Prognostic DNA methylation biomarkers in ovarian cancer.

PURPOSE: Aberrant DNA methylation, now recognized as a contributing factor to neoplasia, often shows definitive gene/sequence preferences unique to specific cancer types. Correspondingly, distinct combinations of methylated loci can function as biomarkers for numerous clinical correlates of ovarian and other cancers. EXPERIMENTAL DESIGN: We used a microarray approach to identify methylated loci prognostic for reduced progression-free survival (PFS) in advanced ovarian cancer patients. Two data set classification algorithms, Significance Analysis of Microarray and Prediction Analysis of Microarray, successfully identified 220 candidate PFS-discriminatory methylated loci. Of those, 112 were found capable of predicting PFS with 95% accuracy, by Prediction Analysis of Microarray, using an independent set of 40 advanced ovarian tumors (from 20 short-PFS and 20 long-PFS patients, respectively). Additionally, we showed the use of these predictive loci using two bioinformatics machine-learning algorithms, Support Vector Machine and Multilayer Perceptron. CONCLUSION: In this report, we show that highly prognostic DNA methylation biomarkers can be successfully identified and characterized, using previously unused, rigorous classifying algorithms. Such ovarian cancer biomarkers represent a promising approach for the assessment and management of this devastating disease.

Hypermethylation of 18S and 28S ribosomal DNAs predicts progression-free survival in patients with ovarian cancer.

PURPOSE: Repetitive ribosomal DNA (rDNA) genes are GC-rich clusters in the human genome. The aim of the study was to determine the methylation status of two rDNA subunits, the 18S and 28S genes, in ovarian tumors and to correlate methylation levels with clinicopathologic features in a cohort of ovarian cancer patients. EXPERIMENTAL DESIGN: 18S and 28S rDNA methylation was examined by quantitative methylation-specific PCR in 74 late-stage ovarian cancers, 9 histologically uninvolved, and 11 normal ovarian surface epithelial samples. In addition, methylation and gene expression levels of 18S and 28S rDNAs in two ovarian cancer cell lines were examined by reverse transcription-PCR before and after treatment with the demethylating drug 5'-aza-2'-deoxycytidine. RESULTS: The methylation level (amount of methylated rDNA/beta-actin) of 18S and 28S rDNAs was significantly higher (P < 0.05) in tumors than in normal ovarian surface epithelial samples. Methylation of 18S and 28S rDNA was highly correlated (R2= 0.842). Multivariate analysis by Cox regression found that rDNA hypermethylation [hazard ratio (HR), 0.25; P < 0.01], but not age (HR, 1.29; P = 0.291) and stage (HR, 1.09; P = 0.709), was independently associated with longer progression-free survival. In ovarian cancer cell lines, methylation levels of rDNA correlated with gene down-regulation and 5'-aza-2'-deoxycytidine treatment resulted in a moderate increase in 18S and 28S rDNA gene expressions. CONCLUSION: This is the first report of rDNA hypermethylation in ovarian tumors. Furthermore, rDNA methylation levels were higher in patients with long progression-free survival versus patients with short survival. Thus, rDNA methylation as a prognostic marker in ovarian cancer warrants further investigation.

Triple analysis of the cancer epigenome: an integrated microarray system for assessing gene expression, DNA methylation, and histone acetylation.

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.

Double RNA interference of DNMT3b and DNMT1 enhances DNA demethylation and gene reactivation.

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.

Loss of estrogen receptor signaling triggers epigenetic silencing of downstream targets in breast cancer.

Alterations in histones, chromatin-related proteins, and DNA methylation contribute to transcriptional silencing in cancer, but the sequence of these molecular events is not well understood. Here we demonstrate that on disruption of estrogen receptor (ER) alpha signaling by small interfering RNA, polycomb repressors and histone deacetylases are recruited to initiate stable repression of the progesterone receptor (PR) gene, a known ERalpha target, in breast cancer cells. The event is accompanied by acquired DNA methylation of the PR promoter, leaving a stable mark that can be inherited by cancer cell progeny. Reestablishing ERalpha signaling alone was not sufficient to reactivate the PR gene; reactivation of the PR gene also requires DNA demethylation. Methylation microarray analysis further showed that progressive DNA methylation occurs in multiple ERalpha targets in breast cancer genomes. The results imply, for the first time, the significance of epigenetic regulation on ERalpha target genes, providing new direction for research in this classical signaling pathway.

