High throughput screening of methylation status of genes in prostate cancer using an oligonucleotide methylation array
Yan Ping Yu,
Shirish Paranjpe,
Joel Nelson1,
Sydney Finkelstein,
Baoguo Ren,
Demetrius Kokkinakis,
George Michalopoulos and
Jian-Hua Luo2
Department of Pathology and 1 Department of Urology, University of Pittsburgh School of Medicine, 3550 Terrace Street, Pittsburgh, PA 15261, USA
2 To whom correspondence should be addressed. Tel: +1 412 648 8791; Fax: +1 412 648 5997; Email: luoj{at}msx.upmc.edu
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Abstract
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Recent work using high-throughput microarray technology has discovered altered expression of a large number of genes in prostate cancer. Many of these alterations may be the consequence of changes in methylation status in the CpG islands of promoter or exon 1 regions of these genes. In order to determine the methylation status of a large number of genes and ESTs we combined the principle of match/mismatch hybridization with the technique of whole genome labeling to develop a highly specific oligonucleotide-based methylation microarray. Using this array, we analyzed the methylation status of 105 genes and ESTs in three prostate cancer cell lines. Between 32 and 47% of these genes and ESTs were methylated in these cell lines. By correlating the methylation status of this array with the results of Affymetrix expression arrays of three prostate cancer cell lines, we determined that methylation of genes played a significant role (37%) in down-regulating the expression of certain genes in prostate cancer. We also tested this array on a number of primary prostate tissue samples. Our results indicated that a subset of genes in this microarray (25/105) were methylated in all prostate cancer samples but not in normal prostate, suggesting the potential significance of alterations in the methylation status of certain genes in the development of prostate cancer.
Abbreviations: FBS, fetal bovine serum; GST, glutathione S-transferase; MSP, methylation-specific PCR; PBS, phosphate-buffered saline
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Introduction
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In eukaryotic cells transcriptional silencing via methylation of CpG dinucleotide clusters in the promoter region is one important transcriptional regulation mechanism of gene expression, in addition to histone acetylation and deacetylation and the binding of activators or repressors to regulatory elements upstream of the 5'-end of the genes (14). Transcriptional inactivation resulting from imprinting genes on the inactive X chromosome physiologically ensures female phenotype expression (4,5). The discovery of transcriptional inactivation of certain genes by methylation sheds further light on the mechanism of tumorigenesis in humans. Hypermethylation of CpG dinucleotides in the promoters of p16 and ZNF185 has been reported in prostate cancer (6), sarcoma and primitive neuroectodermal tumors (5). These proteins may play the role of repressors in the expression of other genes. Silencing of repressors could be one of the mechanisms leading to tumor development. Recently, the advent of expression array technologies has shown that expression levels of hundreds of genes are altered in various tumors (7). In order to understand the role of gene methylation in dysregulation of gene expression in prostate cancer, we constructed an oligonucleotide-based methylation array to interrogate the methylation status of a large number of genes of interest. We subsequently used this methylation array to determine the methylation status of 105 genes and ESTs in three prostate cancer cell lines (PC-3, Du145 and LNCaP). Correlation analysis indicated that a significant amount of down-regulation of gene expression was induced by methylation in prostate cancer cell lines. Distinct hybridization patterns were also observed in prostate cancer cell lines and primary and metastatic prostate cancer versus normal prostate samples.
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Materials and methods
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Tissue preparation and cell lines
Three human prostate cancer cell lines were purchased from ATCC. LNCaP was grown in RPMI 1640 medium supplemented with 5% fetal bovine serum (FBS), PC-3 in F12K with 5% FBS and Du145 in MEM with 5% FBS at 37°C with 5% CO2. Cells were harvested when they reached 80% confluence. For prostate cancer samples, fresh prostate tissues, recovered from the operating room immediately after removal, were dissected and trimmed to obtain pure tumor. Laser capture microdissections were performed on frozen sections by board certified pathologists to obtain cancer cells. For normal prostate epithelium, prostate tissues were obtained from organ donors totally free of genito-urological abnormality. Normal prostate epithelial cells from the peripheral zone were similarly laser capture microdissected. Approximately 500 000 cells were dissected from each sample. The protocol for tissue procurement was approved by an institutional review board.
