Innovative molecular markers for diagnosis and prognosis in cervical neoplasia Boers, Aniek

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1 University of Groningen Innovative molecular markers for diagnosis and prognosis in cervical neoplasia Boers, Aniek IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below. Document Version Publisher's PDF, also known as Version of record Publication date: 2014 Link to publication in University of Groningen/UMCG research database Citation for published version (APA): Boers, A. (2014). Innovative molecular markers for diagnosis and prognosis in cervical neoplasia. [S.l.]: [S.n.]. Copyright Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons). Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Downloaded from the University of Groningen/UMCG research database (Pure): For technical reasons the number of authors shown on this cover page is limited to 10 maximum. Download date:

2 Chapter 2 Diagnostic value of methylation markers in screening for cervical cancer: a systematic review Boers A. 1, de Bock G.H. 2, de Kroon L. 1, Schuuring E. 3, van der Zee A.G.J. 1, Wisman G.B.A 1. 1 Department of Gynecologic Oncology, University of Groningen, University Medical Center Groningen, the Netherlands. 2 Department of Epidemiology, University of Groningen, University Medical Center Groningen, the Netherlands 3 Department of Pathology, University of Groningen, University Medical Center Groningen, the Netherlands Submitted for publication

3 Chapter 2 Abstract Introduction: A large number of studies explored the suitability of DNA methylation markers to apply as a screening test for cervical neoplasia. In this systematic review, we summarize the results of studies analyzing the diagnostic potential of methylation markers in cervical scrapings by (Quantitative) Methylation Specific PCR ((Q)MSP). Methods: A Pubmed, Embase and Cochrane literature search for methylation markers in cervical cancer screening was performed. Studies that used cervical scrapings, (Q)MSP for the methylation analysis and histology as a reference were included. Data were stratified for studies that used methylation marker analysis as a primary test versus studies that used methylation marker analysis as triage test in hrhpv positive women. Results: The initial search resulted in 356 publications, of which 37 studies describing 61 genes fulfilled our criteria. Methylation analysis used as a primary test to compare highgrade squamous intraepithelial lesions (HSIL) versus normal/low-grade (L)SIL revealed 6 genes (EPB41L3, HS3ST2, JAM3, NKX6, SOX9, and ZNF582) with relatively high sensitivity (49%-93%) and specificity (67%-100%). Methylation analysis comparing normal/lsil with carcinoma scrapings resulted in 4 genes (PAX1, CCNA1, EPB41L3, and JAM3) with consistently high sensitivity (72%-100%) and specificity (82%-100%). Methylation analysis used as a triage test in hrhpv positive women revealed 6 genes (DKK3, SFRP2, MAL, CADM1, JAM3 and EPB41L3) that showed a combined sensitivity and specificity for the detecting of HSIL comparable or higher than for other triage strategies. Conclusion: Our analysis reveals that methylation analysis of 10 genes showed high sensitivity and specificity to detect (pre)malignant cervical lesions when used as a primary screening test. Especially, triage testing of hrhpv positive women by methylation analysis is interesting for implementation in population-based screening. However, standardization of methodology for methylation analysis needs to be further defined. Final implementation of selected methylation markers can only occur after validation in population-based settings. 22

4 Diagnostic value of methylation markers Introduction Due to the introduction of population-based screening programs in developed countries, the incidence and mortality of cervical cancer has declined dramatically 1-3. Cytomorphological examination of cervical smears is the most common screening method used, but is not ideal because of a relatively low sensitivity 4. With high-risk HPV (hrhpv) testing the sensitivity of the screening test will improve 5-7. However, the specificity of hrhpv testing, especially in a young screening population is relatively low 8. Promoter hypermethylation of tumor suppressor genes is an early event in carcinogenesis 9. A test based on detection of DNA methylation might be an attractive tool for cervical cancer screening. Assessment of methylation markers in cervical scrapings for detection of (pre)malignant lesions is proven to be feasible with quantitative methylation specific PCR (QMSP) QMSP is a specific and sensitive method that allows high throughput analysis, making it suitable as a screening tool. 2 Many studies have been performed to find the ideal methylation marker for identifying cervical neoplasia. For this journal, Wentzensen et al. 12 summarized the results of methylation studies until 2008, in which they analyzed 51 studies comprising 68 genes. They included studies that analyzed fresh-frozen material, paraffin embedded tissue or exfoliated cells. The methylation analysis techniques used in the different studies were heterogeneous, as well as the ethnicity of the study populations, HPV status, cut-off values and choices of normal control tissue. Methylation frequencies for the same gene varied widely between studies. They concluded that three markers, DAPK1, CADM1 and RARB, showed elevated methylation levels in cervical cancers consistently across all studies, but that no single methylation marker was suited for cervical cancer screening yet and more research was needed 12. Over the last years, new methylation markers have been discovered and validation of these markers is often performed on cervical scrapings, which is relevant as this material is also used in cervical cancer screening and can easily be obtained. Since several randomised trials have demonstrated that hrhpv testing has higher sensitivity for detecting (pre)malignant cervical lesions and consequently improves screening for cervical cancer, several countries including the Netherlands have decided to change the population-based screening program to primary hrhpv screening 4,6,13,14. However, because of the lower specificity of the hrhpv test, a triage test is necessary to prevent unnecessary referral. Methylation marker analysis might be interesting for primary cervical cancer screening, but also as triage test in hrhpv positive women and a variety of studies has become available that analyzed the performance of methylation markers as a screening test for cervical 23

