Discovery of Novel Methylation Biomarkers in Cervical Carcinoma by Global Demethylation and Microarray Analysis

114 Discovery of Novel Methylation Biomarkers in Cervical Carcinoma by Global Demethylation and Microarray Analysis

Pavel Sova,1 Qinghua Feng,1 Gary Geiss,2 Troy Wood,1 Robert Strauss,2 Vania Rudolf,1 Andre Lieber,2 and Nancy Kiviat1 1Department of Pathology, School of Medicine at South Lake Union and 2Division of Medical Genetics, University of Washington, Seattle, Washington

Abstract

A genome-wide screening study for identification of hyper- RRAD, SFRP1, MT1G, and NMES1) is present in a high methylated genes in invasive cervical cancer (ICC) was proportion of ICC clinical samples but not in normal carried out to augment our previously discovered panel of samples. Of these genes, SPARC and TFPI2 showed the three genes found to be useful for detection of ICC and highest frequency of aberrant methylation in ICC speci- its precursor neoplasia. Putatively hypermethylated and mens (86.4% for either) and together were hypermethylated silenced genes were reactivated in four ICC cell lines by in all but one ICC cases examined. We conclude that treatment with 5-aza-2V-deoxycytidine and trichostatin A expression profiling of epigenetically reactivated genes and identified on expression microarrays. Thirty-nine of followed by methylation analysis in clinical samples is a the 235 genes up-regulated in multiple ICC cell lines were powerful tool for comprehensive identification of methyl- further examined to determine the methylation status of ation markers. Several novel genes identified in our study associated CpG islands. The diagnostic use of 23 genes that may be clinically useful for detection or stratification of were aberrantly methylated in multiple ICC cell lines were ICC and/or of its precursor lesions and provide a basis for then analyzed in DNA from exfoliated cells obtained from better understanding of mechanisms involved in develop- patients with or without ICC. We show, for the first time, ment of ICC. (Cancer Epidemiol Biomarkers Prev that aberrant methylation of six genes (SPARC, TFPI2, 2006;15(1):114–23)

Introduction

The control of ICC is based upon detection and treatment of make this approach impractical in resource poor settings. the cervical intraepithelial neoplasia stage III (CIN-3) precur- Lastly, our studies showed that vaccines that prevent HPV sor lesions and carcinoma in situ (CIS). In the United States infection will eventually be central to cervical cancer control and other developed countries, the incidence of ICC has (3); however, because such vaccines will not offer protection to dramatically decreased as a result of the identification and most of the millions of women already infected with oncogenic ablation of the precursor CIN-3/CIS lesions achieved via HPVs, screening will be necessary for the foreseeable future. regular Papanicolaou screening with referral of all women Thus, development of more accurate molecular screening with abnormal Papanicolaou smears (atypical squamous cells methods that could be automated would be of significant of undetermined significance and greater) to repeat cytology interest. or colposcopy and biopsy. This approach is costly and Epigenetic silencing of a variety of genes by hypermethy- extremely burdensome to the health care system but deemed lation of promoter-associated CpG islands is now recognized necessary in light of the low reproducibility of cytology and as a frequent and early event in the pathogenesis of many the low sensitivity of a single cytologic smear (range, 30-60%) cancers, including ICC, making such changes of potential to detect CIN-3 (1). More recently, testing for oncogenic interest as biomarkers for identification of individuals with or human papillomavirus (HPV) types has been introduced to at risk for cancer (4). Currently, relatively little is known about help triage women with atypical squamous cells of undeter- specific patterns of CpG island hypermethylation in ICC. mined significance. Nevertheless, current recommendations Most previous studies examining DNA hypermethylation in (2) based on a screening approach, which include HPV-based ICC have generally focused on testing of genes known to be triage of atypical squamous cells of undetermined significance, aberrantly methylated in other cancers (the candidate gene will send over three million women each year for colposcopy approach; refs. 5-7). In the largest such study thus far, we and biopsy, although most are at little risk of ICC. Further- studied 21 candidate hypermethylated genes and identified a more, the cost and infrastructure requirements of primary panel of three (DAPK1, RARB, and TWIST1), which were screening based on cytology (with or without HPV testing) sensitive and specific for ICC and its immediate precursor CIS. We estimated that detection of hypermethylation of these three genes in exfoliated cell samples would identify histologically Received 5/4/05; revised 8/23/05; accepted 11/14/05. confirmed CIN-3 or worse with a sensitivity of 60% and Grant support: NIH grant CA097275 (N.B. Kiviat). a specificity of 95% in unscreened women over age 35, The costs of publication of this article were defrayed in part by the payment of page charges. presenting to community based clinics for reasons other than This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. cervical neoplasia (8). This study also showed that exfoliated Note: Supplementary data for this article are available at Cancer Epidemiology Biomakers and cell samples could be used to identify women who had Prevention Online (http://cebp.aacrjournals.org/). acquired hypermethylated changes in their cervical epithelial Requests for reprints: Pavel Sova, Department of Pathology, University of Washington, 815 cells that are highly associated with CIS/ICC (8). However, Mercer Street, Box 358050, Seattle, WA 98109-4325. Phone: 206-897-1584; Fax: 206-897-1334. E-mail: [email protected] whereas the performance of this panel of hypermethylated Copyright D 2006 American Association for Cancer Research. genes compared favorably with the performance of exfoliated doi:10.1158/1055-9965.EPI-05-0323 cervical cytology and detection of high-risk types of HPV

