Clinical performance of methylation as a biomarker for cervical carcinoma in situ and cancer diagnosis: A worldwide study

The shift towards primary human papillomavirus (HPV)‐based screening has necessitated the search for a secondary triage test that provides sufficient sensitivity to detect high‐grade cervical intraepithelial neoplasia (CIN) and cancer, but also brings an improved specificity to avoid unnecessary clinical work and colposcopy referrals. We evaluated the performance of the previously described DNA‐methylation test (S5) in detecting CIN3 and cancers from diverse geographic settings in high‐, medium‐ and low‐income countries, using the cut‐off of 0.80 and exploratory cut‐offs of 2.62 and 3.70. Assays were performed using exfoliated cervical specimens (n = 808) and formalin‐fixed biopsies (n = 166) from women diagnosed with cytology‐negative results (n = 220), CIN3 (n = 204) and cancer stages I (n = 245), II (n = 249), III (n = 28) and IV (n = 22). Methylation increased proportionally with disease severity (Cuzick test for trend, P < .0001). S5 accurately separated women with negative‐histology from CIN3 or cancer (P < .0001). At the 0.80 cut‐off, 543/544 cancers were correctly identified as S5 positive (99.81%). At cut‐off 3.70, S5 showed a sensitivity of 95.77% with improved specificity. The S5 odds ratios of women negative for cervical disease vs CIN3+ were significantly higher than for HPV16/18 genotyping at all cut‐offs (all P < .0001). At S5 cut‐off 0.80, 96.15% of consistently high‐risk human papillomavirus (hrHPV)‐negative cancers (tested with multiple hrHPV‐genotyping assay) were positive by S5. These cancers may have been missed in current primary hrHPV‐screening programmes. The S5 test can accurately detect CIN3 and malignancy irrespective of geographic context and setting. The test can be used as a screening and triage tool. Adjustment of the S5 cut‐off can be performed considering the relative importance given to sensitivity vs specificity.


| INTRODUCTION
The implementation of cervical cancer prevention programmes by systematic cytology screening 1 has contributed to a reduction in cervical cancer-associated deaths in high-income countries. 2 Yet, cervical cancer is currently the fourth most common cancer in women and continues to increase worldwide, with 604 000 cases in 2020, accounting for 7.5% of all female cancer deaths. 3 To allow a further reduction in the incidence of cervical cancer, screening has shifted towards highrisk human papillomavirus (hrHPV) testing with triage of HPV-positive women. Cervical cancer incidence, ranges from 5 to 50 per 100 000 women depending on setting and while hrHPV testing is highly sensitive for the detection of disease, specificity is less optimal given the benign trajectory of most infections. Triage generally relies on cytology as the preferred secondary test in HPV-positive women. 4 However, being subjective, cytology has limitations and objective secondary triage tests are urgently needed to identify the minority of hrHPV-positive women with high-grade disease. 4 Furthermore, triage tests that rely on molecular rather than morphological signatures (such as cytology) remove the requirement for specialised expertise.
Methylation biomarkers can offer an accurate alternative to detect clinically significant infection and associated disease and can identify women who have the highest risk of progressing into invasive cervical cancer. 5,6 Aberrant DNA methylation has been reported to increase with cervical cancer disease progression, 7 allowing this epigenetic event to be used as a temporal biomarker, with a potential to accurately predict whether hr-HPV infection will lead to cervical intraepithelial neoplasia grade 2 or above (CIN2+) or disappear. 5,8 Several methylation biomarkers tests including our S5 DNAmethylation classifier, which tests for methylation on the host tumour suppressor gene EPB41L3 and viral late genes (L1 and L2) of HPV16, HPV18, HPV31 and HPV33, can accurately separate women with CIN2/3 and cancer from those with CIN1 or normal cytology. 9 The S5-classifier has demonstrated improved triage performance compared to hrHPV genotyping, cytology or the combination thereof and has been validated in a HPV-positive cohort of women as part of the Canadian FOCAL clinical trial, in the FRIDA screening trial in Mexico and the Colombian ASC-US-COL trial. [10][11][12] Additionally, the S5-classifier demonstrated a potential prognostic utility, in its ability to identify women with progressive CIN2. 8 Together, these data support the prospect of using the S5-classifier as a molecular tool to identify clinically significant cervical abnormalities and predicting their clinical course.
Validation of the S5-classifier in a large number of CIN3+ samples from both high-income and low-and middle-income countries (LMICs) is required to demonstrate that the methylation test can consistently detect cervical cancers worldwide. Extensive validation of the S5 classifier will support implementation of the test in global screening and disease-management systems, especially with the rise in acceptance of screening based on self-sampling. 13,14 The main objective of the present study is to analyse the performance and consistency of S5 in detecting high-grade lesions and cervical cancers from diverse settings that reflect Asia, Europe, Africa and the Americas. The present study aims to complement previous works on the S5 DNA-methylation classifier. 6,9,11,12,15 2 | MATERIALS AND METHODS