5 Chapter 2 cancer. The most optimal methylation marker assay should primarily have a high sensitivity for detecting (pre)malignant disease, but also high specificity is important to prevent unnecessary referral to the gynecologist. In addition, the sensitivity of such methylation markers should be at least as high as for the currently widely used cytological assessment (~55%) 6. In the discussion of this review we further elaborate on the requirements needed to implement methylation analysis as a screening test in population-based cervical cancer screening programs. The aim of this systematic review was to summarize the results of studies that analyzed methylation markers in cervical scrapings by (Q)MSP in different patient groups as primary screening test as well as triage test after primary hrhpv screening. Methods and Materials Search strategy and selection criteria A systematic Pubmed/Medline, Embase and Cochrane literature search was performed to identify studies that analyzed methylation markers in cervical scrapings. Studies published until December 2013 were examined for this review. MESH words used were ( cervical cancer or cervical intraepithelial neoplasia or CIN or uterine cervical neoplasm or uterine cervical dysplasia ) AND ( methylation marker or methylation or DNA methylation ) AND ( screening or detection or diagnostic or diagnos* ). The references of all publications and reviews were hand-searched in order to identify missing relevant publications. Included were English studies that described (premalignant) cervical cancer and used cervical scrapings for the methylation marker analysis (Figure 1). Two researchers (AB and LdK) independently examined all titles and abstracts. Of the remaining studies full-text was obtained. During full-text evaluation, articles that did not use histology as the reference standard test for diagnosis and studies that used assays other than (Q)MSP were excluded. Study quality was assessed independently by two researchers (AB and LdK). Cases of disagreement were resolved by discussing the article with a third reviewer (GBAW). The quality measurement form was prepared in advance and was based on the REMARK criteria from McShane et al. 15 and the work of Hayes et al. 16. Supplement table 1 shows the criteria used for this review. Studies with a maximum score of 7 were considered to be of very high study quality, while a zero score indicated the lowest quality. Studies with a relatively low quality score ( 5) were excluded. If methylation frequencies or percentages could not be extracted, the article had to be excluded. Articles that analyzed genes in only one group (for examples only normal scrapings) were not included in this review, since we were interested in genes that showed differences in methylation during the progression of cervical carcinogenesis. 24

6 Diagnostic value of methylation markers Data extraction Methylation frequencies of different genes were extracted by two investigators (AB and LdK) according to a predefined registration form. Topics in this form were: first author, country, year of publication, number of scrapings, genes that were analyzed, methylation frequency/percentage per different subgroup (normal, cervical intraepithelial neoplasia grade 1 (CIN1), CIN2, CIN3, cervical cancer), definition of high-grade intraepithelial neoplasia (HSIL), assay by MSP or QMSP, cut-off value that was used, HPV status, and whether methylation testing was used as a primary test or as triage test in hrhpv positive women. 2 Figure 1. Overview search strategy Data analysis Data were grouped in the following way: (1) methylation frequency data of the normal controls and CIN1 patients were combined into the normal/low-grade SIL (LSIL) group; (2) methylation frequency data of CIN2 and CIN3 were combined into the HSIL group and (3) methylation frequency data of adenocarcinoma (AC) and squamous cell carcinoma (SCC) were combined into the carcinoma group. Data were stratified for studies using methylation marker analysis as a primary test versus studies analyzing methylation markers as a triage test in hrhpv positive women. Methylation used as a primary screening test to differentiate between normal/lsil and HSIL scrapings should reach a sensitivity for HSIL or higher (HSIL+) at least as high as the 25

