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. 2018 Mar;10(1):33-42.
doi: 10.1007/s12539-018-0285-4. Epub 2018 Feb 5.

Region-Specific Methylation Profiling in Acute Myeloid Leukemia

Agnieszka Cecotka  1 , Joanna Polanska  2
Affiliations

Region-Specific Methylation Profiling in Acute Myeloid Leukemia

Agnieszka Cecotka et al. Interdiscip Sci. 2018 Mar.

Abstract

Alteration of DNA methylation level in cancer diseases leads to deregulation of gene expression-silencing of tumor suppressor genes and enhancing of protooncogenes. There are several tools devoted to the problem of identification of CpG sites' demethylation but majority of them focuses on single site level and does not allow for quantification of region methylation changes. The aim was to create an adaptive algorithm supporting detection of differentially methylated CpG sites and genomic regions specific for acute myeloid leukemia. Knowledge on AML methylation fingerprint helps in better understanding the epigenetics of leukemogenesis. Proposed algorithm is data driven and does not use predefined quantification thresholds. Gaussian mixture modeling supports classification of CpG sites to several levels of demethylation. p value integration allows for translation from single site demethylation to the demethylation of gene promoter and body regions. Methylation profiles of healthy controls and AML patients were examined (GEO:GSE63409). The differences in whole genome methylation profiles were observed. The methylation profile differs significantly among genomic regions. The lowest methylation level was observed for promoter regions, while sites from intergenic regions were by average higher methylated. The observed number of AML related down methylated sites has not substantially exceeded the expected number by chance. Intergenic regions were characterized by the highest percentage of AML up methylated sites. Methylation enhancement/diminution is the most frequent for intergenic region while methylation compensation (positive or negative) is specific for promoter regions. Functional analysis performed for AML down methylated or extreme high up methylated genes showed strong connection to the leukemic processes.

Keywords: AML; Acute myeloid leukemia; DMR; DNA methylation; Data driven algorithm; Differentially methylated regions; Epigenetics; Gaussian mixture modeling.

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Figures

Fig. 1
Fig. 1
Whole genome pooled empirical cdf for HSC and AML samples
Fig. 2
Fig. 2
Empirical cdfs for a TSS, b gene body, and c intergenic regions
Fig. 3
Fig. 3
Distribution of HL statistics, its GM model, and the identified classes of low, medium, high and extreme high AML up methylation
Fig. 4
Fig. 4
Methylation profiles for exemplary genes
See this image and copyright information in PMC

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