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Li, Z.* ; Herold, T. ; He, C.* ; Valk, P.J.* ; Chen, P.* ; Jurinovic, V.* ; Mansmann, U.* ; Radmacher, M.D.* ; Maharry, K.S.* ; Sun, M.* ; Yang, X.* ; Huang, H.* ; Jiang, X.* ; Sauerland, M.C.* ; Büchner, T.* ; Hiddemann, W. ; Elkahloun, A.* ; Neilly, M.B.* ; Zhang, Y.* ; Larson, R.A.* ; Le Beau, M.M.* ; Caligiuri, M.A.* ; Döhner, K.* ; Bullinger, L.* ; Liu, P.P.* ; Delwel, R.* ; Marcucci, G.* ; Lowenberg, B.* ; Bloomfield, C.D.* ; Rowley, J.D.* ; Bohlander, S.K. ; Chen, J.*

Identification of a 24-gene prognostic signature that improves the European LeukemiaNet risk classification of acute myeloid leukemia: An international collaborative study.

J. Clin. Oncol. 31, 1172-1181 (2013)
Verlagsversion Volltext DOI PMC
Free by publisher
PURPOSE: To identify a robust prognostic gene expression signature as an independent predictor of survival of patients with acute myeloid leukemia (AML) and use it to improve established risk classification. PATIENTS AND METHODS: Four independent sets totaling 499 patients with AML carrying various cytogenetic and molecular abnormalities were used as training sets. Two independent patient sets composed of 825 patients were used as validation sets. Notably, patients from different sets were treated with different protocols, and their gene expression profiles were derived using different microarray platforms. Cox regression and Kaplan-Meier methods were used for survival analyses. RESULTS: A prognostic signature composed of 24 genes was derived from a meta-analysis of Cox regression values of each gene across the four training sets. In multivariable models, a higher sum value of the 24-gene signature was an independent predictor of shorter overall (OS) and event-free survival (EFS) in both training and validation sets (P < .01). Moreover, this signature could substantially improve the European LeukemiaNet (ELN) risk classification of AML, and patients in three new risk groups classified by the integrated risk classification showed significantly (P < .001) distinct OS and EFS. CONCLUSION: Despite different treatment protocols applied to patients and use of different microarray platforms for expression profiling, a common prognostic gene signature was identified as an independent predictor of survival of patients with AML. The integrated risk classification incorporating this gene signature provides a better framework for risk stratification and outcome prediction than the ELN classification.  
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
ISSN (print) / ISBN 0732-183X
e-ISSN 1527-7755
Zeitschrift Journal of Clinical Oncology - JCO
Quellenangaben Band: 31, Heft: 9, Seiten: 1172-1181 Artikelnummer: , Supplement: ,
Verlag American Society of Clinical Oncology
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) CCG Pathogenesis of Acute Myeloid Leukemia (KKG-KPL)