7 Chapter 2 sensitivity of the currently widely used cytology (~55%) 4-6. Therefore, in this patient group, we first selected only those genes that showed a sensitivity and specificity for HSIL+ of 60%. After this selection of genes, we added again those studies that described the same gene but did not reach the sensitivity and specificity for HSIL+ 60% in order to illustrate the whole spectrum of methylation data shown for the selected genes. When possible we calculated the sensitivity for the HSIL (CIN2/3) group. However, sometimes data of CIN2 lesions was not available (only CIN3) or it was only possible to calculate the sensitivity for CIN2+ or CIN3+ (including carcinomas). As this may affect the diagnostic performance of that specific marker, this group was marked separately. Methylation used as a primary screening test to differentiate between normal/lsil and carcinoma scrapings needed more stringent criteria to reduce the risk of false-negative results in the carcinoma group. Therefore, in this group we selected those genes that reached a sensitivity and specificity for carcinoma of 80%. After this selection of genes, we added the studies that described the same gene, but did not reach this sensitivity/ specificity in order to illustrate again the whole spectrum of methylation data shown for these genes. Methylation used as a triage test in hrhpv positive women was analyzed separately. For this group, results of all genes are shown, without making a selection based on sensitivity and/or specificity. Results of the markers are shown in sensitivity versus 1-specificity graphs. Results Study characteristics The initial Pubmed/Medline search identified 317 publications, an additional 39 publications were found in Embase and no publications were found in the Cochrane database, resulting in a total number of 356 identified publications. After title and abstract evaluation 291 manuscripts were excluded because they (1) described tumors other than cervical cancer, (2) did not use cervical scrapings, but only fresh-frozen or paraffin embedded material or (3) were non English. Of the remaining 65 studies full-text articles were obtained. Evaluation of the full-text articles excluded 19 manuscripts that used other analysis than (Q)MSP, 3 manuscripts because histology was not the reference standard, 2 manuscripts with a quality score 5 and 4 manuscripts because methylation percentages could not be calculated. The remaining 37 manuscripts were included in this review (Figure 1). The 37 studies that fulfilled all criteria described 61 single genes; 28 genes were analyzed in 1 study, 14 genes in 2 studies, 5 genes in 3 studies, 5 genes in 4 studies and 9 genes were described in 5 or more studies. For an overview of the methylation percentages per 26

8 Diagnostic value of methylation markers gene and per subgroup, see supplemental table 2. In addition to these single gene results, 15 studies also described combinations of genes that were analyzed. Most studies showed results for both single genes and combinations of the single genes, but one study showed only results for a combination of genes and not for the single genes separately 17. Primary methylation based screening comparing normal/lsil versus HSIL scrapings analyzed 50 genes described in 28 studies. For the normal/lsil versus carcinoma scrapings 48 genes described in 18 studies were analyzed. Methylation marker analysis used as a triage test analyzed 17 genes described in 9 studies. 2 Methylation marker analysis used as a primary test to compare normal/lsil versus HSIL Of the 50 genes described, the following 13 genes showed a sensitivity and specificity for HSIL+ 60% in at least one of the studies: CADM1, DAPK1, EPB41L3, HS3ST2, JAM3, LMX1A, MGMT, NKX6-1, PAX1, SOX1, SOX9, TERT and ZNF582 (Table 1). Figure 2 shows the sensitivity versus 1-specificity graph, taking the number of scrapings analyzed and type of scrapings included in the HSIL group (CIN2/3, CIN2+ or CIN3+) into account. Number of scrapings : Genes (n) > 200 Cut-off CIN3+ HSIL+SCC Sensitivity (%) 1-Specificity (%) Figure 2. Methylation marker analysis used as a primary test to discriminate normal/lsil versus HSIL scrapings. Sensitivity versus 1-specifcity graph for the most interesting genes. The grey box indicates genes that show a sensitivity and specificity for HSIL of 60% 27

9 Chapter 2 Table 1. Most interesting genes differentiating between normal/lsil and HSIL scrapings with in at least one study a sensitivity and specificity of 60%. Genes CADM1 DAPK1 EPB41L3 Reference Number of scrapings used Specificity Normal/ LSIL (in %) Sensitivity HSIL (in %) HS3ST JAM3 LMX1A MGMT NKX6-1 PAX1 SOX Cut-off* CIN3+samples and cut-off based on ROC curve was used CIN3+samples and cut-off based on ROC curve was used Cut-off based on PMR was used CIN3+samples and cut-off based on ROC curve was used Cut-off based on PMR was used *The HSIL group consisted of CIN2/3 and no cut-off was used, unless otherwise specified. CIN3+samples and cut-off based on ROC curve was used 28