| Study population
Cervical swabs and biopsies were collected from a total of 973 patients aged 21 to 64 as described in the referenced papers. [16][17][18][19][20][21][22] All samples included in the study were analysed by cytology or histology and had results of negative, CIN3 or invasive cervical cancer. We excluded CIN1 and CIN2 from our study because the CIN1 is a low-grade lesion and CIN2 is considered increasingly, a heterogenous lesion that does not serve as a robust histological indicator of high-grade disease. Our study focussed mainly on cervical cancer stages I and II in order to have a sharper view of the epigenetic contrast between CIN3 vs early cancer and to complement previously published data on S5 performance.
Details regarding patient characteristics are described in Table 1.  and viral late genes (L1 and L2) of HPV16, HPV18, HPV31 and HPV33 as previously described. 9 Percentage methylation was taken as the mean for CpG sites involved in each case.

| HPV genotyping
The clinical samples used in the study have been initially genotyped as part of previously approved research studies. The following technologies were used: GP5+/6+ PCR assay (n = 641), 17

| Statistical analysis
We validated the performance sensitivity of the S5 classifier on CIN3 The main groups being compared were HPV negative cytology negative: We compared differences in methylation levels between groups using Kruskal-Wallis and Dunn's multiple comparison tests and the Cuzick test for trend to assess any methylation trend with disease progression. We evaluated the S5 diagnostic potential using the predefined cut-off of 0.80. In addition, we explored cut-off points more suited for LMIC, using a previously defined alternative cut-off and Youden-J index. 12 McNemar's test with continuity correction was used for differences in sensitivity and specificity.
We also used unconditional logistic regression to study the relationship between methylation in the invasive cervical cancer group and the covariatesstage of cancer, type, age, demographics and HPV status.
Additionally, we calculated the odds ratios (ORs) for the associations between HPV16/18 positivity, S5 classifier positivity at different cut-offs and CIN3 or cervical cancer (CSI-IV, FIGO stage unknown included) diagnosis. All P values were two-sided with α ≤ .05 considered significant.
Analysis was performed with GraphPad Prism v8.0 as well as R v 3.4.1 for Cuzick tests, ORs and for unconditional logistic regression analyses.

| Characteristics and selection criteria
We present a cross-sectional retrospective study including 973 women from 10 countries to evaluate the S5 methylation classifier performance to detect CIN3 and cervical cancer. The present study aims to complement previous work on the S5 DNA-methylation classifier. 6,9,11,12,15 We selected 220 women cytology negative or HPV(À/+)/Cyt(À), 204 women diagnosed with CIN3 and 544 with invasive cervical cancer as described in Figure 1. Baseline characteristics of the women are presented in Table 1.

