Identification of a new locus and validation of previously reported loci showing differential methylation associated with smoking. The REGICOR study

Smoking increases the risk of many diseases and could act through changes in DNA methylation patterns. The aims of this study were to determine the association between smoking and DNA methylation throughout the genome at cytosine-phosphate-guanine (CpG) site level and genomic regions. A discovery cross-sectional epigenome-wide association study nested in the follow-up of the REGICOR cohort was designed and included 645 individuals. Blood DNA methylation was assessed using the Illumina HumanMethylation450 BeadChip. Smoking status was self-reported using a standardized questionnaire. We identified 66 differentially methylated CpG sites associated with smoking, located in 38 genes. In most of these CpG sites, we observed a trend among those quitting smoking to recover methylation levels typical of never smokers. A CpG site located in a novel smoking-associated gene (cg06394460 in LNX2) was hypomethylated in current smokers. Moreover, we validated two previously reported CpG sites (cg05886626 in THBS1, and cg24838345 in MTSS1) for their potential relation to atherosclerosis and cancer diseases, using several different approaches: CpG site methylation, gene expression, and plasma protein level determinations. Smoking was also associated with higher THBS1 gene expression but with lower levels of thrombospondin-1 in plasma. Finally, we identified differential methylation regions in 13 genes and in four non-coding RNAs. In summary, this study replicated previous findings and identified and validated a new CpG site located in LNX2 associated with smoking.     

Exploring genome-wide DNA methylation profiles altered in hepatocellular carcinoma using Infinium HumanMethylation 450 BeadChips

Hepatocellular carcinoma (HCC) incidence has increased in the US and also has one of the fastest growing death rates of any cancer. The purpose of the current study was to discover novel genome-wide aberrant DNA methylation patterns in HCC tumors that are predominantly HCV-related. Infinium HumanMethylation 450K BeadChip arrays were used to examine genome-wide DNA methylation profiles in 66 pairs of HCC tumor and adjacent non-tumor tissues. After Bonferroni adjustment, a total of 130,512 CpG sites significantly differed in methylation level in tumor compared with non-tumor tissues, with 28,017 CpG sites hypermethylated and 102,495 hypomethylated in tumor tissues. Absolute tumor/non-tumor methylation differences ≥ 20% were found in 24.9% of the hypermethylated and 43.1% of the hypomethylated CpG sites; almost 10,000 CpG sites have ≥ 30% DNA methylation differences. Most (60.1%) significantly hypermethylated CpG sites are located in CpG islands, with 21.6% in CpG shores and 3.6% in shelves. In contrast, only a small proportion (8.2%) of significantly hypomethylated CpG sites are situated in islands, while most are found in open sea (60.2%), shore (17.3%) or shelf (14.3%) regions. A total of 2,568 significant CpG sites (2,441 hypermethylated and 127 hypomethylated) covering 589 genes are located within 684 differentially methylated regions defined as regions with at least two significant CpG sites displaying > 20% methylation differences in the same direction within 250-bp. The top 500 significant CpG sites can significantly distinguish HCC tumor from adjacent tissues with one misclassification. Within adjacent non-tumor tissues, we also identified 75 CpG sites significantly associated with gender, 228 with HCV infection, 17,207 with cirrhosis, and 56 with both HCV infection and cirrhosis after multiple comparisons adjustment. Aberrant DNA methylation profiles across the genome were identified in tumor tissues from US HCC cases that are predominantly related to HCV infection. These results demonstrate the significance of aberrant DNA methylation in HCC tumorigenesis.     

