Expression differences between African American and Caucasian prostate cancer tissue reveals that stroma is the site of aggressive changes.

In prostate cancer, race/ethnicity is the highest risk factor after adjusting for age. African Americans have more aggressive tumors at every clinical stage of the disease, resulting in poorer prognosis and increased mortality. A major barrier to identifying crucial gene activity differences is heterogeneity, including tissue composition variation intrinsic to the histology of prostate cancer. We hypothesized that differences in gene expression in specific tissue types would reveal mechanisms involved in the racial disparities of prostate cancer. We examined 17 pairs of arrays for AAs and Caucasians that were formed by closely matching the samples based on the known tissue type composition of the tumors. Using pair-wise t-test we found significantly altered gene expression between AAs and CAs. Independently, we performed multiple linear regression analyses to associate gene expression with race considering variation in percent tumor and stroma tissue. The majority of differentially expressed genes were associated with tumor-adjacent stroma rather than tumor tissue. Extracellular matrix, integrin family and signaling mediators of the epithelial-to-mesenchymal transition (EMT) pathways were all downregulated in stroma of AAs. Using MetaCore (GeneGo) analysis, we observed that 35% of significant (p < 10(-3)) pathways identified EMT and 25% identified immune response pathways especially for interleukins-2, -4, -5, -6, -7, -10, -13, -15 and -22 as the major changes. Our studies reveal that altered immune and EMT processes in tumor-adjacent stroma may be responsible for the aggressive nature of prostate cancer in AAs.

Relational analysis of CpG islands methylation and gene expression in human lymphomas using possibilistic C-means clustering and modified cluster fuzzy density.

Heterogeneous genetic and epigenetic alterations are commonly found in human non-Hodgkin's lymphomas (NHL). One such epigenetic alteration is aberrant methylation of gene promoter-related CpG islands, where hypermethylation frequently results in transcriptional inactivation of target genes, while a decrease or loss of promoter methylation (hypomethylation) is frequently associated with transcriptional activation. Discovering genes with these relationships in NHL or other types of cancers could lead to a better understanding of the pathobiology of these diseases. The simultaneous analysis of promoter methylation using Differential Methylation Hybridization (DMH) and its associated gene expression using Expressed CpG Island Sequence Tag (ECIST) microarrays generates a large volume of methylation-expression relational data. To analyze this data, we propose a set of algorithms based on fuzzy sets theory, in particular Possibilistic c-Means (PCM) and cluster fuzzy density. For each gene, these algorithms calculate measures of confidence of various methylation-expression relationships in each NHL subclass. Thus, these tools can be used as a means of high volume data exploration to better guide biological confirmation using independent molecular biology methods.

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.

Differential distribution of DNA methylation within the RASSF1A CpG island in breast cancer.

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.

Expressed CpG island sequence tag microarray for dual screening of DNA hypermethylation and gene silencing in cancer cells.

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.

Differential DNA methylation of gene promoters in small B-cell lymphomas.

Improved care of patients with small B-cell lymphomas (SBCLs) is likely to result from the ongoing discovery of molecular markers that better define these malignant neoplasms. We identified multiple gene loci whose DNA methylation patterns differed between 3 types of SBCL: B-cell chronic lymphocytic leukemia/small lymphocytic lymphoma, mantle cell lymphoma, and grades I and II follicular lymphoma. This analysis was performed using an oligonucleotide microarray that allowed determination of the DNA methylation status of 156 loci in 38 genes. Combined bisulfite restriction analysis and methylation-specific polymerase chain reaction were used to validate the differential methylation of 6 of these genes. By using non-Hodgkin lymphoma cell lines as models, these genes were examined further for methylation and gene expression relationships. This study illustrates nonrandom epigenetic alterations in SBCLs that seem to preferentially involve lymphomas of germinal center derivation.

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.

TGF-ß mediated DNA methylation in prostate cancer.

Almost all tumors harbor a defective negative feedback loop of signaling by transforming growth factor-ß (TGF-ß). Epigenetic mechanisms of gene regulation, including DNA methylation, are fundamental to normal cellular function and also play a major role in carcinogenesis. Recent evidence demonstrated that TGF-ß signaling mediates cancer development and progression. Many key events in TGF-ß signaling in cancer included auto-induction of TGF-ß1 and increased expression of DNA methyltransferases (DNMTs), suggesting that DNA methylation plays a significant role in cancer development and progression. In this review, we performed an extensive survey of the literature linking TGF-ß signaling to DNA methylation in prostate cancer. It appeared that almost all DNA methylated genes detected in prostate cancer are directly or indirectly related to TGF-ß signaling. This knowledge has provided a basis for our future directions of prostate cancer research and strategies for prevention and therapy for prostate cancer.

