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More than one million prostate biopsies are performed in the United States every year. A failure to find cancer is not definitive in a significant percentage of patients due to the presence of equivocal structures or continuing clinical suspicion. We have identified gene expression changes in stroma that can detect tumor nearby. We compared gene expression profiles of 13 biopsies containing stroma near tumor and 15 biopsies from volunteers without prostate cancer. About 3,800 significant expression changes were found and thereafter filtered using independent expression profiles to eliminate possible age-related genes and genes expressed at detectable levels in tumor cells. A stroma-specific classifier for nearby tumor was constructed on the basis of 114 candidate genes and tested on 364 independent samples including 243 tumor-bearing samples and 121 nontumor samples (normal biopsies, normal autopsies, remote stroma, as well as stroma within a few millimeters of tumor). The classifier predicted the tumor status of patients using tumor-free samples with an average accuracy of 97% (sensitivity = 98% and specificity = 88%) whereas classifiers trained with sets of 100 randomly generated genes had no diagnostic value. These results indicate that the prostate cancer microenvironment exhibits reproducible changes useful for categorizing the presence of tumor in patients when a prostate sample is derived from near the tumor but does not contain any recognizable tumor.

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.

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.

It is now clear that aberrant DNA methylation observed in cancer cells is not restricted to a few CpG islands, but affects multiple loci. When this epigenetic event occurs at the 5'-end of the regulatory region of genes, it is frequently associated with transcriptional silencing. To investigate further this widespread event in the tumor genome, we developed a novel microarray containing 7776 short GC-rich tags tethered to glass slide surfaces. This DNA chip was used to study 17 paired tissues of breast tumors and normal controls. Amplicons, representing differential pools of methylated DNA fragments between tumors and normal controls, were cohybridized to the microarray panel. Hypermethylation of multiple CpG island loci was then detected in a two-color fluorescence system. Approximately 1% (on average, 83 loci) of these CpG islands examined were hypermethylated in this patient group. Hierarchical clustering segregated these tumors based on their methylation profiles and identified a group of CpG island loci that corresponds to the hormone-receptor status of breast cancer. This observation was independently confirmed by examining a single locus, the promoter of the human glypican 3 gene, which was predominately hypermethylated in the hormone receptor-negative tumors. Our findings support the notion that hypermethylation of critical CpG island loci influences cancer development and produces distinct epigenetic signatures for particular tumor subtypes.