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    Unified classification and risk-stratification in Acute Myeloid Leukemia

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    Authors
    Tazi, Y.
    Ossa, J. A.
    Zhou, Y. Y.
    Bernard, E.
    Thomas, I.
    Gilkes, A.
    Freeman, S.
    Pradat, Y.
    Johnson, S.
    Hills, R.
    Dillon, R.
    Levine, M.
    Leongamornlert, D.
    Butler, A.
    Ganser, A.
    Bullinger, L.
    Dohner, K.
    Ottmann, O.
    Adams, R.
    Dohner, H.
    Campbell, P.
    Burnett, A.
    Dennis, Michael
    Russell, N.
    Devlin, S.
    Huntly, B.
    Papaemmanuil, E.
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    Affiliation
    Computational Oncology Service, Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY
    Issue Date
    2022
    
    Metadata
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    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.
    Citation
    Tazi Y, Ossa JA, Zhou YY, Bernard E, Thomas I, Gilkes A, et al. Unified classification and risk-stratification in Acute Myeloid Leukemia. Nature communications. 2022 Aug;13(1). PubMed PMID: WOS:000837856500001.
    Journal
    Nature Communications
    URI
    http://hdl.handle.net/10541/625598
    DOI
    10.1038/s41467-022-32103-8
    PubMed ID
    35941135
    Additional Links
    https://dx.doi.org/10.1038/s41467-022-32103-8
    Type
    Article
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.1038/s41467-022-32103-8
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