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[Cancer Research 66, 5021-5028, May 15, 2006]
© 2006 American Association for Cancer Research

Molecular Biology, Pathobiology, and Genetics

Identification of Novel Target Genes by an Epigenetic Reactivation Screen of Renal Cancer

Inmaculada Ibanez de Caceres1, Essel Dulaimi1, Amanda M. Hoffman1, Tahseen Al-Saleem2, Robert G. Uzzo1 and Paul Cairns1,2

Departments of 1 Surgical Oncology and 2 Pathology, Fox Chase Cancer Center, Philadelphia, Pennsylvania

Requests for reprints: Paul Cairns, Fox Chase Cancer Center, 333 Cottman Avenue, Philadelphia, PA 19111. Phone: 215-7285635; Fax: 215-7282487; E-mail: Paul.Cairns{at}fccc.edu.


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results and Discussion
 References
 
Aberrant promoter hypermethylation is a common mechanism for inactivation of tumor suppressor genes in cancer cells. To generate a global profile of genes silenced by hypermethylation in renal cell cancer (RCC), we did an expression microarray-based analysis of genes reactivated in the 786-0, ACHN, HRC51, and HRC59 RCC lines after treatment with the demethylating drug 5-aza-2 deoxycytidine and histone deacetylation inhibiting drug trichostatin A. Between 111 to 170 genes were found to have at least 3-fold up-regulation of expression after treatment in each cell line. To establish the specificity of the screen for identification of genes, epigenetically silenced in cancer cells, we validated a subset of 12 up-regulated genes. Three genes (IGFBP1, IGFBP3, and COL1A1) showed promoter methylation in tumor DNA but were unmethylated in normal cell DNA. One gene (GDF15) was methylated in normal cells but more densely methylated in tumor cells. One gene (PLAU) showed cancer cell–specific methylation that did not correlate well with expression status. The remaining seven genes had unmethylated promoters, although at least one of these genes (TGM2) may be regulated by RASSF1A, which was methylated in the RCC lines. Thus, we were able to show that up-regulation of at least 6 of the 12 genes examined was due to epigenetic reactivation. The IGFBP1, IGFBP3, and COL1A1 gene promoter regions were found to be frequently methylated in primary renal cell tumors, and further study will provide insight into the biology of the disease and facilitate translational studies in renal cancer. (Cancer Res 2006; 66(10): 5021-8)


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results and Discussion
 References
 
There will be >25,000 new cases of renal cell cancer (RCC) in 2005, and the incidence of this disease has increased by 60% over the last two decades (1). RCCs are heterogeneous in histology, genetics, and clinical behavior. Clear cell (75-80%), and papillary (10-15%) carcinoma are the two most frequent subtypes of RCC (2–4). Tumorigenesis is a multistep process that results from the accumulation and interplay of genetic and epigenetic mutations. The epigenetic alteration of aberrant DNA methylation of CpG islands in the promoter region of genes is well established as a common mechanism for the silencing of tumor suppressor gene (TSG) in cancer cells (5, 6). Several TSG have been identified as hypermethylated with associated loss of expression in renal cancer by a candidate approach. The VHL and p16INK4a TSG are inactivated by promoter hypermethylation in up to 20% of clear cell (7) and 10% of all RCC (8), respectively. However, to date, few genes have been found to be frequently hypermethylated in RCC. The RASSF1A gene is hypermethylated in 27% to 56% (9–11), and the Timp-3 gene is hypermethylated in 58% to 78%, of primary RCC (11, 12). By definition, a candidate gene approach has resulted in the examination of a limited number of genes for epigenetic alteration (11). Many other tumor suppressor and cancer genes important in renal tumorigenesis likely remain to be identified. A global approach to the identification of epigenetically silenced genes in renal tumor cells could provide methylation signatures for early detection and for prognostic stratification, identify novel targets for therapy, and lead to further elucidation of the biology of this disease.

