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Detection of DNA hypermethylation as a diagnostic tool in cervical neoplasma tool in cervicalneoplasiaYang, Nan

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CHAPTER 4

Methylation markers for CCNA1 and C13ORF18 are

strongly associated with high-grade cervical

intraepithelial neoplasia and cervical cancer in

cervical scrapings

Nan Yang1,#, Jasper J.H. Eijsink1,#, Ágnes Lendvai1, Haukeline H. Volders1, Harry Klip1,

Henk J. Buikema2, Bettien M. van Hemel2, Ed Schuuring2,

Ate G. J. van der Zee1, G. Bea A. Wisman1

Departments of Gynecologic Oncology1 and Pathology2, University Medical Center

Groningen, University of Groningen, Groningen, the Netherlands

# These authors contributed equally

Cancer Epidemiol Biomarkers Prev. 2009 Nov; 18(11):3000-7

Chapter 4

76

Abstract Purpose: Recently, we reported 13 possible cervical cancer specific methylated biomarkers

identified by pharmacological unmasking microarray in combination with large-genome

computational screening. Aim of the present study was to perform an in-depth analysis of the

methylation patterns of these 13 candidate genes in cervical neoplasia and to determine their

diagnostic relevance.

Experimental design and results: 5 of 13 gene promoters (C13ORF18, CCNA1, TFPI2

C1ORF166 and NPTX1) were found to be more frequently methylated in frozen cervical cancer

compared to normal cervix specimens. Quantitative methylation analysis for these 5 markers

revealed that CCNA1 and C13ORF18 methylation were both present in 68/97 cervical scrapings

from cervical cancer patients and in only 5 and 3 scrapings, respectively, from 103 healthy

controls (p<0.0005). In cervical scrapings from patients referred with an abnormal PAP smear,

CCNA1 and C13ORF18 were methylated in 2/43 and 0/43 CIN 0 and in 1/41 and 0/41 CIN I,

respectively. Furthermore, 8/43 CIN II, 22/43 CIN III and 3/3 micro-invasive cancer patients

were positive for both markers. Although sensitivity for CIN II or higher (for both markers 37%)

was low, specificity (96% and 100%, respectively) and positive predictive value (92% and 100%,

respectively) were high.

Conclusion: Methylation of CCNA1 and C13ORF18 in cervical scrapings is strongly associated

with CIN II or higher grade lesions. Therefore, these markers might be used for direct referral to

gynecologists for patients with a methylation positive scraping.

Methylation markers in cervical cancer screening

77

Introduction Cervical cancer is an important cause of death in women worldwide(1). Cervical carcinogenesis

is strongly associated with (high-risk) human papillomavirus (HPV) infections(2).

Cytomorphological examination of cervical smears is a widely applied, though not ideal

screening method for cervical cancer and its precursors (cervical intraepithelial neoplasia

(CIN)(1;3;4). High risk HPV (hr-HPV) testing has been suggested to improve cervical cancer

screening (5;6). However the specificity of hr-HPV testing, especially in a young screening

population is relatively low(7;8). Therefore, other objective biomarkers are needed to improve

specificity for cervical cancer screening(9). Promoter hypermethylation analysis(10-12) might

represent such markers.

Promoter hypermethylation of tumor suppressor genes is a common feature of human

cancers mostly resulting in silencing of gene expression(13). 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 (MSP). In fact, one would like to have a similar methylation marker as has been

reported for GST-P1 in prostate cancer, in which promoter methylation is present in 95% of the

adenocarcinomas, whereas the normal prostate tissue is negative(14). Promoter

hypermethylation of tumor suppressor genes in general has been reported to be an early event

in cervical carcinogenesis(15) and consequently hypermethylation analysis might be relevant

especially for the early detection of cervical neoplasia.

