Site-specific CpG methylation in the CCAAT/enhancer binding protein delta (CEBPδ) CpG island in breast cancer is associated with metastatic relapse.
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ABSTRACT:
SUBMITTER: Palmieri C
PROVIDER: S-EPMC3419957 | biostudies-other | 2012 Aug
REPOSITORIES: biostudies-other
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Project description:BACKGROUND: The computational prediction of DNA methylation has become an important topic in the recent years due to its role in the epigenetic control of normal and cancer-related processes. While previous prediction approaches focused merely on differences between methylated and unmethylated DNA sequences, recent experimental results have shown the presence of much more complex patterns of methylation across tissues and time in the human genome. These patterns are only partially described by a binary model of DNA methylation. In this work we propose a novel approach, based on profile analysis of tissue-specific methylation that uncovers significant differences in the sequences of CpG islands (CGIs) that predispose them to a tissue- specific methylation pattern. RESULTS: We defined CGI methylation profiles that separate not only between constitutively methylated and unmethylated CGIs, but also identify CGIs showing a differential degree of methylation across tissues and cell-types or a lack of methylation exclusively in sperm. These profiles are clearly distinguished by a number of CGI attributes including their evolutionary conservation, their significance, as well as the evolutionary evidence of prior methylation. Additionally, we assess profile functionality with respect to the different compartments of protein coding genes and their possible use in the prediction of DNA methylation. CONCLUSION: Our approach provides new insights into the biological features that determine if a CGI has a functional role in the epigenetic control of gene expression and the features associated with CGI methylation susceptibility. Moreover, we show that the ability to predict CGI methylation is based primarily on the quality of the biological information used and the relationships uncovered between different sources of knowledge. The strategy presented here is able to predict, besides the constitutively methylated and unmethylated classes, two more tissue specific methylation classes conserving the accuracy provided by leading binary methylation classification methods.
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Project description:Epigenetic silencing associated with aberrant methylation of promoter region CpG islands is one mechanism leading to loss of tumor suppressor function in human cancer. Profiling of CpG island methylation indicates that some genes are more frequently methylated than others, and that each tumor type is associated with a unique set of methylated genes. However, little is known about why certain genes succumb to this aberrant event. To address this question, we used Restriction Landmark Genome Scanning to analyze the susceptibility of 1,749 unselected CpG islands to de novo methylation driven by overexpression of DNA cytosine-5-methyltransferase 1 (DNMT1). We found that although the overall incidence of CpG island methylation was increased in cells overexpressing DNMT1, not all loci were equally affected. The majority of CpG islands (69.9%) were resistant to de novo methylation, regardless of DNMT1 overexpression. In contrast, we identified a subset of methylation-prone CpG islands (3.8%) that were consistently hypermethylated in multiple DNMT1 overexpressing clones. Methylation-prone and methylation-resistant CpG islands were not significantly different with respect to size, C+G content, CpG frequency, chromosomal location, or promoter association. We used DNA pattern recognition and supervised learning techniques to derive a classification function based on the frequency of seven novel sequence patterns that was capable of discriminating methylation-prone from methylation-resistant CpG islands with 82% accuracy. The data indicate that CpG islands differ in their intrinsic susceptibility to de novo methylation, and suggest that the propensity for a CpG island to become aberrantly methylated can be predicted based on its sequence context.
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Project description:Aberrant DNA methylation plays a significant role in nearly all human cancers and may contribute to disease progression to advanced phenotypes. Study of advanced prostate cancer phenotypes in the human disease is hampered by limited availability of tissues. We therefore took advantage of the Transgenic Adenocarcinoma of Mouse Prostate (TRAMP) model to study whether three different phenotypes of TRAMP tumors (PRIM, late-stage primary tumors; AIP, androgen-independent primary tumors; and MET, metastases) displayed specific patterns of CpG island hypermethylation using Restriction Landmark Genomic Scanning. Each tumor phenotype displayed numerous hypermethylation events, with the most homogeneous methylation pattern in AIP and the most heterogeneous pattern in MET. Several loci displayed a phenotype-specific methylation pattern; the most striking pattern being loci methylated at high frequency in PRIM and AIP but rarely in MET. Examination of the mRNA expression of three genes, BC058385, Goosecoid, and Neurexin 2, which exhibited nonpromoter methylation, revealed increased expression associated with downstream methylation. Only methylated samples showed mRNA expression, in which tumor phenotype was a key factor determining the level of expression. The CpG island in the human orthologue of BC058385 was methylated in human AIP but not in primary androgen-stimulated prostate cancer or benign prostate. The clinical data show a proof-of-principle that the TRAMP model can be used to identify targets of aberrant CpG island methylation relevant to human disease. In conclusion, phenotype-specific hypermethylation events were associated with the overexpression of different genes and may provide new markers of prostate tumorigenesis.