Principle and design of methylation array
Bisulfite treatment of DNA deaminates cytosine bases such that it converts cytosine to a structure similar to uracil. However, methylation of the amide group of cytosine protects it from deamination by chemical treatment. Thus, a fragment of DNA with methylation of its CpG islands will generate a different template compared with the unmethylated version after bisulfite treatment. Built on this principle, we designed sets of oligonucleotides of 2125 bases corresponding to methylated and unmethylated versions of the sequence of the CpG island of a given gene and constructed a microarray to detect the methylation status of multiple genes simultaneously. The methylated version of a probe set differs by at least 3 nt (of 21 bp) from the unmethylated one, which will eliminate any possible cross-hybridization between methylated and unmethylated DNA of a given gene. As a result, a much stronger hybridization signal should be detected for a methylated probe set if there is methylation and vice versa.
Most functionally significant methylation occurs in the first exon and the sequence immediately upstream to the 5'-end of a mRNA start site. Approximately 80% of genes and ESTs contain sequences in these regions, meeting the criteria of a CpG island proposed by Jones and Takai (8). In order to differentiate methylation from non-methylation, several criteria were built in to our array design. First, in order to generate differential hybridization signals, at least three matched/mismatched bases were introduced into each pair of methylation/unmethylation olignucleotides, i.e. the oligonucleotide sequences must encompass 35 CpG dinucleotides. Second, a sufficient number of cytosines not associated with CpG islands must be present to eliminate cross-hybridization with residual unconverted DNA. Third, the GC content of the oligonucleotide was limited to between 50 and 70%. Fourth, triplicate printing was used to allow statistical analysis to evaluate the consistency of methylation/non-methylation differential signals.
Target DNA preparation
Genomic DNA was extracted from the cell lines with QIAamp DNA mini kits (Qiagen, CA), digested with KpnI and NdeI (New England Biolab, Boston, MA), followed by sodium bisulfite treatment as described previously (9). Briefly, 500 ng genomic DNA was denatured in 0.3 M NaOH at 37°C for 30 min. The denatured DNA was incubated in 40.5% sodium hydrogen sulfite (Sigma, OH), 10% hydroquinone (Sigma) at 50°C for 16 h. The modified DNA was then purified using a Wizard DNA Cleanup System (Promega, WI), eluted in 100 µl of TE buffer (pH 8.0), further denatured in 0.3 M NaOH at 37°C for 15 min and precipitated with 7 M amonnium acetate in 80% ethanol. Five hundred nanograms of DNA were amplified and labeled by PCR, using 5'-end Cy5-labeled random 12mer for 50 cycles as follows: 95°C for 30 s, 28°C for 5 min, 45°C for 5 min, 72°C for 3 min. To remove the residual primers and dNTPs, the amplified DNA was purified through microcon YM-10 membrane (Millipore, MA). The procedure followed the manufacturer's recommendations. To evaluate the completeness of deamination of cytosine, a PCR using primers corresponding to the non-CpG island region of human ß-actin was performed. The signal intensities of the wild-type and deaminated versions of the same region were evaluated. It appeared that only at pH 5.05.4 were high ratios of deamination/wild-type signals achieved. The experiments for this data set were performed at pH 5.0, the condition we considered optimal.