Over the past years, assessment of methylation markers in cervical scrapings for the

detection of cervical cancer and CIN appeared to be feasible(9-12;16-22). In these studies a

variety of gene promoters has been investigated, mainly chosen due to their previously reported

methylation status in cervical cancer tissue or in other tumor types. However, still only few of

these methylation markers have been reported to be cervical cancer specific, i.e. most cancers/

high-grade CIN are methylated and simultaneously no false positive results in scrapings of

women with no or low-grade CIN. However, for most of these markers a threshold was set in

order to obtain a high specificity. Recently, an editorial emphasized the need for greater

standardization of current approaches and suggested that large-scale, non-targeted studies are

necessary to further characterize DNA methylation biomarkers in cervical cancer(23).

The identification of cancer-specific methylated markers should provide new targets for

diagnostic and therapeutic intervention. Methods for identifying such markers based on

pharmacologic unmasking of the promoter region and detection of re-expression on microarray

analysis have indeed revealed such new candidate cancer specific methylated genes(18;24;25).

Using this approach in combination with a novel relaxation ranking methodology, we recently

showed that genes were significantly enriched towards methylation in cervical cancer(26). In

addition, we reported on the modification and improvement of the selection of candidate

markers based on a promoter structure algorithm and microarray data generated from 20 cancer

cell lines of 5 major cancer types(27). Regarding cervical cancer, our initial large-genome

computational screening approach identified 45 cervical cancer specific putatively methylated

Chapter 4

78

biomarkers. Preliminary screening indicated 13 potential cervical cancer specific genes, using

BSP on 2 normal cervices and 10 cervical cancers(27).

Aim of the present study was 1) to perform an in-depth analysis of the methylation

patterns of these 13 candidate genes in cervical cancer and normal tissue specimens and 2) to

evaluate their possible relevance for detection of cervical neoplasia in a large series of

scrapings from patients with cervical cancer, low- and high-grade CIN and from otherwise

healthy women.

Patients and Methods General strategy For our in depth analysis of the methylation patterns of the 13 putative cervical cancer specific

genes, previously identified by us(27), the following strategy was used (see figure 1). First MSP

for 13 genes was performed on DNA isolated from 20 normal cervices and 20 cervical cancers.

In this first step, macrodissected frozen tissue sections were used, as the amount of DNA

isolated from frozen tissue sections is much larger than from cervical scrapings, thereby

allowing multiple MSPs. Genes selected in the first step were further evaluated in a second step

by QMSP in cervical scrapings from a large series of cervical cancer patients (n=97) and

healthy age-matched controls (n=103). This second step enabled us to investigate the

discriminative power of methylation analysis for cervical cancers compared to normal scrapings

and to analyze if methylation is related to stage or histology (in the cervical cancer group) or to

age (in the group of controls). The potential as a diagnostic tool of QMSP for the genes selected

in the second step was finally evaluated in a third step in a large series of scrapings (n=185)

from selected patients, referred to our department with an abnormal Pap smear and with no CIN

(i.e. CIN 0), CIN grade I-III or cervical cancer.

Patients All patients referred between 2001 and 2007 because of cervical cancer or an abnormal Pap

smear 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 anaesthesia

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

anaesthesia. In patients referred for an abnormal Pap smear CIN diagnosis was always based

on histology, from either a biopsy or large loop excision specimen. As healthy controls,

scrapings and tissue of normal cervices were obtained from patients without a history of

abnormal Pap smears or any form of cancer who were planned to undergo a hysterectomy for

non-malignant reasons during the same period. Indications for hysterectomy were fibroids,

prolaps uteri, adenomyosis, hypermenorrhea or a combination of these. All cervical tissues were

judged as histopathologically normal.

For MSP analysis (step 1), frozen tissue samples of 20 squamous cell cervical cancer

patients were selected (7 FIGO stage IB (35%), 6 FIGO stage IIA (30%), 3 FIGO stage IIB


79

(15%), 2 FIGO stage IIIB (10%) and 2 FIGO stage IV (10%)) and as controls frozen tissue

samples of 20 normal cervices. Median age of cervical cancer patients was 55 years (IQ range

24 – 86) and of healthy controls 50 years (IQ range 38 – 66). For QMSP analysis (step 2),

scrapings were selected randomly from our larger database (n = 411), including 97 cervical

cancer patients (45 FIGO stage IB (46%), 11 FIGO stage IIA (11%), 11 FIGO stage IIA=B (11%),

