Performance of ASLC1/LHX8 DNA methylation and extended HPV genotyping in first-void urine for high-grade cervical intraepithelial neoplasia detection in an HPV-positive referral population - a cross-sectional study

Performance of ASLC1/LHX8 DNA methylation and extended HPV genotyping in first-void urine for high-grade cervical intraepithelial neoplasia detection in an HPV-positive referral population - a cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Performance of ASLC1/LHX8 DNA methylation and extended HPV genotyping in first-void urine for high-grade cervical intraepithelial neoplasia detection in an HPV-positive referral population - a cross-sectional study mette tranberg, Severien Van Keer, Albertus T Hesselink, Pia Nørgaard, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8249226/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Apr, 2026 Read the published version in BMC Medicine → Version 1 posted 13 You are reading this latest preprint version Abstract Background: First-void urine (FVU) collection for high-risk human papillomavirus (HPV) testing is a promising tool to reach un(der)-screened women in cervical cancer screening programs. This cross-sectional study investigated the clinical performance of host-cell DNA methylation markers ASCL1 and LHX8 in HPV-positive FVU to detect high-grade cervical intraepithelial neoplasia and cancer (CIN2+ and CIN3+). Secondly, comparative analysis to paired HPV-positive clinician-collected cervical samples (CS) and HPV genotyping was examined. Methods: Paired FVU and CS samples were collected from 286 women aged 23-64 years referred for colposcopy or cervical excision. Histological endpoints included 123 ≤CIN1 (no dysplasia and CIN1), 38 CIN2, and 123 CIN3/AIS and 2 cancers. FVU and CS were tested for HPV DNA and ASCL1 / LHX8 methylation. Methylation test performance was evaluated by area under the curve (AUC) and logistic regression analysis. Accuracy differences between paired samples and across methylation, HPV16/18, and extended 16/18/31/33/52 genotyping testing in FVU were tested using McNemar’s test. Results: ASCL1 and LHX8 methylation levels in HPV-positive FVU increased significantly with disease severity. Methylation testing yielded an AUC of 0.76 (95% CI: 0.70-0.82) for CIN3+ and 0.73 (95% CI: 0.67-0.79) for CIN2+, with corresponding sensitivities of 79.2% (95% CI: 71.0-85.9%) and 75.5% (95% CI: 68.1-81.9%) and a specificity of 57.0% (95% CI: 47.8-65.8%) for ≤CIN1. In CS, methylation testing yielded an AUC of 0.84 (95% CI: 0.79-0.89) for CIN3+ and 0.80 (95% CI: 0.75-0.85) for CIN2+, corresponding to significantly higher sensitivities (p≤0.02) but lower specificity (p=0.04) compared to FVU. In women aged ≥30 years, CIN3+ sensitivity and specificity for ≤CIN1 were similar between FVU and CS (both p=0.09). Methylation testing in HPV-positive FVU had similar diagnostic accuracy as extended genotyping (p≥0.35), but had a higher sensitivity (p=0.01) and a lower specificity (p=0.01) than HPV16/18 genotyping. Conclusions: ASCL1/LHX8 methylation testing in HPV-positive FVU showed promise for detecting high-grade cervical disease. ASCL1/LHX8 methylation performance in FVU was similar to extended HPV genotyping and, in women aged ≥30 years, similar to performance in CS. This supports the potential of methylation analysis as a direct and single triage test in urine-based cervical cancer screening, removing the need for follow-up cervical sampling. Trial registration: Clinicaltrials.gov: NCT05065853 DNA methylation cervical cancer screening HPV DNA testing urinary HPV testing early detection of cancer/methods Figures Figure 1 Figure 2 Background With the shift from cytology-based to the more sensitive high-risk human papillomavirus (HPV)-based cervical cancer screening, several countries have adopted HPV vaginal self-sampling in routine screening to improve coverage among un(der)-screened women who have the highest cancer risk 1 – 3 . However, translating the benefits of vaginal self-sampling into real-world settings has proven surprisingly difficult 4 . Therefore, urinary HPV testing, particulary using first-void urine (FVU), for early detection of high-grade cervical intraepithelial neoplasia and cancer (CIN2 + and CIN3+) has been suggested as a promising, accurate, non-invasive, and easier-to-use screening option 5 – 7 . Primary HPV screening requires triage testing to distinguish HPV-positive women with clinically relevant disease from those with irrelevant, transient HPV