DNA, hypermethylated genes with increased sensitivity and and 30 Ag were labeled by incorporating amino-allyl dUTP in specificity for ICC and precursor neoplasia will need to be cDNA using reverse transcriptase (Invitrogen) according to identified if detection of DNA hypermethylation in exfoliated the manufacturer’s instructions. For C4I, CaSki, and SiHa cells, cell samples is to have clinical utility for cervical cancer total RNA was amplified and labeled with amino-allyl dUTP screening. The present study was undertaken to find such using the Amino Allyl MessageAmpTM aRNA amplification kit genes using a genome-wide examination of the methylation (Ambion, Austin, TX). Genomic DNA from untreated cells pattern of cervical cancer cell lines. lines was isolated using the QiaAmp DNA Mini kit (Qiagen). A number of different approaches to genome-wide identi- cDNA Array Hybridization. Human cDNA microarrays fication of cancer-associated hypermethylated genes have been consisting of 17,568 sequence-verified clones from the Re- developed, including restriction landmark genome scanning, search Genetic IMAGE (Integrated Molecular Analysis of methylation-sensitive arbitrarily primed PCR, and methylated Genomes and their Expression) clone set, available through CpG island amplification (4). An alternative approach is to Invitrogen (http://clones.invitrogen.com) were printed by the treat cells with epigenetic modifying drugs to allow expression Fred Hutchinson Cancer Research Center’s DNA microarray of hypermethylated/silenced genes and to then compare the facility. Labeled cDNA or aRNA were coupled from both expression profile by microarray analysis of untreated and directions with Cy3 and Cy5 dyes according to the manufac- drug-treated cells to identify putatively hypermethylated turer’s instructions (Amersham Biosciences, Piscataway, NJ). genes. The methylation status of such genes can then be Replicate hybridizations to microarrays were done with three confirmed in untreated cells using methylation-specific PCR independent RNA isolates for C4I, HeLa, and SiHa and two analyses. Global demethylation and expression microarray independent RNA isolates for CaSki; each isolate was analysis has been successfully used to identify a number of hybridized twice with a dye swap. Microarray slides were novel genes hypermethylated in association with colorectal scanned at wavelengths of 532 and 635 nm using a dual-laser and pancreatic cancer (9, 10). In the present study, we treated V GenePix4000A microarray scanner (Axon Instruments, Union four ICC cell lines (C4I, CaSki, HeLa, and SiHa) with 5-aza-2 - City, CA), and fluorescence data were extracted using the deoxycytidine (DAC), a DNA methyltransferase inhibitor, and GenePix Pro 3.0 program. trichostain A, a histone deacetylase inhibitor and compared the pretreatment and post-treatment expression profiles to identify Array Data Analysis and Statistical Methods. Raw hybrid- putatively hypermethylated genes. Genes with low initial ization signals were normalized using the locfit (LOWESS) expression that were strongly up-regulated after treatment in method in MIDAS program (12). The two numbers for each the cancer cell lines were considered of potential interest as spot, representing its normalized median fluorescence minus ICC-associated hypermethylated genes. For such potentially the median background fluorescence in both scanning wave- hypermethylated genes, methylation-specific PCR analyses lengths, were used to calculate the log2-transformed ratios were carried out to examine the presence of aberrantly of normalized intensities. The ratios reflected the expression methylated CpG dinucleotides in cell lines. Twenty-three changes of individual transcripts upon DAC/trichostain A genes, thus identified as hypermethylated in cell lines, were treatment. The basal expression of genes was estimated from assessed for the diagnostic use in clinical samples. Using this fluorescence signals of hybridized cDNA or aRNA targets approach, we identified six genes whose methylation has not generated from mock-treated cells; the signal values were log2 been previously described in ICC but which seem to be of a transformed and mean centered. For hierarchical clustering great interest as methylation biomarkers for detection of this analysis, expression ratios from 11 experiments in cervical disease. carcinoma cell lines were combined and filtered to include only genes that were up-regulated at least 2-fold in five or more individual experiments (i.e., up-regulated in at least two Materials and Methods cell lines; 235 genes). To include basal expression pattern in our analysis, expression ratios of 235 up-regulated genes were Cell Lines and Tissue Samples. HeLa, SiHa, CaSki, and C4I combined with basal expression values and clustered such that were obtained from the American Type Culture Collection basal expression values were given twice the weight of ratio (Manassas, VA) and grown in DMEM (HeLa, SiHa, and C4I) or values. Clustering and visualization were done in Cluster and RPMI (CaSki) supplemented with penicillin (0.5 units/mL), TreeView (13). To ascertain the reproducibility of array data streptomycin (0.5 Ag/mL), Glutamax (2 mmol/L), and 10% (v/ obtained in repeated experiments, we calculated the SD of v) fetal bovine serum. All media and supplements were from expression ratio and coefficient of variance. Data summarizing Invitrogen (Carlsbad, CA). Cervical exfoliated cell samples expression ratios have been deposited in GEO database were obtained as previously described (11) from women with (http://www.ncbi.nlm.nih.gov/projects/geo/) in series and without cervical neoplasia in a study in Dakar, Senegal, GSE2097, in accordance with MIAME standards (14). A proba- approved by the University of Washington Internal Review bility associated with methylation pattern of candidate genes in Board. Median age and high-risk and low-risk HPV prevalence ICC-positive and ICC-negative exfoliated cervical cell clinical in patient population is listed in Table 1. DNA from 43 samples was calculated using Fisher’s exact test. exfoliated cell samples was isolated using the QiaAmp DNA Mini kit (Qiagen, Valencia, CA). Real-time Reverse Transcription-PCR. Five micrograms of total RNA were reverse-transcribed using Superscript II Treatment with DAC and Trichostain A and RNA Isolation and Processing. The four cervical carcinoma cell lines listed above were seeded in 10-cm culture dishes at a low Table 1. Basic characteristics of patient population density and treated with 200 nmol/L DAC for 3 days and with 300 nmol/L trichostain A for the last 24 hours. Medium Patient group containing fresh drugs was replaced daily. Controls consisted Normal ICC of cells treated identically with drug solvents (PBS and 100% ethanol), and all experiments were done in duplicate or No. cases 21 22 triplicate (see below). After treatment, cells were removed Age median 45 39 High-risk HPV 65% 91% from dishes using trypsin/EDTA solution (Invitrogen) and Low-risk HPV 35% 9% rinsed with media containing 10% fetal bovine serum. Total RNA from mock-treated and DAC/trichostain A–treated NOTE: 100% of patients tested positive for HPV; table breaks down the presence HeLa cells was isolated using the RNEasy Mini kit (Qiagen), of high-risk or low-risk HPV types.

