Citation: Epigenetic landscape correlates with genetic subtype but does not predict outcome in childhood acute lymphoblastic leukemia

Epigenetic landscape correlates with genetic subtype but does not predict outcome in childhood acute lymphoblastic leukemia. Epigenetics, 10 (8 Northumbria University has developed Northumbria Research Link (NRL) to enable users to access the University's research output. Copyright © and moral rights for items on NRL are retained by the individual author(s) and/or other copyright owners. Single copies of full items can be reproduced, displayed or performed, and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided the authors, title and full bibliographic details are given, as well as a hyperlink and/or URL to the original metadata page. The content must not be changed in any way. Full items must not be sold commercially in any format or medium without formal permission of the copyright holder. The full policy is available online: http://nrl.northumbria.ac.uk/policies.html This document may differ from the final, published version of the research and has been made available online in accordance with publisher policies. To read and/or cite from the published version of the research, please visit the publisher's website (a subscription may be required.) Although children with acute lymphoblastic leukemia (ALL) generally have a good outcome, some patients do relapse and survival following relapse is poor. Altered DNA methylation is highly prevalent in ALL and raises the possibility that DNA methylation-based biomarkers could predict patient outcome. In this study, genome-wide methylation analysis, using the Illumina Infinium HumanMethylation450 BeadChip platform, was carried out on 52 diagnostic patient samples from 4 genetic subtypes [ETV6-RUNX1, high hyperdiploidy (HeH), TCF3-PBX1 and dic(9;20) (p11-13;q11)] in a 1:1 case-control design with patients who went on to relapse (as cases) and patients achieving longterm remission (as controls). Pyrosequencing assays for selected loci were used to confirm the array-generated data. Non-negative matrix factorization consensus clustering readily clustered samples according to genetic subgroups and gene enrichment pathway analysis suggested that this is in part driven by epigenetic disruption of subtype specific signaling pathways. Multiple bioinformatics approaches (including bump hunting and individual locus analysis) were used to identify CpG sites or regions associated with outcome. However, no associations with relapse were identified. Our data revealed that ETV6-RUNX1 and dic(9;20) subtypes were mostly associated with hypermethylation; conversely, TCF3-PBX1 and HeH were associated with hypomethylation. We observed significant enrichment of the neuroactive ligand-receptor interaction pathway in TCF3-PBX1 as well as an enrichment of genes involved in immunity and infection pathways in ETV6-RUNX1 subtype. Taken together, our results suggest that altered DNA methylation may have differential impacts in distinct ALL genetic subtypes

Epigenetic landscape correlates with genetic subtype but does not predict outcome in childhood acute lymphoblastic leukemia.

Although children with acute lymphoblastic leukemia (ALL) generally have a good outcome, some patients do relapse and survival following relapse is poor. Altered DNA methylation is highly prevalent in ALL and raises the possibility that DNA methylation-based biomarkers could predict patient outcome. In this study, genome-wide methylation analysis, using the Illumina Infinium HumanMethylation450 BeadChip platform, was carried out on 52 diagnostic patient samples from 4 genetic subtypes [ETV6-RUNX1, high hyperdiploidy (HeH), TCF3-PBX1 and dic(9;20)(p11–13;q11)] in a 1:1 case-control design with patients who went on to relapse (as cases) and patients achieving long-term remission (as controls). Pyrosequencing assays for selected loci were used to confirm the array-generated data. Non-negative matrix factorization consensus clustering readily clustered samples according to genetic subgroups and gene enrichment pathway analysis suggested that this is in part driven by epigenetic disruption of subtype specific signaling pathways. Multiple bioinformatics approaches (including bump hunting and individual locus analysis) were used to identify CpG sites or regions associated with outcome. However, no associations with relapse were identified. Our data revealed that ETV6-RUNX1 and dic(9;20) subtypes were mostly associated with hypermethylation; conversely, TCF3-PBX1 and HeH were associated with hypomethylation. We observed significant enrichment of the neuroactive ligand-receptor interaction pathway in TCF3-PBX1 as well as an enrichment of genes involved in immunity and infection pathways in ETV6-RUNX1 subtype. Taken together, our results suggest that altered DNA methylation may have differential impacts in distinct ALL genetic subtypes