Diagnosis of prostate cancer using differentially expressed genes in stroma.

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.

Epigenetic regulation of WNT signaling in chronic lymphocytic leukemia.

Certain WNT and WNT network target genes are expressed at higher or lower levels in chronic lymphocytic leukemia compared with normal B-cells. This includes upregulation of nuclear complex genes, as well as genes for cytoplasmic proteins and WNT ligands and their cognate receptors. In addition, epigenetic silencing of several negative regulators of the WNT pathway have been identified. The balance between epigenetic downregulation of negative effector genes and increased expression of positive effector genes demonstrate that the epigenetic downregulation of WNT antagonists is one mechanism, perhaps the main mechanism, that is permissive to active WNT signaling in chronic lymphocytic leukemia. Moreover, constitutive activation of the WNT network and target genes is likely to impact on additional interacting signaling pathways. Based on published studies, we propose a model of WNT signaling that involves mainly permissive expression, and sometimes overexpression, of positive effectors and downregulation of negative regulators in the network. In this model, DNA methylation, histone modifications and altered expression of microRNA molecules interact to allow continuous WNT signaling.

Large-scale analysis of DNA methylation in chronic lymphocytic leukemia.

AIMS: B-cell chronic lymphocytic leukemia (CLL) is a heterogeneous malignancy that clinically ranges from indolent to rapidly progressive. CLL, like other cancers, can be affected by epigenetic alterations. MATERIALS & METHODS: A microarray discovery-based study was initiated to determine DNA methylation in CLL cases with a range of CD38 expression (1­92%). RESULTS: Many loci were either methylated or unmethylated across all CD38 levels, but differential methylation was also observed for some genes. Genomic sequencing of DLEU7 confirmed extensive cytosine methylation preferentially in patient samples with low CD38 expression, whereas NRP2, SFRP2 and ADAM12 were more commonly methylated in those with high CD38 expression. CONCLUSION: This study demonstrates that CLL is affected by CpG island methylation in some genes that segregate with CD38 expression levels, while most others show similar methylation patterns across all levels. The CpG island methylation in certain functional gene groups and pathway-associated genes that are known to be deregulated in CLL provides additional insights into the CLL methylome and epigenetic contribution to cellular dysfunction. It will now be useful to investigate the effectiveness of epigenetic therapeutic reversal of these alterations to develop effective treatments for the disease.

Algorithmic discovery of methylation "hot spots" in DNA from lymphoma patients.

The computational aspects of the problem in this paper involve, firstly, selective mapping of methylated DNA clones according to methylation level and, secondly, extracting motif information from all the mapped elements in the absence of prior probability distribution. Our novel implementation of algorithms to map and maximize expectation in this setting has generated data that appear to be distinct for each lymphoma subtype examined. A "clone" represents a polymerase chain reaction (PCR) product (on average approximately 500 bp) which belongs to a microarray of 8544 such sequences preserving CpG-rich islands (CGIs) [1]. Accumulating evidence indicates that cancers including lymphomas demonstrate hypermethylation of CGIs "silencing" an increasing number of tumor suppressor (TS) genes which can lead to tumorigenesis.

Discovery of novel epigenetic markers in non-Hodgkin's lymphoma.

Non-Hodgkin's lymphoma (NHL) is a group of malignancies with heterogeneous genetic and epigenetic alterations. Discovery of molecular markers that better define NHL should improve diagnosis, prognosis and understanding of the biology. We developed a CpG island DNA microarray for discovery of aberrant methylation targets in cancer, and now apply this method to examine NHL cell lines and primary tumors. This methylation profiling revealed differential patterns in six cell lines originating from different subtypes of NHL. We identified 30 hypermethylated genes in these cell lines and independently confirmed 10 of them. Methylation of 6 of these genes was then further examined in 75 primary NHL specimens composed of four subtypes representing different stages of maturation. Each gene (DLC-1, PCDHGB7, CYP27B1, EFNA5, CCND1 and RARbeta2) was frequently hypermethylated in these NHLs (87, 78, 61, 53, 40 and 38%, respectively), but not in benign follicular hyperplasia. Although some genes such as DLC-1 and PCDHGB7 were methylated in the vast majority of NHLs, others were differentially methylated in specific subtypes. The methylation of the candidate tumor suppressor gene DLC-1 was detected in a high proportion of primary tumor and plasma DNA samples by using quantitative methylation-specific PCR analysis. This promoter hypermethylation inversely correlated with DLC-1 gene expression in primary NHL samples. Thus, this CpG island microarray is a powerful discovery tool to identify novel methylated genes for further studies of their relevant molecular pathways in NHLs and identification of potential epigenetic biomarkers of disease.

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.