16 FIGO stage IIB (16%), 2 FIGO stage IIIA (2%), 9 FIGO stage IIIB (9%), 2 FIGO stage IVA

(2%) and 1 FIGO stage IVB (1%); 82 squamous cell carcinomas (85%) and 15

adenocarcinomas (15%)) and 103 patients with a normal cervix. Median age of both cervical

cancer patients (median: 48 yrs, 23-88) and controls (median: 48 yrs, 30-77) was the same. For

evaluation of the diagnostic performance of QMSP analysis for selected genes (step 3), we

collected from our large database comprising all patients referred with an abnormal Pap smear

(n=808), five groups, based on their histological diagnosis: CIN 0 (n=45, median age=38 yrs.),

CIN I (n=44, median age=35 yrs.), CIN II (n=45, median age=35 yrs.), CIN III (n=47, median

age=33 yrs.) and (micro)invasive cervical cancer (n=4, median age=42.5 yrs.). Informed

consent was obtained from all patients and controls participating in this study. This study was

approved by the Institutional Review Board of the UMCG.

Sample collection procedure and DNA isolation From the frozen tissue samples, sections (10 μm) were cut and in case of normal cervices

macrodissection was performed to enrich for epithelial cells. The percentage of either normal or

tumor cells present in the frozen sections used for DNA isolation was determined by staining

parallel sections with hematoxylin and eosin. Cervical scrapings were collected using an Ayre's

spatula and endocervical brush. The spatula and brush with the collected cells were then

suspended in 5 ml of phosphate buffered saline (PBS: 6.4 mM Na2HPO4; 1.5 mM KH2PO4;

0.14 M NaCl; 2.7 mM KCl (pH 7.2)) and kept on ice until further processing. Of this cell

suspension, 1 ml was used for cytomorphological assessment. Cytospins were Pap stained and

routinely classified by two independent pathologists without knowledge of the molecular and

clinical data according to a modified Papanicolaou system(29). The remaining part (4 ml) was

pelleted, snap-frozen in liquid nitrogen and stored at -80°C as described previously(12). DNA

was extracted using standard salt-chloroform extraction and ethanol precipitation for high

molecular DNA and dissolved in 150 µl TE-4 buffer (10 mM Tris; 1 mM EDTA (pH 8.0)(12). For

quality control, genomic DNA was amplified in a multiplex PCR according to the BIOMED-2

protocol(30).

HPV detection and typing In all samples, presence of high risk HPV was analyzed by PCR using HPV16 and HPV18

specific primers. On all HPV16- or HPV18- negative cases, a general primer-mediated PCR was

performed using two HPV consensus primer sets, CPI/CPIIG and GP5+/6+, with subsequent

nucleotide sequence analysis as described previously(12). As a control for the specificity and

sensitivity of each HPV-PCR, a serial dilution of DNA extracted from HPV16-positive CaSki and

HPV18-positive HeLa cell lines.

Chapter 4

80

Methylation specific PCR (MSP) MSP was performed after bisulfite treatment on denatured genomic DNA as previously

reported(31). Bisulfite treatment was performed with the EZ DNA methylation kit according to

manufacturer’s protocol (Zymogen, BaseClear, Leiden, the Netherlands). For PCR, 50 ng of

DNA was used. Primer pairs are available upon request. A sample was considered methylation

positive when a PCR product of the right size was visible after 40 cycles of PCR. As a positive

control, in vitro methylated genomic DNA with Sss I (CpG) methyltransferase (New England

Biolabs. Inc., Beverly, MA) and a negative control, a pool of leukocyte DNA from healthy women

were used in each experiment.

