The complexity of interpreting genomic data in patients with acute myeloid leukemia

Acute myeloid leukemia (AML) is a heterogeneous neoplasm characterized by the accumulation of complex genetic alterations responsible for the initiation and progression of the disease. Translating genomic information into clinical practice remained challenging with conflicting results regarding the impact of certain mutations on disease phenotype and overall survival (OS) especially when clinical variables are controlled for when interpreting the result. We sequenced the coding region for 62 genes in 468 patients with secondary AML (sAML) and primary AML (pAML). Overall, mutations in FLT3, DNMT3A, NPM1 and IDH2 were more specific for pAML whereas UTAF1, STAG2, BCORL1, BCOR, EZH2, JAK2, CBL, PRPF8, SF3B1, ASXL1 and DHX29 were more specific for sAML. However, in multivariate analysis that included clinical variables, only FLT3 and DNMT3A remained specific for pAML and EZH2, BCOR, SF3B1 and ASXL1 for sAML. When the impact of mutations on OS was evaluated in the entire cohort, mutations in DNMT3A, PRPF8, ASXL1, CBL EZH2 and TP53 had a negative impact on OS; no mutation impacted OS favorably; however, in a cox multivariate analysis that included clinical data, mutations in DNMT3A, ASXL1, CBL, EZH2 and TP53 became significant. Thus, controlling for clinical variables is important when interpreting genomic data in AML.