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 DöhnerPeter J. Campbell, Alan K. Burnett, Michael Dennis, Nigel H. Russell, Sean M. Devlin, Brian J.P. Huntly, Elli Papaemmanuil*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

84 Citations (Scopus)

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.

Original languageEnglish
Article number4622
JournalNature Communications
Volume13
Issue number1
Early online date8 Aug 2022
DOIs
Publication statusPublished - Dec 2022

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