Genome-Wide Methylation Analysis Using the Digital Restriction Enzyme Analysis of Methylation for Stratification of Patients with Juvenile Myelomonocytic Leukemia

• Published in: Blood 2019-11, Vol.134 (Supplement_1), p.2973-2973
• Main Authors: Kitazawa, Hironobu, Muramatsu, Hideki, Murakami, Norihiro, Okuno, Yusuke, Wakamatsu, Manabu, Yoshida, Taro, Imaya, Masayuki, Yamamori, Ayako, Miwata, Shunsuke, Narita, Kotaro, Hamada, Motoharu, Ichikawa, Daisuke, Taniguchi, Rieko, Kawashima, Nozomu, Nishikawa, Eri, Narita, Atsushi, Nishio, Nobuhiro, Kojima, Seiji, Takahashi, Yoshiyuki
• Format: Article
• Language: English
• ISSN: 0006-4971; 1528-0020
• DOI: 10.1182/blood-2019-127792

Background Juvenile myelomonocytic leukemia (JMML) is a rare myelodysplastic/ myeloproliferative neoplasm that occurs during infancy and early childhood. The clinical course of the disease varies widely. The majority of children require allogenic hematopoietic stem cell transplantation (HSCT) for long term survival, but the disease will eventually resolve spontaneously in ~15% of patients. Previous studies have identified clinical and molecular risk factors in JMML. More recently, three groups independently discovered that genome-wide methylation profiling using 450K Illumina array revealed that the high methylation (HM) subgroup was significantly associated with poor survival compared to the low methylation (LM) subgroup (Murakami 2018 Blood, Stieglitz 2017 Nat. Commun., Lipka 2017 Nat. Commun.). 450K could be a standard assay for stratification of JMML. However, it is now unavailable because the manufacture replaced it with EPIC array. Here, we developed a next-generation sequencing-based clinical test recapitulate 450K clustering results using the digital restriction enzyme analysis of methylation (DREAM) method (Jelinek 2012 Epigenetics). Patients and Methods We studied 99 children (67 boys and 32 girls) with JMML. All the patients were included in our previous publications. First, we assessed JMML samples with DREAM. Briefly, genomic DNA was sequentially cut with two enzymes SmaI and XmaI recognizing the same sequence, CCCGGG sites in DNA. Enzyme-treated DNA was then used to generate sequencing libraries according to the Illumina protocols, and run on an Illumina Hiseq 2500. We assessed 10 JMML samples with reduced representation bisulfite sequencing (RRBS) (Meissner 2005 Nucleic Acids Res.). In brief, purified genomic DNA was digested by the methylation-insensitive restriction enzyme MspI to generate short fragments that contain CpG dinucleotides at the ends. The CpG-rich DNA fragments (40-220 bp) were size selected, subjected to bisulfite conversion, PCR amplified and end sequenced on an Illumina Genome analyzer. Results We analyzed 99 samples using the DREAM with 8.87 (4.09-16.35) million reads (median, [range]), and determined methylation level in 62,525 (52,356-75,185) CpG sites (median [range]). We observed a strong correlation between DREAM methylation ratio and 450K beta-value of overlapping CpG sites (Pearson r2 = 0.95 [0.913-0.962], median [range]). We performed unsupervised consensus clustering with DREAM methylation data of 7,704 CpG sites