Association between mutation clearance after induction therapy and outcomes in acute myeloid leukemia

Abstract

Importance: Tests that predict outcomes for patients with acutemyeloid 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 sequencingwas 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 Required]. 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.