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Whole Genome MBD‐seq reveals different CpG methylation patterns in Azacytidine‐treated Juvenile Myelomonocytic Leukaemia (JMML) patients

Juvenile myelomonocytic leukaemia (JMML) is a rare and severe form of early childhood leukaemia characterized by clonal proliferation of myelomonocytic cells, progressive anaemia, thrombocytopenia, hepatosplenomegaly and increased fetal haemoglobin (HbF) (Chan et al, 2009). The only available curative treatment is allogeneic haematopoietic stem cell transplantation (HSCT), but prognosis remains poor (Niemeyer & Kratz, 2008; Locatelli & Niemeyer, 2015). It has previously been shown that aberrant DNA hypermethylation of distinct target genes defines more aggressive variants of JMML (Flotho et al, 2007; Furlan et al, 2009; Olk-Batz et al, 2011; Poetsch et al, 2014). Azacytidine (AZA) is a DNA hypomethylating agent recently employed for JMML treatment (Locatelli & Niemeyer, 2015). To evaluate AZA treatment impact on aberrant methylation in JMML, we screened global DNA methylation in 3 JMML patients before and after AZA treatment. We found global DNA hypermethylation in both preand post-AZA treated patient samples compared to healthy controls, and a significant, although patient-specific, AZA-induced hypomethylation effect. Furthermore, we identified several differentially methylated coding and non-coding species of RNA, depicting a complex deregulation at different levels of transcription and translation in JMML. CD34 cells were isolated from frozen mononuclear cell suspensions. Three JMML patients at both diagnosis (t0 group) and after the third cycle of AZA (t1 group) (Furlan et al, 2009) were studied (Table SI); three additional healthy donor (HD) control samples were also included (HD group). Informed consent was obtained from either parents or legal guardians according to the Declaration of Helsinki. Approval for this study was obtained from the Institutional Review Board of the “Bambino Ges u” Children’s Hospital, Rome. JMML patients were treated with AZA as a compassionate use. Methods for CD34 cells isolation, their percentage assessment and genomic DNA extraction and sequence analysis are detailed in Data S1. The complete DNA-seq datasets are available at the European Bioinformatics Institute European Nucleotide Archive (EBI ENA) database (http://www. ebi.ac.uk/ena; accession number: PRJEB19377). Gene lists and ontologies are available in supplemental files. After Methyl Binding Domain (MBD) sequencing (EBI ENA database; http://www.ebi.ac.uk/ena) we compared t0 and HD groups (File S1), detecting 987 different transcriptional units corresponding to 714 coding and 273 non-coding sequences, mostly hypermethylated in t0 (Fig 1A Panel i, ii). A functional protein association network (STRING; http://string-db.org/) (Szklarczyk et al, 2015) identified 18 different pathways possibly impaired by deregulated DNA-methylation (Figure S1; Table I; false discovery rate [FDR] < 0 05). The same analysis on t1 and HD groups identified 643 unique transcriptional units, with 468 coding and 175 non-coding sequences, indicating a strong tendency towards hypermethylation in JMML samples (File S2; Fig 1A Panel i, ii). Again, the functional protein association network identified 10 putative impaired pathways, similarly to t0 vs. HD analysis (Figure S2; Table I; FDR < 0 05), even if DNA hypermethylation after AZA treatment was reduced. Involvement of membrane elements, such as adhesion molecules, developmental processes and cell cycle-related genes was recurrent in our analysis, meaning that identifying insights of these pathways could help to further enlighten pathogenic mechanisms and novel targets for therapy in JMML. Unexpectedly, direct comparative methylation analysis of samples obtained at onset of JMML and after AZA treatment (t0 vs. t1) did not show any significant difference (File S3), suggesting a probable unspecific and unique patient-related pharmacological effect, which was also evident when considering single-case analysis (Figure S3; File S4, S5, S6). Notably, 453 differentially methylated coding regions were shared between newly diagnosed JMML and AZA-treated samples compared to HD (Table SII). Additionally, 261 and 15 coding regions with different methylation status were specific for t0 and t1 respectively (Fig 1B Panel i; Table SII). Among non-coding regions, we also found 165 sequences shared between the two groups (Table SII), while 107 and 10 were unique in the t0 vs. HD and t1 vs. HD, respectively (Fig 1B Panel ii; Table SII). Interestingly, 439 coding and 161 non-coding specific genomic regions preserved their hypermethylated status, describing an apparent resistance to AZA treatment (Fig 1B Panel iii, iv; Table SII). We found different non-coding RNA species, such as microRNAs, splicing RNAs, long noncoding RNAs/antisense transcripts (AS) and other nondescript RNA species (Table SII; Supplemental files), identifying a complex deregulation of preand post-transcriptional processes in JMML pathogenesis possibly acting in a cooperative way. correspondence