10 Diagnostic value of methylation markers Table 1. Continued. Genes Reference Number of scrapings used Specificity Normal/ LSIL (in %) Sensitivity HSIL (in %) SOX TERT ZNF Cut-off* CIN2/3+ samples, including carcinomas and cut-off based on ROC curve was used 2 *The HSIL group consisted of CIN2/3 and no cut-off was used, unless otherwise specified. DAPK was described most often in 8 different studies. Three out of the 8 studies fulfilled the criteria of a sensitivity and specificity for HSIL 60% One study indicated a sensitivity for HSIL of 100% with a corresponding specificity of 85%, but in this study a relatively small number of samples (n=39) was used 19. The other 7 studies describing DAPK showed very divergent results with the lowest sensitivity for HSIL of 22% and the maximal sensitivity for HSIL of 64%. Specificity results were between 70%-100%, with one outlier that showed a specificity of only 35% 18, MGMT was described in 6 studies of which only one fulfilled the criteria of a sensitivity and specificity for HSIL 60% 19. This study with a relatively small number of samples (n=39) showed a sensitivity for HSIL of 75% and a specificity of 89% 19. The other 5 studies describing MGMT revealed much lower sensitivity for HSIL, in two studies sensitivity was 0% and in 3 other studies it ranged between 25%- 43%, while specificity differed between 62%-98% 18,21,22,26,27. TERT was described in 4 studies; 3 studies analyzed a relatively small number of samples (n=23 44) and one study analyzed larger numbers of samples (n=202). The study with the larger number of samples showed a sensitivity for detecting HSIL of 37% with a specificity of 90% 28. The other three studies revealed sensitivities for HSIL between 40%-78% and specificities between 67%-100% 19,29,30. Two out of the four studies fulfilled our criteria of a sensitivity and specificity for HSIL 60% 19,30. CADM1 was described in 3 studies of which one fulfilled our criteria 18. CADM1 showed very divergent results, sensitivity for HSIL was between 26%-63% and specificity between 35%-100% 18,24,2518,23. EPB41L3 and JAM3 were both described in the same two studies; the study that analyzed a relatively small number of scrapings (n=23) showed a sensitivity for HSIL of 73% and a specificity of 100% for EPB41L3, and for JAM3 the sensitivity for HSIL was 67%, with a specificity of 100% 29. The other study that analyzed both genes in a larger number of scrapings (n=202) showed for EPB41L3 a sensitivity for HSIL of 50% with a specificity of 88% and for JAM3 the sensitivity for HSIL was 49% with a specificity of 92% 28. ZNF582 and HS3ST2 were both described only once (n=285 and n=155), ZNF582 showed a sensitivity for HSIL of 63% with a specificity of 85% 31. For HS3ST2 sensitivity for HSIL was 73% and specificity 75%

11 Chapter 2 Some manuscripts used a pre-defined cut-off value, an artificially set methylation ratio that defines methylation positive and negative samples. In addition, for some manuscripts it was not possible to calculate the sensitivity of the HSIL group, since only scrapings of CIN3+ lesions were included. This group was marked separately (Figure 2, Table 1). PAX1 was described in 6 different studies of which 2 fulfilled our criteria of a sensitivity and specificity for HSIL 60% 32,33. One study used both a cut-off value and CIN3+ samples (comprising 24 CIN3, 22 carcinoma in situ (CIS) and 27 carcinoma scrapings) 32 and the other study used a cut-off value and a very small number of HSIL samples (n=8) 33. Both studies showed high sensitivity for CIN3+/HSIL (78% and 88%) compared to the studies that did not use a cut-off value and included CIN2 scrapings as well. These studies showed sensitivities for HSIL between 25-42%, specificities in the 6 studies were between 90%-99% 20, SOX1, NKX6-1 and LMX1A were all described in the same two studies; in one study CIN3+ samples (comprising 24 CIN3, 22 CIS and 27 carcinoma scrapings) were analyzed and a cut-off value was used. This study showed sensitivities for CIN3+ of 88%, 93% and 77% with specificities of 82%, 97% and 88% for SOX1, NKX6-1 and LMX1A, respectively 32. The other study analyzed HSIL samples (CIN2/3) with no cut-off value, and showed much lower sensitivities for HSIL of 9%, 55% and 16% with specificities of 97%, 67% and 90% for SOX1, NKX6-1 and LMX1A, respectively 35. SOX9 was described in 1 study comparing normal/lsil with CIN2+ (comprising 30 CIN2/3 scrapings and 48 SCC scrapings) and also used a cut-off value. This study showed a high sensitivity for CIN2+ of 92% with a specificity of 90% 37. Methylation marker analysis used as a primary test to compare normal/lsil versus cancer Of the 48 described genes, the following 7 genes showed a sensitivity and specificity for carcinoma of 80% in at least one of the studies: CCNA1, EPB41L3, JAM3, p16, PAX1, SPARC, and TERT (Table 2). Figure 3 shows the sensitivity versus 1-specificity graph, taking the number of samples analyzed into account. Table 2. Most interesting genes differentiating between normal/lsil and cancer scrapings with in at least one study a sensitivity and specificity of 80%. Genes CCNA1 EPB41L3 JAM3 Reference Number of scrapings used Specificity Normal/ LSIL (in %) Sensitivity Cancer (in %) Cut-off 30

12 Diagnostic value of methylation markers Table 2. Continued. Genes P16 PAX1 SPARC TERT Reference Number of scrapings used Specificity Normal/ LSIL (in %) Sensitivity Cancer (in %) Cut-off Cut-off based on PMR was used Cut-off based on PMR was used Sensitivity (%) Number of scrapings: > 200 Genes (n) 1-Specificity (%) Figure 3. Methylation marker analysis used as a primary test to discriminate normal/lsil versus cancer scrapings. Sensitivity versus 1-specifcity graph for the most interesting genes. The grey box indicates genes that show a sensitivity and specificity for cancer 80%. 31