Methylation array preparation
GOLD SEAL micro slides were pretreated in 10% NaOH and 60% ethanol for 1 h. The slides were thoroughly rinsed with deionized water to remove residual NaOH. The cleaned slides were then transferred to poly-L-lysine solution [25 ml of poly-L-lysine (Sigma), 25 ml of phosphate-buffered saline (PBS) and 200 ml of deionized water] for coating. After rinsing once with water, poly-L-lysine-coated slides were printed with oligo probes in an Affymetrix GMS-417 arrayer. The principle of oligo probe design was described in the previous section. All methylation/non-methylation pairs were derived from sequences within the CpG islands in the promoter and exon 1 region of 105 genes and ESTs and were synthesized by MWG Biotech (NC). The probes, dissolved in 3x SSC, were printed onto poly-L-lysine-coated slides in triplicate in a linear pattern by a GMS-417 arrayer. Oligonucleotides corresponding to regions outside the CpG island of human ß-actin and
phage DNA were used as negative controls, printed at the ends of the slides. Cy5-, Cy3- or Hex-labeled oligos were also printed at the ends of the arrays in order to track the quality of printing and cross-linking in the preparation. DNA cross-linking on the slides was carried out by baking the slides at 50°C overnight with an additional 60 mJ UV irradiation in a StrataLinker 1800 (Stratagene). Unbound probes were removed with l-methyl-2-pyrrolindinone solution (60 mM sodium borate, 160 mM succinic anhydride; Sigma) and water.
Target DNA hybridization and data analysis
Fifteen microliters of Cy5-labeled genomic DNA in 1x hybridization buffer were hybridized with the array in a slide hybridization chamber (Fisher Biotech) at 45°C overnight in a dark and humid incubator. A series of post-hybridization washes was carried out in 0.01% SDS in 2x SSC, 1x SSC and 0.1x SSC. Slides were then scanned with a GMS-428 array scanner (Affymetrix, CA). The scanning resolution was set at 10 µm. The auto gain setting determined the signal strength by selecting an appropriate gain setting based on the intensity range of the image. Jaguar 2.0 software (Affymetrix) was used to compute the background signal, which was subtracted from the experimental data set. The algorithm threshold was determined as 75% of background + 1.5 x interquartile range (IQR) background. Each duplicate set of data was obtained under identical conditions. To compare the data from array to array, normalization was performed by factoring the average pixel intensity of each array to an arbitrary level of 10 000 units. Methylated and unmethylated data were analyzed using the pair-wise Student's t-test.
MSP and sequencing
To validate the information obtained from the methylation arrays, two sets of primers, methylated and unmethylated, were designed in the region of the CpG islands of the genes of interest. High specificity of the primers was achieved by including a CpG at the 3'-end of each primer and, in addition, at least three more CpG in the sequence. Aliquots of 200 ng bisulfite-treated genomic DNA were included in a MSP for 45 cycles as follows: 30 s at 95°C, 30 s at 59°C, 2 min at 72°C. To verify conversion from cytosine to uracil, PCRs using a set of ß-actin primers corresponding to wild-type and deaminated sequences were performed to test each batch of bisulfite-treated genomic DNA. Positive and negative controls were included in the experiments. Products of MSP were visualized in 2% agarose gels. Whenever possible, PCR products were gel purified using GeneClean II (BIO101, CA). Sequencing of these PCR products was carried out with the automatic sequencing facility in the University of Pittsburgh Biotechnology Support Center.
Chromatin immunoprecipitation
Prostate cancer cell line LNCaP was treated with 1% formaldehyde for 10 min at 37°C to cross-link histone to DNA. The cells were then washed with cold PBS containing protease inhibitors (1 mM phenylmethylsulfonyl fluoride, 1 mg/ml aprotinin and 1 mg/ml pepstatin A) and scraped. The cell pellets were resuspended in 200 ml of SDS lysis buffer containing protease inhibitors. The lysate was sonicated for 10 s at 30% maximum power five times (Sonics, CT) and centrifuged at 10 000 r.p.m. for 10 min. The supernatant was diluted 10-fold in Chip dilution buffer (Upstate), pre-cleaned with salmon sperm DNA/protein Aagarose (Upstate) for 30 min at 4°C and immunoprecipitated with rabbit serum against one of the following histones, acetylated H3, acetylated H4, methylated H3 and methylated H4 (Upstate), following manufacturer's recommendations. The immunocomplex was purified by adding 60 ml of salmon sperm DNA/protein A agarose slurry and rotating at 4°C for 1 h. The protein Aagarose pellet was washed sequentially with low salt immune complex buffer, high salt immune complex wash buffer, LiCl immune complex wash buffer and TE buffer (Upstate). The histoneDNA complex was eluted with elution buffer (1% SDS and 0.1 M NaHCO3). The DNA was released by incubation with 200 mM NaCl at 65°C for 4 h. The DNA samples from acetylated histones H3 and H4 were assayed by PCR. Two sets of primers were designed to encompass a small region in the promoter area of a given gene. An aliquot of 2 µl of 500 ml of DNA was assayed for 30 cycles of PCR and visualized by ethidium bromide in agarose gel. The DNAs obtained by immunoprecipitation of anti-methylated H3 and H4 were purified by the phenol/chloroform extration and ethanol precipitation before the PCR reactions.
