Expression data from pediatric AML patients

Pediatric acute myeloid leukemia (AML) is a heterogeneous disease characterized by non-random genetic aberrations related to outcome. Detecting these aberrations however still lead to failures or false negative results. Therefore, we focused on the potential of gene expression profiles (GEP) to classify pediatric AML. Gene expression microarray data of 237 children with AML were generated and cases were split into a discovery cohort (n=157) and an independent validation cohort (n=80). Next, a double-loop cross validation approach was used to generate a subtype-predictive GEP in the discovery cohort which was then tested for its true predictive value in the independent validation cohort. 237 bone marrow and peripheral blood samples were collected at diagnosis and frozen. They were later thawed and hybridized to Affymetrix U133 Plus 2.0 arrays.