13 Chapter 2 PAX1 showed in 3 studies consistently high sensitivity and specificity for cervical cancer. One study analyzed a relatively small number of samples (n=41), used a cut-off value and showed a sensitivity for cervical cancer of 100% with a specificity of 96% 34. The other two studies analyzed larger numbers of scrapings (n=107 and n=124), used no cut-off values, and obtained a sensitivity of 86% and of 90% and a specificity of 99% and 98%, respectively 20,35. The gene p16 was described in 4 different studies and showed divergent results with only one study that fulfilled our criteria of a sensitivity and specificity for carcinoma 80% 38. The sensitivity for cancer ranged from 5%-94% and specificity from 81%-97% 21,23,27,38. CCNA1 and TERT were both described in three studies; for CCNA1 the study with the best sensitivity (100%) and specificity (95%) for cervical cancer analyzed 124 scrapings 20. The other two studies that analyzed CCNA1 (n=37 and n=284) showed sensitivities of 72% and 75% and specificities of 96% and 82% for detection of cervical cancer 25,39. For TERT, two studies (n=203 and n=28) showed similar results in sensitivity for cervical cancer (80-90%) and also for specificity (90-100%) 28,29. The third study describing TERT (n=88) showed a lower sensitivity and specificity (66% and 67%) 19. EPB4L3, JAM3 and SPARC were all described in two studies: EPB41L3 and JAM3 were both described in the same two studies. One study analyzed a relatively small number of scrapings (n=28), revealing a sensitivity and specificity for detection of cervical cancer by EPB41L3 of 90% and 100% and for JAM3 of 75% and 100% 29. The other study analyzed larger numbers of scrapings (n=203) and showed a sensitivity and specificity for detection of cervical cancer by EPB41L3 of 83% and 88% and for JAM3 83% and 92% 28. SPARC was described in two smaller studies (n=37 and n=43); one study used a cut-off value and showed high sensitivity (91%) and high specificity (95%) for detection of cervical cancer 40, while the other study that did not use a cut-off value also showed a high sensitivity (100%) for detecting cervical cancer but very low specificity (12%) 25. Combinations of methylation markers used as a primary test in cervical cancer screening Twelve studies described combinations of different methylation markers to improve sensitivity and specificity results. We show only the results of those combinations that reached a sensitivity and specificity of 60% for discriminating normal/lsil versus HSIL scrapings and 80% for discriminating normal/lsil versus cancer scrapings (Table 3). Most combinations did not show better results than the single genes. The best combinations for discriminating normal/lsil versus HSIL scrapings were: PAX1/NKX6-1, PAX1/LMX1A, SOX1/NKX6-1, LMX1A/NKX6-1, with sensitivities between 88%-96% and specificities between 77%-88%. However, all these markers came from the same study using a cutoff value and analyzing CIN3+ samples (comprising 24 CIN3, 22 CIS and 27 carcinoma scrapings) 32. Another interesting combination was C13ORF18/JAM3/EPB41L3/TERT since this combination showed high sensitivity for both HSIL (65%-80%) and for cancer (94%-95%) with also high specificity (77%-100%) without setting a cut-off value and including CIN2 samples 28,29. 32

14 Diagnostic value of methylation markers Table 3. Combinations of different methylation markers with a sensitivity and specificity of 60% for discriminating normal/lsil versus HSIL scrapings and of 80% for discriminating normal/lsil versus cancer scrapings. Gene combinations Number of scrapings used Specificity normal/ LSIL (in %) Sensitivity HSIL (in %) DAPK1,CADM DAPK1, CADM1, SPARC, TFPI RASSF1A, HIN RASSF1A, RARβ RASSF1A, TWIST RASSF1A, TWIST, HIN1 RASSF1A, TWIST, RARβ PAX1, NKX PAX1, LMX1A SOX1, NKX SOX1, LMX1A SOX1, PAX LMX1A, NKX JAM3, EPB41L3, C13ORF18, TERT JAM3, EPB41L3, C13ORF18, TERT JAM3, EPB41L3, C13ORF19, TERT JAM3, EPB41L3, C13ORF19, TERT CALCA, DAPK1, ESR1 CALCA, DAPK1, ESR1, APC Extra* HSIL/SCC samples and cut-off based on ROC curve was used HSIL/SCC samples and cut-off based on ROC curve was used HSIL/SCC samples and cut-off based on ROC curve was used HSIL/SCC samples and cut-off based on ROC curve was used HSIL/SCC samples and cut-off based on ROC curve was used CIN3+samples and cut-off based on ROC curve was used CIN3+samples and cut-off based on ROC curve was used CIN3+samples and cut-off based on ROC curve was used CIN3+samples and cut-off based on ROC curve was used CIN3+samples and cut-off based on ROC curve was used CIN3+samples and cut-off based on ROC curve was used Specificity set at 100% Specificity set at 100% 2 *The HSIL group consisted of CIN2/3 and no cut-off was used, unless otherwise specified. In the combination of genes any one of the genes was methylated. 33

