Journal
SCIENTIFIC REPORTS
Volume 7, Issue -, Pages -Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41598-017-13644-1
Keywords
-
Categories
Funding
- Cancer Research UK [C8464/A13457, C8464/A23391]
- UK Children's Cancer and Leukaemia Group (CCLG)/Tom Grahame Trust
- Cancer Research UK
- Swedish Childhood Cancer Foundation
- French Ministry of Health/French National Cancer Institute
- German Children's Cancer Foundation
- MRC [MR/N005872/1] Funding Source: UKRI
- Cancer Research UK [23804, 15008] Funding Source: researchfish
- Medical Research Council [MR/N005872/1] Funding Source: researchfish
Ask authors/readers for more resources
Rapid and reliable detection of disease-associated DNA methylation patterns has major potential to advance molecular diagnostics and underpin research investigations. We describe the development and validation of minimal methylation classifier (MIMIC), combining CpG signature design from genome-wide datasets, multiplex-PCR and detection by single-base extension and MALDI-TOF mass spectrometry, in a novel method to assess multi-locus DNA methylation profiles within routine clinically-applicable assays. We illustrate the application of MIMIC to successfully identify the methylation-dependent diagnostic molecular subgroups of medulloblastoma (the most common malignant childhood brain tumour), using scant/low-quality samples remaining from the most recently completed pan-European medulloblastoma clinical trial, refractory to analysis by conventional genome-wide DNA methylation analysis. Using this approach, we identify critical DNA methylation patterns from previously inaccessible cohorts, and reveal novel survival differences between the medulloblastoma disease subgroups with significant potential for clinical exploitation.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available