Restriction landmark genome scanning

Restriction landmark genome scanning (RLGS) is a quantitative approach that is uniquely suited for simultaneously assessing the methylation status of thousands of CpG islands. RLGS separates radiolabeled NotI fragments (or other CpG-containing restriction enzyme fragments) in two dimensions and allows distinction of single-copy CpG islands from multicopy CpG-rich sequences. The methylation sensitivity of the endonuclease activity of NotI provides the basis for differential methylation analysis, and NotI sites occur primarily in CpG islands and genes. RLGS has been used to identify novel imprinted genes, novel targets of DNA amplification and methylation in human cancer, and to identify deletion, methylation, and gene amplification in a mouse model of tumorigenesis. Such massively parallel analyses are critical for pattern recognition within and between tumor types, and for estimating the overall influence of CpG island methylation on the cancer cell genome. RLGS is also a useful method for integrating methylation analyses with high-resolution gene copy number analyses.     

Comparative genome-wide DNA methylation analysis of colorectal tumor and matched normal tissues

Aberrant DNA methylation often occurs in colorectal cancer (CRC). In our study we applied a genome-wide DNA methylation analysis approach, MethylCap-seq, to map the differentially methylated regions (DMRs) in 24 tumors and matched normal colon samples. In total, 2687 frequently hypermethylated and 468 frequently hypomethylated regions were identified, which include potential biomarkers for CRC diagnosis. Hypermethylation in the tumor samples was enriched at CpG islands and gene promoters, while hypomethylation was distributed throughout the genome. Using epigenetic data from human embryonic stem cells, we show that frequently hypermethylated regions coincide with bivalent loci in human embryonic stem cells. DNA methylation is commonly thought to lead to gene silencing; however, integration of publically available gene expression data indicates that 75% of the frequently hypermethylated genes were most likely already lowly or not expressed in normal tissue. Collectively, our study provides genome-wide DNA methylation maps of CRC, comprehensive lists of DMRs, and gives insights into the role of aberrant DNA methylation in CRC formation.     

Comparative genome-wide DNA methylation analysis of colorectal tumor and matched normal tissues

Aberrant DNA methylation often occurs in colorectal cancer (CRC). In our study we applied a genome-wide DNA methylation analysis approach, MethylCap-seq, to map the differentially methylated regions (DMRs) in 24 tumors and matched normal colon samples. In total, 2687 frequently hypermethylated and 468 frequently hypomethylated regions were identified, which include potential biomarkers for CRC diagnosis. Hypermethylation in the tumor samples was enriched at CpG islands and gene promoters, while hypomethylation was distributed throughout the genome. Using epigenetic data from human embryonic stem cells, we show that frequently hypermethylated regions coincide with bivalent loci in human embryonic stem cells. DNA methylation is commonly thought to lead to gene silencing; however, integration of publically available gene expression data indicates that 75% of the frequently hypermethylated genes were most likely already lowly or not expressed in normal tissue. Collectively, our study provides genome-wide DNA methylation maps of CRC, comprehensive lists of DMRs, and gives insights into the role of aberrant DNA methylation in CRC formation.     

Genome-scale analysis of DNA methylation in colorectal cancer using Infinium HumanMethylation450 BeadChips

Illumina’s Infinium HumanMethylation450 BeadChip arrays were used to examine genome-wide DNA methylation profiles in 22 sample pairs from colorectal cancer (CRC) and adjacent tissues and 19 colon tissue samples from cancer-free donors. We show that the methylation profiles of tumors and healthy tissue samples can be clearly distinguished from one another and that the main source of methylation variability is associated with disease status. We used different statistical approaches to evaluate the methylation data. In general, at the CpG-site level, we found that common CRC-specific methylation patterns consist of at least 15,667 CpG sites that were significantly different from either adjacent healthy tissue or tissue from cancer-free subjects. Of these sites, 10,342 were hypermethylated in CRC, and 5,325 were hypomethylated. Hypermethylated sites were common in the maximum number of sample pairs and were mostly located in CpG islands, where they were significantly enriched for differentially methylated regions known to be cancer-specific. In contrast, hypomethylated sites were mostly located in CpG shores and were generally sample-specific. Despite the considerable variability in methylation data, we selected a panel of 14 highly robust candidates showing methylation marks in genes SND1, ADHFE1, OPLAH, TLX2, C1orf70, ZFP64, NR5A2, and COL4A. This set was successfully cross-validated using methylation data from 209 CRC samples and 38 healthy tissue samples from The Cancer Genome Atlas consortium (AUC = 0.981 [95% CI: 0.9677–0.9939], sensitivity = 100% and specificity = 82%). In summary, this study reports a large number of loci with novel differential methylation statuses, some of which may serve as candidate markers for diagnostic purposes.     