15 Chapter 2 Methylation markers used as a triage test in hrhpv positive women DNA methylation analysis can also be implemented as triage test for hrhpv positive women. Seventeen genes were analyzed as a triage marker after primary hrhpv screening to discriminate between normal/lsil and HSIL/cancer lesions, namely C13ORF18, CADM1(M12/M18), CCNA1, DKK3, EPB41L3, Hsa-mir-124, Hsa-mir-203, JAM3, LMX1A, MAL(M1/M2), NKX6-1, PAX1, PCDH10, SFRP2, SOX1, TERT and WT1 (Table 4). The sensitivity versus 1-specificity graph shows that all but one (Hsa-mir-203) of the 17 genes showed high specificity (between 88%-100%), while sensitivity was more divers (Figure 4). specifcity graph for all genes. Number of scrapings: Genes (n) > 200 Sensitivity (%) AdCIS/AdCa CIN2+ CIN3+ and cut-off used 1-Specificity (%) Figure 4. Methylation used as a triage test in hrhpv positive women. Sensitivity versus 1-specifcity graph for all genes. 34

16 Diagnostic value of methylation markers Table 4. Sensitivity and specificity of methylation markers tested as triage test in hrhpv positive scrapings. Genes C13ORF18 Reference Number of scrapings used Specificity Normal/ LSIL (in %) Sensitivity HSIL (in %) Extra* CADM1 M CIN3 samples and cut-off based on 99% CI CADM1 M normals was used CCNA DKK EPB41L Hsa-mir Hsa-mir Hsa-mir Only 8 AdCIS/Adca samples were used and cut-off based on 99% CI normals was used CIN3 samples and cut-off based on 99% CI normals was used Hsa-mir CIN3 samples used only JAM LMX1A 35 NR MAL M1 MAL M NKX NR PAX1 35 NR PCDH SFRP SOX1 35 NR TERT WT NR CIN3 samples and cut-off based on 99% CI normals was used Only 8 AdCIS/Adca samples were used and cut-off based on 99% CI normals was used 2 *The HSIL group consisted of CIN2/3 and no cut-off was used, unless otherwise specified. Triage testing of hrhpv positive women by cytology showed sensitivities between 48-63% 41,42. Therefore methylation markers should have a sensitivity for HSIL+ of at least 50% and DKK3, SFRP2, MAL, CADM1, EPB41L3 and JAM3 fulfilled these criteria. The genes DKK3 and SFRP2 were both described in the same study (n=39) and showed high sensitivity (100%) for adenocarcinoma in situ or worse (ACIS+) with high specificity (97-100%), although only 8 patients with ACIS+ scrapings were included and the cut-off was set at 99% confidence interval (CI) of the normal scrapings 43. The gene MAL, represented by 2 primer sets MAL M1 and MAL M2, was described in two studies. These studies analyzed a relatively small number of scrapings (n=38 and 70), comprising only normal and CIN3 scrapings and the cut-off level was set at the 99% CI of the normal scrapings. For MAL 35

17 Chapter 2 M1 sensitivity for CIN3 was 71% and 83% and specificity 88% and 93%, while for MAL M2 sensitivity for CIN3 was 62% and 53% and specificity 100% and 95% in these two studies 44,45. CADM1, represented by 2 primers sets CADM1 M12 and CADM1 M18, was described in one study analyzing 70 scrapings. Also in this study the cut-off was set at the 99% CI of the normal scrapings and only normal and CIN3 scrapings were analyzed. Sensitivity for CIN3 of CADM1 M18 was 87% and specificity 95% and for CADM1 M12 sensitivity for CIN3 was 67% with a specificity of 95% 45. JAM3 and EPB41L3 were both described in one study analyzing 101 scrapings, using no cut-off. For JAM3 the sensitivity for detecting CIN2+ was 53% with a specificity of 88%, for CIN3+ sensitivity was 70% with a specificity of 83%. For EPB41L3 the sensitivity for detecting CIN2+ was 55%, for CIN3+ 70%, with a specificity of 88% and 83% respectively 28. Six studies described 19 different combinations of methylation markers as a triage test in hrhpv positive women. Table 5 shows the results for all combinations of genes tested as a triage methylation marker assay. The combination CADM1/MAL was tested most often and with different primer sets 17,44,45. It showed consistently high sensitivity (82%-90%) and specificity (63%-88%), although all results were based on studies analyzing only CIN3 samples and using a cut-off value. Table 5. Combinations of different methylation markers used as a triage test in hrhpv positive scrapings to discriminate normal/lsil and HSIL scrapings. Gene combinations Number of scrapings used Specificity normal/ LSIL (in %) Sensitivity HSIL (in %) C13ORF18/EPB41L3/JAM3/TERT CCNA1/C13ORF Hsa-Mir-124-1/Hsa-mir-124-2** CADM1-M18/MAL-M1 MAL-M1/MAL-M CADM1-M12/CADM1 -M MAL-M1/CADM1-M MAL-M1/ CADM1-M12/ CADM-M MAL-M1/MAL-M2/CADM1-M MAL-M1/MAL-M2/CADM1-M MAL-M2/CADM1-M MAL-M2/CADM-M12/CADM1-M MAL-M2/CADM1-M Extra* CIN3 samples and cut-off based on 99% CI normals was used CIN3+samples and cut-off based on ROC curve was used CIN3 samples and cut-off based on 99% CI normals was used * The HSIL group consisted of CIN2/3 and no cut-off was used, unless otherwise specified. In the combination of genes any one of the genes was methylated. ** Different combination of hsa-mir-123-1/2/3 were tested, results of highest sensitivity and specificity are shown in this table. 36

