SEARCH

SEARCH BY CITATION

Keywords:

  • methylation;
  • cervical cancer;
  • QMSP;
  • DAPK;
  • ESR1

Abstract

  1. Top of page
  2. Abstract
  3. Patients and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

Current cervical cancer screening is based on morphological assessment of Pap smears and associated with significant false negative and false positive results. Previously, we have shown that detection of hypermethylated genes in cervical scrapings using quantitative methylation-specific PCR (QMSP) is a promising tool for identification of squamous cell cervical cancer. Aim of the present pilot-study was to evaluate presence of hypermethylated genes in cervical carcinogenesis, both in squamous cell as well as adenocarcinomas. Cervical scrapings were obtained from 30 patients diagnosed with cervical cancer (20 squamous cell carcinomas and 10 adenocarcinomas) and 19 women with histologically normal cervices. The scraped cells were used for determination of promoter hypermethylation by QMSP for 12 genes and for morphological assessment. Overall, CALCA, DAPK, ESR1, TIMP3, APC and RAR-β2 promoters were significantly more often hypermethylated in cancers than in controls, while adenocarcinomas were more often hypermethylated above the highest control ratio for APC, TIMP3 and RASSF1A promoters. Combining 4 genes (CALCA, DAPK, ESR1 and APC) yielded a sensitivity of 89% (with all adenocarcinomas identified), equal to cytomorphology (89%) and high-risk human papilloma virus (Hr-HPV; 90%). The 4-gene QMSP proved theoretically superior to cytomorphology as well as Hr-HPV in specificity (100% vs. 83 and 68%, respectively), because cytology identified 3 controls as moderate or severe dyskaryosis and 6 controls were positive for Hr-HPV. In conclusions, QMSP of 4 gene promoters combined appears to have comparable sensitivity and potentially better specificity in comparison to “classic” cytomorphological assessment and Hr-HPV detection. QMSP holds promise as a new diagnostic tool for both squamous cell carcinoma and adenocarcinoma of the cervix. © 2006 Wiley-Liss, Inc.

Cervical cancer is an important cause of death in women worldwide.1 Cervical carcinogenesis is highly associated with (high-risk) human papilloma virus (HPV) infections.2 Cytomorphological examination of cervical smears is a widely applied, though not ideal screening method for cervical cancer and its precursors, since the Pap smear has false negative rates of 2–40%, due to a combination of sampling error, processing artifacts and the nature of subjective interpretation.1, 3, 4 False-negative cytology can also be found in about 50% of cases when previous negative smears are reviewed from the small proportion of screened women who develop invasive cancer.4 Moreover, as many as 20% of all Pap smears are interpreted as atypical squamous cells of undetermined significance (ASCUS) or borderline dyskaryotic, leading to increased surveillance and more invasive tests in many of these patients.3, 5 The incidence of squamous cell carcinoma of the cervix has decreased since introduction of nation wide screening programs, compared to a relative increased incidence of adenocarcinoma of the cervix.6 The efficacy of cytological screening appears to be diminished for adenocarcinomas, possibly because glandular atypia is more difficult toassess than dyskariosis of squamous cells.7 High-risk HPV (Hr-HPV) testing has been suggested to improve cervical cancer screening8, 9; however, the specificity of Hr-HPV testing, especially in a young screening population is relatively low10 and adding more HPV subtypes to the test will lower the specificity even more.11 Therefore, new objective diagnostic methods, based on molecular changes specific for cervical carcinogenesis are needed.

Silencing of (candidate) tumor suppressor genes by hypermethylation of CpG islands, located in the promoter regions of many genes, is a common feature of human cancers.12 CpG island hypermethylation is often associated with a transcriptional block and loss of the relevant protein and is an early event in carcinogenesis.12 In addition to the functional implications of gene inactivation in tumor development, these aberrant methylation patterns represent excellent targets for novel diagnostic approaches based on methylation sensitive PCR techniques. In previous studies, several genes were identified as being aberrantly methylated in cervical cancer. Most of these studies focused on a single gene and only a few studies investigated several genes.13, 14, 15, 16, 17, 18, 19 Virmani et al.,17 Dong et al.19 and Narayan et al.18 studied methylation patterns of several genes in cervical cancer and found 74, 79 and 87% of cervical cancers to be aberrantly methylated, respectively. It seems that by combining more genes or cervical cancer-specific genes, an increasing number of cervical cancers should be identified through hypermethylation analysis. These previous studies were carried out using conventional methylation specific PCR (MSP) rather than real-time quantitative MSP (QMSP), which permits reliable quantification of methylated DNA.20 QMSP is reported to be more specific and more sensitive than conventional MSP and allows for high throughput analysis, making it more suitable as a screening tool.20 Very few studies investigated the use of (Q)MSP as a diagnostic tool for cervical neoplasia using cervical scrapings.21, 22 Recently, we reported that hypermethylation of genes in cervical scrapings reflect the methylation status of underlying tissue, by comparing methylation ratios of paired fresh frozen tissue samples and cervical scrapings of both cervical cancer patients and healthy controls.21 Feng et al.22 also found a strong concordance between cervical scrapings and biopsy specimens for DAPK, RARβ and TWIST1.

