Innovations in LEukemia study, a diagnostic classification model was investigated to distinguish the distinct subclasses of pediatric and adult leukemia, as well as MDS. Overall, the accuracy of the diagnostic classification model for subtyping leukemia was approximately 93%, but this was not reflected for the MDS samples giving only approximately 50% accuracy. Discordant samples of MDS were classified either into acute myeloid leukemia (AML) or "none-of-the-targets" (neither leukemia nor MDS) categories. To clarify the discordant results, all submitted 174 MDS samples were externally reviewed, although this did not improve the molecular classification results. However, a significant correlation was noted between the AML and "none-of-the-targets" categories and prognosis, leading to a prognostic classification model to predict for time-dependent probability of leukemic transformation. The prognostic classification model accurately discriminated patients with a rapid transformation to AML within 18 months from those with more indolent disease.


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A. Tefferi and J. W. Vardiman
Myelodysplastic Syndromes
N. Engl. J. Med., November 5, 2009; 361(19): 1872 - 1885.
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