Recent reports support a possible future application of gene expression profiling for the diagnosis of leukemias. However, the robustness of subtype-specific gene expression signatures has to be proven on independent patient samples. Here, we present gene expression data of 34 adult acute lymphoblastic leukemia (ALL) patients (Affymetrix U133A microarrays). Support Vector Machines (SVMs) were applied to stratify our samples based on given gene lists reported to predict MLL, BCR-ABL, and T-ALL, as well as MLL and non-MLL gene rearrangement positive pediatric ALL. In addition, seven other B-precursor ALL cases not bearing t(9;22) or t(11q23)/MLL chromosomal aberrations were analyzed. Using top differentially expressed genes, hierarchical cluster and principal component analyses demonstrate that the genetically more heterogeneous B-precursor ALL samples intercalate with BCR-ABL-positive cases, but were clearly distinct from T-ALL and MLL profiles. Similar expression signatures were observed for both heterogeneous B-precursor ALL and for BCR-ABL-positive cases. As an unrelated laboratory, we demonstrate that gene signatures defined for childhood ALL were also capable of stratifying distinct subtypes in our cohort of adult ALL patients. As such, previously reported gene expression patterns identified by microarray technology are validated and confirmed on truly independent leukemia patient samples.