RAS-pathway mutation patterns define epigenetic subclasses in juvenile myelomonocytic leukemia.
Daniel B LipkaTania Witte TobarReka TothJing YangManuel WiesenfarthPeter NoellkeAlexandra FischerDavid BrocksZuguang GuJeongbin ParkBrigitte StrahmMarcin W WlodarskiAyami YoshimiRainer ClausMichael LübbertHauke BuschMelanie BoerriesMark HartmannMaximilian SchönungUmut KilikJens LangsteinJustyna A WierzbinskaCaroline PabstSwati GargAlbert CatalàBarbara De MoerlooseMichael DworzakHenrik HasleFranco LocatelliRiccardo MasettiMarkus SchmuggeOwen SmithJan StaryMarek UssowiczMarry M van den Heuvel-EibrinkYassen AssenovMatthias SchlesnerCharlotte NiemeyerChristian FlothoChristoph PlassPublished in: Nature communications (2017)
Juvenile myelomonocytic leukemia (JMML) is an aggressive myeloproliferative disorder of early childhood characterized by mutations activating RAS signaling. Established clinical and genetic markers fail to fully recapitulate the clinical and biological heterogeneity of this disease. Here we report DNA methylome analysis and mutation profiling of 167 JMML samples. We identify three JMML subgroups with unique molecular and clinical characteristics. The high methylation group (HM) is characterized by somatic PTPN11 mutations and poor clinical outcome. The low methylation group is enriched for somatic NRAS and CBL mutations, as well as for Noonan patients, and has a good prognosis. The intermediate methylation group (IM) shows enrichment for monosomy 7 and somatic KRAS mutations. Hypermethylation is associated with repressed chromatin, genes regulated by RAS signaling, frequent co-occurrence of RAS pathway mutations and upregulation of DNMT1 and DNMT3B, suggesting a link between activation of the DNA methylation machinery and mutational patterns in JMML.
Keyphrases
- dna methylation
- genome wide
- wild type
- copy number
- gene expression
- end stage renal disease
- acute myeloid leukemia
- signaling pathway
- bone marrow
- ejection fraction
- single cell
- chronic kidney disease
- newly diagnosed
- dna damage
- transcription factor
- cell proliferation
- patient reported outcomes
- long non coding rna
- bioinformatics analysis
- genome wide identification
- nucleic acid
- data analysis