Does childhood leukaemia develop in cells which are pre- primed by the presence of aberrant patterns of DNA methylation? Sanne van Otterdijk Northern Institute of Cancer Research Exon CpG Island
Aims • Understand how abnormal methylation develops in and contributes to haematological malignancies – Quantify the extent and variability of DNA methylation in healthy populations at different ages – Quantify the extent and variability of DNA methylation in childhood and adult ALL patients at different stages of the disease – Examine the overlap between methylation patterns in healthy individuals and ALL patients – Assess the potential of differential methylation in apparently healthy samples for leukaemia risk assessment or detection of early disease – Assess the potential of differential methylation in ALL remission samples for prediction of outcome
DNA methylation is increasing with age N33 methylation with age * # * # 40 Methylation levels (%) 35 30 * # 25 * # 20 15 Patient 10 5 Mean 0 0 20 40 60 80 100 Age (years) * A significant difference in methylation levels is observed # A significant difference in variance of methylation is observed Similar patterns observed in 4 other leukaemia related genes; TWIST2, HOXD4, EphA10 and HAND2
DNA methylation during ALL remission N33 methylation during ALL remission 30 ethylation levels (%) 25 Childhood 20 ALL patient Adult ALL 15 patient M ean 10 Controls 5 M 0 0 20 40 60 80 100 Age (years) Similar patterns observed in 4 other leukaemia related genes; TWIST2, HOXD4, EphA10 and HAND2
“Leukaemia-like” features are already present in healthy individuals TWIST2 CpG Site Gene TWIST2 HOXD4 EphA10 N33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 TWIST2 HOXD4 R Value = 0.51 p value = 0.0002 EphA10 R value = R value 0.55 = 0.36 p value = p value = 0.00004 0.01 N33 R value = R value R value = 0.49 = 0.72 0.31 p value = p value = p value = 0.0003 5.0E-09 0.03 HAND2 R value = R value R value = R value = 0.43 = 0.64 0.38 0.64 P value = p value = p value = p value = 0.001 7.0E-07 0.006 0.000002 Highly methylated alleles CIMP
Pre-existing methylation may underlie susceptibility to cancer Genes are unmethylated Partial methylation in all cells Densely hypermethylated alleles Several genes methylated
Acknowledgements Supervisors Newcastle biobank Dr Gordon Strathdee Professor John Matters Newcastle 85+ study Professor Iokim Spyridopoulos Newcastle 85+ Study Core Team The Newcastle Thousand Families Crucible Team study Hannah Gautry Dr Mark Pearce Shabnam Thathia Stefano Tonin North Cumbria Community Genetics Fadhel Lafta Project (NCCGP) Dr Caroline Relton Funding Newcastle NIHR Biomedical Research Centre Newcastle Healthcare Charity and Newcastle upon Tyne hospitals NHS Charity
Recommend
More recommend
