Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Transcription profiling of human 164 MDS, 202 AML and 69 non-leukemia bone marrow samples to develop a gene array prediction of AML transformation in MDSm subset of MILE study data


ABSTRACT: Microarray-based classifiers and prognosis models identify subgroups with distinct clinical outcomes and high risk of AML transformation of myelodysplastic syndrome (MDS); An array-based Diagnostic Classifier (DC) model, developed for and evaluated during the MILE study, correctly identified ~50% of the unfractionated MDS specimens submitted to the study; predictions for the other samples were split between “none-of-the-targets” classes and AML signatures, but this distinction also reflected clinical outcome in terms of time to AML transformation. Furthermore, an improved Prognostic Classifier (PC) model was developed that correlated with both time to AML transformation and overall survival. Experiment Overall Design: 164 MDS, 202 AML and 69 non-leukemia bone marrow samples were hybridized to Affymetrix HG-U133 Plus 2.0 GeneChips. Experiment Overall Design: This dataset is a subset of the MILE Study (Microarray Innovations In LEukemia) program, headed by the European Leukemia Network (ELN) and sponsored by Roche Molecular Systems, Inc.

ORGANISM(S): Homo sapiens

SUBMITTER: Wei-Min Liu 

PROVIDER: E-GEOD-15061 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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

Mills Ken I KI   Kohlmann Alexander A   Williams P Mickey PM   Wieczorek Lothar L   Liu Wei-min WM   Li Rachel R   Wei Wen W   Bowen David T DT   Loeffler Helmut H   Hernandez Jesus M JM   Hofmann Wolf-Karsten WK   Haferlach Torsten T  

Blood 20090514 5


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 m  ...[more]

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