Identification of New Differentially Methylated Genes That Have Potential Functional Consequences in Prostate Cancer

Many differentially methylated genes have been identified in prostate cancer (PCa), primarily using candidate gene-based assays. Recently, several global DNA methylation profiles have been reported in PCa, however, each of these has weaknesses in terms of ability to observe global DNA methylation alterations in PCa. We hypothesize that there remains unidentified aberrant DNA methylation in PCa, which may be identified using higher resolution assay methods. We used the newly developed Illumina HumanMethylation450 BeadChip in PCa (n = 19) and adjacent normal tissues (n = 4) and combined these with gene expression data for identifying new DNA methylation that may have functional consequences in PCa development and progression. We also confirmed our methylation results in an independent data set. Two aberrant DNA methylation genes were validated among an additional 56 PCa samples and 55 adjacent normal tissues. A total 28,735 CpG sites showed significant differences in DNA methylation (FDR adjusted P<0.05), defined as a mean methylation difference of at least 20% between PCa and normal samples. Furthermore, a total of 122 genes had more than one differentially methylated CpG site in their promoter region and a gene expression pattern that was inverse to the direction of change in DNA methylation (e.g. decreased expression with increased methylation, and vice-versa). Aberrant DNA methylation of two genes, AOX1 and SPON2, were confirmed via bisulfate sequencing, with most of the respective CpG sites showing significant differences between tumor samples and normal tissues. The AOX1 promoter region showed hypermethylation in 92.6% of 54 tested PCa samples in contrast to only three out of 53 tested normal tissues. This study used a new BeadChip combined with gene expression data in PCa to identify novel differentially methylated CpG sites located within genes. The newly identified differentially methylated genes may be used as biomarkers for PCa diagnosis.     

HORMAD2 methylation‐mediated epigenetic regulation of gene expression in thyroid cancer

This study is aimed to investigate the methylation level of candidate genes and its impact on thyroid carcinoma (THCA) development. Infinium Human Methylation 450 BeadChip Arrays by Illumina (Illumina HM450K) was the most popular CpG microarray platform widely used in biological and medical research. The methylation level of differentially expressed genes and their corresponding CpG sites were analysed by R programme. The expression of HORMAD2 was evaluated by qRT‐PCR and Western blot, while the methylation level was examined via methylation‐specific PCR. Cell viability, metastasis, cell cycle and apoptosis were detected by MTT assay, transwell and wound healing assay and flow cytometry, respectively, after treatment with 5‐aza‐2′‐deoxycytidine (5‐Aza). Tumour formation assay was used to analyse thyroid tumour growth in nude mice in vivo. The methylation levels of all 116 differentially expressed genes were analysed. HORMAD2 was significantly hypermethylated and its mRNA expression was inhibited in THCA cells. After treatment with 5‐Aza, HORMAD2 expression was up‐regulated in THCA cells and its overexpression can suppress thyroid cancer cell viability, mobility and invasiveness remarkably. Up‐regulation of HORMAD2 in THCA cells could prolong G0/G1 phase and shorten S phase to impede cell mitosis as well as promote thyroid cancer cells apoptosis. Furthermore, tumour formation assay showed that increased HORMAD2 level impeded tumour growth in vivo. Hypermethylation of HORMAD2 could induce THCA progression, while hypomethylation of HORMAD2 retard cell growth and mobility and facilitate apoptosis through increasing its mRNA expression.     

癌症DNA甲基化调控位点的识别

DNA甲基化是一种重要的表观遗传学修饰,在基因的转录调控方面具有重要的作用。异常的DNA甲基化可以导致癌症等复杂疾病发生,癌基因相关的DNA甲基化调控位点的识别对于解析癌症的发生发展机制及识别新的癌症标记具有重要意义。本研究通过整合The Cancer Genome Atlas(TCGA)的泛癌症基因组的高通量甲基化谱和基因表达谱,识别癌基因相关的DNA甲基化调控位点。对于每种癌症分批次计算Cp G位点甲基化与相关基因表达之间的相关性,并筛选调控下游基因的Cp G位点(包括强调控位点、弱调控位点和不调控位点),结果表明仅有一半的Cp G位点对下游基因具有调控作用;对癌症间共享的调控位点的分析发现不同癌症间共享的调控位点不尽相同,表明癌症特异的甲基化调控位点的存在。进一步地,对差异甲基化和差异表达基因的功能富集分析揭示了受甲基化调控的基因确实参与了癌症发生发展相关的功能。本研究的结果是对当前甲基化调控位点集的重要补充,也是识别癌症新型分子标记特征的重要资源。     