In the present study, we investigated promoter hypermethylation of 12 genes in cervical scrapings, obtained from cervical cancer patients (squamous cell carcinomas as well as adenocarcinomas) and controls. For the present study, 12 genes were chosen for a variety of reasons: CALCA and TIMP3 because these genes were reported to be frequently methylated in cervical cancer, but so far the methylation status of these genes was unknown in normal cervices.23 Hypermethylation patterns of ESR1 and β-Catenin were unknown in cervical tissue at the time of our analysis. However, based on differential mRNA or protein expression levels (e.g. higher expression in controls compared to cervical cancer specimens using either RT-PCR, Western blotting or immunohistochemistry), we hypothesized that this could be due to hypermethylation and therefore these genes were selected.24, 25 Muller et al. recently observed hypermethylation of ESR1 in 48/65 cervical cancers.26APC, CDH1, DAPK, FHIT, HIC1, MLH1, RAR-β2 and RASSF1A were selected based on differential hypermethylation patterns between cervical cancer specimens and normal cervices.13, 14, 17, 18, 19, 27 Previously, it was reported that APC, HIC1 and RASSF1A were more often methylated in adenocarcinomas compared to squamous cell cervical cancer.19, 27 Our aims were to evaluate genes that may distinguish cervical cancer cases from controls as well as those genes that are specifically hypermethylated in adenocarcinoma, since one of the pitfalls of the current screening method is the unreliable identification of cervical adenocarcinomas.

Patients and methods

  1. Top of page
  2. Abstract
  3. Patients and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

Patients

Cervical scrapings were collected from cervical cancer patients and controls.

All cervical cancer patients referred between March 2001 and September 2003 because of cervical cancer were asked to participate in our study during their initial visit to the outpatient clinic of the University Medical Center Groningen. Gynecological examination under general anesthesia was performed in all cervical cancer patients for staging in accordance with the International Federation of Gynecology and Obstetrics (FIGO) criteria.28 Cervical scrapings were collected during the initial visit to the outpatient department or at gynecologic examination under general anesthesia.

For the present study, we selected 30 cervical cancer patients; 20 with squamous cell carcinoma (67%) and 10 with adenocarcinoma (33%); 1 FIGO stage IA (3%), 10 FIGO stage IB (33%), 4 FIGO stage IIA (13%), 2 FIGO stage IIA/B (7%), 9 FIGO stage IIB (30%), 2 FIGO stage III (2%) and 2 FIGO stage IV (7%). The median age of the cervical cancer patients was 42 years (IQ range 35–58 years). There were no differences between the adenocarcinomas and squamous cell cancers regarding stage and/or age. Control scrapings were obtained from patients (n = 19) without a history of abnormal Pap smears or any form of cancer and planned to undergo a hysterectomy for nonmalignant reasons during the same period. Indications for hysterectomy were fibroids (n = 7), prolaps uteri (n= 6), adenomyosis (n = 1), hypermenorrhea (n = 1) or a combination of fibroids and either prolaps or adenomyosis (n = 4). Cervical scrapings were collected after anesthesia and just before surgery. Median age for controls was 49 years (IQ range 44–57 years). All specimens were judged as benign at pathology.

Informed consent was obtained from all patients and controls participating in this study. The study was approved by the ethics committee of our hospital.

Sample collection and DNA extraction

The cervical scrapings were collected as described previously.21 In brief, after scraping of the cervix, cells were resuspended in 5 ml PBS. One milliliter was used to make cytospins for cytomorphological assessment in ethanol-carbowax (7% polyethylene glycol, 50% ethanol). Cytospins were Pap-stained and routinely classified by 2 independent pathologists without knowledge of the molecular and clinical data according to a modified Papanicolaou system.29 The remaining part (4 ml) was used for DNA isolation using standard salt-chloroform extraction and ethanol precipitation.

HPV detection and typing

For the detection of the presence of Hr-HPV, genomic DNA was first analysed with HPV16- and HPV18-specific primers. In short, the HPV16-specific PCR was performed as described previously.30 The HPV18-specific PCR was performed as described by Baay et al.31 using 2 sets of primers: HPV18-long (217 bp), 5′-AAG GAT GCT GCA CCG GCT GA-3′and 5′-CAC GCA CAC GCT TGG CAG GT-3′; and HPV18-short (115 bp), 5′-CCT TGG AGG ACG TAA ATT TTT GG-3′ and 5′-CAC GCA CAC GCT TGG CAG GT-3′. On all HPV16- or HPV18-negative cases, a general primer-mediated PCR was performed using 2 HPV consensus primer sets, CPI/CPIIG and GP5+/6+, with subsequent nucleotide sequence analysis as we described previously.32 For nucleotide sequence analysis and comparisons, the programs Blast2-WU and Align of the EMBL-EBI sequence analysis software package were used (www.ebi.ac.uk). As a control for specificity and sensitivity of each HPV-PCR, a serial dilution of DNA was extracted from HPV16-positive CaSki and HPV18-positive HeLa cell lines. All standard precautions were taken to avoid contamination of amplification products. For quality control, genomic DNA was amplified in a multiplex PCR containing a control gene primer set resulting in products of 100, 200, 300, 400 and 600 bp according to the BIOMED-2 protocol.33 Only DNA samples with PCR products of 300 bp and larger were used for the detection of HPV.

