Aberrant Patterns of DNA Methylation in Cancer

Abstract

Deoxyribonucleic acid (DNA) methylation is an epigenetic mechanism involved in the regulation of gene expression and preservation of genome stability in normal cells. Alterations of DNA methylation code have been associated with the development and progression of many diseases, including cancer. Novel technologies allow genome‐wide interrogation of methylation patterns. Data on different types of cancer are accumulating; however, elucidation of the consequences of all observed demethylation or methylation events and understanding their associations with other genomic aberrations present great challenges for the future research. Nevertheless, several findings regarding gene silencing by hypermethylation of CpG islands in promoters of genes have been successfully transferred in clinical setting aiding in diagnosis or prognosis of different types of cancer. In addition, therapeutic application of small molecule inhibitors of DNA methyltransferases (DNMTs) to reverse epigenetic silencing has been proven to be beneficial for treatment of various cancers.

Key Concepts

  • Alterations of epigenetic mechanisms, including DNA methylation, are implicated in the pathogenesis of many diseases, including cancer.
  • DNA methylation of CpG dinucleotides distributed in the genome can either repress or enable transcription of genes, depending on the location of CpGs and the level of methylation.
  • DNA methylation can be influenced by different internal and external factors, which contribute to the establishment of heterogeneous DNA methylation patterns in cancers.
  • Observed heterogeneity of methylation profiles between tumours and within tumours represents an obstacle in obtaining relevant biological information that could be translated into the knowledge of molecular mechanisms leading to cancer.
  • Advancements in genome‐wide methodologies and bioinformatic tools used for deciphering the consequences of altered DNA methylation patterns will enable deeper understanding of molecular mechanisms leading to the development of cancer.

Keywords: cancer; CpG island; CIMP phenotype; DNA methylation; epigenetics; gene expression; gene silencing; genomic instability; tumour heterogeneity

Figure 1. Distribution of DNA (deoxyribonucleic acid) methylation in specific gene regions. Data were obtained from 17 somatic tissues. Each gene region is divided into bins that correspond to the percentage of methylation (β values) with 0.1 intervals. The area of each bin corresponds to total number of CpGs. The overall distributions and the means of β values of the CpGs in each gene region are shown as box plots. The numbers on the x‐axis correspond to total number of CpGs in each gene region. Gene regions were classified as TSS200 (200 nucleotides upstream of TSS), TSS1500 (1500 nucleotides upstream of TSS), 5′‐untranslated region (5′‐UTR), first exon, gene body (all exons and introns except the first exon) and 3′‐untranslated region (3′‐UTR). The lowest percentage of methylation was observed in promoter sequences (TSS1500, TSS200 and 5′‐UTR) and the first exon, whereas the most methylated regions were in the gene bodies and 3′‐UTR. Reprinted from Lokk et al. 2014 © BioMed Central distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0).
Figure 2. Distribution of CGI methylation in different genomic regions. Data were obtained from 17 somatic tissues. Each gene region is divided into bins that correspond to the percentage of methylation (β values) with 0.1 intervals. The area of each bin corresponds to total number of CpGs. The overall distributions and the means of β values of the CpGs in each genomic region are shown as box plots. The numbers on the x‐axis correspond to total number of CpGs in each gene region. CpG island‐oriented classification was as follows: CGI (CpG island), nonisland CpGs (CpG nucleotides not associated with CGIs), CGI shores (2 kb long regions on the left (north shore, Nshore) and right (south shore, Sshore) sides of CGIs), CGI shelves (regions, 2 kb upstream of north CGI shore (north shelf, Nshelf) or downstream of south CGI shore (south shelf, Sshelf)). (a), (b) and (c) represent the distribution of DNA methylation in designated regions in (a) CGI regions, (b) islands in intragenic regions and (c) islands in intergenic regions. CGIs, intergenic and intragenic islands were largely unmethylated, whereas the boundaries of CGIs, namely shores and shelves, as well as nonisland CpGs, were frequently methylated. Reprinted from Lokk et al. 2014 © BioMed Central distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0).
Figure 3. Frequency of gene methylation in colorectal neoplasia detected with quantitative methylation‐specific PCR (qMSP). The spots represent the percentage of samples showing greater than 10% methylation in colorectal cancer samples (red spots), matched nontumour tissues (green) and adenomas (purple). The size of the spots is proportional to a log2 transformation of the number of samples tested (see legend at the bottom). The histogram on the right side is showing the difference in the detection cycles between fully methylated commercial CpGenome™ DNA (Millipore) and wbc DNA (DNA obtained from pooled peripheral blood of healthy individuals) (ΔCt ). An asterisk denotes cases where reaction products from wbc DNA were not detected. Reprinted from Mitchell et al. 2014 © BioMed Central distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0).
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Hudler, Petra(Nov 2016) Aberrant Patterns of DNA Methylation in Cancer. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1002/9780470015902.a0006160]