Epigenetic silencing of a gene can be reversed, resulting in reexpression, by drugs, such as 5-aza-2 deoxycytidine (5Aza-dC), which acts by incorporation into the new strand during DNA replication where it forms a covalent complex with the methyltransferase active sites, depleting methyltransferase activity, which results in generalized demethylation (5). Trichostatin A (TSA) is a histone deacetylase inhibitor agent that can reverse the formation of transcriptionally repressive chromatin structure by facilitating an accumulation of acetylated histones (13). These two drugs have been reported to act in synergy for reactivation of epigenetically silenced genes (14). Until recently, global analyses of methylation in cancer cells were largely restricted to array or gel-based comparisons of CpG islands between normal and tumor cell DNA. A microarray-based screen has the advantage of a more global analysis and, coupled with a reactivation strategy, has the further advantage that it should preferentially identify reexpression of epigenetically silenced genes over methylated CpG islands that do not influence transcription. The potential of this approach has been highlighted in bladder (15), colorectal (16), esophageal (17), and other cancers (18–20). In the present study, we examined the global reactivation of epigenetically silenced genes in renal cancer by analysis of a 14,802 gene expression array with RNA from four RCC lines after treatment with 5Aza-dC and TSA. Through validation, we have shown that the screen preferentially selects for epigenetically silenced genes and identified three genes unmethylated in normal cells but frequently hypermethylated in primary RCC.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results and Discussion
 References
 
Cell lines and tissue specimens. The clear cell renal tumor line 786-0 and the papillary renal tumor cell line ACHN were obtained from the American Type Culture Collection (ATCC, Manassas, VA). The HRC51 cell line was established from an organ-confined primary clear cell renal tumor (T1b, grade 1), and the HRC59 cell line was established from a localized papillary renal tumor (T3a, grade 3) at Fox Chase Cancer Center (FCCC). 786-0 was grown in RPMI; ACHN was grown in MEM; and HRC51 and 59 were grown in type IIA (available upon request) medium supplemented with 10% FCS. Primary renal tumors and normal kidney tissue were microdissected with the assistance of a pathologist (T. A-S.) as described (21). Areas of immune cell infiltration, observed in a minority of tumor specimens, were avoided. DNA was extracted using conventional techniques of digestion with proteinase K (Invitrogen, Carlsbad, CA) followed by phenol/chloroform extraction (22).

5Aza-2dC and TSA treatment. 5Aza-dC (Sigma, St. Louis, MO) was dissolved in PBS as a 5 mmol/L stock solution and stored in aliquots at –80°C. TSA (Wako, Richmond, VA) was dissolved in absolute ethanol as a 330 µmol/L stock solution and stored at –20°C. The four renal cell lines were split to low density and exposed to 5Aza-dC at a final concentration of 5 µmol/L, again 24 hours after the beginning of treatment and, if necessary, further treatment until the cells had undergone at least two doublings. The cells were also treated with TSA at a final concentration of 500 nmol/L during 24 hours before harvest for RNA extraction. Untreated (mock) cells were cultured over an identical period of time with an equivalent volume of PBS and, for the final 24 hours, with an equivalent volume of ethanol.

Oligonucleotide array hybridization. Total RNA was isolated from drug-treated and untreated cultured cells using TRIZOL reagent (Invitrogen) and purified with the RNAeasy Mini kit (Qiagen, Valencia, CA), combined with DNase treatment. The RNA quality was confirmed by the ratio of 28S and 18S rRNA after agarose gel electrophoresis. Twenty micrograms of total RNA was reverse transcribed using oligo (dT)24 primer and Superscript II reverse transcriptase (Invitrogen) for 1.5 hours at 42°C.

For each cell line, both treated and untreated cDNA was labeled with Cy3 or Cy5 (Amersham Biosciences, Piscataway, NJ) and then hybridized to separate human 15 k oligoarrays (MWG Biotech, Inc., High Point, NC), according to the manufacturer's recommendation for 18 hours at 42°C. The microarrays were processed and spotted in the DNA Microarray Facility at FCCC. The Gene list, Gene ID, and Template files can be viewed at http://research.fccc.edu/facilities/microarray. In addition, we did microarray hybridization with the opposite labels (dye flip) from each cell line. The hybridized slides were scanned using a GMS 428 Scanner (Affymetrix, Santa Clara, CA) to generate high-resolution images for both Cy3 and Cy5 channels. Image analysis was done using the ImaGene software (BioDiscovery, Inc., El Segundo, CA).