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(Invitrogen). Each cDNA sample was additionally prepared in Copy number of specific genes in samples was enumerated the absence of enzyme and used as a negative control to using the standard curve generated from known amount of estimate the amount of contaminating DNA. From a resulting bisulfite-converted h-actin sequence. The ‘‘percent of methyl- 20-AL reaction mix, 0.17 AL was used as a template in triplicate ated reference’’ (PMR) values were calculated using a formula PCR reactions in a Prism HT7900 Sequence Detection System [Ngene / Nactb(sample)] / [Ngene / Nactb(M)] Â 100%, where N (ABI, Foster City, CA) under the following conditions: (a)95jC denotes copy number for a gene or h-actin amplicon in a for 10 minutes; (b) 40 cycles of 95jC for 20 seconds, 60jC for clinical sample or in fully SssI-methylated DNA (M). A cutoff 20 seconds, and 72jC for 45 seconds; (c) final extension PMR value, above which samples were considered methylated for 2 minutes at 72jC; and (d) denaturation/renaturation and below which samples were considered unmethylated, step for melting curve analysis. The TMP21 gene that has was determined to discriminate best between histologically previously been found to be expressed in most tissues (15) was normal and ICC clinical samples. The cutoff value was used as an external standard for each plate. The primers for calculated as a median PMR value of histologically normal genes examined in our study are listed in Supplementary Table samples (if >0) plus 1 percentage point. If none or only one S01. The change in gene expression was calculated using the 2- PMR value among negative samples was >0, cutoff was DDCt method, in which the DCt value was calculated by automatically adjusted to 1. subtracting the Ct value of TMP21 from a gene-specific Ct value. The DDC value was calculated by subtracting the DC t t Results value, obtained from mock-treated cells, from the DCt value obtained from drug-treated cells. Presence of single amplifica- Identification of DAC and Trichostain A Induced Genes tion products in reactions was ascertained by melting curve in Cervical Carcinoma Cell Lines. To identify hypermethy- analysis and gel electrophoresis. lated genes associated with cervical cancer, we first treated Detection of CpG Methylation. Genes selected for methyl- four cervical carcinoma cell lines (C4I, CaSki, HeLa, and SiHa) ation analysis were evaluated using methylation specific PCR with DAC and trichostain A. The treatment conditions were (MSP), methylation-specific melting curve analysis (MS-MCA), chosen such that they would induce low toxicity but cause and MethyLight assay (16-18). CpG island sequences were widespread reactivation of genes silenced by aberrant meth- obtained from the University of California Santa Cruz genome ylation of their CpG islands (21). A cDNA expression micro- browser (http://genome.ucsc.edu/) or from genomic informa- array hybridization comparing the mock and drug treatment tion using CpGPlot (http://www.ebi.ac.uk/emboss/cpgplot/). expression patterns in these cultures was then done to identify MSP and MS-MCA primers were designed using MethPrimer reactivated genes (summarized in Fig. 1). The number of genes (19). MethyLight primers and MGB probes were designed differentially expressed (>2-fold) in specific cell lines varied using Primer Express (ABI). Sequences of primers and probes are listed in Supplementary Table S01. For methylation analysis, DNA from cultured cells or exfoliated cervical epithelial cells isolated using the QiaAmp DNA Mini kit (Qiagen) was first converted by sodium bisulfite method (20). Briefly, a saturated solution of sodium bisulfite containing 100 mmol/L hydroquinone was added to denatured DNA, and the resulting mixture was incubated at 55jC for 4 hours. DNA was subsequently recovered using the Qiaex II Gel Extraction kit (Qiagen), air-dried, eluted, and desulfonated, and finally ethanol precipitated in the presence of 1.93 mol/L NH4OAc and coprecipitant (Pellet Paint, Novagen, San Diego, CA) and dissolved in 100 AL TE [2 mmol/L Tris-HCl (pH 8), 0.3 mmol/L EDTA]. For MSP or MS-MCA, 1 AL of this solution was used as a template for PCR in a Prism HT7900 instrument using 1 unit AmpliTaq Gold, in a mix containing 1.5 mmol/L MgCl2, 62.5 Amol/L each deoxynucleotide triphosphate, 150 nmol/L each primer, and 0.134 AL of 1,000Â diluted SYBR Green I (Molecular Probes, Eugene, OR), with PCR cycling conditions as above. A DNA melting curve was acquired by measuring fluorescence of SYBR Green I during a linear temperature transition from 60jCto95jC at 0.2jC/s, and fluorescence data were converted into melting peaks by the HT7900 instrument SDS 2.0 software. In MS-MCA, the extent of methylation (TM index) in cell lines was calculated based on the increase of melting temperature using the formula (TM,M À TM,SAMPLE)/(TM,M À TM,U) Â 100, where TM denotes the melting temperature of the amplicon obtained from the Figure 1. Identification of upregulated and silenced genes in four melting peak plot, and U and M denote the fully methylated or cervical carcinoma cell lines following treatment with DAC and fully unmethylated templates, respectively. For MethyLight, trichostatin A and subsequent microarray analysis. A. Number of up- 0.5 AL of bisulfite-converted DNA solution was combined regulated or down-regulated genes (z2-fold) in individual cell lines with 600 nmol/L each primer and 100 nmol/L probe in ABI after treatment. Numbers of genes are indicated above or below bars. Universal PCR Master Mix and amplified under the default Open columns, down-regulated genes; solid columns, up-regulated cycling conditions for Prism HT7900 instrument. Human genes. B. Venn diagram showing the total number of genes up- sperm DNA and human sperm DNA methylated in vitro regulated z2-fold in each cell line and in combinations of cell lines. using the SssI (CpG) methylase (New England Biolabs, C4, C4I; Ca, CaSki; He, HeLa; Si, SiHa. C. Flowchart of selection Beverly, MA), respectively, were used as U (unmethylated) and validation of candidate hypermethylated genes. Dotted line and M (fully methylated) control DNA. Size of PCR products denotes the quantitative RT-PCR (qRT-PCR) and/or methylation in representative samples was ascertained on agarose gels. analysis steps in cell line, where 63 genes were examined.

