Integrative analysis of type-I and type-II aberrations underscores the genetic heterogeneity of pediatric acute myeloid leukemia
Abstract
We studied the different genetic aberrations, their associations and their impact on prognosis in a large pediatric acute myeloid leukemia series (n=506). Karyotypes were studied, and hotspot regions of NPM1, CEPBA, MLL, WT1, FLT3, N-RAS, K-RAS, PTPN11 and KIT were screened for mutations of available samples.
The mutational status of all type-I and type-II aberrations was available in 330 and 263 cases, respectively. Survival analysis was performed in a subset (n=385) treated on consecutive acute myeloid leukemia Berlin-Frankfurt-Munster Study Group and Dutch Childhood Oncology Group treatment protocols.
Genetic aberrations were associated with specific clinical characteristics, e. g. significantly higher diagnostic white blood cell counts in MLL-rearranged, WT1-mutated and FLT3-ITD-positive acute myeloid leukemia. Furthermore, there was a significant difference in the distribution of these aberrations between children below and above the age of two years.
Non-random associations, e. g. KIT mutations with core-binding factor acute myeloid leukemia, and FLT3-ITD with t(15;17)(q22;q21), NPM1- and WT1-mutated acute myeloid leukemia, respectively, were observed.
Multivariate analysis revealed a 'favorable karyotype', i.e. t(15;17)(q22;q21), t(8;21)(q22;q22) and inv(16)(p13q22)/t(16;16)(p13;q22). NPM1 and CEBPA double mutations were independent factors for favorable event-free survival.
WT1 mutations combined with FLT3-ITD showed the worst outcome for 5-year overall survival (22 +/- 14%) and 5-year event-free survival (20 +/- 13%), although it was not an independent factor in multivariate analysis. Integrative analysis of type-I and type-II aberrations provides an insight into the frequencies, non-random associations and prognostic impact of the various aberrations, reflecting the heterogeneity of pediatric AML.
These aberrations are likely to guide the stratification of pediatric AML and may direct the development of targeted therapies.