Analysis of expression up-regulation after demethylating treatment. The genes corresponding to each oligonucleotide spotted on the array were identified using an optimized segmentation algorithm. Spots of poor quality and spots with signal levels indistinguishable from the background were excluded. The image data were extracted and used for data analysis. Data were analyzed using the GeneSight software (BioDiscovery), which includes background subtraction, data normalization (Lowess tranformation), calculation of ratios, and statistical analysis of replicate spots and slides.

Selection of genes for validation. We selected a subset of genes for validation by the following criteria. We chose genes that showed at least 3-fold up-regulation in at least three of the four cell lines. We excluded those genes with no evidence of expression in normal renal tissue according to the Cancer Genome Anatomy Project (CGAP) Serial Analysis Gene Expression (SAGE) database (http//cgap.nci.nih.gov). We then analyzed the promoter region using the GeneCard web site (http://bioinfo.weizmann.ac.il/cards/index.html) to obtain the genomic and cDNA sequences from the up-regulated genes. We searched for the CpG island most proximal to the transcription start site using the CpG island revealing program on WebGene Home Page web site (http://www.itba.mi.cnr.it/webgene/). Criteria for a CpG island was based on Takai and Jones: GC ≥ 55%; Obs/Exp ≥ 65, and length >200 bp, at http://cpgislands.usc.edu reported to exclude most Alu-repetitive elements (23). We used the RepeatMasker Web Server (ftp.genome.washington.edu/cgi-bin/RepeatMasker) to examine whether the promoter CpG island contained repetitive elements.

Reverse transcription-PCR. The cDNA template used for reverse transcription-PCR (RT-PCR) was aliquoted from the same cDNA used for hybridization to the microarray. For each gene examined, primers for the housekeeping gene GAPDH were included in the RT-PCR reaction mix as a control for successful amplification. Forward and reverse primers were chosen from different exons to avoid amplification of any contaminating genomic DNA. Primer sequences are available upon request.

Bisulfite modification of DNA. Genomic DNA (1 µg) from untreated cell line cultures and from normal kidney tissue and primary tumors was denatured by NaOH (0.2 mol/L) for 10 minutes at 37°C and then modified by hydroquinone and sodium bisulfite treatment at 50°C for 17 hours under a mineral oil layer. Modified DNA was purified using the Wizard DNA Clean-Up system (Promega, Madison, WI). Modification was completed by NaOH (0.3 mol/L) treatment for 5 minutes at room temperature followed by precipitation with glycogen, 10 mol/L ammonium acetate, and ethanol precipitation. Bisulfite modification of DNA results in the conversion of unmethylated cytosines to uracil, whereas methylated cytosines are resistant to modification and remain as cytosine.

Bisulfite sequencing of gene promoter CpG islands. DNA fragments of 258 to 461 bp in size containing the promoter CpG island were PCR amplified from bisulfite-modified cell line DNAs and normal tissue DNAs for each gene analyzed. PCR products were run in a 1.5% agarose gel; the gel slice was purified by Qiaquick (Qiagen); and direct sequencing was done on all genes. In addition, some gene products were cloned into a TOPO vector (Invitrogen), and at least 10 colonies from each gene were analyzed. Sequencing was done on an ABI 3100A capillary genetic analyzer, and data were analyzed by Sequencer Version 4.2.2 software. Primer sequences used for PCR amplification and sequencing are available upon request.

Methylation-specific PCR. Bisulfite-modified primary renal tumor DNAs were PCR amplified with primers specific for methylated versus unmethylated DNA for the IGFBP1, IGFBP3, COL1AI, and RASSF1A genes. The methylation-specific PCR (MSP) primer sequences for IGFBP1, IGFBP3, and COL1AI are available upon request, and for RASSF1A, were as previously described (21). PCR amplification of tumor DNA was done for 31 to 35 cycles at 95°C denaturing, 58°C to 66°C annealing, and 72°C extension with a final extension step of 5 minutes. In each set of DNAs modified and PCR amplified, a cell line with known hypermethylation from the bisulfite sequencing data was used as a positive control, and normal renal tissue DNA as a negative control was included. After PCR, samples were run on a 6% nondenaturing acrylamide gel with appropriate size markers, and the presence or absence of a PCR product was analyzed.


