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Genome-wide signatures of differential DNA methylation in pediatric acute lymphoblastic leukemia
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular Medicine. Uppsala University, Science for Life Laboratory, SciLifeLab.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cancer Pharmacology and Computational Medicine.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular Medicine. Uppsala University, Science for Life Laboratory, SciLifeLab.
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2013 (English)In: Genome Biology, ISSN 1465-6906, E-ISSN 1465-6914, Vol. 14, no 9, r105- p.Article in journal (Refereed) Published
Abstract [en]


Although aberrant DNA methylation has been observed previously in acute lymphoblastic leukemia (ALL), the patterns of differential methylation have not been comprehensively determined in all subtypes of ALL on a genome-wide scale. The relationship between DNA methylation, cytogenetic background, drug resistance and relapse in ALL is poorly understood.


We surveyed the DNA methylation levels of 435,941 CpG sites in samples from 764 children at diagnosis of ALL and from 27 children at relapse. This survey uncovered four characteristic methylation signatures. First, compared with control blood cells, the methylomes of ALL cells shared 9,406 predominantly hypermethylated CpG sites, independent of cytogenetic background. Second, each cytogenetic subtype of ALL displayed a unique set of hyper- and hypomethylated CpG sites. The CpG sites that constituted these two signatures differed in their functional genomic enrichment to regions with marks of active or repressed chromatin. Third, we identified subtype-specific differential methylation in promoter and enhancer regions that were strongly correlated with gene expression. Fourth, a set of 6,612 CpG sites was predominantly hypermethylated in ALL cells at relapse, compared with matched samples at diagnosis. Analysis of relapse-free survival identified CpG sites with subtype-specific differential methylation that divided the patients into different risk groups, depending on their methylation status.


Our results suggest an important biological role for DNA methylation in the differences between ALL subtypes and in their clinical outcome after treatment.

Place, publisher, year, edition, pages
2013. Vol. 14, no 9, r105- p.
National Category
Medical Genetics
URN: urn:nbn:se:uu:diva-208296DOI: 10.1186/gb-2013-14-9-r105ISI: 000328195700011PubMedID: 24063430OAI: oai:DiVA.org:uu-208296DiVA: diva2:651822

De två första författarna delar förstaförfattarskapet.

Available from: 2013-09-27 Created: 2013-09-27 Last updated: 2015-03-11Bibliographically approved
In thesis
1. Machine Learning Based Analysis of DNA Methylation Patterns in Pediatric Acute Leukemia
Open this publication in new window or tab >>Machine Learning Based Analysis of DNA Methylation Patterns in Pediatric Acute Leukemia
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Maskininlärningsbaserad analys av DNA-metyleringsmönster i pediatrisk akut lymfatisk leukemi
Abstract [en]

Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer in the Nordic countries. Recent evidence indicate that DNA methylation (DNAm) play a central role in the development and progression of the disease.

DNAm profiles of a collection of ALL patient samples and a panel of non-leukemic reference samples were analyzed using the Infinium 450k methylation assay. State-of-the-art machine learning algorithms were used to search the large amounts of data produced for patterns predictive of future relapses, in vitro drug resistance, and cytogenetic subtypes, aiming at improving our understanding of the disease and ultimately improving treatment.

In paper I, the predictive modeling framework developed to perform the analyses of DNAm dataset was presented. It focused on uncompromising statistical rigor and computational efficiency, while allowing a high level of modeling flexibility and usability. In paper II, the DNAm landscape of ALL was comprehensively characterized, discovering widespread aberrant methylation at diagnosis strongly influenced by cytogenetic subtype. The aberrantly methylated regions were enriched for genes repressed by polycomb group proteins, repressively marked histones in healthy cells, and genes associated with embryonic development. A consistent trend of hypermethylation at relapse was also discovered. In paper III, a tool for DNAm-based subtyping was presented, validated using blinded samples and used to re-classify samples with incomplete phenotypic information. Using RNA-sequencing, previously undetected non-canonical aberrations were found in many re-classified samples. In paper IV, the relationship between DNAm and in vitro drug resistance was investigated and predictive signatures were obtained for seven of the eight therapeutic drugs studied. Interpretation was challenging due to poor correlation between DNAm and gene expression, further complicated by the discovery that random subsets of the array can yield comparable classification accuracy. Paper V presents a novel Bayesian method for multivariate density estimation with variable bandwidths. Simulations showed comparable performance to the current state-of-the-art methods and an advantage on skewed distributions.

In conclusion, the studies characterize the information contained in the aberrant DNAm patterns of ALL and assess its predictive capabilities for future relapses, in vitro drug sensitivity and subtyping. They also present three publicly available tools for the scientific community to use.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2015. 68 p.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1069
National Category
Bioinformatics (Computational Biology) Hematology Cancer and Oncology
urn:nbn:se:uu:diva-242544 (URN)978-91-554-9151-2 (ISBN)
Public defence
2015-03-13, Auditorium minus, Museum Gustavianum, Akademigatan 3, Uppsala, 14:00 (English)
Swedish Foundation for Strategic Research , RBc08-008
Available from: 2015-02-19 Created: 2015-01-27 Last updated: 2015-03-27Bibliographically approved

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Nordlund, JessicaBäcklin, Christofer LWahlberg, PerBerglund, Eva CEloranta, Maija-LeenaFrost, Britt-MarieLarsson, RolfPalle, JosefineRönnblom, LarsGustafsson, Mats GLönnerholm, GudmarSyvänen, Ann-Christine
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