Cancer Epidemiol Biomarkers Prev 2006;15(1). January 2006 Downloaded from cebp.aacrjournals.org on September 29, 2021. © 2006 American Association for Cancer Research. Cancer Epidemiology, Biomarkers & Prevention 117 from high 1,136 genes in SiHa to low 126 genes in C4I. As Methods) corresponded to CpG methylation data obtained by expected in tumor-derived cell lines containing many hyper- bisulfite sequencing of target areas and found an excellent methylated and silenced genes (22), the number of match. An example is shown in Fig. 3 for SFRP1-associated up-regulated genes was higher than the number of down- amplicon. The 275-bp amplicon located within the CpG island regulated genes in all cell lines except in CaSki (Fig. 1A). associated with this gene contains 24 CpG dinucleotides, 61.5% Overall, 1,068 genes were up-regulated z2-fold in at least of which were methylated in HeLa on average and 93.8% and one cervical carcinoma cell line after treatment (Fig. 1B). The 97.2% in SiHa and CaSki, respectively (Fig. 3A; sequence data specific sets of up-regulated genes varied in individual cell for C4I was not obtained). The position of cell line–specific lines, and only 15 genes were up-regulated in all cell lines melting peaks relative to U and M DNA (Fig. 3B) matched well simultaneously (Fig. 1B). We reasoned that genes hyper- with the relative proportion of methylated CpGs as the TM methylated in primary ICC tumors would be hypermethylated index, indicating this density was 75 in HeLa and 95 in CaSki and reactivated by drug treatment in multiple cervical and SiHa, respectively. For a number of genes, a classic MSP carcinoma cell lines. To select such genes, we carried out a assay (17) was done and found to largely confirm data hierarchical clustering analysis of array data obtained from obtained by MS-MCA (data not shown). Subsequently, 39 mock-treated and drug-treated cells that essentially selected genes (21 of the 46 genes whose up-regulation was confirmed genes that were up-regulated z2-fold simultaneously in two or by quantitative RT-PCR, and an additional 18 genes selected more cell lines (data not shown). This analysis identified a based on the array data but not examined by quantitative RT- cluster of 235 genes (data are summarized in Supplementary PCR) were examined by MS-MCA to determine the presence Table S02). Within this cluster, we were especially interested in and extent of CpG dinucleotide methylation in their promoter- genes with low expression in mock-treated cells that separated associated CpG islands (refer to Fig. 1C). These analyses into a subcluster of 125 genes. Sixty-three such genes were showed that 33 of 39 genes were extensively methylated selected for further analysis (Fig. 1C). Among genes that (TM index > 50) in at least one cell line, and 17 of these genes decreased their transcriptional activity after treatment, 134 showed extensive methylation in three or four cell lines were down-regulated in multiple cell lines (Supplementary (Table 2). Specifically, 26 genes were extensively methylated Table S02). Down-regulated genes were not the focus of this in CaSki, 19 in SiHa, 18 in C4I, and 15 in HeLa cells (Table 2). study (see Discussion). Methylation Analysis of Candidate Genes in Clinical Confirmation of Expression Data by Real-time PCR. To Cervical Samples. We next sought to determine whether or confirm expression data obtained from array experiments, we not the hypermethylated genes identified in the preceding did quantitative real-time reverse transcription-PCR (RT-PCR) experiments in cell lines were also hypermethylated in for 46 of the 63 genes of interest, using RNA isolated from primary cervical cancers. This was examined in exfoliated mock-treated and DAC/trichostain A–treated cell lines. cervical cell samples obtained from patients with and without Quantitative RT-PCR allowed us to estimate the pretreatment ICC, as confirmed by a same-day biopsy and histology expression of these genes and the post-treatment ratio examination. We first used MS-MCA and MSP to estimate reflecting their up-regulation or down-regulation indepen- the prevalence of methylation in CpG islands associated with dently of array results (Table 2). Both the pretreatment (mock) 23 genes identified as hypermethylated in cervical cancer cell expression levels and expression changes induced by treat- lines (Table 2). Of these genes, nine (DKK3, HPCAL4, MT1G, ment were estimated using the reference housekeeping gene NMES1, RRAD, SFRP1, SPARC, TFPI2, TPPP) were more often TMP21 (Table 2) that is constitutively expressed in most methylated in ICC-positive clinical samples (n = 22) than in tissues (15). In our experiments using cervical carcinoma cell ICC-negative (normal) samples (n = 21; Table 2), whereas two lines, its expression was determined to be slightly above the genes (FLJ20152 and GSN) were not methylated in any clinical median level of all genes present on the array, and it did not sample, and one gene (SLC7A8) was methylated only in one change after DAC and trichostain A treatment (data not shown). ICC-positive sample and in none of the normal samples. CpG The correlation between ratios obtained from quantitative islands associated with additional nine genes (BRDT, C8ORF4, RT-PCR and array for 42 genes in each of the four cell FLJ13937, FLJ36166, GAGED2, GPNMB, HSPA2, NALP2, and lines is shown in Fig. 2. For all but a few genes in each cell SSX4) displayed partial or complete methylation in most or all line, the direction of expression change was the same in both negative as well as positive samples (Table 2). assays, as indicated by the clustering of data points in the Among nine genes hypermethylated in association with ICC, top right quadrant of the plots. In addition, higher ratios six (MT1G, NMES1, RRAD, SFRP1, SPARC, and TFPI2) were were consistently obtained by quantitative RT-PCR (slopes analyzed in clinical samples by quantitative MethyLight assay. > 1). Based on these results, we were confident that Numbers of negative and positive results of MethyLight assay the identification of reexpressed genes from array data was (i.e., when the PMR value was either 0 or >0, respectively) in valid, and that a 2-fold cutoff for array ratios was sufficient these samples for each gene are shown in Table 3. Results show for identifying differentially regulated and potentially that the aberrant methylation of studied genes was present in methylated genes. ICC-positive samples with high (SPARC and TFPI2_2)to Methylation Analysis of Candidate Genes in Cell Lines. modest (MT1G and NMES1) frequency. At the same time, these The methylation of CpG islands associated with the majority of genes were methylated in ICC-negative samples with generally candidate genes that we selected for further analysis has not low frequency, with RRAD and TFPI2 being the only exception been analyzed previously. Therefore, we employed a method as its PMR value was >0 in nine and eight normal samples, shown earlier to reliably score methylated CpG content in respectively (Table 3). target DNA sequences. The assay, MS-MCA, relies upon We noticed that PMR values for all genes were low in the determination of melting temperature of a PCR product vast majority of normal samples, indicating that the level of derived from bisulfite-converted DNA amplified from methylation within DNA sequences targeted by MethyLight or methylation-insensitive primers (16). Methylated CpG dinu- the proportion of cells containing the methylated alleles (or cleotides are in this assay amplified as CpGs, whereas possibly both) were low in these samples. This is illustrated in unmethylated CpGs are amplified as TG dinucleotides, Fig. 4, in which the PMR values derived from normal and ICC consequently lowering the melting temperature in a typical samples are plotted separately for each gene. Plotted are also amplicon by several degrees Celsius (16). We first confirmed in median PMR values for negative and ICC samples (median DNA isolated from HeLa, SiHa, and CaSki that the amplicon- PMR values for negative samples plus 1 percentage point specific melting temperature shift (TM index, see Materials and were used to set a PMR cutoff, above which samples were