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Results
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In order to achieve genome wide analysis of methylation, we adopted an approach of genome wide labeling of genomic DNA after bisulfite treatment (10,11). Two methods appeared to work equally well for such a purpose: random primer labeling of genomic DNA or random linear amplification of genomic DNA using 5'-labeled random 12mers. The latter approach appeared to have the advantage of requiring lesser amounts of DNA template. These random labeling approaches have a theoretical advantage over the adaptor/primer ligation and amplicon generation method, because they eliminate the uncertainty associated with restriction enzyme cutting sites and the possibility of preferential enrichment of smaller fragments of DNA and they uniformly label the modified genomic DNA. The approach described in this study is also substantially simpler and faster.
Application of the methylation array to human cell lines
To apply the oligonucleotide methylation array to cells and tissues of human lineage, we designed 107 pairs of methylation/non-methylation oligonucleotides corresponding to 105 human genes and ESTs. Eighty-five percent of these genes had down-regulated expression in human prostate cancer cell line LNCaP (in comparison with normal prostate), 5% showed no significant change and 10% were up-regulated. Human genomic target DNA was bisulfite modified, primed with random 12mers 5'-end-labeled with Cy5 fluorescent dye, hybridized onto the array, washed and scanned for hybridization signals as outlined in Figure 1A. As shown in Figure 1B, clear hybridization signals for each of the 105 pairs were achieved with the exception of the negative controls (a wild-type ß-actin sequence in a non-CpG island region and
phage DNA). For each pair of oligonucleotides, two hybridization scenarios may occur. If the DNA is hypermethylated and its CpG islands resistant to bisulfite-induced deamination, the DNA would predominantly hybridize with the designated methylation oligo in the pair. On the other hand, if the DNA is unmethylated, the DNA would be sensitive to bisulfite, its CG pairs would be converted to TG pairs and it would bind to the designated unmethylated oligo with a stronger signal intensity. Examples of methylation array hybridizations are illustrated in Figure 1B. Hybridization of a normal prostate epithelium sample (right image) showed dominant hybridization to the unmethylated oligonucleotides (odd numbered rows from the top), while little or no hybridization signals were found for methylation probes (even numbered rows from the top), indicating that no methylated genes of interest were detected. The left image of Figure 1B represents a sample of methylation array hybridization from prostate cancer cell line LNCaP. It shows a much more complex pattern of hybridization. It appeared that 35% of the oligo pairs contained stronger methylation signals versus the unmethylated ones. Our results indicate that optimum specificity and sensitivity of methylation detection are achieved when the methylated/unmethylated signal ratio reaches 2.5 and a pairwise t-test yields P < 0.05. The hybridization signal intensities of the triplicate printing varied from spot to spot by 1020%. The consistency and reproducibility of hybridization signals between similar experiments are demonstrated as scatter plots in Figure 1C.