Real-time quantitative methylation-specific PCR

QMSP was performed after bisulfite treatment on denatured genomic DNA as previously reported.21, 34, 35 Primer pairs, amplicon size and Genbank accession number QMSP primers and probes are listed in Table I. As internal reference gene, β-actin was chosen. For the TaqMan-based QMSP each sample was analyzed in triplicate. As a positive control, serial dilutions of in vitro-methylated genomic DNA with Sss I (CpG) methyltransferase (New England Biolabs, Beverly, MA) was used in each experiment. For quality control, all amplification curves were visualized and scored without knowledge of the clinical data. A DNA sample was considered hypermethylation positive for a certain gene if at least 2 of 3 triplicates showed a Ct-value below 50 and DNA input was at least 225 pg β-actin (equivalent to a Ct-value of 34). Samples with DNA input below 225 pg frequently showed stochastic amplification.

Table I. Primers and Probe Sequences for QMSP
GeneForward 5′–3′ primer6-FAM 5′–3′ TAMRA probeReverse 5′–3′ primerGenbank no.Amplicon sizeRef
ACTBTGGTGATGGAGGAGGTTTAGTAAGTACCACCACCCAACACACAATAACAAACACAAACCAATAAAACCTACTCCTCCCTTAAY00474133 bp; 390–52236
APCGAACCAAAACGCTCCCCATCCCGTCGAAAACCCGCCGATTA (antisense)TTATATGTCGGTTACGTGCGTTTATATU0250974 bp; 761–83437
β-CATENINGGAAAGGCGCGTCGAGTCGCGCGTTTCCCGAACCGTCCCCTATCCCAAACCCGX8944882 bp; 583–66420
CALCAGTTTTGGAAGTATGAGGGTGACGATTCCGCCAATACACAACAACCAATAAACGTTCCCGCCGCTATAAATCGX15943101 bp; 1706–180620
CDH1AATTTTAGGTTAGAGGGTTATCGCGTCGCCCACCCGACCTCGCAT (antisense)TCCCCAAAACGAAACTAACGACL3454570 bp; 842–91120
DAPKGGATAGTCGGATCGAGTTAACGTCTTCGGTAATTCGTAGCGGTAGGGTTTGGCCCTCCCAAACGCCGAX7610498 bp; 5–10238
ESR1GGCGTTCGTTTTGGGATTGCGATAAAACCGAACGACCCGACGAGCCGACACGCGAACTCTAAX62462101 bp; 2784–288420
FHITGGGCGCGGGTTTGGGTTTTTACAACGACGCCGACCCCACTAAACTCC (antisense)GAAACAAAAACCCACCGCCCCGU7626391 bp; 192-293 
HIC1GTTAGGCGGTTAGGGCGTCCAACATCGTCTACCCAACACACTCTCCTACG (antisense)CCGAACGCCTCCATCGTATL41919101 bp; 562–66220
MLH1CGTTATATATCGTTCGTAGTATTCGTGTTTCGCGACGTCAAACGCCACTACGCTATCGCCGCCTCATCGTU2655988 bp; 254–34120
RAR-β2GGGATTAGAATTTTTTATGCGAGTTGTTGTCGAGAACGCGAGCGATTCGTACCCCGACGATACCCAAACNM_00096592 bp; 63–15435
RASSF1AGCGTTGAAGTCGGGGTTCACAAACGCGAACCGAACGAAACCACCCGTACTTCGCTAACTTTAAACGNM_00718275 bp; 45–11939
TIMP3GCGTCGGAGGTTAAGGTTGTTAACTCGCTCGCCCGCCGAA (antisense)CTCTCCAAAATTACCGTACGCGU3311093 bp; 1051–114320

Statistical analysis

QMSP values were adjusted for DNA input by expressing results as ratios between 2 absolute measurements ((average DNA quantity of methylated gene of interest/average DNA quantity for internal reference gene β-actin) × 10,000).21, 20 Samples were analyzed by plotting hypermethylation ratios for each sample in a scatter plot and choosing a cut-off ratio above the highest control ratio observed for each gene, to set specificity at 100%.21 Differences in prevalence of cancers hypermethylated above the highest control ratio between groups were tested using the chi-square test with Yates' correction for small numbers. Hypermethylation ratios for each gene were compared between cancer cases and controls, and furthermore between adenocarcinomas and squamous cell carcinomas with the Mann-Whitney U test. Once the best individually discriminating genes were found, 2-gene, 3-gene and 4-gene combinations were tested to identify the highest sensitivity with specificity set at 100% for each gene. To compare QMSP as a diagnostic tool with “classic” cytomorphologic assessment, differences in sensitivity and specificity between these assays were analyzed with the chi-square test with Yates' correction for small numbers. All analyses were carried out using the SPSS software package (SPSS 11.5, Chicago, IL). All observed differences were considered to be significant when associated with p < 0.05.

Results

  1. Top of page
  2. Abstract
  3. Patients and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

QMSP as a diagnostic tool

DNA quality was sufficient to perform QMSP on 47 cervical scrapings (20 SCC, 8 adenocarcinomas and 19 controls). CDH1, FHIT, HIC1, MLH1 and RASSF1A promoters were hypermethylated in cervical cancers as often as in controls, whereas no hypermethylation was observed for β-Catenin promoter (data not shown). Figure 1 shows that CALCA, ESR1, DAPK, TIMP3, APC and RAR-β2 promoters were more hypermethylated in cervical cancers than in controls. RAR-β2 was the only gene promoter out of these 6 genes that was never found to be hypermethylated in controls. APC and TIMP3 promoters were also more hypermethylated in adenocarcinomas than in squamous cell cervical cancers (for p-values, see legend to Fig. 1).

