Genomic classification and prognosis in acute myeloid leukemia

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Item Type:	Article
Title:	Genomic classification and prognosis in acute myeloid leukemia
Creators Name:	Papaemmanuil, E., Gerstung, M., Bullinger, L., Gaidzik, V.I., Paschka, P., Roberts, N.D., Potter, N.E., Heuser, M., Thol, F., Bolli, N., Gundem, G., Van Loo, P., Martincorena, I., Ganly, P., Mudie, L., McLaren, S., O'Meara, S., Raine, K., Jones, D.R., Teague, J.W., Butler, A.P., Greaves, M.F., Ganser, A., Döhner, K., Schlenk, R.F., Döhner, H. and Campbell, P.J.
Abstract:	BACKGROUND: Recent studies have provided a detailed census of genes that are mutated in acute myeloid leukemia (AML). Our next challenge is to understand how this genetic diversity defines the pathophysiology of AML and informs clinical practice. METHODS: We enrolled a total of 1540 patients in three prospective trials of intensive therapy. Combining driver mutations in 111 cancer genes with cytogenetic and clinical data, we defined AML genomic subgroups and their relevance to clinical outcomes. RESULTS: We identified 5234 driver mutations across 76 genes or genomic regions, with 2 or more drivers identified in 86% of the patients. Patterns of co-mutation compartmentalized the cohort into 11 classes, each with distinct diagnostic features and clinical outcomes. In addition to currently defined AML subgroups, three heterogeneous genomic categories emerged: AML with mutations in genes encoding chromatin, RNA-splicing regulators, or both (in 18% of patients); AML with TP53 mutations, chromosomal aneuploidies, or both (in 13%); and, provisionally, AML with IDH2R172 mutations (in 1%). Patients with chromatin–spliceosome and TP53–aneuploidy AML had poor outcomes, with the various class-defining mutations contributing independently and additively to the outcome. In addition to class-defining lesions, other co-occurring driver mutations also had a substantial effect on overall survival. The prognostic effects of individual mutations were often significantly altered by the presence or absence of other driver mutations. Such gene–gene interactions were especially pronounced for NPM1-mutated AML, in which patterns of co-mutation identified groups with a favorable or adverse prognosis. These predictions require validation in prospective clinical trials. CONCLUSIONS: The driver landscape in AML reveals distinct molecular subgroups that reflect discrete paths in the evolution of AML, informing disease classification and prognostic stratification.
Keywords:	Acute Myeloid Leukemia, DNA (Cytosine-5-)-Methyltransferases, DNA Methyltransferase 3A, DNA Mutational Analysis, Genetic Epistasis, Gene Fusion, Genotype, Intracellular Signaling Peptides and Proteins, Mutation, Nuclear Proteins, Nucleophosmin, Prognosis, Proportional Hazards Models, Prospective Studies, RNA Splicing, Survival Analysis
Source:	New England Journal of Medicine
ISSN:	0028-4793
Publisher:	Massachusetts Medical Society
Volume:	374
Number:	23
Page Range:	2209-2221
Date:	12 July 2016
Additional Information:	Copyright © 2016 Massachusetts Medical Society. All rights reserved.
Official Publication:	https://doi.org/10.1056/NEJMoa1516192
External Fulltext:	View full text on PubMed Central
PubMed:	View item in PubMed

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