IMPORTANCE: Tests that predict outcomes for patients with acute myeloid leukemia (AML) are imprecise, especially for those with intermediate risk AML. OBJECTIVES: To determine whether genomic approaches can provide novel prognostic information for adult patients with de novo AML. DESIGN, SETTING, AND PARTICIPANTS: Whole-genome or exome sequencing was performed on samples obtained at disease presentation from 71 patients with AML (mean age, 50.8 years) treated with standard induction chemotherapy at a single site starting in March 2002, with follow-up through January 2015. In addition, deep digital sequencing was performed on paired diagnosis and remission samples from 50 patients (including 32 with intermediate-risk AML), approximately 30 days after successful induction therapy. Twenty-five of the 50 were from the cohort of 71 patients, and 25 were new, additional cases. EXPOSURES: Whole-genome or exome sequencing and targeted deep sequencing. Risk of identification based on genetic data. MAIN OUTCOMES AND MEASURES: Mutation patterns (including clearance of leukemia-associated variants after chemotherapy) and their association with event-free survival and overall survival. RESULTS: Analysis of comprehensive genomic data from the 71 patients did not improve outcome assessment over current standard-of-care metrics. In an analysis of 50 patients with both presentation and documented remission samples, 24 (48%) had persistent leukemia-associated mutations in at least 5% of bone marrow cells at remission. The 24 with persistent mutations had significantly reduced event-free and overall survival vs the 26 who cleared all mutations. Patients with intermediate cytogenetic risk profiles had similar findings. [table: see text]. CONCLUSIONS AND RELEVANCE: The detection of persistent leukemia-associated mutations in at least 5% of bone marrow cells in day 30 remission samples was associated with a significantly increased risk of relapse, and reduced overall survival. These data suggest that this genomic approach may improve risk stratification for patients with AML.
Chris Miller, Ph.D., Malachi Griffith, Ph.D., Obi Griffith, Ph.D., Allegra A. Petti, Ph.D., Shamika Ketkar-Kulkarni, Lukas Wartman, Dong Shen, Ph.D., Jasreet Hundal, Gue Su Chang, Ph.D., Robert Fulton, Michelle O'Laughlin, Catrina Fronick, Ryan Demeter, David Larson, Ph.D., Shashikant Kulkarni, Elaine R. Mardis, Ph.D., Richard K. Wilson, Ph.D., Timothy Ley, M.D.