thumbnail image

Figure 1. Methylation ratios of ESR1, DAPK, CALCA, RAR-β2, TIMP3 and APC in controls and cancer patients are shown. Cancers are subdivided into squamous cells and adenocarcinomas. The horizontal line indicates the cut-off ratio per gene arbitrarily chosen to be above the highest control ratio. The cut-off ratio is 14 for ESR1, 28 for DAPK, 897 for CALCA, 28 for RAR-β2, 943 for TIMP3 and 1045 for APC. CALCA, ESR1, DAPK, TIMP3, APC and RAR-β2 promoters were more hypermethylated in cervical cancers than in controls (p < 0.0005, p < 0.0005,p = 0.001, p = 0.048, p = 0.032 and p = 0.054, respectively using Mann-Whitney U test). APC and TIMP3 were more hypermethylated in adenocarcinomas than in squamous cell cervical cancers (p = 0.022 and p = 0.014 using Mann-Whitney U test).

Download figure to PowerPoint

To determine discriminative ability between normal and cancer cases for each gene, specificity was set at 100% by choosing a cut-off value above the highest control ratio for each gene. Table II shows the number of cervical cancer scrapings that were hypermethylated above the highest control ratio. CALCA, DAPK, ESR1, TIMP3, APC and RAR-β2 promoter hypermethylation discriminated between cervical cancer cases and controls. In an analysis of different histological subtypes, in adenocarcinomas hypermethylation above the highest control ratio for the APC, TIMP3 and RASSF1A promoters was significantly more often compared to squamous cell carcinomas (Table II).

Table II. Hypermethylation above the Highest Control Ratio in all Cervical Cancer Scrapings (CC) and Squamous Cell Carcinomas (SCC) Versus Adenocarcinomas (AC)
GenesCC1p2SCC1AC1p2
  • 1

    Number of cancers hypermethylated above the highest control ratio.

  • 2

    χ2, comparing number of hypermethylated cases.

CALCA19 (68%)<0.000513 (65%)6 (75%)0.61
DAPK13 (46%)<0.000511 (55%)2 (25%)0.15
ESR19 (32%)0.0065 (25%)4 (50%)0.20
TIMP36 (21%)0.0311 (5%)5 (63%)0.001
APC5 (18%)0.0511 (5%)4 (50%)0.005
RAR-β25 (18%)0.0513 (15%)2 (25%)0.53
MLH13 (11%)0.141 (5%)2 (25%)0.12
RASSF1A2 (7%)0.230 (0%)2 (25%)0.02
HIC11 (4%)0.411 (5%)0 (0%)0.52
FHIT0 0 (0%)0 (0%) 
CDH10 0 (0%)0 (0%) 
β-CATENIN0 00 

Setting specificity at 100%, CALCA, DAPK, ESR1, TIMP3, RAR-β2 and APC had a sensitivity for the detection of cancer of 68, 46, 32, 21, 18 and 18%, respectively (Table II). Table III shows the sensitivity of different combinations of these genes. Combinations of 2, 3 or 4 genes were tested while maintaining perfect specificity for each gene. Our best result was obtained by combining 4 genes, CALCA, DAPK, ESR1 and APC, reaching a sensitivity of 89.3%. Addition of more genes did not increase sensitivity. The best 3-gene combination was CALCA combined with ESR1 and DAPK (sensitivity of 85.7%). The sensitivity of the 2-gene combination CALCA together with either ESR1 or DAPK was 78.6, while ESR1 together with DAPK reached a sensitivity of 67.8%.

Table III. Sensitivity and 95% Confidence Interval (CI) for Combination of Hypermethylated Genes, with Specificity set at 100% for each Gene Promoter
GenesSensitivity95% CI
CALCA, DAPK, ESR1, APC89.3%(67–95%)
CALCA, DAPK, ESR185.7%(63–93%)
ESR1, CALCA78.6%(55–88%)
CALCA, DAPK78.6%(55–88%)
ESR1, DAPK67.8%(43–80%)

Cytomorphology and HPV analysis

Cytomorphological analysis could be performed on 18 of 19 control samples (1 inadequate sample). Cervical tissue of all controls was histologically diagnosed as normal cervical epithelium. Nevertheless, 2 scrapings were classified as borderline dyskaryotic and 1 as severe dyskaryotic (Table IV). Specificity for cytomorphology was therefore 83.3% (15/18) in our study.

Table IV. Morphological Assessment Compared with Hypermethylation of at least one Gene in Cervical Scrapings of Histologically Confirmed Normal Controls and Cervical Cancer Patients
CytomorphologyNSufficient DNA for QMSPHypermethylation1Hr-HPV2
  • a

    Hypermethylation is defined as methylation above highest control ratio.

  • 2

    High-risk HPV include HPV16, HPV18, HPV31 and HPV45.

  • 3

    Controls are by definition negative for hypermethylation.

  • 4

    Borderline dysplasia is Pap II and Pap IIIA mild dyskaryosis.

  • 5

    Severe dysplasia/CIS is Pap IIIA moderate dyskaryosis, Pap IIIB and Pap IV.

Controls
 No dysplasia1515033
 Borderline dysplasia222031
 Severe Dysplasia/CIS311031
 Not assessed11031
Cancers
 No dysplasia1111
 Borderline dysplasia42102
 Severe Dysplasia/CIS57756
 Cell cancer17171715
 Inadequate3223
 Total50482533

All 30 cervical cancer scrapings were morphologically analyzed. Three scrapings were classified as no or borderline dyskaryosis, of which 2 were obtained from adenocarcinoma cases. Furthermore, 3 scrapings were inadequate for morphological diagnosis because they contained an insufficient amount of cells (Table IV). Since 1 cancer case was scored as normal and 2 as borderline dyskaryosis (according to Dutch screening guidelines leading to a delay in diagnosis of at least 6 months) sensitivity for cytomorphology was calculated to be 88.9%(24/27).

