Purpose: To analyze the frequency and associations with prognostic markers and outcome of mutations in IDH genes encoding isocitrate dehydrogenases in adult de novo cytogenetically normal acute myeloid leukemia (CN-AML). Patients and Methods: Diagnostic bone marrow or blood samples from 358 patients were analyzed for IDH1 and IDH2 mutations by DNA polymerase chain reaction amplification/sequencing. FLT3, NPM1, CEBPA, WT1, and MLL mutational analyses and gene- and microRNA-expression profiling were performed centrally. Results: IDH mutations were found in 33% of the patients. IDH1 mutations were detected in 49 patients (14%; 47 with R132). IDH2 mutations, previously unreported in AML, were detected in 69 patients (19%; 13 with R172 and 56 with R140). R172 IDH2 mutations were mutually exclusive with all other prognostic mutations analyzed. Younger age (< 60 years), molecular low-risk (NPM1-mutated/FLT3-internal tandem duplication–negative) IDH1-mutated patients had shorter disease-free survival than molecular low-risk IDH1/IDH2-wild-type (wt) patients (P = .046). R172 IDH2-mutated patients had lower complete remission rates than IDH1/IDH2wt patients (P = .007). Distinctive microarray gene- and microRNA-expression profiles accurately predicted R172 IDH2 mutations. The highest expressed gene and microRNAs in R172 IDH2-mutated patients compared with the IDH1/IDH2wt patients were APP (previously associated with complex karyotype AML) and miR-1 and miR-133 (involved in embryonal stem-cell differentiation), respectively. Conclusion: IDH1 and IDH2 mutations are recurrent in CN-AML and have an unfavorable impact on outcome. The R172 IDH2 mutations, previously unreported in AML, characterize a novel subset of CN-AML patients lacking other prognostic mutations and associate with unique gene- and microRNA-expression profiles that may lead to the discovery of novel, therapeutically targetable leukemogenic mechanisms.

The clinical and prognostic relevance of many recently identified driver gene mutations in adult acute myeloid leukemia (AML) is poorly defined. We sequenced the coding regions or hotspot areas of 68 recurrently mutated genes in a cohort of 664 patients aged 18 to 86 years treated on 2 phase 3 trials of the German AML Cooperative Group (AMLCG). The median number of 4 mutations per patient varied according to cytogenetic subgroup, age, and history of previous hematologic disorder or antineoplastic therapy. We found patterns of significantly comutated driver genes suggesting functional synergism. Conversely, we identified 8 virtually nonoverlapping patient subgroups, jointly comprising 78% of AML patients, that are defined by mutually exclusive genetic alterations. These subgroups, likely representing distinct underlying pathways of leukemogenesis, show widely divergent outcomes. Furthermore, we provide detailed information on associations between gene mutations, clinical patient characteristics, and therapeutic outcomes in this large cohort of uniformly treated AML patients. In multivariate analyses including a comprehensive set of molecular and clinical variables, we identified DNMT3A and RUNX1 mutations as important predictors of shorter overall survival (OS) in AML patients <60 years, and particularly in those with intermediate-risk cytogenetics. NPM1 mutations in the absence of FLT3-ITD, mutated TP53, and biallelic CEBPA mutations were identified as important molecular prognosticators of OS irrespective of patient age. In summary, our study provides a comprehensive overview of the spectrum, clinical associations, and prognostic relevance of recurrent driver gene mutations in a large cohort representing a broad spectrum and age range of intensively treated AML patients. Key Points We present comprehensive information on genetic driver events in a uniformly treated cohort of 664 adult AML patients aged 18 to 86 years. Mutations in NPM1, FLT3, CEBPA, TP53, and, in patients <60 years, DNMT3A and RUNX1, are the most important molecular risk factors in AML.

Patients with cytogenetically normal acute myeloid leukemia (CN-AML) show heterogeneous treatment outcomes. We used gene-expression profiling to develop a gene signature that predicts overall survival (OS) in CN-AML. Based on data from 163 patients treated in the German AMLCG 1999 trial and analyzed on oligonucleotide microarrays, we used supervised principal component analysis to identify 86 probe sets (representing 66 different genes), which correlated with OS, and defined a prognostic score based on this signature. When applied to an independent cohort of 79 CN-AML patients, this continuous score remained a significant predictor for OS (hazard ratio [HR], 1.85; P = .002), event-free survival (HR = 1.73; P = .001), and relapse-free survival (HR = 1.76; P = .025). It kept its prognostic value in multivariate analyses adjusting for age, FLT3 ITD, and NPM1 status. In a validation cohort of 64 CN-AML patients treated on CALGB study 9621, the score also predicted OS (HR = 4.11; P < .001), event-free survival (HR = 2.90; P < .001), and relapse-free survival (HR = 3.14, P < .001) and retained its significance in a multivariate model for OS. In summary, we present a novel gene-expression signature that offers additional prognostic information for patients with CN-AML.

Purpose: To evaluate the prognostic significance of the international European LeukemiaNet (ELN) guidelines for reporting genetic alterations in acute myeloid leukemia (AML). Patients and Methods: We analyzed 1,550 adults with primary AML, treated on Cancer and Leukemia Group B first-line trials, who had pretreatment cytogenetics and, for cytogenetically normal patients, mutational status of NPM1, CEBPA, and FLT3 available. We compared complete remission (CR) rates, disease-free survival (DFS), and overall survival (OS) among patients classified into the four ELN genetic groups (favorable, intermediate-I, intermediate-II, adverse) separately for 818 younger (age < 60 years) and 732 older (age ≥ 60 years) patients. Results: The percentages of younger versus older patients in the favorable (41% v 20%; P < .001), intermediate-II (19% v 30%; P < .001), and adverse (22% v 31%; P < .001) genetic groups differed. The favorable group had the best and the adverse group the worst CR rates, DFS, and OS in both age groups. Both intermediate groups had significantly worse outcomes than the favorable but better than the adverse group. Intermediate-I and intermediate-II groups in older patients had similar outcomes, whereas the intermediate-II group in younger patients had better OS but not better CR rates or DFS than the intermediate-I group. The prognostic significance of ELN classification was confirmed by multivariable analyses. For each ELN group, older patients had worse outcomes than younger patients. Conclusion: The ELN classification clearly separates the genetic groups by outcome, supporting its use for risk stratification in clinical trials. Because they have different proportions of genetic alterations and outcomes, younger and older patients should be reported separately when using the ELN classification.