Real time quantitative methylation specific PCR (QMSP) QMSP was performed with bisulfite treated DNA as previously reported(12;31;32). Primer pairs

and probes are available upon request. The housekeeping gene β-actin was chosen as

reference for total DNA input measurement. QMSP was carried out in a total volume of 20 μl in

384 well plates in an Applied Biosystems 7900 Sequence Detector (Applied Biosystems,

Nieuwerkerk a/d IJsel, the Netherlands). Each sample was analyzed in triplicate. The final

reaction mixture consisted of 300 nM of each primer, 200 nM probe, 1X QuantiTect Probe PCR

Kit (Qiagen, Venlo, the Netherlands) and 50 ng of bisulfite-converted genomic DNA. As a

positive control, serial dilutions of in vitro methylated genomic leucocyte DNA with Sss I (CpG)

methyltransferase (New England Biolabs. Inc., Beverly, MA) were used in each experiment. All

amplification curves were visualized and scored without knowledge of the clinical data. A DNA

sample was considered methylated if at least 2 of 3 triplicates showed exponential curves with a

Ct-value below 50 and DNA input was at least 225 pg β-actin (equivalent to a Ct-value of 34).

QMSP values were adjusted for DNA input by expressing results as ratios between two

absolute measurements ((average DNA quantity of methylated gene of interest / average DNA

quantity for internal reference gene β-actin) x 10000)(12;31;32).

Statistics

All analyses were carried out using the SPSS software package (SPSS 14.0, Chicago, IL, USA).

Methylation ratios between groups were compared using the Mann-Whitney U test (2 groups) or

the Kruskal-Wallis test (>2 groups). Associations between numerical parameters were analyzed

using the χ² test with Fisher’s exact test for small numbers when appropriate. Associations

between positive methylation and age were analyzed with Student T-test. Observed differences

with a p-value <0.05 were considered statistically significant.

Results MSP analysis in normal cervices and cervical cancer tissues Table 1 summarizes MSP analysis in frozen tissue specimens from 20 normal cervices and 20

cervical cancer patients. C13ORF18, CCNA1, TFPI, C1ORF166 and NPTX1 were more

frequently methylated in cancers versus controls. OGDHL was methylated in almost all cancers

and normal cervices and GDAP1L1 was methylated in half of the cancers and half of the normal


81

cervices. PTGS2, ASMTL, ARMC7, HCP1, C9ORF19 and DLL4 showed no or less methylation

in cancers versus normal cervices. In sum, of the initial 13 markers five gene promoters

(C13ORF18, CCNA1, TFPI2, C1ORF166 and NPTX1) showed significantly more methylation in

cervical cancers compared to normal cervices and were therefore selected for further evaluation

in cervical scrapings.

QMSP analysis in scrapings from cervical cancer patients and controls QMSP for 5 gene promoters (C13ORF18, CCNA1, TFPI2, C1ORF166 and NPTX1) was

performed on scrapings of normal cervices (n=103) and cervical cancers (n=97) (figure 2). Both

the level and frequency of methylation of all 5 gene promoters were higher in the cancer

samples compared to the normal cervices (p<0.0005). CCNA1 and C13ORF18 showed almost

no methylation in the normal cervices (5% and 3%, respectively), while for both genes 71% of

cancers were methylation positive. C1ORF166 was never positive in the normal cervices,

however, only 34% of cervical cancers were positive and this positivity was not additive to

CCNA1 and/or C13ORF13 positivity. The other 2 gene promoters, TFPI2 and NPTX1,

frequently showed methylation in the normal cervical scrapings. Therefore, CCNA1 and

C13ORF18 were selected for further validation of their diagnostic performance. In the control

group, methylation positivity of the 5 analyzed genes was not related to age indicating that

methylation is not due to aging in the scrapings of the cancer group.

QMSP and hr-HPV analysis in scrapings from patients with an abnormal Pap smear QMSP for CCNA1 and C13ORF18 was performed on scrapings from 173 patients referred to

our department with an abnormal Pap smear, as DNA input was too low for 12 patients. QMSP

analysis for CCNA1 and C13ORF18 (figure 3) revealed that levels and positivity of both gene

promoters were increased with the severity of the underlying histological lesion (p<0.0005).

Almost all scrapings from CIN 0 and CIN I patients were unmethylated for CCNA1 and

C13ORF18, while 25% of scrapings from CIN II, 51% of CIN III and all (n=3) micro-invasive

cancers showed methylation (see figure 3).