18 Diagnostic value of methylation markers Discussion Our systematic review shows that methylation analysis of 6 genes (EPB41L3, JAM3, HS3ST2, NKX6-1, SOX9 and ZNF582) used as a primary screening test in cervical scrapings allows discriminating between normal/lsil and HSIL lesions with relatively high sensitivity (49%-93%) and high specificity (67%-100%). In addition our review indicated that methylation analysis of 4 genes (PAX1, CCNA1, EPB41L3, and JAM3) used as a primary screening test allows discrimination between normal/lsil and carcinoma scrapings with consistently high sensitivity (72%-100%) and specificity (82%-100%) across different studies. For methylation markers analyzed as a triage test in hrhpv positive scrapings, 6 genes (DKK3, SFRP2, MAL, CADM1, EPB41L3 and JAM3) showed relatively high sensitivity (53%-87%) for detection of HSIL with combined high specificity (88%-100%). However, in this group especially high sensitivity for detecting CIN3+ lesions was found, while the sensitivity of CIN2+ lesions was much lower. 2 For this review we systematically analyzed studies that compared different methylation markers in cervical scrapings by (Q)MSP. For population-based screening, cervical scrapings are collected for diagnostic analysis, which stresses the fact that this material should also be used for the diagnostic evaluation of new methylation markers. For the same genes a wide range of methylation frequencies is reported in different studies, which can be due to a variety of reasons i.e. use of different primers and/or probes for the same gene, use of any or different cut-off values (e.g. set above the highest positive normal to retrieve a high specificity or based on ROC curves), the number of PCR cycles used and a different composition of the patient groups. Sample size of the study also seems to be important, as studies that used a relatively small number of samples often showed better results in terms of high sensitivity and specificity. For example, when using methylation as a primary screening test to discriminate between normal/lsil and HSIL scrapings DAPK1, MGMT, EPB41L3 and JAM3 were described in different studies and all showed the best result in those studies that used a relatively small number of scrapings (n<40). This implies that the number and probably also selection of scrapings used for analysis has great influence on the sensitivity and specificity results of the test and this should be taken into account when interpreting studies on new methylation markers. The composition of the HSIL group is also of great importance, since methylation levels often increase with the severity and duration of CIN disease 46. The composition of the HSIL group varied greatly between the different studies: some studies included CIN2 and CIN3 into the HSIL group, while others used only CIN3 scrapings and some studies also included carcinoma scrapings. It can be expected that markers perform better if CIN3+ scrapings (including carcinomas) are analyzed compared to only CIN2/3 scrapings. Most 37

19 Chapter 2 studies did not use population-based scrapings but hospital-based scrapings, for example from a bio-bank, and included more CIN3 lesions then can be expected in a population-based cohort. The diagnostic performance of methylation markers might be over- or underestimated by testing them in a selected population. In order to truly evaluate the diagnostic value of any biomarker one should first define for which diagnostic purpose the biomarker is meant, which consequently also determines in what kind of patient population the biomarker should be evaluated. Evaluation of methylation markers as triage tool can be performed in hospital-based populations of consecutive patients referred for either an abnormal Pap smear or HPV positive test from population-based screening. In contrast, evaluation of methylation markers as tools for primary screening should ultimately performed in unselected women invited for population-based screening, as has been performed for HPV screening 13. Studies in selected hospital populations should only be regarded as pilot-studies that will guide the choice for which markers should be further tested. The use of different cut-off values to differentiate between women without abnormalities and women with HSIL lesions may also result in different sensitivity and specificity results. Cut-off values are often used to improve the specificity results of the methylation marker test, which explains the high specificity results found for some markers. Implementation of a cut-off value might be feasible, but only when there are large differences in methylation levels between the normal/lsil compared to the HSIL+ group. If a cut-off value needs to be set, this should be based on a large cohort, and subsequently tested in multiple independent cohorts. Preferably, no cut-off value should be set; if there is no amplification of a specific product, the sample is called negative and any methylation ratio above zero makes the sample positive, thereby making the methylation analysis an objective and easy to interpret test. Furthermore, to guarantee reliable results each sample should be tested in duplicate or triplicate. Because of the diversity found in methylation frequencies of the same genes across different studies, the results of markers that were analyzed only once per sample should be carefully interpreted. Methylation markers have been tested as primary screening marker in various studies. However, since in several countries including the Netherlands, national population-based screening programs will change from primary cytological screening to primary hrhpv screening in the near future, also triage testing with methylation markers is of high interest. Different triage strategies have been described in hrhpv positive women, to prevent unnecessary referral to the gynecologist 41,42. Triage testing of hrhpv positive women by cytology ( ASCUS) showed sensitivities between 48-63% and specificities between 81-99% 41,42,47. Although awareness of a positive hrhpv test may affect the interpretation of cytology and alter the specificity of this test, this has not been taken into account in many of the studies performed. Triage testing with immunohistochemical staining for p16in- 38