   Results and Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results and Discussion
References
 
Determination of the optimal 5Aza-dC dose array-based reactivation of expression. To determine the optimal 5Aza-dC dosage for robust detection of transcriptional reactivation on the microarray without excessive toxicity to the treated cells, we examined the reexpression of five tumor suppressor genes (p16INK4a, MLH1, MGMT, RARß, and Timp-3) well characterized as hypermethylated with associated silencing in the SW48 colorectal tumor cell line (8, 12, 24–26), which has a similar cell doubling time to the RCC lines, at different doses of 5Aza-dC. RNA was extracted from SW48 cell cultures after treatment with 1, 5, or 10 µmol/L 5Aza-dC and TSA (500 nmol/L); RT-PCR was done; and the product was labeled and hybridized to the expression array. Analysis of up-regulation of the five TSG showed that treatment with 5 µmol/L 5Aza-dC for at least two cell doubling times resulted in reexpression of the five TSG with minimal toxicity as assessed by comparison of cell morphology and cell death between control and treated cells. We combined the 5Aza-dC treatment with TSA because there is good evidence that the processes of methylation and deacetylation interact to silence transcription (14, 27), although it is believed that TSA has less synergistic effect at the relatively higher 5 µmol/L 5Aza-dC dose we used, than when combined with lower doses of 5Aza-dC. The optimal synergistic concentration will also vary with different cell lines depending upon uptake and the epigenomic background. Furthermore, different genes in the same cell line, or the same gene locus in different cell lines, may be more, or less, strongly epigenetically silenced. The use of TSA alone may result in gene reactivation (16) but was not a focus of our present study. Another obvious issue of an epigenetic reactivation and expression array approach is that sensitivity of signal might vary depending upon different baseline expression levels of genes and different types of array. Interestingly, MLH1 showed least up-regulation of the five TSGs examined in SW48, and a similar observation was noted for MLH1 reactivation in the RKO colorectal tumor cell line (16).

We then analyzed up-regulation of the 14,802 gene microarray in four RCC lines treated with 5 µmol/L 5Aza-dC and 500 nmol/L TSA. We analyzed two ATCC renal tumor cell lines (786-0 and ACHN); in addition, because all ATCC renal tumor lines were derived from clinically advanced tumors, a further two cell lines were established from localized primary renal tumors. After treatment, we found 170 (786-0), 112 (HRC51), 178 (HRC59), and 111 (ACHN) genes up-regulated at least 3-fold in the RCC cell lines compared with the untreated cells (Supplementary Table S1). To verify the specificity of our screen for genes hypermethylated in renal cancer, we applied selection criteria to the list of up-regulated genes. We first identified 27 genes that were up-regulated in at least three of the four RCC lines on the basis that such genes might be expected to be frequently methylated in primary renal cancer. In addition, we examined one gene up-regulated after drug treatment in both clear cell lines but neither of the papillary lines to investigate cell type–specific methylation. We next examined the CGAP SAGE database to determine if each gene was known to be expressed in normal renal cells and excluded 12 genes with no evidence of expression or no data available. We then analyzed the promoter region of each gene for the presence of a CpG island with the characteristics described by Takai and Jones (23) and found 14 of the 15 genes had such a CpG island (Table 1 ) within 500 bp either side of the transcription start site. The CpG islands of three genes contained repetitive elements and were excluded from the initial validation. We, therefore, selected the remaining 12 genes for validation (Table 1).