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Table 2. Quantitative RT-PCR and methylation analysis in cell lines for 62 candidate genes selected based on array data

Gene description Pretreatment Quantitative MS-MCA Methylation expression RT-PCR fold (TM index) or in clinical change MSP (+ or À) samples after DAC/TSA in cell lines treatment

Symbol Gene name HeLa SiHa CaSki C4I HeLa SiHa CaSki C4I HeLa SiHa CaSki C4I

AQP3 Aquaporin 3 (F)(F)(À)(F) 3.8 1.2 28 15 ATF3 Activating transcription factor 3 (F)(F)(F)(F) 1.7 1.5 6.6 3 12 6 0 0 (À) BIRC3 Baculoviral IAP (++) (++) (++) (++) 6.1 0.5 224 52 repeat-containing 3 BMP2 Bone morphogenetic (++) (F)(F)(F) 2.5 1.3 6.7 2.9 protein 2 BRDT Bromodomain, testis-specific 82 100 100 100 (+)* C8ORF4 Chromosome 8 open (++) (F)(F)(F) 3.8 25 126 5.8 + + + + (+)* reading frame 4 CAMK1 Calcium/calmodulin–dependent 2 0 95 0 protein kinase I CDH1 Cadherin 1, type 1, (++) (À) (++) (++) 119 3.1 1.1 0.9 6 6 81 0 E-cadherin (epithelial) CDH16 Cadherin 16, KSP-cadherin 58 108 108 100 CITED2 Cbp/p300-interacting (À)(À)(À)(À) 7.4 1.9 429 8.5 0 0 0 0 transactivator CKB Creatine kinase, brain (F)(À)(À)(À) 0.7 1.9 14 5.2 12 112 96 CRYM Crystallin, mu 4 0 100 U+M CTGF Connective tissue growth factor (F)(F)(À)(À) 13 1.8 30 0.7 CYP1A1 Cytochrome P450, family 1, 0 0 82 0 subfamily A, polypept. 1 CYP24A1 Cytochrome P450, family 24, 26 33 87 U+M (À) subfamily A, polypeptide 1 DKK3 Dickkopf homologue 3 97 100 100 103 (+) (Xenopus laevis) DNAJ6 DnaJ (Hsp40) homologue, (++) (F)(F)(F) 1.2 1.2 2 1.4 subfamily B, member 6 DNER Delta-notch-like EGF (À)(À)(À)(À) 1.7 22 5.5 188 repeat-containing transmembrane DUSP5 Dual specificity phosphatase 5 (F)(À)(F)(F) 3.8 1.5 2.8 1.9 0 0 EFHC1 EF-hand domain (COOH-terminal) (F)(F)(F)(F) 2.4 1.4 4 2.6 containing 1 F2RL1 Coagulation factor II (thrombin) (F)(F)(F)(F) 3.9 1.4 1 2.2 receptor-like 1 FLJ11127 Hypothetical protein FLJ11127 (++) (F)(F)(À) 7 3.1 2.2 10 FLJ13937 Hypothetical protein FLJ13937 100 100 100 100 (+)* FLJ20152 Hypothetical protein FLJ20152 (F)(F)(F)(F) 5.2 1.3 2.9 11 66 41 24 17 (À) FLJ36166 Hypothetical protein FLJ36166 (À)(F)(À)(À) 69 0.9 27 11 72 90 79 77 (+)* FN1 Fibronectin 1 (À)(À) (++) (++) 443 4.5 2.4 4.1 75 35 35 10 GAGED2 XAGE-1 protein (À)(À)(À)(À) 214 31 72178 2268 44 97 100 86 (+)* GEM GTP-binding protein overexpressed (À)(À)(À)(À) 1 1.1 5.6 36 13 67 7 73 in skeletal muscle GPNMB Glycoprotein (transmembrane) nmb (F)(À)(À)(À) 4.5 5.6 9.6 9.9 86 95 95 95 (+)* GSN Gelsolin (amyloidosis, Finnish type) 13 13 74 0 (À) HPCAL4 Hippocalcin-like protein 4 (À)(À)(À)(À) 20 4.6 48 19 23 95 95 73 (+) HSPA2 Heat shock-related (À)(À)(F)(À) 28 8.2 5.1 6.5 100 97 13 100 (+)* 70-kDa protein 2 HSPB8 Heat shock 22-kDa protein 8 (++) (F)(F)(F) 1.4 2 4 11 INA Internexin neuronal (À) (++) (++) (À) 809 1.3 2.8 10 intermediate filament protein, a M17S2 Membrane component, (++) (F)(F) (++) 3.7 113 1.3 1.1 chromosome 17 (CA125) MPP1 Membrane protein, (F)(F)(À)(F) 2.5 1.1 12 2.3 palmitoylated 1 (55 kDa) MT1G Metallothionein 1G (À)(À)(À)(À) 2018 13 206 196 44 100 103 97 (+) N68271 Hypothetical protein PTD015 (À)(À)(À)(À) 4.7 1.8 7 6.7 NALP2 NACHT, leucine rich repeat and 18 86 86 75 (+)* PYD containing 2 NEU1 Sialidase 1 (lysosomal sialidase) (À)(À)(À)(À) 11 1 6.8 2.7 NMES1 Homo sapiens normal mucosa of (À)(F)(À) (++) 278 2.7 66 0.8 21 0 75 0 (+) esophagus specific 1 PLAC1 Placenta-specific 1 (F)(À)(F)(F) 8.6 12 4.4 57 PRKAR2B Protein kinase, cAMP-dependent, 7 7 80 9 regulatory, type II, b PTEN Phosphatase and tensin homologue (F)(F)(F)(F) 1.2 0.73 1 0.75 ROPN1L Ropporin 1-like 000 0 (À) RRAD Ras-related associated with diabetes 92 100 100 96 (+)

