Cited by 4,350Acute Myeloid Leukemia ResearchRetinoids in leukemia and cellular processesCancer Genomics and Diagnostics

The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.

Genomic Classification and Prognosis in Acute Myeloid Leukemia

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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.).

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Metadata

Authors
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., & Campbell, P. J.
Affiliations
  • European Bioinformatics Institute (GB)
  • Wellcome Sanger Institute (GB)
Venue
New England Journal of Medicine
Published
2016-06-09
Volume
374
Issue
23
Pages
2209-2221
ISSN
  • 0028-4793 (ISSN-L)
  • 1533-4406
OpenAlex
W2419140434
Cited by
4,350
References
40
Citations by year
2026: 345 · 2025: 403 · 2024: 468 · 2023: 460 · 2022: 551 · 2021: 583 · 2020: 481 · 2019: 415 · 2018: 286 · 2017: 282 · 2016: 63
FWCI
331.83
Type
journal article
Language
en
Open access
Locations
  • New England Journal of Medicine (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) (submittedVersion, other-oa)
  • MDC Repository (Max-Delbrueck-Center for Molecular Medicine) (submittedVersion)
  • Lirias (KU Leuven) (submittedVersion)
Funders
  • Wellcome Trust (103858/Z/14/Z, 105104, 077012/Z/05/Z, 077012, 103858, 105104/Z/14/Z, WT088340MA)
  • Francis Crick Institute (10202)
Topics
  • Health Sciences › Medicine › Hematology › Acute Myeloid Leukemia Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Retinoids in leukemia and cellular processes
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
Keywords
acute myeloid leukemia, driver mutations, genomic subgroups, prognostic stratification, TP53 mutation, aneuploidy, NPM1 mutation, IDH2 mutation, gene-gene interaction, co-mutation patterns, overall survival, intensive treatment
MeSH terms
DNA Methyltransferase 3A, Nucleophosmin, Adult, DNA (Cytosine-5-)-Methyltransferases, DNA Mutational Analysis, Epistasis, Genetic, Genotype, Humans, Middle Aged, Mutation, Nuclear Proteins, Prognosis, Prospective Studies, RNA Splicing, Leukemia, Myeloid, Acute, Proportional Hazards Models, Survival Analysis, Intracellular Signaling Peptides and Proteins, Gene Fusion

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