Abstract
7534 Background: Conventional cytogenetics remain one of the most important prognostic factors in acute myeloid leukemia (AML), though 50-60% of patients (pts) have normal karyotype (NK), conventionally classified as intermediate-risk, and have very heterogeneous outcomes. A fraction of mutations such as NPM1, FLT3-ITD, and CEBPa can improve risk stratification for some pts but underestimate the molecular complexity and interactions between these genes and others. Methods: Genomic and clinical data of 2,793 primary AML (pAML) pts were analyzed. A panel of 35 genes that are commonly mutated in AML and myeloid malignancies and have shown to impact OS was included. Correlation of each mutation with others and their impact on OS were evaluated. OS was calculated from the date of diagnosis to date of death or last follow-up. Results: Of 2,793 pts with pAML, 1,352 (48%) had NK and were included in the final analysis. The median age was 55 years (range, 18-93). The median number of mutations/sample was 3 (range, 0-7). The most commonly mutated genes were: NPM1 (49%), DNMT3A (37%), FLT3-ITD (24%), CEBPa (19%), TET2 (17%), IDH2 (17%), and RUNX1 (15%). In univariate Cox regression analysis, mutations in NPM1 (HR 0.81, p =0.008), and CEBPa (single mutant, HR 0.8, double mutant, HR 0.69, p< 0.001, respectively) were associated with longer OS, while mutations in DNMT3a (HR 1.26, p =0.003), FLT3-ITD (HR 1.49, p< 0.001), TET2 (HR 1.26, p =0.02), RUNX1 (HR 1.36, p =0.003), SRSF2 (HR 1.58, p <0.001), IDH1 (HR 1.29, p <0.001), and ASXL1 (HR 1.89, p <0.001) were associated with shorter OS. A total of 67% of pts had NPM1, DNMT3A, and FLT3-ITD mutated alone or in combination with each other. The median OS for pts with NMP1Mut/ DNMT3AWT/FLT3-ITDWT was 99.1 months(m), NMP1Mut/DNMT3AMut /FLT3-ITDWT 54.8m, NMP1Mu t/DNMT3AWT/FLT3-ITDMut 42.3m, NMP1Mut/DNMT3AMut/FLT3-ITDMut 13.4m, NMP1WT/DNMT3AMut/FLT3-ITDMut 13.1m, and NMP1WT/DNMT3AWT/FLT3-ITDWT (triple negative) 32.7m. The median OS for pts with 0-2 mutations/sample was 59.3m, compared to 34.1m for pts with 3-4 mutations, and 16.1m for pts with > 5 mutations ( p< 0.001). Conclusions: We propose a simplified and robust approach to risk stratify AML pts with NK based on the mutational status of NPM1, DNMT3A, FLT3-ITD (alone or in combination with each other), CEBPa, and the number of mutations/sample.
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