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Table 2. Quantitative RT-PCR and methylation analysis in cell lines for 62 candidate genes selected based on array data (Cont’d)

Gene description Pretreatment Quantitative MS-MCA Methylation expression RT-PCR fold (TM index) or in clinical change MSP (+ or À) samples after DAC/TSA in cell lines treatment

Symbol Gene name HeLa SiHa CaSki C4I HeLa SiHa CaSki C4I HeLa SiHa CaSki C4I

SAT Spermidine/spermine (++) (++) (++) (++) 2.5 2.2 41 2.6 N1-acetyltransferase SERPINI1 Serine (or cysteine) (++) (F)(À)(F) 1.8 5.4 87 16 0 0 0 0 proteinase inhibitor, clade I, member 1 SFRP1 Secreted frizzled-related protein 1 (À)(F)(À)(À) 313 3 115 10 75 95 95 32 (+) SILV Silver homologue (mouse) (À)(À)(À)(F) 26 7 55 42 SLC2A3 Solute carrier family 2 (facilitated 55 109 114 36 glucose transporter), member 3 SLC7A8 SLC7A8: solute carrier family 7 100 76 100 0 (À) (cationic amino acid transporter, y+ system), member 8 SPARC SPARC (osteonectin) (À)(À)(À)(À) 247 89 685 222 117 100 100 96 (+) SSBP2 Single-stranded-DNA-binding (À)(F)(À)(À) 2.8 1.2 11 17.1 protein SSX4 Synovial sarcoma, X breakpoint 4 (F)(À)(À)(À) 593 473 495 114 57 104 100 89 (+)* STAC Src homology three (SH3) and (À)(F)(F)(À) 34 0.9 0.7 1 cysteine rich domain TFPI2 Tissue factor pathway inhibitor 2 (À)(À)(F) (++) 23488 390 132 2.7 + 96 + 0 (+) TIMP3 Tissue inhibitor of 0000 metalloproteinase 3 TPPP Brain-specific protein p25 alpha 47 35 76 18 (+) TSPAN-2 Tetraspanin 2 (À)(À)(À)(À) 44 1.4 2.9 2.1 UCHL1 Ubiquitin COOH-terminal (À) (++) (++) (F) 2134.4 5.1 1.8 7.7 0 0 0 0 esterase L1 ZFP1 Zinc finger protein 1 (À)(À)(À)(À) 0.9 0.6 0.4 0.6 homologue (mouse) ZNF589 KRAB-zinc finger protein SZF1-1 (F)(F)(F)(F) 2.3 1.6 1.1 1.6

NOTE: Pretreatment expression was derived from quantitative RT-PCR data as DC t value [C t(gene) À C t(TMP21)]. Genes with DC t < 4 were considered expressed (++), F ÀDDCt DC t between 4 and 8 weakly expressed ( ), DC t > 8 not expressed (À). Quantitative RT-PCR fold change after DAC/TSA treatment was calculated using 2 method as explained in Materials and Methods. MS-MCA extent of methylation is expressed by T M index as explained in the Materials and Methods. MSP result: +, for presence of methylation; À, for absence of methylation. Data are not available when space is empty. Abbreviations: TSA, trichostatin A; EGF, epidermal growth factor. *Presence of methylation in normal (ICC negative) clinical samples. considered methylated; such cutoffs resulted in optimal observed for any single gene in cervical cancer, while at the specificity and sensitivity of our assays). Consequently, if the same time, displaying very low frequency of methylation cutoff value was taken into account, only three normal samples in normal cervical tissue. We have previously identified three scored as methylated for TFPI2_2 and none for RRAD.On genes (DAPK1, RARB, and TWIST1) as frequently hyper- the other hand, 13 ICC samples scored positive for TFPI2_2 methylated in ICC (8) and wished to compare the rate of and nine for RRAD. We subsequently generated a heatmap methylation of these ‘‘benchmark’’ genes with our new genes. The methylation status of these three genes was determined showing the log10-transformed PMR values for all samples and genes, if they exceeded the cutoff (Fig. 5A). by MethyLight in the same set of samples as above. Resulting PMR values, if above the cutoff, were plotted in Fig. 5 along High Frequency of Aberrant Methylation of SPARC and with six newly identified genes (SPARC, TFPI2, SFRP1, RRAD, TFPI2 Compared with DAPK1, RARB, and TWIST1. The data MT1G, NMES1). For both DAPK1 and RARB, 13 ICC samples obtained thus far (Table 3; Fig. 4 and Fig. 5A) suggested scored above the cutoff. SPARC and TFPI2 compared that some of the novel genes (e.g., SPARC and TFPI2) may be favorably with these markers (18 and 19 scored above cutoff, aberrantly methylated in ICC with the highest frequency ever respectively), suggesting the potential value of these two novel