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Fig. 1. Procedure, image and consistency of oligonucleotide methylation array. (A) Schema of methylation array procedure. Five hundred nanograms of bisulfite deaminated genomic DNA was used in random priming PCR to prepare target DNA. Hybridization signals were scanned in an Affymetrix 428 scanner and analyzed with Jaguar 2.0 software. (B) Image of oligonucleotide methylation array hybridization. (Left) Hybridization with LNCaP genome; (right) hybridization with normal prostate epithelium (PD6). (C) Scattered plots of experiments performed with Du145 (top), LNCaP (middle) and PC-3 (bottom). Average values of triplicate spotting were plotted against a separate experiment for the same cell line.
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Concordance of methylation array, methylation-specific PCR (MSP) and methylation sequencing
To evaluate the specificity of this methylation array hybridization, 16 genes and ESTs were selected for MSP and methylation sequencing. MSPs were performed on bisulfite-modified templates from LNCap, Du145 and PC-3 cells. As demonstrated in Figure 2 and Table I, the results of 15 of 16 MSP agreed with the methylation array for LNCaP cells, while 15 of 15 and 13 of 13 agreed with the methylation array for PC-3 and Du145 cells, respectively, when there was a MSP product. Twelve MSP products from all these cell lines were further verified by methylation sequencing. Representative results are shown in Figure 3. Overall, the concordance rate between the methylation array and MSP results was >91%. If failed MSP were excluded the concordance rate reached 97%. The methylaton status of many of these genes or ESTs was confirmed by methylation sequencing.

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Fig. 2. Methylation-specific PCR validation of methylation status of genes of LNCaP cells. (A) Methylation-specific PCR of 16 genes on templates from LNCaP cells. PCR was performed on 200 ng bisulfite-treated genomic DNA for the genes indicated. (B) Methylation-specific PCR of 15 genes on templates from PC-3 cells. PCR was performed with primers specific for the genes indicated. (C) Methylation-specific PCR of 13 genes on templates from Du145 cells. PCR was performed with primers specific for the gene indicated. M, reaction using primers specific for methylated, U for unmethylated.
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Fig. 3. Diagrammatic representation of methylation sequencing of PCR products from LNCaP and PC-3 cells. Methylation sequencing was performed on PCR products of LNCaP cells, except for ADCY4 and DUSP2, for which templates were obtained from PC-3 cells. CpG methylation is indicated by hexagons, non-methylation by circles.
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Inhibition of gene expression by methylation
The Affymetrix array data (u95a, u95b and u95c) for Du145, PC-3 and LNCaP cells were statistically analyzed against 23 normal prostate samples (12). Down-regulation of expression was defined as two standard deviations below the mean of the normal prostate samples. In contrast, up-regulation of expression was at two standard deviations above the mean of the normal. Among 105 genes and ESTs, 87 were down-regulated in LNCaP cells; 31 being methylated, accounting for >35% inhibition of gene expression (Table II). Methylation-induced gene expression appeared more pronounced in Du145 cells, since 27 of 58 (47%) down-regulated genes were methylated. Paradoxically, several genes and ESTs were found to be unchanged or showed increased expression in these prostate cancer cell lines, but were also methylated, indicating that other gene expression regulation mechanisms may mediate this unusual observation. To investigate these paradoxical results, we performed histone modification analysis on several genes, including CKS2, a gene up-regulated in LNCaP cells despite its promoter being methylated. Histone modification analysis indicated that methylation of histones H3 and H4 occurs in the region of the CKS2 promoter (Figure 4). The same findings apply to OCLN, which shows a similar paradoxical phenomenon. However, histone H4 methylation alone on the GAS1 promoter is associated with down-regulation, even without promoter methylation. Interestingly, glutathione S-transferase (GST)
is down-regulated and methylated in LNCaP cells, but it appears that histone modification is active, since it is positive in both methylation and acetylation analyses. This result probably reflects the outcome of a dynamic counterbalance of positive and negative regulation of GST
expression. A similar interpretation may apply to GAPDH, whose expression was minimally changed, even though it is methylated and the histones associated with its promoter are heavily modified (Figure 4). Overall, our results indicate that methylation accounts for a significant fraction (38%) of gene expression suppression in cancer cells.