Comparison of DNA methylation measured by Illumina 450K and EPIC BeadChips in blood of newborns and 14-year-old children

Analysis of DNA methylation helps to understand the effects of environmental exposures as well as the role of epigenetics in human health. Illumina, Inc. recently replaced the HumanMethylation450 BeadChip (450K) with the EPIC BeadChip, which nearly doubles the measured CpG sites to >850,000. Although the new chip uses the same underlying technology, it is important to establish if data between the two platforms are comparable within cohorts and for meta-analyses. DNA methylation was assessed by 450K and EPIC using whole blood from newborn (n = 109) and 14-year-old (n = 86) participants of the Center for the Health Assessment of Mothers and Children of Salinas. The overall per-sample correlations were very high (r >0.99), although many individual CpG sites, especially those with low variance of methylation, had lower correlations (median r = 0.24). There was also a small subset of CpGs with large mean methylation β-value differences between platforms, in both the newborn and 14-year datasets. However, estimates of cell type proportion prediction by 450K and EPIC were highly correlated at both ages. Finally, differentially methylated positions between boys and girls replicated very well by both platforms in newborns and older children. These findings are encouraging for application of combined data from EPIC and 450K platforms for birth cohorts and other population studies. These data in children corroborate recent comparisons of the two BeadChips in adults and in cancer cell lines. However, researchers should be cautious when characterizing individual CpG sites and consider independent methods for validation of significant hits.     

奶牛产奶性状与乳房炎相关基因CpG含量及分布特征的比较分析

DNA甲基化是表观遗传学的重要组成部分,基因启动子区及第一外显子区的CpG甲基化通常抑制该基因的表达,而去甲基化则促进基因表达。已有的研究发现荷斯坦牛的乳房炎指标SCC(Somatic cell count)与产奶量呈较强负相关。文章分析并比较了这两类性状的相关基因的启动子区、第一外显子、下游2 000 bp序列中CpG含量及分布特征。结果表明,乳房炎相关基因的启动子、第一外显子中CpG含量显著低于产奶性状相关基因,而两类性状基因下游2 000 bp序列中CpG含量无显著性差异。另外,文中提出了两个量化基因序列中CpG特征的指标,一个是CpG平均距离,用来衡量序列中的CpG分布;另一个是条件概率p(G|C),用以量化序列中二核苷酸CpG随碱基C出现的可能性,并对两类基因的启动子和第一外显子区域的这两个指标做了统计检验。研究结果对产奶性状与乳房炎相关基因的DNA甲基化调控研究奠定了基础。     

Microarray-based methylation analysis using dual-color fluorescence hybridization

BACKGROUND: Aberrant DNA methylation of CpG sites is among the earliest and most frequent alterations in cancer. It is of great importance to develop simple, high-throughput and quantitative methods for methylation detection. METHODS: A high-throughput methylation analysis method has been developed based on microarray and dual-color fluorescence hybridization. The genomic DNA was treated with bisulfite, resulting in conversion of non-methylated cytosine, but not methylated cytosine, into uracil within CpG islands of interest. PCR products of the treated genomic templates were spotted and immobilized onto a poly-l-lysine coated glass slide to fabricate a microarray and then interrogated by hybridization with dual-color probes to determine the methylation status. The hybridized signals were obtained with a scanner and the results were analyzed with the software Genepix Pro 3.0. RESULTS: The methylation status of the CpG islands of IGFBP7 gene has been successfully evaluated by the microarray method for twenty-seven samples. All the investigated samples, including twenty human breast tumor tissues, six corresponding normal human breast tissues and one liver cell line, all CpG sites were found completely methylated. CONCLUSIONS: The microarray technology has been proven to have potential for high-throughput detection of the methylation status for a given gene in multi-genomic samples, which could be a novel approach for rapidly screening DNA methylation marker for early stage cancer diagnosis.     