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  		Table 1. Up-regulated genes identified by intuitive selection

 
Validation analysis of reactivated genes. We did RT-PCR for the 12 genes on untreated and treated cell line RNA to independently confirm the up-regulation of expression observed by array analysis (Fig. 1 ; Supplementary Fig. S1). The RT-PCR results were tightly concordant with the microarray analysis for all 12 genes examined. For example, COL1A1 and IGFBP3 up-regulation after treatment is confirmed by RT-PCR in Fig. 1, where a strong signal from the four cell lines is seen for COL1A1 and, in the HRC59 and ACHN cell lines for IGFBP3, after treatment compared with the signal obtained from the untreated cell lines. IGFBP3 also showed strong up-regulation in the cell lines 786-0 and HRC51, although these two cell lines had weak basal expression of the gene before the treatment. This basal expression may represent unmethylated, or less densely methylated, subclones in the cell lines (15, 28).


Figure 1
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  		Figure 1. RT-PCR validation of expression up-regulation after drug treatment. Reverse transcribed and PCR amplified untreated (U) and treated (T) DNA from the four RCC cell lines analyzed for expression of six genes and the GAPDH control (left). The stronger signal in the majority of the treated samples confirms the up-regulation of the genes, indicated by the array results, after demethylation treatment of the cell lines.

 
We next analyzed the methylation status of the promoter CpG island proximal to the transcription start site for the 12 genes in the four RCC cell lines and normal renal epithelial cells by bisulfite sequencing (Fig. 2 ). Five genes were densely methylated in the untreated RCC lines (Fig. 2A), indicating potential epigenetic regulation of these genes. Importantly, only the individual RCC lines where a particular gene was methylated showed up-regulation of expression for the same gene after demethylating treatment by the microarray and RT-PCR assays, whereas the cell lines where a gene was unmethylated did not show up-regulation after treatment. Promoter hypermethylation of IGFBP1, IGFBP3, and COL1A1 was cancer cell specific because methylated CpGs were seen only in the RCC lines and not in the normal cell DNA specimens sequenced (Fig. 2A).


Figure 2
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  		Figure 2. Bisulfite sequencing of the gene promoter CpG islands in tumor and normal DNA. A, sequencing of normal tissue (NK) DNA and RCC cell line DNA (right) after bisulfite modification for six genes. Unmethylated cytosines (C) are converted to uracil (T). The presence of C preceding a G in the sites indicated by arrows shows that these cytosines were methylated in the RCC cell line DNA, whereas the presence of T instead of C in the same positions in the normal DNA shows that these C were unmethylated in the normal tissue DNA. GDF15 shows methylation of CG dinucleotides in normal cell DNA and more dense CG methylation in the tumor cell DNA. TGM2 was unmethylated in both the normal and tumor cell line DNAs. B, representative bisulfite sequencing of a RCC cell line (right) for six genes with unmethylated promoter regions. Unmethylated cytosines (C) are converted to uracil (T). The absence of C preceding a G in the sites indicated by arrows shows that these cytosines were unmethylated in the tumor cell line DNA.

 
Frequency of hypermethylation of IGFBP1, IGFBP3, and COL1A1 in primary RCC. To determine if hypermethylation of the three genes was frequent in primary renal cancer and not limited to, or more common in, tumor cell lines, we did MSP analysis of 32 primary, mainly organ-confined (stage I or II), renal tumors of the most common histologic cell types (20 clear cell, 10 papillary, and 2 chromophobe). IGFBP1 was methylated in 10 of 32 (31%), IGFBP3 in 12 of 32 (37%), and COL1A1 in 18 of 32 (56%) primary RCC (Fig. 3A ; Table 2 ). Because conventional MSP is not quantitative, we cannot be certain the methylation of the genes in the primary renal tumors is clonal, as we observed in the RCC cell lines, without further studies. IGFBP3 showed a similar percentage of methylation between clear cell (7 of 20, 35%) and papillary (4 of 10, 40%) tumors. IGFBP1 was more frequently methylated in clear cell (7 of 20, 35%) than papillary tumors (2 of 10, 20%) as was COL1A1 (13 of 20, 65% clear cell versus 4 of 10, 40% papillary). Thus, the three genes were frequently methylated in early-stage tumors of the most common histologic subtypes of RCC, implicating these genes in renal tumorigenesis and as novel candidate markers for the molecular detection and prognosis of kidney cancer. Further impetus has been provided by studies showing the feasibility of detecting gene hypermethylation in urine, a readily accessible bodily fluid for diagnosis and monitoring of renal cancer (21, 29).