Hr-HPV was detected in 20 of 43 CIN 0, 27 of 41 CIN I, 32 of 43 CIN II, 41 of 43 CIN III

and 3 of micro-invasive cancers. Hr-HPV was related with the severity of the underlying lesion

(p<0.0005). The following high-risk types were found: 16, 18, 31, 33, 35, 45, 51, 52, 56, 58, 59

and 66. In addition, HPV6, 70 and 90 were found in 2 CIN 0, 3 CIN I and 1 CIN II, however

these were not depicted as hr-HPV.

Diagnostic performance of hr-HPV and QMSP for CCNA1 and C13ORF18 Table 2 shows the sensitivity, specificity, positive predictive value (PPV) and negative predictive

value (NPV) for CIN II or higher of the different assays. Specificity for CIN II or higher of CCNA1

and C13ORF18 promoter methylation analysis alone or combined was high (>93%) with a low

sensitivity (37%). Interestingly, all 3 cancers were depicted by QMSP and 51% of the CIN III

patients. Especially, the PPVs for CIN II or higher of promoter methylation analysis for CCNA1

and C13ORF18 were high (92% and 100%, respectively).

Chapter 4

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Hr-HPV analysis showed the opposite result compared to methylation analysis i.e. high

sensitivity (85%), but low specificity (53%-44%) for detection of CIN II or higher, with a moderate

PPV and NPV.

As HPV DNA testing has also been suggested as a primary screening tool in

population-based cervical screening, we also determined sensitivity, specificity, PPV and NPV

of hypermethylation detection for CCNA1 and C13ORF18 in hr-HPV positive patients. This

analysis indicates that the test performance of our methylation markers in the hr-HPV positive

patients is equal to the test performance in the whole group of patients (see table 2).

Finally, we also analyzed the performance of hr-HPV DNA testing and methylation

analysis as triage tests in patients referred with a Pap smear comprising atypical squamous

cells of unknown significance (ASCUS) or low-grade dysplasia. The test performance of hr-HPV

in this specific group was moderate (41%-80%). The specificity and PPV for CIN II or higher of

methylation analysis was high (>93%) and equal when compared to the whole group.

Discussion Using a promoter structure algorithm and microarray expression data, we previously identified

13 potential gene promoters specifically methylated in cervical cancer(27). Our present strategy

using both cervical tissue specimens as well as cervical scrapings allows for a straightforward

in-depth analysis of the methylation patterns of these gene promoters and their possible

diagnostic relevance in cervical neoplasia. Our study indicates that in cervical scrapings

hypermethylation analysis for two markers (CCNA1 and C13ORF18) has a high specificity (96%

and 100%, respectively) and high positive predictive value (PPV) (100% and 92%, respectively),

but low sensitivity for CIN II or higher (36% and 38%, respectively).

The current approach for early detection of cervical neoplasia in population based

screening programs is still cytomorphological assessment of cervical scrapings, despite its low

sensitivity(33). Therefore, new approaches for detection of cervical neoplasia need to be

developed. In this respect, population based screening with hr-HPV DNA testing has been

extensively studied by many different investigators and appears to be on the brink of (Western)

worldwide introduction. Our study however shows again the low specificity of hr-HPV testing

and it is clear that especially in younger populations this approach for population based

screening needs a triage test to prevent massive referrals to gynecologists(34). Examples of

such triage tests are cytology or methylation tests. Different characteristics of a triage test after

a positive hr-HPV test can be envisioned. Our methylation test has a high positive predictive

value for CIN II or higher and therefore, hr-HPV positive patients with a positive methylation test

could be referred to a gynecologist directly for colposcopy and treatment in the same procedure.

An important advantage of a methylation test in this respect is, that such a test can be

performed on the already available specimen, thus avoiding extra visits to general practioners or

gynecologists. Besides using our methylation test as a triage test in primary hr-HPV screening,

this test might also be applied in a triage setting after primary cytological screening for patients

referred with a smear showing ASCUS or mild dysplasia. In case of a positive test, again a more

efficient see and treat policy could be followed instead of taking colposcopically guided biopsies


83

first. It is obvious that cost-effectiveness of the introduction of our methylation test as a triage

test should be further explored in prospective large-scale trials in women participating in

population-based screening programs.

Figure 4 shows possible scenarios for applications of our current methylation test.