Figure 2. Relationship between array and quantitative RT-PCR expression ratios. Log2-transformed ratios (see Materials and Methods for details how these ratios were obtained) were plotted against each other for 42 genes, in which quantitative RT-PCR was done for each cell line in a separate panel. Arrows indicate the position of the TFPI2 gene as an example.

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derived from CIN3/CIS precursor lesions, where TFPI2_4 was negative.3 This suggests a variable methylation pattern along TFPI2-associated CpG island and also provides a rationale for designing multiple MSP or MethyLight assays per gene to achieve maximum detection sensitivity. Altogether, the two TFPI2 assays (TFPI2_2 and TFPI2_4) scored in 20 of 22 ICC samples as positive while being so in only three normal samples. Both SPARC and TFPI2 were methylated in all but one ICC samples. However, the sample negative for these two genes was positive for RARB (Fig. 5). Thus, methylation of CpG islands associated with three genes (SPARC, TFPI2, and RARB) was detected in 100% of cancers and in only 19% of normal cervical samples. These three CpG islands together may therefore represent the most sensitive and specific methylation markers for detection of cervical cancer identified to date.

Discussion

In this study, we did a systematic global search for aberrantly methylated CpG islands to identify potential novel methylation biomarkers for the detection of ICC. We used DNA methyltransferase and histone deacetylase inhibitors, DAC and trichostain A, to demethylate/reactivate hypermethylated/silenced genes in four cervical carcinoma cell lines and then followed by their identification on expression microarray and by examination of their methylation status in cell lines and in clinical samples. The impetus for our investigation has been provided by encouraging results of published studies using methylation biomarkers for detection of ICC and its precursor stages (5-8). Treatment of cell lines with DNA methyltransferase and histone deacetylase inhibitors induced widespread expression changes in hundreds of genes in all cell lines. A total of 235 genes were up-regulated after treatment in at least two cell lines. These 235 up-regulated genes included genes with known or putative tumor suppressor activity, such as CDH1, DKK3, PTEN, SFRP1, TFPI2, and TIMP3 (9, 23-25). Some of the genes that were up-regulated in cervical carcinoma cell lines have been previously reported to be up-regulated by epigenetic reactivation in pancreatic (10), colorectal (9), and the head and neck squamous cell cancer cell lines (26). We examined the Figure 3. MS-MCA analysis of the SFRP1 gene in cell lines. A. methylation status of CpG islands in 39 of the 235 putatively Position of MS-MCA amplicon in SFRP1-associated CpG island. hypermethylated genes by MS-MCA and MSP and found 33 Transcriptional start (arrow), individual CpGs (vertical lines), and (85%) to be hypermethylated in at least one of the four cervical 275-bp amplicon containing 24 CpG dinucleotides (thick bar). carcinoma cell lines, and 17 (44%) to be hypermethylated Methylation of individual CpG dinucleotides in CaSki, HeLa, and in three or more of the four cell lines (Table 2). Treatment- SiHa (.); absence of methylation (o). Bisulfite sequencing was not induced up-regulation of some genes was not a direct carried out for C4I. B. Dissociation curves generated by MS-MCA consequence of CpG island demethylation, as 6 of 39 analyzed analysis for the SFRP1 gene. Fully unmethylated (U) and methylated genes (15%) were not methylated in cell lines at all (Table 2). (M) control sperm DNA. Arrows indicate position of peaks generated Up-regulation of such genes could have been a secondary from cell lines. effect caused by an induced upstream factor, or an effect of histone reacetylation induced by trichostain A. A substantial number of putatively hypermethylated genes remain unexam- genes as methylation markers for detection of cervical cancer ined at present (Supplementary Tables S02 and S03). A and its precursor lesions. considerable number of genes were down-regulated rather than up-regulated by the drug treatment (Supplementary Multiple MSP Amplicons in TFPI2-Accociated CpG Table S02). Although these genes were not the main focus of Island Detect Its Methylation in Most ICC Samples. We this study, we examined methylation of CpG islands associ- noticed that an alternative amplicon TFPI2_4 placed outside of ated with 10 genes down-regulated in multiple cervical original MethyLight amplicon TFPI2_2 in the CpG island carcinoma cell lines (SERPINH2, GBE1, HMG17, NUCKS, associated with TFPI2 gene (see map in Fig. 5C) was able to LY6K, CCNA2, PLK1, DDIT4, PSMB10, and NMI). Among score additional ICC samples as positive while remaining these, only a CpG island associated with SERPINH2 was found undetected in all but one negative samples (Fig. 5B). hypermethylated in cell lines as well as in DNA derived from Interestingly, detection of TFPI2_4 was observed in 13 normal cells (data not shown). samples, where TFPI2_2 was positive but also in six samples with undetectable or below-cutoff TFPI2_2 result (Fig. 5B). On the other hand, whereas TFPI2_2 was not positive in any samples where TFPI2_4 scored negative among ICC samples described in this study, we have detected TFPI2_2 in DNA 3 Sova, unpublished data.