Identification of thresholds for dichotomizing DNA methylation data

DNA methylation plays an important role in many biological processes by regulating gene expression. It is commonly accepted that turning on the DNA methylation leads to silencing of the expression of the corresponding genes. While methylation is often described as a binary on-off signal, it is typically measured using beta values derived from either microarray or sequencing technologies, which takes continuous values between 0 and 1. If we would like to interpret methylation in a binary fashion, appropriate thresholds are needed to dichotomize the continuous measurements. In this paper, we use data from The Cancer Genome Atlas project. For a total of 992 samples across five cancer types, both methylation and gene expression data are available. A bivariate extension of the StepMiner algorithm is used to identify thresholds for dichotomizing both methylation and expression data. Hypergeometric test is applied to identify CpG sites whose methylation status is significantly associated to silencing of the expression of their corresponding genes. The test is performed on either all five cancer types together or individual cancer types separately. We notice that the appropriate thresholds vary across different CpG sites. In addition, the negative association between methylation and expression is highly tissue specific.     

DNA Methylation-Dependent Epigenetic Regulation of Gene Expression in MCF-7 Breast Cancer Cells

To identify epigenetically-regulated genes in breast cancer, MCF-7 cells were exposed to 250nM 5-aza or 5-aza + 50nM TSA for 3 weeks followed by a 5 week recovery period after treatment withdrawal and gene expression patterns were examined by microarray analysis. We identified 20 genes that are associated with a >2-fold increase in expression in response to the demethylating treatment but returned to control levels after treatment withdrawal. RT-PCR verified that the genes identified were expressed at low or undetectable levels in control MCF-7 cells, but increased expression in treated cells. Most of these putative epigentically-regulated genes in MCF-7 cells do not contain CpG islands. In fact, these genes could be classified based upon their promoter CpG features, including genes with: (i) typical CpG features (CpG islands), (ii) intermediate CpG features (weak CpG islands), and (iii) atypical CpG features (no CpG islands). Prototype genes from each class (including CpG-deficient genes) were shown to be methylation-sensitive (subject to CpG methylation and responsive to demethylating agents), suggesting that not all gene targets of DNA methylation in breast cancer will contain a CpG island. Based upon the results of the current study and observations from the literature, we propose expansion of the current model for methylation-dependent regulation of gene expression to include genes lacking typical CpG islands. The expanded model we propose recognizes that all promoter CpG dinucleotides represent legitimate targets for DNA methylation and that the methylation of specific CpG dinucleotides in critical domains of regulatory regions can result in gene silencing.      

High-throughput method for detecting DNA methylation

Aberrant DNA methylation of CpG site is among the earliest and most frequent alterations in cancer. Detection of promoter hypermethylation of cancer-related gene may be useful for cancer diagnosis or the detection of recurrence. However, most of the studies have focused on a single gene only and gave little information about the concurrent methylation status of multiple genes. In this study, we attempted to develop a microarray method coupled with linker-PCR for detecting methylation status of multiple genes in the tumor tissue. A series of synthesized oligonucleotides were synthesised and purified to completely match with 16 investigated targets. Then they were immobilized on the aldehyde-coated glass slide to fabricate a DNA microarray for detecting methylation status of these genes. The results indicated that these genes were all methylated in the positive control. However, no methylated was found in these genes for the negative control. Only p16 and p15 genes were methylated in investigated genes for the gastric tumor tissue, whereas others were not methylated. The above results were validated by bisulfite DNA sequencing. Our experiments successfully demonstrated that the DNA microarray could be applied as a high-throughput tool to determine methylation status of the investigated genes.     

