Comparative methylome analysis of benign and malignant peripheral nerve sheath tumors

Abstract

Aberrant DNA methylation (DNAm) was first linked to cancer over 25 yr ago. Since then, many studies have associated hypermethylation of tumor suppressor genes and hypomethylation of oncogenes to the tumorigenic process. However, most of these studies have been limited to the analysis of promoters and CpG islands (CGIs). Recently, new technologies for whole-genome DNAm (methylome) analysis have been developed, enabling unbiased analysis of cancer methylomes. By using MeDIP-seq, we report a sequencing-based comparative methylome analysis of malignant peripheral nerve sheath tumors (MPNSTs), benign neurofibromas, and normal Schwann cells. Analysis of these methylomes revealed a complex landscape of DNAm alterations. In contrast to what has been reported for other tumor types, no significant global hypomethylation was observed in MPNSTs using methylome analysis by MeDIP-seq. However, a highly significant (P < 10−100) directional difference in DNAm was found in satellite repeats, suggesting these repeats to be the main target for hypomethylation in MPNSTs. Comparative analysis of the MPNST and Schwann cell methylomes identified 101,466 cancer-associated differentially methylated regions (cDMRs). Analysis showed these cDMRs to be significantly enriched for two satellite repeat types (SATR1 and ARLα) and suggests an association between aberrant DNAm of these sequences and transition from healthy cells to malignant disease. Significant enrichment of hypermethylated cDMRs in CGI shores (P < 10−60), non–CGI-associated promoters (P < 10−4) and hypomethylated cDMRs in SINE repeats (P < 10−100) was also identified. Integration of DNAm and gene expression data showed that the expression pattern of genes associated with CGI shore cDMRs was able to discriminate between disease phenotypes. This study establishes MeDIP-seq as an effective method to analyze cancer methylomes.

Next Generation Sequencing - Advances, Applications and Challenges

“…It has been used in numerous studies including the first mammalian methylome [33] and the first cancer methylome [26]. In the next section, approaches for the analysis of MeDIP-seq data will be discussed in greater detail.…”

“…CpG islands, exons) within a methylome. Batman was used for the analysis of the first mammalian methylome [33] and also the first cancer methylome [26]. Unfortunately, Batman was disproportionately time consuming to run, even when running with multiple processors.…”

“…Many cancers have shown hypomethylation at repetitive sequences thus promoting chromosomal instability. Examples include the LINE repeat L1 in a range of tumours [25] and satellite repeats ALRα and SATR1 in peripheral nerve sheath tumours [26]. Hypomethylation at specific promoters can lead to aberrant expression of oncogenes, whilst in contrast hypermethylation at specific island or shore sites can lead to transcriptional inactivation of genes involved in pathways such as DNA repair and apoptosis [2,13].…”

Epigenetic regulation in obesity

“…In fact, the degree of methylation of cytosines 1-2 kb downstream or upstream the islands, so called 'shores', have been found to associate strongly to cell type and to disease, with the shores containing B80% of the regions with tissuespecific methylation. 17 Although recent reports support the importance of cytosine methylation in both shore and repeat regions, 18 cytosine methylation has primarily been studied in gene promoters because they are known to be central in regulation of transcription. Human studies of DNA methylation have typically been done using peripheral blood mononuclear cells.…”

Genome-wide DNA Methylation Events in TMPRSS2–ERG Fusion-Negative Prostate Cancers Implicate an EZH2-Dependent Mechanism with miR-26a Hypermethylation

“…However, the epigenetic landscapes of prostate cancer subgroups are still not suffi ciently investigated to draw any conclusions. To understand alterations in the ERG fusion-negative class of prostate cancer, we used a deep sequencing readout of methylated DNA immunoprecipitation sequencing (MeDIPSeq) to screen 51 tumor and 53 benign prostate tissues (23)(24)(25)(26). We integrated the results with gene and microRNA (miRNA) expression analyses and proposed a model for the development of aberrant DNA methylation patterns in ERG fusion-negative (FUS − ) prostate cancers.…”