Methylation microarray analysis of late-stage ovarian carcinomas distinguishes progression-free survival in patients and identifies candidate epigenetic markers.

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.

Structure and Macromolecular Composition of the Egg and Embryo Jelly Coats of the Anuran Lepidobatrachus laevis: (frog jelly coat/fertilization/glycoprotein).

Eggs and cleavage-stage embryos of the frog Lepidobatrachus laevis are encased by 3 µm thick vitelline/fertilization envelope and two jelly layers, termed J1 (innermost) and J2 (outermost). Based on light and transmission electron microscopy, J1 had a dense reticular appearance whereas J2 had a laminar structure. Direct dissolution of the jelly coats was accomplished by reduction of disulfide bonds with 0.08 M 2-mercaptoethanol at pH 10. Soluble jelly preparations were uncontaminated with nucleic acid (A280 /A260 =1.44) and yielded an average of 150 µg protein/egg or embryo (n=5). The biochemical composition of the jelly coats in unfertilized eggs was different from that in embryos. When examined via gel permeation chromatography, soluble jelly from unfertilized eggs contained macromolecules which were markedly larger and more heterogeneous (earlier eluting and broader peaks) than jelly from embryos. Differences in the components of jelly from unfertilized eggs and embryos were also observed by electrophoresis, however, a 29,700 molecular weight glycoprotein chain was common to both jelly preparations. The electrophoretic pattern of jelly obtained from parthenogenetically activated eggs was identical to that of unfertilized eggs, therefore the fertilization-associated changes are not due to the exclusive action of cortical granule products.

Aberrant DNA methylation in ovarian cancer: is there an epigenetic predisposition to drug response?

Epigenetic regulation of gene expression has been observed in a variety of tumor types. We have used microarray technology to evaluate the predisposition of drug response by aberrant methylation in ovarian cancer. Results indicate that loss of gene activity due to hypermethylation potentially confers a predisposition in certain cancer types and is an early event in disease progression. Methylation profiles of ovarian cancer might be useful for early cancer detection and prediction of chemotherapy outcome in a clinical context.

Methylation-specific oligonucleotide microarray.

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.

Applications of CpG island microarrays for high-throughput analysis of DNA methylation.

Differential methylation hybridization (DMH) is a high-throughput microarray technique designed to identify changes in DNA methylation patterns commonly observed in cancer and other disease states. The DMH methodology comprises three fundamental components: the arraying of CpG island clones on glass slides, the preparation of the sample amplicons under investigation, and the hybridization of amplicon targets onto the CpG island microarray. Herein, we outline the DMH protocol and illustrate its utility and the validation approaches used in analyzing the hypermethylation profile of breast tumor and normal samples.

Methylation target array for rapid analysis of CpG island hypermethylation in multiple tissue genomes.

Hypermethylation of multiple CpG islands is a common event in cancer. To assess the prognostic values of this epigenetic alteration, we developed Methylation Target Array (MTA), derived from the concept of tissue microarray, for simultaneous analysis of DNA hypermethylation in hundreds of tissue genomes. In MTA, linker-ligated CpG island fragments were digested with methylation-sensitive endonucleases and amplified with flanking primers. A panel of 468 MTA amplicons, which represented the whole repertoire of methylated CpG islands in 93 breast tumors, 20 normal breast tissues, and 4 breast cancer cell lines, were arrayed on nylon membrane for probe hybridization. Positive hybridization signals detected in tumor amplicons, but not in normal amplicons, were indicative of aberrant hypermethylation in tumor samples. This is attributed to aberrant sites that were protected from methylation-sensitive restriction and were amplified by PCR in tumor samples, while the same sites were restricted and could not be amplified in normal samples. Hypermethylation frequencies of the 10 genes tested in breast tumors and cancer cell lines were 60% for GPC3, 58% for RASSF1A, 32% for 3OST3B, 30% for HOXA5, 28% for uPA, 25% for WT1, 23% for BRCA1, 9% for DAPK1, and 0% for KL. Furthermore, hypermethylation of 5 to 7 loci of these genes was significantly correlated with hormone receptor status, clinical stages, and ages at diagnosis of the patients analyzed. This novel approach thus provides an additional avenue for assessing clinicopathological consequences of DNA hypermethylation in breast cancer.