Repository logo
 

Unified classification and risk-stratification in Acute Myeloid Leukemia.

Published version
Peer-reviewed

Type

Article

Change log

Authors

Arango-Ossa, Juan E 
Zhou, Yangyu 
Thomas, Ian 

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.

Description

Keywords

Humans, Cytogenetic Analysis, Flow Cytometry, Induction Chemotherapy, Leukemia, Myeloid, Acute, Neoplasm, Residual

Journal Title

Nat Commun

Conference Name

Journal ISSN

2041-1723
2041-1723

Volume Title

13

Publisher

Springer Science and Business Media LLC
Sponsorship
European Research Council (647685)
Cancer Research UK (25508)
Kay Kendall Leukaemia Fund (KKL1243)
Wellcome Trust (203151/Z/16/Z)
Cancer Research UK (A25117)
Cambridge University Hospitals NHS Foundation Trust (CUH) (146281)
Wellcome Trust (205254/Z/16/Z)
Medical Research Council (MR/R009708/1)
National Institute for Health and Care Research (IS-BRC-1215-20014)
Medical Research Council (MC_PC_17230)