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Differential methylation hybridization (DMH) is a high-throughput DNA methylation screening tool that utilizes methylation-sensitive restriction enzymes to profile methylated fragments by hybridizing them to a CpG island microarray. This array contains probes spanning all the 27,800 islands annotated in the UCSC Genome Browser. Herein we describe a revised DMH protocol with clearly identified quality control points. In this manner, samples that are unlikely to provide good readouts for differential methylation profiles between the test and the control samples will be identified and repeated with appropriate modifications. In addition to the step-by-step laboratory DMH protocol, we also provide a detailed description regarding DMH data analysis. The suggested microarray platform contains 244,000 probes and it can be a daunting barrier for researchers with no prior experience in analyzing DNA methylation data. We have created a data analysis pipeline available in a user friendly, publicly available interface, the Broad Institute's GenePattern software, which can be accessed at http://bisr.osumc.edu :8080/gp. This permits scientists to use our existing data analysis modules on their own data. As we continue to update our analysis algorithm and approaches to integrate high-throughput methylation data with other large-scale data types, we will make these new computation protocols available through the GenePattern platform.

Transforming growth factor-beta (TGF-beta)/SMAD signaling is a key growth regulatory pathway often dysregulated in ovarian cancer and other malignancies. Although loss of TGF-beta-mediated growth inhibition has been shown to contribute to aberrant cell behavior, the epigenetic consequence(s) of impaired TGF-beta/SMAD signaling on target genes is not well established. In this study, we show that TGF-beta1 causes growth inhibition of normal ovarian surface epithelial cells, induction of nuclear translocation SMAD4, and up-regulation of ADAM19 (a disintegrin and metalloprotease domain 19), a newly identified TGF-beta1 target gene. Conversely, induction and nuclear translocation of SMAD4 were negligible in ovarian cancer cells refractory to TGF-beta1 stimulation, and ADAM19 expression was greatly reduced. Furthermore, in the TGF-beta1 refractory cells, an inactive chromatin environment, marked by repressive histone modifications (trimethyl-H3K27 and dimethyl-H3K9) and histone deacetylase, was associated with the ADAM19 promoter region. However, the CpG island found within the promoter and first exon of ADAM19 remained generally unmethylated. Although disrupted growth factor signaling has been linked to epigenetic gene silencing in cancer, this is the first evidence demonstrating that impaired TGF-beta1 signaling can result in the formation of a repressive chromatin state and epigenetic suppression of ADAM19. Given the emerging role of ADAMs family proteins in growth factor regulation in normal cells, we suggest that epigenetic dysregulation of ADAM19 may contribute to the neoplastic process in ovarian cancer.

INTRODUCTIONThis protocol describes the use of methylated CpG island amplification (MCA) in combination with a microarray platform to analyze genome-wide DNA methylation in a high-throughput fashion. In this approach, termed MCAM, methylated CpG islands are selectively targeted using oligonucleotide adaptors after two rounds of digestion with a combination of methylation-sensitive and methylation-insensitive nucleases. They are then amplified using PCR. The resulting amplicons, representing the methylated fraction of the genome, are labeled with fluorochromes. Subsequently, a comparative hybridization of reference and test samples (typically normal and tumor DNA specimens) is done on a microarray platform.

We present the implementation of an application using caGrid, which is the service-oriented Grid software infrastructure of the NCI cancer Biomedical Informatics Grid (caBIG), to support design and analysis of custom microarray experiments in the study of epigenetic alterations in cancer. The design and execution of these experiments requires synthesis of information from multiple data types and datasets. In our implementation, each data source is implemented as a caGrid Data Service, and analytical resources are wrapped as caGrid Analytical Services. This service-based implementation has several advantages. A backend resource can be modified or upgraded, without needing to change other components in the application. A remote resource can be added easily, since resources are not required to be collected in a centralized infrastructure.

In breast cancer and normal estrogen target tissues, estrogen receptor-alpha (ERalpha) signaling results in the establishment of spatiotemporal patterns of gene expression. Whereas primary target gene regulation by ERalpha involves recruitment of coregulatory proteins, coactivators, or corepressors, activation of these downstream promoters by receptor signaling may also involve partnership of ERalpha with other transcription factors. By using an integrated, genome-wide approach that involves ChIP-chip and computational modeling, we uncovered 13 ERalpha-responsive promoters containing both ERalpha and c-MYC binding elements located within close proximity (13-214 bp) to each other. Estrogen stimulation enhanced the c-MYC-ERalpha interaction and facilitated the association of ERalpha, c-MYC, and the coactivator TRRAP with these estrogen-responsive promoters, resulting in chromatin remodeling and increased transcription. These results suggest that ERalpha and c-MYC physically interact to stabilize the ERalpha-coactivator complex, thereby permitting other signal transduction pathways to fine-tune estrogen-mediated signaling networks.

