Stratification of acute myeloid leukemia based on gene expression profiles

Abstract

Acute myeloid leukemia (AML) is characterized by clonal growth of immature leukemic blasts and develops either de novo or secondarily to anticancer treatment or to other hematologic disorders. Given that the current classification of AML, which is based on blast karyotype and morphology, is not sufficiently robust to predict the prognosis of each affected individual, new stratification schemes that are of better prognostic value are needed. Global profiling of gene expression in AML blasts has the potential both to identify a small number of genes whose expression is associated with clinical outcome and to provide insight into the molecular pathogenesis of this condition. Emerging genomics tools, especially DNA microarray analysis, have been applied in attempts to isolate new molecular markers for the differential diagnosis of AML and to identify genes that contribute to leukemogenesis. Progress in bioinformatics has also yielded means with which to classify patients according to clinical parameters such as long-term prognosis. The application of such analysis to large sets of gene expression data has begun to provide the basis for a new AML classification that is more powerful with regard to prediction of prognosis.