However, due to the low NPV of our current methylation test, massive referrals to gynecologists

after a positive hr-HPV DNA and negative methylation test are still not prevented and therefore

another triage test such as cytology will still be needed.

In order to become integrated in primary screening for cervical neoplasia, better or

additional methylation markers should be added in order to increase the sensitivity, without

loosing the specificity for CIN II or higher grade lesions. Many studies have been conducted to

analyze specific gene promoter methylation in cervical scrapings(10-12;17;20;35), while others

studies searched for novel methylation markers(18;21;36). One of these studies(18) described a

similar approach to our study, in which the pharmacological unmasking microarray approach

was used resulting in the identification of 6 gene promoters (SPARC, TFPI2, RRAD, SFRP1,

MT1G, and NMES1) specifically methylated in cervical cancer. TFPI2 was the only gene

promoter similarly identified from their and our study. In the present study, TFPI2 was evaluated

although not further analyzed in the cross-sectional study as 26% of the normal cervical

scrapings showed methylation. We evaluated methylation of SPARC previously in both paraffin

tissues and matched scrapings of histological proven (pre)malignant cervical lesions (Yang et

al., paper submitted for publication1). SPARC showed more frequent methylation in cervical

cancers, but also many normal cervices were positive (13/20). Although SPARC and TFPI2

were the most promising gene promoters in the study of Sova et al.(18), our evaluation in

paraffin tissues and scrapings showed a low specificity.

Besides the need to identify a methylation marker that is able to detect all CIN II and

higher grade lesions, the biological process of de novo methylation of promoter regions of tumor

suppressor genes in cervical carcinogenesis might be of interest. We show in our study that

approximately 25% of CIN II scrapings and 50% of CIN III scrapings are positive for C13ORF18

and/or CCNA1. It is also generally assumed that approximately these percentages of CIN II/III

will progress to cancer when left untreated(37). One could hypothesize that only methylation

positive lesions are propelled to progress and therefore need treatment. However, it will be

difficult to explore such a hypothesis. E.g. patients diagnosed with CIN II/III, preferably based on

as small biopsies as possible(38), should be asked to participate in a wait-and-see study. Long-

term follow-up of these patients by colposcopy should allow us to analyze possible relation

between methylation status and regression/progression of the lesions. However, such studies

are hard to perform and easily flawed by different types of methodological biases.

In this study, we showed that 5 genes were specifically methylated in cervical cancer

compared to normal cervical specimens. CCNA1, TFPI2 and NPTX1 were previously described

to be frequently methylated in cervical cancer(18;26;39). Available data for CCNA1 and TFPI2 is

in line with our present data. However, we found more TFPI2 methylation in scrapings of normal

cervices and less CCNA1 methylation in scrapings of cervical cancers, which might be because

of the small group size of the other studies. C13ORF18 and C1ORF166 have not previously

Chapter 4

84

been described to be methylated in any type of cancer. C1ORF166, now known as MUL1 or

MULAN, is a RING finger E3 ubiquitin ligase, anchored to mitochondria and implicated in the

regulation of mitochondrial dynamics. Because C1OR166 has been reported to activate NF-kB

pathway(40;41), its inactivation due to hypermethylation implies a functional role for NF-kB

during progression of cervical cancer. However, this needs further studies. Finally, C13ORF18,

represents a gene with unknown function. Sequence comparisons suggest a role as

phosphatase inhibitor (www.genecards.com) that would fit with the function of a tumor

suppressor gene inactivated in cancer by hypermethylation. The elucidation of the function of

this gene is now subject of our future research.

In conclusion, two gene promoters, CCNA1 and C13ORF18 showed more methylation

with increasing severity of the underlying lesion analyzed in cervical scrapings from patients

with an abnormal smear. The PPV for our methylation test with these markers was high.

Whether patients with a methylation positive scraping should be directly referred for treatment of

their cervical neoplasia deserves further exploration in prospective studies on population-based

screening for cervical cancer.