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Fig. 4. Chromatin immunoprecipitation analysis of histone acetylation and methylation. Antibodies against acetylated histones H3 (top panel) and H4 (second panel) and methylated histones H3 (third panel) and H4 (bottom panel) were used in chromatin immunoprecipitation assays. DNAs eluted from the precipitates were used as templates for PCR reactions for ADCY4, CKS2, GAS1, OCLN, GSTpi, GAPDH and PSA. Two sets of primers corresponding to the promoter region of each gene were used.
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Alteration of methylation patterns in prostate cancer
Altered methylation is one of the important features of human malignancy. We applied our methylation array to several normal (3) and cancerous prostate samples (9). All samples other than cell lines were epithelial cells obtained by microdissection. Dramatic differences in methylation patterns were found between the three normal prostate epithelial samples and the malignant ones, including three metastatic cell lines. As shown in Figure 5, a few selected genes were methylated in the normal prostate samples, while up to 35% of these genes were methylated in prostate cancer samples. One of these genes, GST
is an enzyme involved in detoxification of oxygen free radicals. GST
is known to be widely methylated in prostate cancers (13). Our results indicate that GST
was methylated in all prostate cancer samples on our methylation arrays. Annexin II, another gene previously reported to be methylated in prostate cancer (14), was also found to be widely methylated in prostate cancer samples but not in normal prostate tissues.

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Fig. 5. Hierarchical clustering of prostate epithelial samples. Twelve samples of prostate epithelial lineage, including three normal prostate epithelia (PD6, PD9 and PD10), two metastatic (MT16-13 and MT12-19) and four primary prostatic cancinomas (PT91, 678, 45 and 7504) and three prostate cancer cell lines (Du145, LNCaP and PC-3) were assessed for methylation status of 105 genes and ESTs and clustered using Michael Eisen's cluster and tree view tools. Red indicates methylation and blue non-methylation.
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In order to elucidate the relatedness of each of these samples in terms of methylation pattern, a phylogenetic tree was constructed. To simplify the algorithm, genes and ESTs with a methylation signal were given a value of 1, while unmethylated genes and ESTs were given a value of 0. As shown in Figure 5, all cancer samples were closely related and clustered in a branch. The normal prostate samples were only distantly related to the cancer samples. The relative unrelatedness among normal prostate samples may result from the low level of methylation of the selected genes. Among the prostate cancer samples, three cell lines tended to loosely cluster into a sub-branch, because they contained a few methylated genes that were infrequently methylated in other primary cancer samples. Two samples obtained from metastatic sites also clustered well with each other, implying that the surrounding milieu played a role in influencing gene methylation. Overall, there are dramatic differences in methylation patterns and gene numbers between normal prostate epithelial cells and malignant ones. Since prostate cancer develops by abnormal differentiation of the prostate epithelium and simplification of gene expression occurs in most of the advanced stages of prostate cancer, hypermethylation of a large number of genes in prostate cancer samples may contribute to or underlie the abnormal differentiation process observed in cancer.
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Discussion
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The methylation array is a new application of DNA array technology that allows the rapid detection of methylation status of hundreds or even thousands of genes at a time, using a limited amount of genomic DNA. High throughput screening of methylation status may have three potential applications. First, it can be used to examine the methylation status of a large number of genes during embryonic development and tissue differentiation. Even though other important mechanisms may contribute to gene expression regulation in these processes, methylation remains one of the most intriguing factors in gene expression silencing. Second, methylation arrays can be applied to understand the abnormal gene expression patterns seen in a variety of human malignancies and diseases. This is particularly interesting given the number of reports on altered methylation of human tumor suppressor or other genes in a variety of human cancers and other diseases. The correlation of the pattern of methylation of a large number of genes with patterns of gene expression silencing may help to define the underlying mechanisms of tumor development. Third, identification of methylation critical to disease development provides targets for epigenetic therapy. It provides a tool to monitor and to predict the response to certain chemotherapeutic demethylation agents. To our knowledge, this is the first report using a methylation array to study the methylation status of a large number of genes in prostate cancer.