Figure 3
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  		Figure 3. A, MSP of IGFBP1, IGFBP3, and COL1A1 in primary renal tumors. The presence of a PCR product in the methylated lane (M) indicates that tumors KT28, KT31, and KT78 have methylated alleles for IGFBP1; KT49, KT31, and KT53 for IGFBP3; and KT15, KT19, and KT38 for COL1A1. The PCR product in the unmethylated lane (U) from tumor DNA most likely arises from normal cell contamination of the tumor specimen. Because of the different base composition of the unmethylated versus methylated primers and template sequence, MSP products are nonquantitative and do not necessarily reflect the relative levels of unmethylated to methylated alleles in the primary tumor. Tumor cell lines 786-0 for IGFBP1 and ACHN for IGFBP3 and COL1A1 as positive controls and normal renal cell DNA as a negative control (far right). B, MSP of RASSF1A in the four RCC lines. The presence of a PCR product in the methylated lane (M) indicates that RASSF1A is hypermethylated in RCC lines 786-0, HRC59, and ACHN. The absence of a product in lane M of HRC51 indicates that RASSF1A is unmethylated in this line. Normal renal cell DNA as a negative control and tumor cell line MDA231 DNA as a positive control.

 

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  		Table 2. Clinicopathologic data of primary RCC

 
Aberrant hypermethylation of normally unmethylated promoter regions with associated transcriptional silencing in cancer cells is a characteristic of TSG (5, 6). The three genes we have identified are, therefore, candidate TSGs, although further testing is needed. The IGFBP1 gene maps to chromosome 7p13; IGFBP3 maps to 7p14; and COL1A1 maps to 17q21. These chromosomal regions have not been examined for loss of heterozygosity in renal cancer (30, 31). High-density single nucleotide polymorphism array analysis will establish if allelic deletion occurs at these loci.

Role of the reactivated genes in tumorigenesis. With regard to the putative role of these genes in cancer, the insulin-like growth factor binding protein 1 (IGFBP1) and IGFBP3 are major forms of the IGFBP family that can inhibit the growth promoting activity of both IGF-I and IGF-II. IGFBP3 is known to inhibit cell growth by sequestering IGF-I; however, the mechanism by which IGFBP1 exerts its activity is less well understood. Down-regulation of IGFBP3 expression has been reported in non–small cell lung cancer (32), prostate cancer (33), and hepatocellular carcinoma (34), where IGFBP3 promoter hypermethylation was also described (35). IGFBP3 was also recently identified as hypermethylated in a mouse skin multistage carcinogenesis model (36). Clearly, methylation-based silencing of IGFBP1 and IGFBP3 could provide growth advantages to the neoplastic cell. Activation of this pathway may be of therapeutic advantage in limiting tumor growth.

COL1A1 is the human gene coding for the {alpha}1 chain of type I collagen, the major extracellular matrix component of skin and bone. Changes in the synthesis of type I collagen are associated with normal growth and tissue repair processes. The related genes COL1A2 and COL1A5 have also been reported to be hypermethylated in cancer cells (37, 38). Alterations in extracellular matrix composition have been implicated in tumor progression and metastasis. Both the IGFBP and the COL1A gene families seem prone to hypermethylation, and it is interesting that other global epigenetic screens have shown reactivation of gene families [e.g., IFN in bladder (15) and SFRP family members in colorectal cancer (16)].

The fourth reactivated gene found to have promoter methylation was a growth differentiation factor gene (GDF15) located on chromosome 19p. GDF15 showed methylation of CpG dinucleotides in normal cell DNA but more dense CG methylation in the tumor cell DNA and thus merits further study. Hypermethylation of GDF15 in normal cells may be age related as described for myoD1 and other cancer genes (39). The fifth gene (PLAU) was densely methylated in one of the four RCC lines (HRC51); however, by RT-PCR analysis, PLAU expression did not seem up-regulated after demethylating treatment of this line. The other three lines did show PLAU up-regulation by RT-PCR, but all had unmethylated promoters. The functional significance of PLAU promoter hypermethylation is therefore unclear.