In a microarray-based methylation analysis of astrocytomas [World Health Organization (WHO) grade II], we identified a CpG island within the first exon of the protocadherin-gamma subfamily A11 (PCDH-gamma-A11) gene that showed hypermethylation compared to normal brain tissue. Bisulfite sequencing and combined bisulfite restriction analysis (COBRA) was performed to screen low- and high-grade astrocytomas for the methylation status of this CpG island. Hypermethylation was detected in 30 of 34 (88%) astrocytomas (WHO grades II and III), 20 of 23 (87%) glioblastomas (WHO grade IV), and 8 of 8 (100%) glioma cell lines. There was a highly significant correlation (P = .00028) between PCDH-gamma-A11 hypermethylation and decreased transcription as determined by competitive reverse transcription polymerase chain reaction in WHO grades II and III astrocytomas. After treatment of glioma cell lines with a demethylating agent, transcription of PCDH-gamma-A11 was restored. In summary, we have identified PCDH-gamma-A11 as a new target silenced epigenetically in astrocytic gliomas. The inactivation of this cell-cell contact molecule might be involved in the invasive growth of astrocytoma cells into normal brain parenchyma.

Hypermethylation of CpG island is an epigenetic event prevalent in human gliomas. Here we employed a high-throughput microarray approach for a global search of DNA methylation to identify novel epigenetic loci in specific glioma subtypes. Hierarchical clustering analysis separated 20 glioma samples according to their WHO histopathological subtypes - pilocytic astrocytomas (PAs, grade I), oligoastrocytomas (OAs, grade II) and glioblastomas (GBMs, grade IV), based on their unique methylation patterns. The overall methylation frequency of the low-grade PAs was significantly less than that of the more aggressive OAs and GBMs (0.45% versus 2.0% and 1.4%; PAs versus OAs, p<0.01; PAs versus GBMs, p<0.01). The lower level of DNA methylation observed in PAs may be in part due to the increased methylation of multiple CpG islands which occur in more advanced tumors. However, the young age of onset of PAs may also contribute to this observed difference. Although there were many hypermethylated loci exclusive to the OA and GBM subtypes, the methylation frequencies between these groups were not significantly different. Analysis by methylation-specific PCR on an expanded set of samples and on more glioma subtypes further confirmed an epigenetic marker, SMARCA5, the hypermethylation of which was preferentially observed in grade IV, but not in grades I or II gliomas (p<0.0001). The intermediate grade III gliomas showed low levels of SMARCA5 hypermethylation. Epigenetic loci uncovered in the present study recapitulate the histopathological differences of these gliomas, indicating that these molecular changes may be responsible for the development of the different glioma subtypes. On-going work in our laboratory has shown that some of these loci are indeed hypermethylated in the early stages of astrocytic tumors., (Copyright© 2004 International Institute of Anticaner Research (Dr. John G. Delinassios), All rights reserved.)

The methylation-specific oligonucleotide (MSO) microarray is a high-throughput approach capable of detecting DNA methylation in genes across several CpG sites. Based on the bisulfite modification of DNA that converts unmethylated cytosines to uracil but leaves the 5'methylcytosine intact, the method utilizes short oligonucleotides corresponding to the methylated and unmethylated alleles as probes affixed on solid support and products amplified from bisulfite-treated DNA as targets for hybridization. MSO is suitable for examining a panel of genes across multiple clinical samples. This approach can generate a robust dataset for discovering profiles of gene methylation in cancer with aberrant DNA methylation in the neoplastic genome and widespread hypermethylation in tumor suppressor genes. MSO and other oligonucleotide-based arrays have been applied successfully for analyses of single genes and have been useful in delineating and predicting tumor subgroups using clustering methods. Here we focus on design criteria important to the interrogation of multiple CpG sites across several genes.

Small interfering RNAs (siRNAs) are newly identified molecules shown to silence genes via targeted mRNA degradation. In this study, we used specific siRNAs as a tool to probe the relationship between two DNA methyltransferase genes, DNMT3b and DNMT1, in the maintenance of DNA methylation patterns in the genome. Levels of DNMT3b or DNMT1 mRNAs and proteins were markedly decreased (up to 80%) on transfecting these siRNAs into the ovarian cancer cell line CP70. The resulting RNA interference showed differential effects on DNA demethylation and gene reactivation in the treated cells. The DNMT1 siRNA treatment led to a partial removal of DNA methylation from three inactive promoter CpG islands, TWIST, RASSF1A, and HIN-1, and restored the expression of these genes. This epigenetic alteration appeared less effective in cells transfected with DNMT3b siRNA. However, the combined treatment of DNMT3b and DNMT1 siRNAs greatly enhanced this demethylation effect, producing 7-15-fold increases in their expression. We also used a microarray approach to examine this RNA interference on 8640 CpG island loci in CP70 cells. The combined siRNA treatment had a greater demethylation effect on 241 methylated loci and selected repetitive sequences than that of the single treatment. Our data thus suggest that whereas DNMT1 plays a key role in methylation maintenance, DNMT3b may act as an accessory to support the function in CP70 cells. This study also shows that siRNA is a powerful tool for interrogating the mechanisms of DNA methylation in normal and pathological genomes.