HPV analysis was performed on all cervical scrapings (19 controls and 30 cervical cancers) (Table IV). Hr-HPV was detected in 6 of 19 controls and in 27 of 30 cervical cancers, resulting in a specificity and sensitivity of 68.4% (13/19) and 90% (27/30), respectively.

Cytomorphology versus QMSP and HPV

Two cervical cancer scrapings (both adenocarcinomas) had insufficient DNA to perform QMSP. Of the 28 remaining cervical cancer samples, 25 were hypermethylated above the highest control ratio for at least 1 gene (sensitivity 89.3% (25/28)). Of the 3 cervical cancer scrapings that were morphologically classified as borderline or no dyskaryosis 2 had sufficient DNA input for QMSP analysis and 1 was hypermethylated above the highest control ratio for at least 1 gene. Of the 3 scrapings that were insufficient for cytomorphological assessment, 2 had sufficient DNA input and were also hypermethylated above the highest control ratio for at least 1 gene (Table IV). All of these 6 cervical cancer scrapings were positive for Hr-HPV.

In summary, our data reveal that the combination of 4 genes (CALCA, DAPK, ESR1 and APC) had a theoretical sensitivity of 89.3%, equal to cytomorphology (88.9%) and Hr-HPV (90.0%) with a specificity of QMSP (each gene cutoff set at 100%) compared to cytomorphology (83%) and Hr-HPV (68%) (both p < 0.05).

Discussion

  1. Top of page
  2. Abstract
  3. Patients and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

Current screening for cervical cancer by Pap smear analysis is associated with significant false positive and false negative rates3 and especially adenocarcinomas are easily missed.7, 6 Previously, we and others have shown that detection of hypermethylated gene promoters in cervical scrapings using (Q)MSP is a promising tool for identification of squamous cell cervical cancer patients.21, 22 However, the published sensitivity of (Q)MSP for detection of cervical cancer (67–74%) needs to be improved and more data on the detection of adenocarcinoma are needed.21, 22 In the present study, we evaluated the hypermethylation status of the promoters of 12 genes. These 12 genes were selected, because they were either previously shown to be frequently hypermethylated in cervical cancer specimens or to have frequently downregulated mRNA or protein expression in cervical cancer. We hypothesized that sensitivity could be increased by analyzing genes frequently hypermethylated in cervical cancer and we demonstrate that this is indeed the case. We identified 89% of cervical cancer scrapings as cases, by combining ESR1, DAPK, APC and CALCA, with high theoretical specificity. Furthermore, we identified 3 genes, APC, TIMP3 and RASSF1A that could distinguish adenocarcinomas from squamous cell carcinomas, despite the fact that we only analyzed a relatively small series of cervical cancers. In fact, QMSP identified all 8 adenocarcinomas as cancers with high sensitivity and specificity, which well exceeded the performance of cytomorphology in identifying adenocarcinomas. Overall, our results suggest that QMSP of gene promoters, frequently hypermethylated in cervical cancer (squamous cell and adenocarcinoma) show promise in augmenting current cervical cancer screening based on cytomorphology. However, our study has some important limitations; the number of patients is relatively small, only cancer cases were analyzed and patients already known to have cervical cancer were included in the study, which is of course quite different from a real screening population where cases and controls are unknown at presentation. Moreover, despite the fact that we evaluated a panel of genes in a very selected group of patients, no 100% sensitivity could be reached, pointing to the fact that the ideal combination of genes still needs to be defined. After we performed our present study, several studies showed other genes to be potential candidate markers for QMSP in cervical cancer screening, such as Tumor Suppressor Lung Cancer 1 (TSLC1), the anti-apoptotic decoy receptor 1 (DcR1) and the cell differentiation gene TWIST140, 41, 22. In future studies, these genes need to be further evaluated and when a sensitivity of >95% for cervical cancers will be reached, it will be interesting to expand these studies also to patients with higher grades CIN.

Ideally hypermethylation of 1 marker should be able to identify most (perhaps >90%) cancers as cases and none of controls, as appears to be the case for GSTP1 hypermethylation in adenocarcinoma of the prostate.42 Many studies have been conducted trying to find such markers for cervical cancer using either MSP or QMSP.40, 41, 43, 44 Of the 12 genes we analyzed, RAR-β2 was the only gene not hypermethylated in controls (Fig. 1), suggesting that it may be difficult to find a marker that is highly sensitive and still rarely hypermethylated in controls. As a consequence, one may imagine that only a quantitative assay will be able to really distinguish cancer cases from controls by setting cut-off values. An important quality of a candidate gene should then be that there is a large difference in median hypermethylation ratios between cancer cases and controls. Markers such as ESR1 might also make good candidates. Very recently Müller et al. observed hypermethylation of ESR1 in 48/65 (73%) cervical cancers.26 In our study 64% of cervical cancers were hypermethylated for ESR1 versus only 1 out of 19 controls (Fig. 1). If larger studies show that ESR1 indeed is only rarely hypermethylated in controls it might be possible to lower the positive threshold for this gene, thus increasing sensitivity.

