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N Engl J Med. 2016 Jun 9;374(23):2209-2221. doi: 10.1056/NEJMoa1516192.

Genomic Classification and Prognosis in Acute Myeloid Leukemia.

Author information

1
Cancer Genome Project, Wellcome Trust Sanger Institute (E.P., M.G., N.D.R., N.B., G.G., P.V.L., I.M., L.M., S.M., S.O., K.R., D.R.J., J.W.T., A.P.B., P.J.C.), and the European Bioinformatics Institute, European Molecular Biology Laboratory (EMBL-EBI) (M.G.), Hinxton, the Centre for Evolution and Cancer, Institute of Cancer Research, London (N.E.P., M.F.G.), and the Department of Haematology, University of Cambridge, Cambridge (N.B.) - all in the United Kingdom; the Departments of Epidemiology and Biostatistics and Cancer Biology, the Center for Molecular Oncology and the Center for Hematologic Malignancies, Memorial Sloan Kettering Cancer Center, New York (E.P.); the Department of Internal Medicine III, Ulm University, Ulm (L.B., V.I.G., P.P., K.D., R.F.S., H.D.), and the Department of Hematology, Hemostasis, Oncology, and Stem Cell Transplantation, Hannover Medical School, Hannover (M.H., F.T., A.G.) - both in Germany; the Division of Hematology, Fondazione IRCCS, Istituto Nazionale dei Tumori, and Department of Oncology and Onco-Hematology, University of Milan, Milan (N.B.); the Department of Human Genetics, University of Leuven, Leuven, Belgium (P.V.L.); and the Department of Pathology, University of Otago, Christchurch, New Zealand (P.G., P.J.C.).
#
Contributed equally

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 IDH2(R172) 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. (Funded by the Wellcome Trust and others; ClinicalTrials.gov number, NCT00146120.).

PMID:
27276561
PMCID:
PMC4979995
DOI:
10.1056/NEJMoa1516192
[Indexed for MEDLINE]
Free PMC Article

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