Nature Communications (Aug 2022)
Unified classification and risk-stratification in Acute Myeloid Leukemia
- Yanis Tazi,
- Juan E. Arango-Ossa,
- Yangyu Zhou,
- Elsa Bernard,
- Ian Thomas,
- Amanda Gilkes,
- Sylvie Freeman,
- Yoann Pradat,
- Sean J. Johnson,
- Robert Hills,
- Richard Dillon,
- Max F. Levine,
- Daniel Leongamornlert,
- Adam Butler,
- Arnold Ganser,
- Lars Bullinger,
- Konstanze Döhner,
- Oliver Ottmann,
- Richard Adams,
- Hartmut Döhner,
- Peter J. Campbell,
- Alan K. Burnett,
- Michael Dennis,
- Nigel H. Russell,
- Sean M. Devlin,
- Brian J. P. Huntly,
- Elli Papaemmanuil
Affiliations
- Yanis Tazi
- Computational Oncology Service, Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center
- Juan E. Arango-Ossa
- Computational Oncology Service, Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center
- Yangyu Zhou
- Computational Oncology Service, Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center
- Elsa Bernard
- Computational Oncology Service, Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center
- Ian Thomas
- Centre for Trials Research, School of Medicine, Cardiff University
- Amanda Gilkes
- Department of Haematology, School of Medicine, Cardiff University
- Sylvie Freeman
- Institute of Immunology and Immunotherapy, University of Birmingham
- Yoann Pradat
- Computational Oncology Service, Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center
- Sean J. Johnson
- Centre for Trials Research, School of Medicine, Cardiff University
- Robert Hills
- Nuffield Department of Population Health, University of Oxford
- Richard Dillon
- Department of Medical and Molecular Genetics, King’s College
- Max F. Levine
- Computational Oncology Service, Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center
- Daniel Leongamornlert
- Cancer, Ageing and Somatic Mutation Programme, Wellcome Sanger Institute
- Adam Butler
- Cancer, Ageing and Somatic Mutation Programme, Wellcome Sanger Institute
- Arnold Ganser
- Department of Hematology, Hemostasis, Oncology, and Stem Cell Transplantation, Hannover Medical School
- Lars Bullinger
- Department of Hematology, Oncology, and Tumorimmunology, Campus Virchow Klinikum, Berlin, Charité—Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin
- Konstanze Döhner
- Department of Internal Medicine III, Ulm University
- Oliver Ottmann
- Department of Haematology, School of Medicine, Cardiff University
- Richard Adams
- Centre for Trials Research, School of Medicine, Cardiff University
- Hartmut Döhner
- Department of Internal Medicine III, Ulm University
- Peter J. Campbell
- Cancer, Ageing and Somatic Mutation Programme, Wellcome Sanger Institute
- Alan K. Burnett
- Visiting Professor University of Glasgow, formerly Cardiff University
- Michael Dennis
- The Christie NHS Foundation Trust
- Nigel H. Russell
- Department of Haematology, Nottingham University Hospital
- Sean M. Devlin
- Computational Oncology Service, Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center
- Brian J. P. Huntly
- Department of Haematology and Wellcome Trust-MRC Cambridge Stem Cell Institute, University of Cambridge
- Elli Papaemmanuil
- Computational Oncology Service, Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center
- DOI
- https://doi.org/10.1038/s41467-022-32103-8
- Journal volume & issue
-
Vol. 13,
no. 1
pp. 1 – 16
Abstract
Classification and risk-stratification for Acute Myeloid Leukemia (AML) at diagnosis are primarily based on cytogenetics and only a few gene mutations. Here, the authors study the genomic landscape of 3653 AML patients and characterize 16 non-overlapping molecular subgroups of clinical relevance for disease classification and risk prognostication.