The results of our analyses of hypermethylation of APC, DAPK, MLH1, RAR-β2 and RASSF1A were similar to those observed in other studies in cervical cancer and normal cervices13, 16, 17, 18, 22, 27, 45 while hypermethylation patterns observed in our study for CDH1, FHIT and HIC1 were not comparable to other studies.17, 18, 19 Other studies found aberrant methylation in 16–58% of cervical cancers versus none of controls, while we observed 75–100% of hypermethylation in both cancer and controls. These differences can be explained by the fact that in these other studies conventional MSP was performed, which is reported to be less sensitive than QMSP.20 We showed that APC, TIMP3 and RASSF1A were more often hypermethylated in adenocarinomas compared to squamous cell cervical cancers, which is in agreement with other reports.19, 27, 45

Currently, implementing HPV DNA testing in cervical cancer screening programs is being considered.8 Infection with Hr-HPV is mandatory for cervical cancer to develop and therefore screening for HPV DNA seems logical. However, screening for Hr-HPV will result in informing many women with normal Pap smears that they are at risk of developing cervical cancer, causing unnecessary anxiety.8, 11 Our study also illustrates that even in our very selected, relatively small study population Hr-HPV testing indeed was less specific than testing for hypermethylation. Subclinical HPV infection is relatively common and often transient, especially among younger, sexually active women, making cervical cancer a rare complication of an HPV infection.10 The percentage of women who are HPV positive but have a cytologically and/or histologically confirmed normal cervix varies from 5% in Europe to 26% in Sub-Saharan Africa.46 One potential advantage of QMSP over HPV detection for cervical cancer identification is that QMSP will hopefully identify clonal lesions that are already present, while HPV detection alone identifies many patients at higher risk, most of whom will never develop cervical neoplasia. The data on the potential of HPV screening are much larger and more mature than that presently available for QMSP. In light of the length of the “HPV experience” with respect to the implementation of HPV detection in cervical screening lessons should be learnt and comparable mistakes should be avoided when designing future studies on the application of QMSP in cervical cancer screening.

In conclusion, our pilot-study on cervical scrapings indicates that a QMSP combination of 4 genes, frequently hypermethylated in cervical cancer appears to have similar sensitivity, but better specificity in comparison to “classic” cytomorphological assessment and Hr-HPV detection. Future studies will uncover whether QMSP on cervical scrapings will be able to augment or improve current screening approaches.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Patients and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

Prof. A.G.J. van der Zee is a paid consultants for OncoMethylome Sciences S.A., Liège, Belgium. Under a licensing agreement between Oncomethylome Sciences, SA and the Johns Hopkins University, Dr. D. Sidransky is entitled to a share of royalty received by the University upon sales of diagnostic products described in this article. Dr. D. Sidransky owns Oncomethylome Sciences, SA stock, which is subject to certain restrictions under the University policy. Dr. D. Sidransky is a paid consultant to Oncomethylome Sciences, SA and is a paid member of the company's Scientific Advisory Board. The Johns Hopkins University in accordance with its conflict of interest policies is managing the terms of this agreement.