DNA-methylation profiling distinguishes malignant melanomas from benign nevi

DNA methylation, an epigenetic alteration typically occurring early in cancer development, could aid in the molecular diagnosis of melanoma. We determined technical feasibility for high-throughput DNA-methylation array-based profiling using formalin-fixed paraffin-embedded tissues for selection of candidate DNA-methylation differences between melanomas and nevi. Promoter methylation was evaluated in 27 common benign nevi and 22 primary invasive melanomas using a 1505 CpG site microarray. Unsupervised hierarchical clustering distinguished melanomas from nevi; 26 CpG sites in 22 genes were identified with significantly different methylation levels between melanomas and nevi after adjustment for age, sex, and multiple comparisons and with β-value differences of ≥ 0.2. Prediction analysis for microarrays identified 12 CpG loci that were highly predictive of melanoma, with area under the receiver operating characteristic curves of > 0.95. Of our panel of 22 genes, 14 were statistically significant in an independent sample set of 29 nevi (including dysplastic nevi) and 25 primary invasive melanomas after adjustment for age, sex, and multiple comparisons. This first report of a DNA-methylation signature discriminating melanomas from nevi indicates that DNA methylation appears promising as an additional tool for enhancing melanoma diagnosis.     

Epigenetic profiling and mRNA expression reveal candidate genes as biomarkers for colorectal cancer

Colorectal cancer (CRC) is characterized by DNA methylation, which is associated with genomic instability and tumor initiation. As an important epigenetic regulation, DNA methylation can be used as a potential therapeutic target for CRC. In our study, we downloaded DNA methylation profiles (GSE17648 and GSE29490) and RNA sequencing microarray data (GSE25070 and GSE32323) from the Gene Expression Omnibus (GEO) database. As a result, 14 aberrantly methylated differentially expressed genes (DEGs) were screened according to the different criteria. We further validated these DEGs in The Cancer Genome Atlas (TCGA) database and obtained Pearson's correlation coefficient (COR) for the relationship between gene expression and DNA methylation. Three candidate genes (SOX9, TCN1, and TGFBI) with COR greater than 0.3 were screened out as Hub genes. The receiver operating characteristic result indicated that SOX9 and TGFBI effectively serve as biomarkers for the early diagnosis of CRC. Furthermore, the potential prognosis of the Hub genes for CRC patients was evaluated. Only TGFBI, which is regulated by methylation, can predict patient disease-free survival. Additionally, we examined the methylation level of the Hub genes in CRC cells in the Cancer Cell Line Encyclopedia database. Considering that methylation status tends to be highly modified on CpG islands in tumorigenesis, we screened the CpG island methylation of TGFBI based on the TCGA database and verified its diagnostic value in the GEO database. Our result revealed two Hub genes (TCN1 and TGFBI) whose aberrant expressions were regulated by DNA methylation. Additionally, we uncovered the hypermethylation of TGFBI on CpG islands and its clinical value in the diagnosis of CRC.     

Identification of differentially methylated regions using streptavidin bisulfite ligand methylation enrichment (SuBLiME), a new method to enrich for methylated DNA prior to deep bisulfite genomic sequencing

We have developed a method that enriches for methylated cytosines by capturing the fraction of bisulfite-treated DNA with unconverted cytosines. The method, called streptavidin bisulfite ligand methylation enrichment (SuBLiME), involves the specific labeling (using a biotin-labeled nucleotide ligand) of methylated cytosines in bisulfite-converted DNA. This step is then followed by affinity capture, using streptavidin-coupled magnetic beads. SuBLiME is highly adaptable and can be combined with deep sequencing library generation and/or genomic complexity-reduction. In this pilot study, we enriched methylated DNA from Csp6I-cut complexity-reduced genomes of colorectal cancer cell lines (HCT-116, HT-29 and SW-480) and normal blood leukocytes with the aim of discovering colorectal cancer biomarkers. Enriched libraries were sequenced with SOLiD-3 technology. In pairwise comparisons, we scored a total of 1,769 gene loci and 33 miRNA loci as differentially methylated between the cell lines and leukocytes. Of these, 516 loci were differently methylated in at least two promoter-proximal CpG sites over two discrete Csp6I fragments. Identified methylated gene loci were associated with anatomical development, differentiation and cell signaling. The data correlated with good agreement to a number of published colorectal cancer DNA methylation biomarkers and genomic data sets. SuBLiME is effective in the enrichment of methylated nucleic acid and in the detection of known and novel biomarkers.