20 Diagnostic value of methylation markers K4a has also been described; the sensitivity for detecting HSIL was around 77% with a specificity of 61% 48,49. The disadvantage of this immunohistochemical triage test is that it requires the use of a well-fixed specimen with preserved morphology and a skilled cytotechnician. Triage testing by HPV 16/18 genotyping showed a sensitivity for HSIL of 65% with a corresponding specificity of 73% 41. All methylation markers tested so far as triage test in hrhpv positive women showed high specificity (88%-100%) and for DKK3, SFRP2, MAL, CADM1, EPB41L3 and JAM3 the reported sensitivity is also higher than for the above mentioned triage test strategies. By repeating triage testing of hrhpv positive women after 6 or 12 months with cytology, the sensitivity for HSIL of cytology as a triage test improved 41,47. However, immediate triage strategies for hrhpv positive women are preferred to prevent loss to follow-up. Studies describing methylation markers as a triage test in hrhpv positive women are limited. In this review 9 studies were included, but none of the reported genes were described in more than two studies. 2 In addition to hrhpv screening on routine cervical scrapings, self-sampling devices have been implicated for the collection of cervical cells to improve the participation rate. Many studies have shown that hrhpv testing on self-sampled specimens is feasible 50. Triage testing of hrhpv positive women directly on self-sampled material is not reliable for cytomorphological assessment or p16ink4a immunohistochemical staining. These methods require a well-fixed specimen with preserved morphology. In self-sampled specimens morphology is not intact, and the specimen contains many cells (e.g. vaginal cells and leukocytes) other than cervical cells. Recently, three studies showed that detection of DNA methylation in self-sampled specimens is feasible and that for the genes C13ORF18, JAM3, EPB41L3 and TERT high concordance between the cervical scraping taken by the physician and the self-sampled specimen was found 29,51. A recently published randomized controlled non-inferiority trial compared triage testing by methylation markers versus cytology in women who tested HPV-positive on self-sampled specimens 52. DNA methylation analysis of MAL (primer set M1) and mir-124 (primer set 2) showed similar sensitivities for detecting CIN2+ lesions compared to cytology triage testing, leading to a shorter time to CIN2+ diagnosis. However, the referral rate was higher in the methylation triage group, because of a lower positive predictive value (PPV) of the methylation test compared to cytology. Many techniques are now available to identify new methylation markers, e.g. pharmacologic unmasking of hypermethylated silenced genes combined with microarray expression analysis, methyl-dna immunoprecipitation (MeDIP) or immunoprecipitation using methyl-binding proteins (MBD) followed by either microarray analysis or next-generation sequencing. Identification of new methylation markers to improve cervical cancer screening is the initial step, but standardized validation of these markers is essential, as some genes show divergent results upon multiple testing. Therefore, validation of the same markers 39

21 Chapter 2 on several independent large (population-based) studies is warranted as also described by Pepe et al. 53. A five-phase framework has been proposed for biomarker validation in cervical cancer screening: Phase 1) Preclinical exploratory studies, comparing tumor tissue (or HSIL lesions) with healthy control tissue to identify genes or clusters of genes that appear to be differentially expressed in tumor tissue compared to control tissue. Phase 2) Clinical assay development, for clinical disease and assessment in non-invasive samples in selected subjects with known outcome. Phase 3) Retrospective longitudinal repository studies, for example from biobank-based case-control studies. Phase 4) Prospective screening studies and follow-up over time. Phase 5) Prospective intervention studies, with a population-based randomized trial that tests the new biomarker against the reference standard 54,55. As also reviewed by Steenbergen et al. 46 most methylation marker panels tested on cervical scrapings have so far only reached the early phases. Another important issue is reproducibility of the methylation markers tested. Most described markers are tested by the same research groups. To ensure high quality of the described methylation markers intra- and inter reproducibility of the most interesting markers should be analyzed. Furthermore, there is a need for a selection of the most interesting and reproducible methylation markers that should be tested in a large randomized controlled population-based study. Preferably cut-off values should be avoided, since establishing a cut-off value can only be based on very large cohorts. In addition, histologically confirmed results should always be used as the reference standard for diagnosis resulting in true diagnostic markers. To conclude, in this review we summarized the results of studies analyzing methylation markers in cervical scrapings by (Q)MSP. Although many genes seem promising for future primary screening, confirmation of the results are needed in large population-based studies. Furthermore, we showed that implementation of methylation analyses as a triage test in hrhpv positive women is on the brink of implementation. Although only 9 studies were included, the results show that for triage testing with methylation markers already higher sensitivity and specificity results could be obtained compared to cytological assessment, p16ink4a staining or HPV16/18 genotyping 41,42, However, as illustrated in this systematic review, results are variable and based on a relative small number of studies and/ or subjects. 40

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