References

  1. Top of page
  2. Abstract
  3. Patients and methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  • 1
    Cervical cancer. NIH Consens Statement 1996; 14: 138.
  • 2
    zur Hausen H. Papillomavirus infections—a major cause of human cancers. Biochim Biophys Acta 1996; 1288: F55F78.
  • 3
    Koss LG. Cervical (Pap) smear. New directions. Cancer 1993; 71: 140612.
  • 4
    Robertson JH, Woodend B. Negative cytology preceding cervical cancer: causes and prevention. J Clin Pathol 1993; 46: 7002.
  • 5
    Herbert A. Is cervical screening working? A cytopathologist's view from the United Kingdom. Hum Pathol 1997; 28: 1206.
  • 6
    Smith HO, Tiffany MF, Qualls CR, Key CR. The rising incidence of adenocarcinoma relative to squamous cell carcinoma of the uterine cervix in the United States—a 24-year population-based study. Gynecol Oncol 2000; 78: 97105.
  • 7
    Zappa M, Visioli CB, Ciatto S, Iossa A, Paci E, Sasieni P. Lower protection of cytological screening for adenocarcinomas and shorter protection for younger women: the results of a case–control study in Florence. Br J Cancer 2004; 90: 17846.
  • 8
    Bovicelli A, Bristow RE, Montz FJ. HPV testing: where are we now? Anticancer Res 2000; 20: 467380.
  • 9
    Sherman ME, Schiffman M, Cox JT. Effects of age and human papilloma viral load on colposcopy triage: data from the randomized Atypical Squamous Cells of Undetermined Significance/Low-Grade Squamous Intraepithelial Lesion Triage Study (ALTS). J Natl Cancer Inst 2002; 94: 1027.
  • 10
    Kulasingam SL, Hughes JP, Kiviat NB, Mao C, Weiss NS, Kuypers JM, Koutsky LA. Evaluation of human papillomavirus testing in primary screening for cervical abnormalities: comparison of sensitivity, specificity, and frequency of referral. JAMA 2002; 288: 174957.
  • 11
    Schiffman M, Khan MJ, Solomon D, Herrero R, Wacholder S, Hildesheim A, Rodriguez AC, Bratti MC, Wheeler CM, Burk RD. A study of the impact of adding HPV types to cervical cancer screening and triage tests. J Natl Cancer Inst 2005; 97: 14750.
  • 12
    Baylin SB, Esteller M, Rountree MR, Bachman KE, Schuebel K, Herman JG. Aberrant patterns of DNA methylation, chromatin formation and gene expression in cancer. Hum Mol Genet 2001; 10: 68792.
  • 13
    Ivanova T, Petrenko A, Gritsko T, Vinokourova S, Eshilev E, Kobzeva V, Kisseljov F, Kisseljova N. Methylation and silencing of the retinoic acid receptor-β2 gene in cervical cancer. BMC Cancer 2002; 2: 4.
  • 14
    Chen CL, Liu SS, Ip SM, Wong LC, Ng TY, Ngan HY. E-cadherin expression is silenced by DNA methylation in cervical cancer cell lines and tumours. Eur J Cancer 2003; 39: 51723.
  • 15
    Wong YF, Chung TK, Cheung TH, Nobori T, Yu AL, Yu J, Batova A, Lai KW, Chang AM. Methylation of p16INK4A in primary gynecologic malignancy. Cancer Lett 1999; 136: 2315.
  • 16
    Yu MY, Tong JH, Chan PK, Lee TL, Chan MW, Chan AW, Lo KW, To KF. Hypermethylation of the tumor suppressor gene RASSFIA and frequent concomitant loss of heterozygosity at 3p21 in cervical cancers. Int J Cancer 2003; 105: 2049.
  • 17
    Virmani AK, Muller C, Rathi A, Zoechbauer-Mueller S, Mathis M, Gazdar AF. Aberrant methylation during cervical carcinogenesis. Clin Cancer Res 2001; 7: 5849.
  • 18
    Narayan G, Arias-Pulido H, Koul S, Vargas H, Zhang FF, Villella J, Schneider A, Terry MB, Mansukhani M, Murty VV. Frequent promoter methylation of CDH1, DAPK, RARB, and HIC1 genes in carcinoma of cervix uteri: its relationship to clinical outcome. Mol Cancer 2003; 2: 24.
  • 19
    Dong SM, Kim HS, Rha SH, Sidransky D. Promoter hypermethylation of multiple genes in carcinoma of the uterine cervix. Clin Cancer Res 2001; 7: 19826.
  • 20
    Eads CA, Danenberg KD, Kawakami K, Saltz LB, Blake C, Shibata D, Danenberg PV, Laird PW MethyLight: a high-throughput assay to measure DNA methylation. Nucleic Acids Res 2000; 28: E32.
  • 21
    Reesink-Peters N, Wisman GBA, Jerónimo C, Tokumaru CY, Cohen Y, Dong SM, Klip HG, Buikema HJ, Suurmeijer AJ, Hollema H, Boezen HM, Sidransky D et al. Detecting cervical cancer by quantitative promoter hypermethylation assay on cervical scrapings: a feasibility study. Mol Cancer Res 2004; 2: 28995.
  • 22
    Feng Q, Balasubramanian A, Hawes SE, Toure P, Sow PS, Dem A, Dembele B, Critchlow CW, Xi L, Lu H, McIntosh MW, Young AM et al. Detection of hypermethylated genes in women with and without cervical neoplasia. J Natl Cancer Inst 2005; 97: 27382.
  • 23
    Widschwendter A, Muller HM, Fiegl H, Ivarsson L, Wiedemair A, Muller-Holzner E, Goebel G, Marth C, Widschwendter M. DNA methylation in serum and tumors of cervical cancer patients. Clin Cancer Res 2004; 10: 56571.
  • 24
    Imura J, Ichikawa K, Takeda J, Fujimori T. Beta-catenin expression as a prognostic indicator in cervical adenocarcinoma. Int J Mol Med 2001; 8: 3538.
  • 25
    Coelho FR, Prado JC, Pereira Sobrinho JS, Hamada G, Landman G, Pinto CA, Nonogaki S, Villa LL. Estrogen and progesterone receptors in human papilloma virus-related cervical neoplasia. Braz J Med Biol Res 2004; 37: 838.
  • 26
    Muller HM, Widschwendter A, Fiegl H, Goebel G, Wiedemair A, Muller-Holzner E, Marth C, Widschwendter M. A DNA methylation pattern similar to normal tissue is associated with better prognosis in human cervical cancer. Cancer Lett 2004; 209: 2316.
  • 27