Acknowledgments This study was supported by OncoMethylome Sciences S.A., Liège, Belgium and by the Dutch

Cancer Society (NKB) (project-number RUG 2004-3161). N. Yang is a bursary of Bernouilli.

http://www.genecards.com/


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Table 1: Methylation positivity in frozen tissue obtained from patients with normal cervix or

cervical cancer.

gene cancer normal p-value1

C13ORF18 13/20 1/20 <0.0005

CCNA1 17/20 7/20 0.001

TFPI2 19/20 9/20 0.001

C1ORF166 8/20 1/20 0.02

NPTX1 4/20 0/20 0.106

GDAP1L1 10/20 6/20 0.197

PTGS2/COX2 2/20 0/20 0.487

ASMTL 0/20 2/20 0.487

OGDHL 17/20 19/20 0.605

ARMC7 3/20 1/20 0.605

HCP1 2/20 4/20 0.661

C9ORF19 0/20 0/20 2

DLL4 0/20 0/20 2

1: p-value was calculated by chi-square. If groups were too small, the Fisher exact test was

applied. 2: No statistics could be computed as methylation mark is a constant.

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Table 2: Sensitivity to detect CIN II/III (HSIL) or cancer, specificity for only CIN 0 or CIN 0/I,

positive predictive value (PPV) for HSIL and cancer and negative predictive value (NPV) for CIN

0 or CIN 0/I of methylation positivity or hr-HPV in scrapings obtained from patients with an

abnormal smear (n=173).

sensitivity specificity PPV NPV

HSIL/ca CIN 0 CIN 0/I HSIL/ca CIN 0 CIN 0/I

CCNA1 33/89

(37%)

41/43

(95%)

81/84

(96%)

33/36

(92%)

41/137

(30%)

81/137

(59%)

C13ORF18 33/89

(37%)

43/43

(100%)

84/84

(100%)

33/33

(100%)

43/140

(31%)

84/140

(60%)

CCNA1/C13ORF18 42/89

(47%)

41/43

(95%)

81/84

(96%)

42/45

(93%)

41/128

(32%)

81/128

(63%)

Hr-HPV 76/89

(85%)

23/43

(53%)

37/84

(44%)

76/123

(62%)

23/50

(46%)

37/50

(74%)

Only Hr-HPV pos pts

CCNA1 29/76

(38%)

19/21

(90%)

45/48

(94%)

29/32

(91%)

19/92

(21%)

45/92

(49%)

C13ORF18 30/76

(39%)

21/21

(100%)

48/48

(100%)

30/30

(100%)

21/94

(22%)

48/94

(51%)


(50%)

19/21

(90%)

45/48

(94%)

38/41

(93%)

19/83

(23%)

45/83

(54%)

Only Pap II/IIIa pts

CCNA1 8/39

(21%)

40/42

(95%)

75/78

(96%)

8/11

(73%)

40/106

(38%)

75/106

(71%)

C13ORF18 5/39

(13%)

42/42

(100%)

78/78

(100%)

5/5

(100)

42/112

(38%)

78/112

(70%)


(26%)

40/42

(95%)

75/78

(96%)

10/13

(77%)

40/104

(38%)

75/104

(72%)

Hr-HPV 30/39

(77%)

23/42

(55%)

35/78

(45%)

30/73

(41%)

23/44

(52%)

35/44

(80%)


91

Figure 1: Flow scheme for analysis of the diagnostic performance of 13 cervical cancer specific

genes identified in our previous study [27].

Chapter 4

92

Figure 2: Methylation ratio and frequency in cervical scrapings obtained from patients with

normal cervix or cervical cancer (squamous cell cervical cancer (SCC) and adenocarcinomas

(AC)). The level and frequency of methylation for all gene promoters are increasing with the

severity of the lesion (all p<0.0005).


93

Figure 3: Methylation ratio and frequency in cervical scrapings obtained from patients referred

with an abnormal smear (n=173). The final diagnosis was no CIN (CIN 0), CIN I, CIN II, CIN III

or micro-invasive cancer ((m)CC). The level and frequency of methylation is increasing with the

severity of the lesion (both p<0.0005).

Chapter 4

94

Figure 4: Proposed scheme for the incorporation of a methylation test in cervical cancer

screening if either hr-HPV or cytology will be used as primary screening.

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