Krali O, Palle J, Bäcklin CL, Abrahamsson J, Norén-Nyström U, Hasle H, Jahnukainen K, Jónsson ÓG, Hovland R, Lausen B, Larsson R, Palmqvist L, Staffas A, Zeller B, Nordlund J
Genes 12 (6) 895 [2021-06-10; online 2021-06-10]
Pediatric acute myeloid leukemia (AML) is a heterogeneous disease composed of clinically relevant subtypes defined by recurrent cytogenetic aberrations. The majority of the aberrations used in risk grouping for treatment decisions are extensively studied, but still a large proportion of pediatric AML patients remain cytogenetically undefined and would therefore benefit from additional molecular investigation. As aberrant epigenetic regulation has been widely observed during leukemogenesis, we hypothesized that DNA methylation signatures could be used to predict molecular subtypes and identify signatures with prognostic impact in AML. To study genome-wide DNA methylation, we analyzed 123 diagnostic and 19 relapse AML samples on Illumina 450k DNA methylation arrays. We designed and validated DNA methylation-based classifiers for AML cytogenetic subtype, resulting in an overall test accuracy of 91%. Furthermore, we identified methylation signatures associated with outcome in t(8;21)/RUNX1-RUNX1T1, normal karyotype, and MLL/KMT2A-rearranged subgroups (p < 0.01). Overall, these results further underscore the clinical value of DNA methylation analysis in AML.
Bioinformatics Support for Computational Resources [Service]
NGI Uppsala (SNP&SEQ Technology Platform) [Collaborative]
National Genomics Infrastructure [Collaborative]
PubMed 34200630
DOI 10.3390/genes12060895
Crossref 10.3390/genes12060895
pii: genes12060895
pmc: PMC8229099