Methylation detection oligonucleotide microarray analysis: a high-resolution method for detection of CpG island methylation

Methylation of CpG islands associated with genes can affect the expression of the proximal gene, and methylation of non-associated CpG islands correlates to genomic instability. This epigenetic modification has been shown to be important in many pathologies, from development and disease to cancer. We report the development of a novel high-resolution microarray that detects the methylation status of over 25 000 CpG islands in the human genome. Experiments were performed to demonstrate low system noise in the methodology and that the array probes have a high signal to noise ratio. Methylation measurements between different cell lines were validated demonstrating the accuracy of measurement. We then identified alterations in CpG islands, both those associated with gene promoters, as well as non-promoter-associated islands in a set of breast and ovarian tumors. We demonstrate that this methodology accurately identifies methylation profiles in cancer and in principle it can differentiate any CpG methylation alterations and can be adapted to analyze other species.     

Identifying hypermethylated CpG islands using a quantile regression model

Background  

DNA methylation has been shown to play an important role in the silencing of tumor suppressor genes in various tumor types. In order to have a system-wide understanding of the methylation changes that occur in tumors, we have developed a differential methylation hybridization (DMH) protocol that can simultaneously assay the methylation status of all known CpG islands (CGIs) using microarray technologies. A large percentage of signals obtained from microarrays can be attributed to various measurable and unmeasurable confounding factors unrelated to the biological question at hand. In order to correct the bias due to noise, we first implemented a quantile regression model, with a quantile level equal to 75%, to identify hypermethylated CGIs in an earlier work. As a proof of concept, we applied this model to methylation microarray data generated from breast cancer cell lines. However, we were unsure whether 75% was the best quantile level for identifying hypermethylated CGIs. In this paper, we attempt to determine which quantile level should be used to identify hypermethylated CGIs and their associated genes.     

DNA methylome profiling identifies novel methylated genes in African American patients with colorectal neoplasia

The identification of genes that are differentially methylated in colorectal cancer (CRC) has potential value for both diagnostic and therapeutic interventions specifically in high-risk populations such as African Americans (AAs). However, DNA methylation patterns in CRC, especially in AAs, have not been systematically explored and remain poorly understood. Here, we performed DNA methylome profiling to identify the methylation status of CpG islands within candidate genes involved in critical pathways important in the initiation and development of CRC. We used reduced representation bisulfite sequencing (RRBS) in colorectal cancer and adenoma tissues that were compared with DNA methylome from a healthy AA subject’s colon tissue and peripheral blood DNA. The identified methylation markers were validated in fresh frozen CRC tissues and corresponding normal tissues from AA patients diagnosed with CRC at Howard University Hospital. We identified and validated the methylation status of 355 CpG sites located within 16 gene promoter regions associated with CpG islands. Fifty CpG sites located within CpG islands—in genes ATXN7L1 (2), BMP3 (7), EID3 (15), GAS7 (1), GPR75 (24), and TNFAIP2 (1)—were significantly hypermethylated in tumor vs. normal tissues (P < 0.05). The methylation status of BMP3, EID3, GAS7, and GPR75 was confirmed in an independent, validation cohort. Ingenuity pathway analysis mapped three of these markers (GAS7, BMP3 and GPR) in the insulin and TGF-β1 network—the two key pathways in CRC. In addition to hypermethylated genes, our analysis also revealed that LINE-1 repeat elements were progressively hypomethylated in the normal-adenoma-cancer sequence. We conclude that DNA methylome profiling based on RRBS is an effective method for screening aberrantly methylated genes in CRC. While previous studies focused on the limited identification of hypermethylated genes, ours is the first study to systematically and comprehensively identify novel hypermethylated genes, as well as hypomethylated LINE-1 sequences, which may serve as potential biomarkers for CRC in African Americans. Our discovered biomarkers were intimately linked to the insulin/TGF-B1 pathway, further strengthening the association of diabetic disorders with colon oncogenic transformation.     

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.     

DNA methylome profiling identifies novel methylated genes in African American patients with colorectal neoplasia

The identification of genes that are differentially methylated in colorectal cancer (CRC) has potential value for both diagnostic and therapeutic interventions specifically in high-risk populations such as African Americans (AAs). However, DNA methylation patterns in CRC, especially in AAs, have not been systematically explored and remain poorly understood. Here, we performed DNA methylome profiling to identify the methylation status of CpG islands within candidate genes involved in critical pathways important in the initiation and development of CRC. We used reduced representation bisulfite sequencing (RRBS) in colorectal cancer and adenoma tissues that were compared with DNA methylome from a healthy AA subject’s colon tissue and peripheral blood DNA. The identified methylation markers were validated in fresh frozen CRC tissues and corresponding normal tissues from AA patients diagnosed with CRC at Howard University Hospital. We identified and validated the methylation status of 355 CpG sites located within 16 gene promoter regions associated with CpG islands. Fifty CpG sites located within CpG islands—in genes ATXN7L1 (2), BMP3 (7), EID3 (15), GAS7 (1), GPR75 (24), and TNFAIP2 (1)—were significantly hypermethylated in tumor vs. normal tissues (P < 0.05). The methylation status of BMP3, EID3, GAS7, and GPR75 was confirmed in an independent, validation cohort. Ingenuity pathway analysis mapped three of these markers (GAS7, BMP3 and GPR) in the insulin and TGF-β1 network—the two key pathways in CRC. In addition to hypermethylated genes, our analysis also revealed that LINE-1 repeat elements were progressively hypomethylated in the normal-adenoma-cancer sequence. We conclude that DNA methylome profiling based on RRBS is an effective method for screening aberrantly methylated genes in CRC. While previous studies focused on the limited identification of hypermethylated genes, ours is the first study to systematically and comprehensively identify novel hypermethylated genes, as well as hypomethylated LINE-1 sequences, which may serve as potential biomarkers for CRC in African Americans. Our discovered biomarkers were intimately linked to the insulin/TGF-B1 pathway, further strengthening the association of diabetic disorders with colon oncogenic transformation.     

