Abstract
Pediatric acute myeloid leukemia (AML) is a heterogeneous disease with respect to biology as well as outcome. In this study, we investigated whether known biological subgroups of pediatric AML are reflected by a common microRNA (miRNA) expression pattern. We assayed 665 miRNAs on 165 pediatric AML samples. First, unsupervised clustering was performed to identify patient clusters with common miRNA expression profiles. Our analysis unraveled 14 clusters, seven of which had a known (cyto-)genetic denominator. Finally, a robust classifier was constructed to discriminate six molecular aberration groups: 11q23-rearrangements, t(8;21)(q22;q22), inv(16)(p13q22), t(15;17) (q21;q22), NPM1 and CEBPA mutations. The classifier achieved accuracies of 89%, 95%, 95%, 98%, 91% and 96%, respectively. Although lower sensitivities were obtained for the NPM1 and CEBPA (32% and 66%), relatively high sensitivities (84%−94%) were attained for the rest. Specificity was high in all groups (87%−100%). Due to a robust double-loop cross validation procedure employed, the classifier only employed 47 miRNAs to achieve the aforementioned accuracies. To validate the 47 miRNA signatures, we applied them to a publicly available adult AML dataset. Albeit partial overlap of the array platforms and molecular differences between pediatric and adult AML, the signatures performed reasonably well. This corroborates our claim that the identified miRNA signatures are not dominated by sample size bias in the pediatric AML dataset. In conclusion, cytogenetic subtypes of pediatric AML have distinct miRNA expression patterns. Reproducibility of the miRNA signatures in adult dataset suggests that the respective aberrations have a similar biology both in pediatric and adult AML.
Highlights
Pediatric acute myeloid leukemia (AML) patients are stratified into risk categories according to response to induction therapy and genetic abnormalities, as defined in the WHO 2008 classification [1]
We investigated whether known biological subgroups of pediatric AML are reflected by a common microRNA expression pattern
Albeit partial overlap of the array platforms and molecular differences between pediatric and adult AML, the signatures performed reasonably well. This corroborates our claim that the identified miRNA signatures are not dominated by sample size bias in the pediatric AML dataset
Summary
Pediatric AML patients are stratified into risk categories according to response to induction therapy and genetic abnormalities, as defined in the WHO 2008 classification [1]. To further improve patient outcome, biological studies that aim to identify leukemogenic drivers and/or signaling pathways that can be directly targeted are needed. This is necessary as further intensification of chemotherapy may cause higher frequency of early and late side effects, including therapyrelated mortality [5]. Patient outcome may be improved by refining the risk-group classification and identify uniform subgroups utilizing (epi-) genetic and molecular aberrations, which may contribute to the design of targeted therapy [6]. Identification of hallmark aberrations and their accompanying molecular targets for the 15–20% of unclassified pediatric AML patients is the subject of many ongoing biological studies [7]
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