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Project description:α-Synuclein is the main component of Lewy bodies, the intracellular protein aggregates representing the histological hallmark of Parkinson's disease. Elevated α-synuclein levels and mutations in SNCA gene are associated with increased risk for Parkinson's disease. Despite this, little is known about the molecular mechanisms regulating SNCA transcription. CCAAT/enhancer binding protein (C/EBP) β and δ are b-zip transcription factors that play distinct roles in neurons and glial cells. C/EBPβ overexpression increases SNCA expression in neuroblastoma cells and putative C/EBPβ and δ binding sites are present in the SNCA genomic region suggesting that these proteins could regulate SNCA transcription. Based on these premises, the goal of this study was to determine if C/EBPβ and δ regulate the expression of SNCA. We first observed that α-synuclein CNS expression was not affected by C/EBPβ deficiency but it was markedly increased in C/EBPδ-deficient mice. This prompted us to characterize further the role of C/EBPδ in SNCA transcription. C/EBPδ absence led to the in vivo increase of α-synuclein in all brain regions analyzed, both at mRNA and protein level, and in primary neuronal cultures. In agreement with this, CEBPD overexpression in neuroblastoma cells and in primary neuronal cultures markedly reduced SNCA expression. ChIP experiments demonstrated C/EBPδ binding to the SNCA genomic region of mice and humans and luciferase experiments showed decreased expression of a reporter gene attributable to C/EBPδ binding to the SNCA promoter. Finally, decreased CEBPD expression was observed in the substantia nigra and in iPSC-derived dopaminergic neurons from Parkinson patients resulting in a significant negative correlation between SNCA and CEBPD levels. This study points to C/EBPδ as an important repressor of SNCA transcription and suggests that reduced C/EBPδ neuronal levels could be a pathogenic factor in Parkinson's disease and other synucleinopathies and C/EBPδ activity a potential pharmacological target for these neurological disorders.
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Project description:CpG islands (CGIs) are dense clusters of CpG sequences that punctuate the CpG-deficient human genome and associate with many gene promoters. As CGIs also differ from bulk chromosomal DNA by their frequent lack of cytosine methylation, we devised a CGI enrichment method based on nonmethylated CpG affinity chromatography. The resulting library was sequenced to define a novel human blood CGI set that includes many that are not detected by current algorithms. Approximately half of CGIs were associated with annotated gene transcription start sites, the remainder being intra- or intergenic. Using an array representing over 17,000 CGIs, we established that 6%-8% of CGIs are methylated in genomic DNA of human blood, brain, muscle, and spleen. Inter- and intragenic CGIs are preferentially susceptible to methylation. CGIs showing tissue-specific methylation were overrepresented at numerous genetic loci that are essential for development, including HOX and PAX family members. The findings enable a comprehensive analysis of the roles played by CGI methylation in normal and diseased human tissues.
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Project description:We compare the methylation status of CpG island clones by MeDIP in SW48 colon cancer cells relative to normal colon mucosa and WI38 primary fibroblasts. Keywords: ordered
2005-07-03 | GSE2653 | GEO
Project description:Genetic changes that modify the function of transcriptional enhancers have been linked to the evolution of biological diversity across species. Multiple studies have focused on the role of nucleotide substitutions, transposition, and insertions and deletions in altering enhancer function. Here we show that turnover of CpG islands (CGIs), which contribute to enhancer activation, is broadly associated with changes in enhancer activity across mammals, including humans. We integrated maps of CGIs and enhancer activity-associated histone modifications obtained from multiple tissues in nine mammalian species and found that CGI content in enhancers was strongly associated with increased histone modification levels. CGIs showed widespread turnover across species and species-specific CGIs were strongly enriched for enhancers exhibiting species-specific activity across all tissues and species we examined. Genes associated with enhancers with species-specific CGIs showed concordant biases in their expression, supporting that CGI turnover contributes to gene regulatory innovation. Our results also implicate CGI turnover in the evolution of Human Gain Enhancers (HGEs), which show increased activity in human embryonic development and may have contributed to the evolution of uniquely human traits. Using a humanized mouse model, we show that a highly conserved HGE with a large CGI absent from the mouse ortholog shows increased activity at the human CGI in the humanized mouse diencephalon. Collectively, our results point to CGI turnover as a mechanism driving gene regulatory changes potentially underlying trait evolution in mammals.
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