Prognostic classification of patients with acute lymphoblastic leukemia by using gene copy number profiles identified from array-based comparative genomic hybridization data.

ABSTRACT

The development of risk-adapted therapy has improved the treatment results of acute lymphoblastic leukemia (ALL) especially in children. However, more accurate risk classifiers are warranted. In this study we aimed at defining a prognostic classifier based on DNA copy number alterations of adolescent and young adult (AYA) (10-25 yrs) ALL patients (n=60) determined by microarray CGH and the relapse status of the patients. As a result of prognostic model identification procedure, we got a model of four genes BAK1, CDKN2C, GSTM1, and MT1F, the copy number profile combinations of which differentiated AYA ALL patients at diagnosis depending on their risk of relapse. The performance of the model was poorer on other age groups. We suggest that this kind of approach produces models simple and accurate enough for potential use in ALL routine classification.