Agglomerative Epigenetic Aberrations Are a Common Event in Human Breast Cancer

Abstract

Changes in DNA methylation patterns are a common characteristic of cancer cells. Recent studies suggest that DNA methylation affects not only discrete genes, but it can also affect large chromosomal regions, potentially leading to LRES. It is unclear whether such long-range epigenetic events are relatively rare or frequent occurrences in cancer. Here, we use a high-resolution promoter tiling array approach to analyze DNA methylation in breast cancer specimens and normal breast tissue to address this question. We identified 3,506 cancer-specific differentially methylated regions (DMR) in human breast cancer with 2,033 being hypermethylation events and 1,473 hypomethylation events. Most of these DMRs are recurrent in breast cancer; 90% of the identified DMRs occurred in at least 33% of the samples. Interestingly, we found a nonrandom spatial distribution of aberrantly methylated regions across the genome that showed a tendency to concentrate in relatively small genomic regions. Such agglomerates of hypermethylated and hypomethylated DMRs spanned up to several hundred kilobases and were frequently found at gene family clusters. The hypermethylation events usually occurred in the proximity of the transcription start site in CpG island promoters, whereas hypomethylation events were frequently found in regions of segmental duplication. One example of a newly discovered agglomerate of hypermethylated DMRs associated with gene silencing in breast cancer that we examined in greater detail involved the protocadherin gene family clusters on chromosome 5 (PCDHA, PCDHB, and PCDHG). Taken together, our results suggest that agglomerative epigenetic aberrations are frequent events in human breast cancer. [Cancer Res 2008;68(20):8616-25]

Transcriptional Regulation of the Protocadherin β Cluster during Her-2 Protein-induced Mammary Tumorigenesis Results from Altered N-Glycan Branching

“…2B); reintroduction of GnT-V cDNA into KO tumor cells significantly attenuated the expression of Pcdh␤ genes in these cells (Fig. 2C), supporting the hypothesis that differential expression of Pcdh␤ genes in GnT-V KO tumors was due to altered expression levels of GnT-V. A recent study has shown that Pcdh gene clusters, including the Pcdh␤ family, are expressed at lower levels in human breast cancer tissues than in normal tissues, and these lower expression levels were linked to human breast tumorigenesis (26). To confirm and extend the observation concerning the differential expression of the Pcdh␤ gene cluster in mouse mammary tumors after deletion of GnT-V, Pcdh␤ gene expression was measured in the human breast cancer cell line MDA-MB231 after knockdown of GnT-V by siRNA.…”

“…As shown in Fig. 2D, three members of the human PCDH␤ cluster (PCDH␤3, PCDH␤6, and PCDH␤13), which were shown to be significantly down-regulated in human breast cancer tissues (26), were dramatically enhanced in MDA-MB231 cells with GnT-V knockdown, further confirming the ability of GnT-V expression levels to regulate the expression of the Pcdh␤ cluster during breast tumorigenesis.…”

“…Protocadherins are predominantly expressed in the nervous system and appear to play an important role in regulating neuron development (21). However, epigenetic aberrations of protocadherin gene clusters caused by hypermethylation have been identified recently in some human tumors, including breast cancer (25)(26)(27)(28), indicating that Pcdh genes may serve as tumor "suppressors" that can inhibit tumor development.…”

Evaluation of affinity-based genome-wide DNA methylation data: Effects of CpG density, amplification bias, and copy number variation

“…There are now numerous methods available for determining CpG methylation status (for review, see Laird 2010), including methods focused at the level of CpG islands (Ponzielli et al 2008;Kaminsky et al 2009), individual promoters (Weber et al 2005(Weber et al , 2007Novak et al 2008), and, increasingly, genome-''scale'' (Meissner et al 2008;Gu et al 2010) and genome-wide methods, either at high (Lister et al 2009) or low resolution (Serre et al 2009;Ruike et al 2010). These later methods can be broadly classified into the following designations: reduced representation approaches that are based on methylation-sensitive (e.g., HELP) (Oda et al 2009) or specific (e.g., CHARM) (Irizarry et al 2008) restriction digestion (for review, see Jeddeloh et al 2008), affinity-based methods such as methyl-DNA immunoprecipitation (MeDIP) (Weber et al 2005(Weber et al , 2007Novak et al 2008) and methyl-CpG binding domain-based capture (MBDCap) (Rauch et al 2006(Rauch et al , 2008Serre et al 2009), and the more direct bisulphite treatment-based methods (Lister et al 2009); coupling of reduced representation and bisulphite treatment has now been demonstrated (Meissner et al 2008;Gu et al 2010), and other combinations are also possible.…”

“…These later methods can be broadly classified into the following designations: reduced representation approaches that are based on methylation-sensitive (e.g., HELP) (Oda et al 2009) or specific (e.g., CHARM) (Irizarry et al 2008) restriction digestion (for review, see Jeddeloh et al 2008), affinity-based methods such as methyl-DNA immunoprecipitation (MeDIP) (Weber et al 2005(Weber et al , 2007Novak et al 2008) and methyl-CpG binding domain-based capture (MBDCap) (Rauch et al 2006(Rauch et al , 2008Serre et al 2009), and the more direct bisulphite treatment-based methods (Lister et al 2009); coupling of reduced representation and bisulphite treatment has now been demonstrated (Meissner et al 2008;Gu et al 2010), and other combinations are also possible. However, there are still many challenges involved in interpreting data from DNA methylation-based assays, due to complex effects, both technical and biological that are introduced at various steps in the procedure, in addition to implicit biases from the methods employed.…”