Aberrant DNA methylation of promoter CpG islands is associated with transcriptionally repressive heterochromatin in neoplasia. The dynamics of this epigenetic process in mediating the transition from an active to an inactive state of transcription remains to be elucidated, however. Here, we used the methylation-specific oligonucleotide microarray to map the methylation patterns of a CpG island, located within the promoter and the first exon regions of RASSF1A, in normal breast tissue controls, primary tumors, and breast cancer cell lines. Oligonucleotide pairs, spaced along the CpG island region, were designed to discriminate between methylated and unmethylated alleles of selected sites. The methylation-specific oligonucleotide data indicate that the majority of test samples show widespread methylation in the first exon of RASSF1A. In contrast, the promoter area was usually undermethylated in normal controls and in 32% of the primary tumors tested, whereas the rest of the primary tumors and breast cancer cell lines showed various degrees of methylation in the region. Methylation profiling of individual tumors further suggest that DNA methylation progressively spreads from the first exon into the promoter area of this gene. Functional analysis indicates that increased density of RASSF1A promoter methylation is associated with altered chromatin, marked by a depletion of acetylated histones and methylated histone 3-lysine 4 and an enrichment of methylated histone 3-lysine 9 in the studied area. The combination of these epigenetic modifications may engender a stable silencing of the gene in breast cancer cells. Thus, this study underscores the importance of detailed mapping of methylation patterns within a CpG island locus that may provide insights into the progressive nature of aberrant DNA methylation and its relationship with transcriptional silencing during the neoplastic process.

We developed a novel microarray system to assess gene expression, DNA methylation, and histone acetylation in parallel, and to dissect the complex hierarchy of epigenetic changes in cancer. An integrated microarray panel consisting of 1507 short CpG island tags located at the 5'-end regions (including the first exons) was used to assess effects of epigenetic treatments on a human epithelial ovarian cancer cell line. Treatment with methylation (5-aza-2'-deoxycytidine) or deacetylation (trichostatin A) inhibitors alone resulted in up-regulation of 1.9 or 1.1% of the genes analyzed; however, the combined treatment resulted in synergistic reactivation of more genes (10.4%; P < 0.001 versus either treatment alone). On the basis of either primary or secondary responses to the treatments, genes were identified as methylation-dependent or -independent. Synergistic reactivation of the methylation-dependent genes by 5-aza-2'-deoxycytidine plus trichostatin A revealed a functional interaction between methylated promoters and deacetylated histones. Increased expression of some methylation-independent genes was associated with enhanced histone acetylation, but up-regulation of most of the genes identified using this technology was because of events downstream of the epigenetic cascade. We demonstrate proof of principle for using the triple microarray system in analyzing the dynamic relationship between transcription factors and promoter targets in cancer genomes.

Purpose: The purpose of this study was to profile methylation alterations of CpG islands in ovarian tumors and to identify candidate markers for diagnosis and prognosis of the disease., Experimental Design: A global analysis of DNA methylation using a novel microarray approach called differential methylation hybridization was performed on 19 patients with stage III and IV ovarian carcinomas., Results: Hierarchical clustering identified two groups of patients with distinct methylation profiles. Tumors from group 1 contained high levels of concurrent methylation, whereas group 2 tumors had lower tumor methylation levels. The duration of progression-free survival after chemotherapy was significantly shorter for patients in group 1 compared with group 2 (P < 0.001). Differential methylation in tumors was independently confirmed by methylation-specific PCR., Conclusions: The data suggest that a higher degree of CpG island methylation is associated with early disease recurrence after chemotherapy. The differential methylation hybridization assay also identified a select group of CpG island loci that are potentially useful as epigenetic markers for predicting treatment outcome in ovarian cancer patients.

We present a novel concept by using expressed CpG island sequence tags (ECISTs)for dual analysis of DNA methylation and gene expression in cancer cells. ECISTs are present in the genome and are DNA fragments expected to be located in the promoter and first exon region of genes. Their GC-rich segments can be used for screening hypermethylated CpG sites in cancer cells, and their exon-containing portions can be used for measuring levels of the corresponding transcripts. A total of 1162 loci met the criteria of ECISTs from an initial screening of 7776 CpG island tags. This ECIST panel was used to analyze the breast cancer cell line MDA-MB-231, which was treated with a demethylating agent. Microarray profile analysis identified 30 methylation-silenced genes, the expression of which could be directly reactivated by demethylation. An additional group of 96 up-regulated genes was also identified but appeared to be downstream from this epigenetic cascade. Thus, this study shows that the ECIST microarray can be used to differentiate the primary and secondary causes of demethylation and provides an effective tool to elucidate the mechanisms of aberrant DNA methylation in cancer.

Previously, identification of promoters regulated by mammalian transcription factors has relied upon overexpression studies. Here we present the identification of a large set of promoters that are bound by E2F in physiological conditions. Probing a human CpG microarray with chromatin immunoprecipitated using an antibody to E2F4, we have identified 68 unique target loci; 15% are bidirectional promoters and 25% recruit E2F via a mechanism distinct from the defined consensus site. Interestingly, although E2F has been shown previously to regulate genes involved in cell cycle progression, many of the new E2F target genes encode proteins involved in DNA repair or recombination. We suggest that human CpG microarrays, in combination with chromatin immunoprecipitation, will allow rapid identification of target promoters for many mammalian transcription factors.