Genetic mutation signature for relapse prediction in normal karyotype acute myeloid leukemia

Abstract

Risk stratification for normal karyotype acute myeloid leukemia (NK-AML) remains unsatisfactory, which is reflected by the high incidence of leukemia relapse. This study aimed to evaluate the role of gene mutations and clinical characterization in predicting the relapse of patients with NK-AML. A prognostic system for NK-AML was constructed. A panel of gene mutations was explored using next-generation sequencing. A nomogram algorithm was used to build a genomic mutation signature (GMS) nomogram (GMSN) model that combines GMS, measurable residual disease, and clinical factors to predict relapse in 347 patients with NK-AML from four centers. Patients in the GMS-high group had a higher 5-year incidence of relapse than those in the GMS-low group (p < 0.001). The 5-year incidence of relapse was also higher in patients in the GMSN-high group than in those in the GMSN-intermediate and -low groups (p < 0.001). The 5-year disease-free survival and overall survival rates were lower in patients in the GMSN-high group than in those in the GMSN-intermediate and -low groups (p < 0.001) as confirmed by training and validation cohorts. This study illustrates the potential of GMSN as a predictor of NK-AML relapse.