Journal of clinical oncology : official journal of the American Society of Clinical Oncology

Prognostic importance of MN1 transcript levels, and biologic insights from MN1-associated gene and microRNA expression signatures in cytogenetically normal acute myeloid leukemia: a cancer and leukemia group B study.

PMID 19451432


PURPOSE To determine the prognostic importance of the meningioma 1 (MN1) gene expression levels in the context of other predictive molecular markers, and to derive MN1 associated gene- and microRNA-expression profiles in cytogenetically normal acute myeloid leukemia (CN-AML). PATIENTS AND METHODS MN1 expression was measured in 119 untreated primary CN-AML adults younger than 60 years by real-time reverse-transcriptase polymerase chain reaction. Patients were also tested for FLT3, NPM1, CEBPA, and WT1 mutations, MLL partial tandem duplications, and BAALC and ERG expression. Gene- and microRNA-expression profiles were attained by performing genome-wide microarray assays. Patients were intensively treated on two first-line Cancer and Leukemia Group B clinical trials. Results Higher MN1 expression associated with NPM1 wild-type (P < .001), increased BAALC expression (P = .004), and less extramedullary involvement (P = .01). In multivariable analyses, higher MN1 expression associated with a lower complete remission rate (P = .005) after adjustment for WBC; shorter disease-free survival (P = .01) after adjustment for WT1 mutations, FLT3 internal tandem duplications (FLT3-ITD), and high ERG expression; and shorter survival (P = .04) after adjustment for WT1 and NPM1 mutations, FLT3-ITD, and WBC. Gene- and microRNA-expression profiles suggested that high MN1 expressers share features with high BAALC expressers and patients with wild-type NPM1. Higher MN1 expression also appears to be associated with genes and microRNAs that are active in aberrant macrophage/monocytoid function and differentiation. CONCLUSION MN1 expression independently predicts outcome in CN-AML patients. The MN1 gene- and microRNA-expression signatures suggest biologic features that could be exploited as therapeutic targets.