| Increasing trend in the S5 methylation scores with disease severity
The S5 methylation scores were clustered according to severity of cervical abnormality. An outline of the methylation scores per country is provided in Figure S2.  3.5 | S5 classifier cut-off adjusted per country to optimise triage capacity   Although we observed a significant decrease in false positive rate with the increase of the cut-off, a similar but less pronounced decrease trend was observed in S5 positivity for CIN3 and cancer detection. 3.6 | Diagnostic potential of S5 classifier compared to HPV16/18 testing methylation showed a linear increase with disease progression (Cuzick test for trend, both, P < .01) as described in Figure S3.
The weight of each component of the S5-classifier was plotted for HPV(+)Cyt(À), CIN3 and the cancer CSI-IV groups in Figure 3.

| DISCUSSION
To our knowledge, our study represents one of the most comprehensive assessments of viral and host cell DNA methylation data in invasive cervical cancer to date, particularly given its multi-site dimension(s) and number of cases of high grade and invasive disease. 27    A limitation to our study is that all CIN3 and cervical cancer cases come from referral populations and do not accurately represent those that may be apparent in the screening population or those that do not present to clinics. The proportion of rare histological subtypes in our study was also small, so this element would benefit from further investigation. Moreover, much more emphasis was placed on cancers FIGO stage I and II as previously published data indicate that aberrant methylation is an early event in cervical carcinogenesis. 14,29 An intentional limitation of our study is that we excluded CIN1 and CIN2 which would be present in a real-world setting. Addition of these samples to our study in realistic proportions would likely lower the sensitivity and specificity of the S5 test. There is a further limitation in our selection of the cytology negative women who were presumed to have no disease on the basis of cytological testing. Although we divided these women into HPV+ and HPVÀ groups, these women may not be representative of the routine screening populations in many geographic locations including in Europe and the United States.
Therefore, the aim of our present work was to assess a larger panel of CIN3+ samples to confirm the sensitivity and robustness of the assay for the detection of significant disease.
The present findings highlight the major contribution of host EPB41L3 methylation in the S5 score. We showed that the relationship between EPB41L3 methylation was approximatively 4.5 times stronger for severity of lesion than age (P < .0001). This indicates that host EPB41L3 methylation might have a strong potential to predict disease progression, independent of increasing natural epigenetic methylation levels occurring with age. This is in line with previously published data on the S5 where it better identified women with CIN2 that were more likely to progress to higher stages of the disease. 8 Additionally, the weight of EPB41L3 methylation shows an increasing trend (P < .0001, Cuzick test for trend), up to cervical cancer FIGO stage II, where it plateaus. However, the strength of this observation is limited by the decreased number of cervical cancer samples of FIGO stage III and IV, included in the study.
The COVID-19 pandemic points towards a shift to self-sampling for hrHPV primary screening to reduce the burdens on the healthcare professionals and access women who do not respond to screening invitations. Having the possibility to triage hrHPV-positive women from the same self-collected specimen would bring many advantages including a reduction in logistical issues associated to systematic screening as well as reducing the subjectivity of cytology. [30][31][32][33][34] A pilot study tested the accuracy of S5 classifier in cervical self-samples. S5 showed a statistically significant separation between <CIN2 and CIN2 + samples for both urine and cervical self-samples (P ≤ .0001). At the pre-defined cut-off of 0.80, the sensitivity for cervical self-samples was 71% and specificity 68% and for urine samples was 66% and specificity 72%. 33 In conclusion, our study shows that the S5 classifier at a cut-off of 0.80 identifies more than 90% CIN3 cases and almost 100% of cervical cancers, independent of histology, FIGO stage hrHPV status, hrHPV genotype, sample type and geographical origin. Adjustment of the cut-off leads to an increase in specificity with only a small decrease in sensitivity. The 3.70 cut-off could allow for a better triage modality for LIMC where screening is not performed as systematically as in higher income countries. Additionally, high methylation levels on the host gene component of the S5 classifier, EPB41L3 is associated with higher severity of the disease, indicating prognostic potential. Thus, considering the growing acceptability of self-sampling, our results support the utility of the S5 classifier as a credible tool for enhanced risk stratification of women in cancer screening programmes.