Table 3. MethyLight results for six genes most frequently hypermethylated in ICC-exfoliated cervical cell samples

SPARC TFPI2_2 SFRP1 RRAD MT1G NMES1 Totals

Normal Assay positive (%) 1 (5) 8 (36) 1 (5) 9 (43) 1 (5) 0 (0) 21 PMR median* 2.17 0.36 2.90 1.58 0.37 0.00 ICC Assay positive (%) 20 (91) 18 (82) 13 (58) 15 (68) 12 (55) 8 (36) 22 PMR median* 17.46 17.63 16.32 3.88 0.96 1.56 P (Fisher’s) <10À8 0.005 2 Â 10À4 0.13 6 Â 10À4 6 Â 10À6

NOTE: Shown are numbers of samples scoring positive (PMR > 0) for a given gene in sets of biopsy; confirmed normal and ICC samples, with percentages givenin parenthesis. Also shown are median PMR values among the samples scoring positive for a given gene. Probabilities associated with number of samples scoring negative and positive in normal and ICC samples are given below (Fisher’s exact test). *PMR medians were based only on nonzero PMR values.

Nine genes that were shown to be hypermethylated methylated in mesotheliomas in relationship with SV40 in multiple cervical cancer cell lines were found to be infection (33). Hypermethylation of NMES1 has not been hypermethylated in clinical samples (exfoliated cervical cell previously noted in any tissue, although this gene has been samples) in association with biopsy-confirmed ICC. Because reported to be expressed in normal but not in malignant neither MS-MCA nor MSP assays provide quantitative infor- esophageal tissues (34). mation about the relative proportion of methylated alleles in Nine genes (BRDT, C8ORF4, FLJ13937, FLJ36166, GAGED2, clinical material, we developed the MethyLight assay for six GPNMB, HSPA2, NALP2, and SSX4) were found to be of these genes (MT1G, NMES1, RRAD, SFRP1, SPARC, and hypermethylated at high frequencies in both benign and TFPI2). Using MethyLight, we identified, most notably, SPARC malignant cervical clinical samples (Table 2). This suggests and TFPI2 as aberrantly methylated in all but 2 of 22 ICC- either that they are hypermethylated in all cells in cervical positive samples (90.9%) and only in 3 of 21 normal samples epithelium (normal and neoplastic) or that they are hyper- (Table 3; Figs. 4-5). These hypermethylated genes are therefore methylated in a subset of cells (e.g., inflammatory cells, of interest as biomarkers for cervical cancer either alone or fibroblasts, or endothelial cells) that were present in exfoliated together with our recently described ‘‘cervical cancer screening cell samples from women with and without cancer. Of these, panel’’ (8) or panels reported by other authors (5-7). SSX4 and GAGED2 reside on the X chromosome and belong Five of the six newly identified genes hypermethylated in to a group of cancer/testis antigens and therefore may be ICC (SPARC, TFPI2, SFRP1, MT1G,andRRAD)have hypermethylated due to X chromosome inactivation or as a previously been reported to be hypermethylated in cancer, general phenomenon related to silencing of many cancer/ although not in ICC. SPARC has been found hypermethylated testis antigen genes in normal somatic tissue (35). Similarly, in pancreatic carcinoma cell lines, tumor xenografts, and in BRDT, located on chromosome 1, is a cancer/testis antigen primary pancreatic carcinoma (27). The protein product of gene (36). this gene (secreted protein acidic and rich in cysteine, also It has been shown previously that the methylation of certain known as osteonectin or BM-40) belongs to a group of CpG islands increases with advanced age (4). We did not find matricellular proteins that mediate cell/extracellular matrix any association between age and the overall prevalence of interactions and is involved in cell proliferation, spreading, methylation among the nine genes we examined. More adhesion, motility, and invasion (28). TFPI2 encodes a Kunitz- specifically, among ICC patients, 31 to 40 and 41 to 50 years type serine protease inhibitor and has been previously age groups had almost identical average number of methyl- reported to be hypermethylated in choriocarcinoma, gliomas, ated genes per patient (4.6 and 4.0, respectively). Among and lung cancer (24, 29, 30). Tumor suppressor and Wnt patients with normal diagnosis, all DNA samples with antagonist SFRP1 has been shown hypermethylated and methylated genes were in the 41 to 50 years age group silenced in colorectal cancer (9). Expression of metal ion- (average, 0.55 methylated gene/patient), whereas no methyl- binding protein MT1G has also been shown silenced by ation was found in almost identical number of patients in 31 to aberrant methylation in thyroid cancer (31). RRAD, encoding 40 and 51 to 60 years age groups. It was impossible to assess a protein belonging to a subfamily of Ras-related GTP- the correlation between HPV type (low risk versus high risk) binding proteins (32), has been recently found aberrantly because of the small number of cases examined.

Figure 4. PMR values of MethyLight assays for six genes in DNA samples derived from exfoliated cervical cells. Cervical cells were collected from patients that were subsequently confirmed histologically as normal or ICC in a same-day biopsy. *, PMR values plotted at 0.01 in samples with PMR = 0 that could not be properly plotted on a log scale (for SPARC, n = 20 and 2 for normal and ICC samples, respectively; for TFPI2_2, n = 13 and 4; for SFRP1, n = 20 and 9; for RRAD, n = 12 and 7; for MT1G, n = 20 and 10, and for NMES1, n = 21 and 14, respectively). Horizontal bars indicate median PMR values (shown only in sample sets where at least two samples scored > 0).

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Acknowledgments We thank Jhon-Chun Ho, Desiree Willis, Cordelie E. Witt, and Yuanjun Deng for technical help and Andy Lin, Daniel Stone, and Randolph L. Woltjer for critical review of the article.

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Pavel Sova, Qinghua Feng, Gary Geiss, et al.

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