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Unified classification and risk-stratification in Acute Myeloid Leukemia.
Tazi, Yanis; Arango-Ossa, Juan E; Zhou, Yangyu; Bernard, Elsa; Thomas, Ian; Gilkes, Amanda; Freeman, Sylvie; Pradat, Yoann; Johnson, Sean J; Hills, Robert; Dillon, Richard; Levine, Max F; Leongamornlert, Daniel; Butler, Adam; Ganser, Arnold; Bullinger, Lars; Döhner, Konstanze; Ottmann, Oliver; Adams, Richard; Döhner, Hartmut; Campbell, Peter J; Burnett, Alan K; Dennis, Michael; Russell, Nigel H; Devlin, Sean M; Huntly, Brian J P; Papaemmanuil, Elli.
Afiliação
  • Tazi Y; Computational Oncology Service, Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Arango-Ossa JE; Center for Hematologic Malignancies, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Zhou Y; Tri-Institutional Computational Biology and Medicine PhD Program, Weill Cornell Medicine of Cornell University and Rockefeller University, New York, NY, USA.
  • Bernard E; The Rockefeller University, New York, NY, USA.
  • Thomas I; Computational Oncology Service, Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Gilkes A; Center for Hematologic Malignancies, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Freeman S; Computational Oncology Service, Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Pradat Y; Center for Hematologic Malignancies, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Johnson SJ; Computational Oncology Service, Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Hills R; Center for Hematologic Malignancies, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Dillon R; Centre for Trials Research, School of Medicine, Cardiff University, Cardiff, UK.
  • Levine MF; Department of Haematology, School of Medicine, Cardiff University, Cardiff, UK.
  • Leongamornlert D; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK.
  • Butler A; Computational Oncology Service, Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Ganser A; Centre for Trials Research, School of Medicine, Cardiff University, Cardiff, UK.
  • Bullinger L; Nuffield Department of Population Health, University of Oxford, Oxford, UK.
  • Döhner K; Department of Medical and Molecular Genetics, King's College, London, UK.
  • Ottmann O; Computational Oncology Service, Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Adams R; Cancer, Ageing and Somatic Mutation Programme, Wellcome Sanger Institute, Hinxton, UK.
  • Döhner H; Cancer, Ageing and Somatic Mutation Programme, Wellcome Sanger Institute, Hinxton, UK.
  • Campbell PJ; Department of Hematology, Hemostasis, Oncology, and Stem Cell Transplantation, Hannover Medical School, Hannover, Germany.
  • Burnett AK; Department of Hematology, Oncology, and Tumorimmunology, Campus Virchow Klinikum, Berlin, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
  • Dennis M; Department of Internal Medicine III, Ulm University, Ulm, Germany.
  • Russell NH; Department of Haematology, School of Medicine, Cardiff University, Cardiff, UK.
  • Devlin SM; Centre for Trials Research, School of Medicine, Cardiff University, Cardiff, UK.
  • Huntly BJP; Department of Internal Medicine III, Ulm University, Ulm, Germany.
  • Papaemmanuil E; Cancer, Ageing and Somatic Mutation Programme, Wellcome Sanger Institute, Hinxton, UK.
Nat Commun ; 13(1): 4622, 2022 08 08.
Article em En | MEDLINE | ID: mdl-35941135
ABSTRACT
Clinical recommendations for Acute Myeloid Leukemia (AML) classification and risk-stratification remain heavily reliant on cytogenetic findings at diagnosis, which are present in <50% of patients. Using comprehensive molecular profiling data from 3,653 patients we characterize and validate 16 molecular classes describing 100% of AML patients. Each class represents diverse biological AML subgroups, and is associated with distinct clinical presentation, likelihood of response to induction chemotherapy, risk of relapse and death over time. Secondary AML-2, emerges as the second largest class (24%), associates with high-risk disease, poor prognosis irrespective of flow Minimal Residual Disease (MRD) negativity, and derives significant benefit from transplantation. Guided by class membership we derive a 3-tier risk-stratification score that re-stratifies 26% of patients as compared to standard of care. This results in a unified framework for disease classification and risk-stratification in AML that relies on information from cytogenetics and 32 genes. Last, we develop an open-access patient-tailored clinical decision support tool.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Leucemia Mieloide Aguda Tipo de estudo: Diagnostic_studies / Etiology_studies / Guideline / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Leucemia Mieloide Aguda Tipo de estudo: Diagnostic_studies / Etiology_studies / Guideline / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article