The remaining seven up-regulated genes had unmethylated promoters by bisulfite sequencing analysis (Fig. 2) but could have been activated by an upstream regulatory gene or transcription factor that was reactivated by demethylation. In support of this idea, TGM2 has been reported to be regulated by the candidate TSG RASSF1A (40), known to be frequently methylated in RCC (9–11). RT-PCR confirmed clear up-regulation of TGM2 in the four RCC lines after treatment (Fig. 1). We examined RASSF1A by MSP and found it to be methylated in three of the four RCC lines (Fig. 3b). The same three RCC cell lines showed up-regulation of RASSF1A on the expression array after demethylating treatment. We identified an equal number of methylated and unmethylated genes; however, because <1% of genes in a human tumor cell are methylated, our screen preferentially identified methylated genes. It is also likely that the epigenetic reactivation of particular genes leads to a cascade of up-regulation in diverse pathways and networks. Other genes may be up-regulated as a direct response to the stress of 5Aza-dC treatment. Lastly, although in this initial validation, we did not bisulfite sequence promoter CpG islands that contained repetitive elements, the three genes excluded from initial validation will require further study because the VHL and p16INK4a TSGs are known to contain repetitive elements in, or near, the promoter CpG island but still to have promoter hypermethylation of functional significance (7, 41). Refinement of intuitive selection criteria will help to better prioritize genes up-regulated after treatment for validation in future studies.

Alternative strategies for global profiling of gene methylation in cancer. Until recently, global strategies to identify methylated genes in cancer tended to use arrayed CpG island fragments identified through restriction enzyme recognition sequences (42, 43). One issue with such an approach is that many CpG islands are located outside promoter regions, and methylation of such islands does not have a functional effect upon transcription (16). A microarray-based screen of genes reexpressed after demethylation treatment can address this issue by using reactivation of transcription, rather than the presence of a CpG island, as the identifying determinant. There have now been several other global epigenetic studies highlighting the advantages and issues of this approach (15–20). The SPINT2 gene was recently identified as methylated in 40% of papillary and 30% of clear cell renal tumors after demethylation treatment of RCC lines (44). These epigenetic reactivation profiles may in part also be array type dependent and sensitive to different 5Aza-dC doses and treatment times. One disadvantage of a drug-based reactivation approach is that unlike CpG island array screening (42), use is essentially restricted to cell cultures and is not amenable to examination of primary tumors.

We validated 12 genes up-regulated after demethylating drug treatment and found IGFBP1, IGFBP3, and COL1A1 to have cancer cell specific hypermethylation, which correlated with epigenetic reactivation of expression: GDF15 to be methylated in normal renal cells but hypermethylated in cancer, PLAU to be methylated but with a weak correlation to expression status, and TGM2 to be unmethylated but known to be regulated by another gene methylated in renal cancer cells. Thus, importantly, at least 6 of 12 genes could be shown to be under epigenetic control in support of the ability of our screen to preferentially identify new hypermethylated genes in renal cancer. The three novel hypermethylated genes are candidate tumor suppressor genes and are frequently methylated in primary renal tumors. Their potential use in current molecular diagnostic or prognostic strategies can now be examined (21, 29). As a gene methylation signature is further developed for renal cancer, we will likely gain important insights into the biology and progression of this disease.


   Acknowledgments
 
Grant support: NIH Early Detection Research Network grant 1 U01 CA111242-01.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.


   Footnotes
 
Note: Supplementary data for this article are available at Cancer Research Online (http://cancerres.aacrjournals.org/).

Disclosure: P. Cairns is a paid consultant to Oncomethylome Sciences. The terms of this arrangement are being managed by Fox Chase Cancer Center in accordance with its conflict of interest policies.

Received 9/19/05. Revised 3/14/06. Accepted 3/21/06.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results and Discussion
 References
 

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