The development of methylation arrays has been previously reported (1517). The earlier methodology involved using methylated, CpG-enriched genomic DNA sequences from a tumor library. These mostly unknown sequence tags were subcloned and overlaid onto a glass slide and subsequently hybridized with amplicons generated from methylation-sensitive, restriction enzyme-digested target (genome) DNA. While this method can perform large-scale analysis of methylation, it is limited by the randomness and largely unknown identities of sequence tags in the array and the susceptibility to polymorphism variation in amplicon generation. Another development from the same group used an oligonucleotide array for methylation analysis, but the methodology required multiplex MSP to generate the target DNA. Such an approach can be time consuming and laborious. In order to perform a large-scale analysis, it may require a large quantity of target DNA that is beyond the practical limits. Recently, a DNA microarray-based methylation-sensitive amplified fragment length polymorphism (AFLP) hybridization method was developed (18). It used the methylation-sensitive restriction enzyme NotI to digest a pair of genomes for comparison. Subsequently, the restriction fragments were amplified and hybridized to a DNA microarray to detect the difference in hybridization signals. This method is able to detect the differences in methylation pattern between two samples. However, it is still limited by the randomness of the restriction sites. The methodology described in this report is substantially simpler and less labor intensive. It requires only a small amount of target DNA (500 ng) and no additional target DNA is required even when the array is expanded to cover tens of thousands of genes and ESTs. This makes our array particularly suited to analysis of samples with limited availability of cells.
Recent expression microarray analysis indicated that over several hundred genes and ESTs were abnormally expressed in prostate cancer (1922). Among verified abnormally silenced genes, many were found to be methylated in the promoter region (23). By comparing the methylation status of three prostate cancer cell lines with gene expression data, we found that methylation might play a significant (37%) role in inducing gene silencing in prostate cancer. Many of these genes are novel in terms of their methylation status in prostate cancer. Among these genes, reprimo, also called candidate mediator for p53-induced G2 arrest, was down-regulated by 7- to 10-fold in all three prostate cancer cell lines and was methylated. Expression of this gene induced growth arrest in G2 phase. Another gene involved in G2 cell growth arrest is ZAK. ZAK, also called MRK or MLTK, is a mixed lineage kinase and contains leucine zipper and
sterile motifs. Irradiation induces expression of ZAK, which in turn produces G2 growth arrest. Twenty- to thirty-fold decreases in expression of this gene were found in cancer cell lines, and this gene was also methylated. Other interesting methylation candidates with down-regulation of expression include synatopodin 2 (a variant of myopodin), TGF receptor ß2 and tumor endothelial marker 8. These genes have been shown to play important roles in the development of cancer in the prostate and other organs. Methylation in the promoter regions of these genes may underlie the mechanism of expression inhibition of these genes in prostate cancer.
An interesting recent study of the methylation pattern of 16 genes in primary and metastatic prostate cancer using real time methylation PCR indicates heavy methylation of some of these genes in both primary and metastatic prostate cancer but under-methylated in normal prostate tissue (24). Similar to this result, our methylation arrays show that there is a dramatic increase in methylation of genes and ESTs in prostate cancer samples. Specifically, 35 genes were found to be methylated in prostate cancer, while 25 of 105 genes were methylated in all the prostate cancer samples, including three aggressive prostate cancer cell lines, but not normal prostate epithelial cells. This raises the possibility of identifying a signature methylation pattern for prostate cancer using our methylation array, even though such an endeavor is beyond the scope of this communication. In conclusion, it appears that a significant fraction of genes and ESTs are methylated in prostate cancer. Such methylation may account for the down-regulation and simplification of expression of a significant number of genes in the process of carcinogenesis.
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Acknowledgments
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We thank Tim Gavel for constructive comments on the manuscript. This work was supported by grants from the National Cancer Institute to G.M. (1UO1CA88110-01) and to J.H.L. (R01 CA098249).
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Received July 15, 2004;
revised October 1, 2004;
accepted October 5, 2004.