    Cohen Y, Singer G, Lavie O, Dong SM, Beller U, Sidransky D. The RASSF1A tumor suppressor gene is commonly inactivated in adenocarcinoma of the uterine cervix. Clin Cancer Res 2003; 9: 29814.
  • 28
    Finan MA, DeCesare S, Fiorica JV, Chambers R, Hoffman MS, Kline RC, Roberts WS, Cavanagh D. Radical hysterectomy for stage IB1 vs IB2 carcinoma of the cervix: does the new staging system predict morbidity and survival? Gynecol Oncol 1996; 62: 13947.
  • 29
    Remmink AJ, Walboomers JM, Helmerhorst TJ, Voorhorst FJ, Rozendaal L, Risse EK, Meijer CJ, Kenemans P. The presence of persistent high-risk HPV genotypes in dysplastic cervical lesions is associated with progressive disease: natural history up to 36 months. Int J Cancer 1995; 61: 30611.
  • 30
    Visser J, van Baarle D, Hoogeboom BN, Reesink N, Klip H, Schuuring E, Nijhuis E, Pawlita M, Bungener L, Vries-Idema J, Nijman H, Miedema F et al. Enhancement of human papilloma virus type 16 E7 specific T cell responses by local invasive procedures in patients with (pre)malignant cervical neoplasia. Int J Cancer 2006; 118: 252937.
  • 31
    Baay MF, Quint WG, Koudstaal J, Hollema H, Duk JM, Burger MP, Stolz E, Herbrink P. Comprehensive study of several general and type-specific primer pairs for detection of human papillomavirus DNA by PCR in paraffin-embedded cervical carcinomas. J Clin Microbiol 1996; 34: 7457.
  • 32
    Krul EJ, van de Vijver MJ, Schuuring E, Van Kanten RW, Peters AA, Fleuren GJ. Human papillomavirus in malignant cervical lesions in Surinam, a high-risk country, compared to the Netherlands, a low-risk country. Int J Gynecol Cancer 1999; 9: 20611.
  • 33
    van Dongen JJ, Langerak AW, Bruggemann M, Evans PA, Hummel M, Lavender FL, Delabesse E, Davi F, Schuuring E, Garcia-Sanz R, Van Krieken JH, Droese J et al. Design and standardization of PCRprimers and protocols for detection of clonal immunoglobulin and T-cell receptor gene recombinations in suspect lymphoproliferations: report of the BIOMED-2 Concerted Action BMH4-CT98-3936. Leukemia 2003; 17: 2257317.
  • 34
    Herman JG, Graff JR, Myohanen S, Nelkin BD, Baylin SB. Methylation-specific PCR: a novel PCR assay for methylation status of CpG islands. Proc Natl Acad Sci USA 1996; 93: 98214.
  • 35
    Jerónimo C, Henrique R, Hoque MO, Ribeiro FR, Oliveira J, Fonseca D, Teixeira MR, Lopes C, Sidransky D. Quantitative RARβ2 hypermethylation: a promising prostate cancer marker. Clin Cancer Res 2004; 10: 401014.
  • 36
    Moon HS, Park WI, Choi EA, Chung HW, Kim SC. The expression and tyrosine phosphorylation of E-cadherin/catenin adhesion complex, and focal adhesion kinase in invasive cervical carcinomas. Int JGynecol Cancer 2003; 13: 6406.
  • 37
    Usadel H, Brabender J, Danenberg KD, Jeronimo C, Harden S, Engles J, Danenberg PV, Yang S, Sidransky D. Quantitative adenomatous polyposis coli promoter methylation analysis in tumor tissue, serum, and plasma DNA of patients with lung cancer. Cancer Res 2002; 62: 3715.
  • 38
    Harden SV, Tokumaru Y, Westra WH, Goodman S, Ahrendt SA, Yang SC, Sidransky D. Gene promoter hypermethylation in tumors and lymph nodes of stage I lung cancer patients. Clin Cancer Res 2003; 9: 13705.
  • 39
    Lehmann U, Langer F, Feist H, Glockner S, Hasemeier B, Kreipe H. Quantitative assessment of promoter hypermethylation during breast cancer development. Am J Pathol 2002; 160: 60512.
  • 40
    Steenbergen RD, Kramer D, Braakhuis BJ, Stern PL, Verheijen RH, Meijer CJ, Snijders PJ. TSLC1 gene silencing in cervical cancer cell lines and cervical neoplasia. J Natl Cancer Inst 2004; 96: 294305.
  • 41
    Shivapurkar N, Toyooka S, Toyooka KO, Reddy J, Miyajima K, Suzuki M, Shigematsu H, Takahashi T, Parikh G, Pass HI, Chaudhary PM, Gazdar AF. Aberrant methylation of trail decoy receptor genes is frequent in multiple tumor types. Int J Cancer 2004; 109: 78692.
  • 42
    Jeronimo C, Usadel H, Henrique R, Oliveira J, Lopes C, Nelson WG, Sidransky D. Quantitation of GSTP1 methylation in non-neoplastic prostatic tissue and organ-confined prostate adenocarcinoma. J Natl Cancer Inst 2001; 93: 174752.
  • 43
    Widschwendter A, Gattringer C, Ivarsson L, Fiegl H, Schneitter A, Ramoni A, Muller HM, Wiedemair A, Jerabek S, Muller-Holzner E, Goebel G, Marth C et al. Analysis of aberrant DNA methylation and human papillomavirus DNA in cervicovaginal specimens to detect invasive cervical cancer and its precursors. Clin Cancer Res 2004; 10: 3396400.
  • 44
    Gustafson KS, Furth EE, Heitjan DF, Fansler ZB, Clark DP. DNA methylation profiling of cervical squamous intraepithelial lesions using liquid-based cytology specimens: an approach that utilizes receiver-operating characteristic analysis. Cancer 2004; 102: 25968.
  • 45
    Kang S, Kim JW, Kang GH, Lee S, Park NH, Song YS, Park SY, Kang SB, Lee HP. Comparison of DNA hypermethylation patterns in different types of uterine cancer: cervical squamous cell carcinoma, cervical adenocarcinoma and endometrial adenocarcinoma. Int J Cancer 2006; 118: 216871.
  • 46
    Clifford GM, Gallus S, Herrero R, Munoz N, Snijders PJ, Vaccarella S, Anh PT, Ferreccio C, Hieu NT, Matos E, Molano M, Rajkumar R et al. Worldwide distribution of human papillomavirus types in cytologically normal women in the International Agency for Research on Cancer HPV prevalence surveys: a pooled analysis. Lancet 2005; 366: 9918.