DNA methylation establishment of CpG islands near maternally imprinted genes on chromosome 7 during mouse oocyte growth

The genome methylation is globally erased in early fetal germ cells, and it is gradually re‐established during gametogenesis. The expression of some imprinted genes is regulated by the methylation status of CpG islands, while the exact time of DNA methylation establishment near maternal imprinted genes during oocyte growth is not well known. Here, growing oocytes were divided into three groups based on follicle diameters including the S‐group (60–100 μm), M‐group (100–140 μm), and L‐group (140–180 μm). The fully grown germinal vesicle (GV)‐stage and metaphase II (M2)‐stage mature oocytes were also collected. These oocytes were used for single‐cell bisulfite sequencing to detect the methylation status of CpG islands near imprinted genes on chromosome 7. The results showed that the CpG islands near Ndn, Magel2, Mkrn3, Peg12, and Igf2 were completely unmethylated, but those of Peg3, Snrpn, and Kcnq1ot1 were hypermethylated in MII‐stage oocytes. The methylation of CpG islands near different maternal imprinted genes occurred asynchronously, being completed in later‐stage growing oocytes, fully grown GV oocytes, and mature MII‐stage oocytes, respectively. These results show that CpG islands near some maternally imprinted genes are not necessarily methylated, and that the establishment of methylation of other maternally imprinted genes is completed at different stages of oocyte growth, providing a novel understanding of the establishment of maternally imprinted genes in oocytes.     

The CpG island methylator phenotype correlates with long-range epigenetic silencing in colorectal cancer

The CpG island methylator phenotype (CIMP), characterized by an exceptionally high frequency of methylation of discrete CpG islands, is observed in 18% to 25% of sporadic colorectal cancers. Another hypermethylation pattern found in colorectal cancers, termed long-range epigenetic silencing, is associated with DNA/histone methylation in three distinct gene clusters at chromosome 2q14.2, showing that DNA hypermethylation can span larger chromosomal domains and lead to the silencing of flanking, unmethylated genes. We investigated whether these two phenotypes are interrelated in colorectal cancers. The CIMP status of 148 sporadic colorectal cancers was determined by methylation-specific PCR. We determined the BRAF V600E mutation by mutant allele-specific PCR amplification. The methylation status of the MLH1 gene and of three CpG islands (EN1, SCTR, and INHBB), corresponding to three distinct clusters along 2q14.2, was determined by methylation-specific PCR. The average number of sites showing methylation in CIMP+ tumors was 2.21, compared with 1.22 for CIMP- individuals, and this difference was highly significant (P = 3.6 x 10(-8), Mann-Whitney test). Moreover, all CIMP+ tumors showed hypermethylation of at least one of these loci, in contrast to CIMP- tumors, where 18 (16%) samples remained unmethylated. The mean number of simultaneously hypermethylated CpG islands at 2q14.2 differs significantly between CIMP- and CIMP+ tumors, suggesting varying effects of domain silencing in this region. Given that the number of hypermethylated loci at 2q14.2 likely affects the range of silenced flanking genes, high frequency of simultaneous hypermethylation of three CpG islands (EN1, SCTR, and INHBB) may have potential influence on specific characteristics of CIMP+ colorectal cancers.     

Detection method for methylation density on microarray using methyl-CpG-binding domain protein

A method for determining methylation density of target CpG islands has been established. In the method, DNA microarray was prepared by spotting a set of PCR products amplified from bisulfite-converted sample DNAs. The PCR products on the microarray were treated by SssI methyltransferase and labeled with TAMRA fluorescence. A recombinant, antibody-like methyl-CpG-binding protein labeled with Cy5 fluorescence was used to identify symmetrical methyl-CpG dinucleotide of the PCR products on the microarray. By use of a standard curve with control mixtures, the ratio of two fluorescence signals can be converted into percentage values to assess methylation density of targeted fragments. We obtained the methylation density of six CpG islands on the two tumor suppressor genes of CDK2A and CDK2B from seven cancer cell line samples and two normal blood samples. The validity of this method was tested by bisulfite sequencing. This method not only allows the quantitative analysis of regional methylation density of a set of given genes but also could provide information of methylation density for a large amount of clinical samples.