Marcucci G, Yan P, Maharry K, Frankhouser D, Nicolet D, Metzeler KH, Kohlschmidt J, Mrózek K, Wu YZ, Bucci D, Curfman JP, Whitman SP, Eisfeld AK, Mendler JH, Schwind S, Becker H, Bär C, Carroll AJ, Baer MR, Wetzler M, Carter TH, Powell BL, Kolitz JE, Byrd
PURPOSE: Molecular risk stratification of acute myeloid leukemia (AML) is largely based on genetic markers. However, epigenetic changes, including DNA methylation, deregulate gene expression and may also have prognostic impact. We evaluated the clinical relevance of integrating DNA methylation and genetic information in AML. METHODS: Next-generation sequencing analysis of methylated DNA identified differentially methylated regions (DMRs) associated with prognostic mutations in older (≥ 60 years) cytogenetically normal (CN) patients with AML (n = 134). Genes with promoter DMRs and expression levels significantly associated with outcome were used to compute a prognostic gene expression weighted summary score that was tested and validated in four independent patient sets (n = 355). RESULTS: In the training set, we identified seven genes (CD34, RHOC, SCRN1, F2RL1, FAM92A1, MIR155HG, and VWA8) with promoter DMRs and expression associated with overall survival (OS; P ≤ .001). Each gene had high DMR methylation and lower expression, which were associated with better outcome. A weighted summary expression score of the seven gene expression levels was computed. A low score was associated with a higher complete remission (CR) rate and longer disease-free survival and OS (P < .001 for all end points). This was validated in multivariable models and in two younger (< 60 years) and two older independent sets of patients with CN-AML. Considering the seven genes individually, the fewer the genes with high expression, the better the outcome. Younger and older patients with no genes or one gene with high expression had the best outcomes (CR rate, 94% and 87%, respectively; 3-year OS, 80% and 42%, respectively). CONCLUSION: A seven-gene score encompassing epigenetic and genetic prognostic information identifies novel AML subsets that are meaningful for treatment guidance.