infections 8 . Since cytology, the most evidenced triage tool, is not applicable to urine samples, women testing HPV-positive on a FVU sample would require recall for clinician-based cervical sampling for onward referral 9 . This approach risks loss to follow-up and delays in diagnosis 10 . In contrast, HPV genotyping and DNA methylation testing can be performed directly on FVU samples 11 . Each high-risk HPV genotype has varying oncogenic potential 12 – 14 and genotyping provides insight into a woman’s individual risk of developing CIN2+. A disadvantage of HPV genotyping is that it cannot differentiate between transient and persistent infections associated with the development of CIN2 + 11 . DNA hypermethylation in the promoter regions of human tumor suppressor genes is a frequent molecular epigenetic change during the early stages of (cervical) carcinogenesis 15 . Detection of hypermethylated host-cell DNA in FVU is biologically explained by the local shedding of cervical (pre)cancerous cells into genital secretions that are subsequently excreted in the urine 16 . In the presence of cancer, detection of hypermethylated DNA may also result from transrenal excretion of tumor-related circulating cell-free DNA fragments 17 . DNA methylation levels have been demonstrated to increase with CIN severity, peaking in cervical cancer across both clinician-collected cervical samples (CS) and self-collected samples (vaginal and urine) 18 – 22 . Accordingly, methylation testing has been proposed as a tool to predict disease development or progression in HPV-positive women 23 , 24 . Furthermore, as nearly all cervical cancers are methylation-positive (98.3%), a negative methylation result is suggested to effectively rule out cancer in HPV-positive women 25 , 26 . Following feasibility studies on the DNA methylation status of host-cell and/or viral genes in urine, including FVU 27 – 31 , two prospective studies revealed promising results of the host-cell ASCL1/LHX8 bi-marker panel in urine samples for the detection of CIN3 and cervical cancer 32 Van Keer (in revision) . While good triage performance of ASCL1/LHX8 methylation testing in HPV-positive vaginal self-samples and CS has been shown 33 – 36 , data on its performance in HPV-positive FVU either or not combined with partial genotyping for HPV16/18 and extended HPV genotyping is sparse. In an HPV-positive referral population, this study investigated the clinical performance of the ASCL1/LHX8 methylation test (PreCursor-M Gold, Self-screen BV, Amsterdam, The Netherlands) for CIN2+/CIN3 + detection in HPV-positive FVU and paired HPV-positive CS. Additionally, methylation test performance was compared to HPV16/18 and extended HPV genotyping to detect high-grade cervical disease in HPV-positive FVU samples. Methods Setting and study design and population In Denmark, women aged 23–64 are invited for cervical cancer screening at their general practitioner with vaginal self-sampling offered to non-attenders. This cross-sectional study included 325 women aged 23–64 years scheduled for 1) colposcopy (due to abnormal cervical cancer screening result or post-coital bleeding or 2) large loop excision of the transformation zone (LLETZ) at public colposcopy clinics in Randers, Horsens, and Gødstrup Hospitals, Central Denmark Region from October 2021 to February 2023 as previously described 5 . Women provided paired FVU and clinician-collected CS for HPV DNA testing followed by a histological reference test (cervical biopsies or LLETZ) for disease verification. Of note, in Denmark, all women referred for colposcopy have a minimum of four cervical biopsies collected, irrespective of the colposcopic impression 37 . After sampling, women completed a short questionnaire on sampling acceptability and HPV vaccination status (vaccinated/unvaccinated) 5 . Women were included if they tested HPV DNA positive in the FVU and/or CS and had DNA methylation analysis performed at the Dept. of Pathology, Randers Regional Hospital, Central Denmark Region. Sample collection, storage, HPV DNA testing, and histological outcomes After obtaining informed consent, the women collected a FVU sample in the clinics using the 10 mL Colli-Pee device (Novosanis Colli-Pee® Small Volumes UCM FV-5010, N00327, part of the Orasure Technologies, Inc. Group, Pennsylvania, USA). The Colli-Pee device collects approximately 7 mL of the FVU, whilst immediately mixing the urine with a DNA preservative (UCM, DNA Genotek, Ottawa, Canada), reaching a total volume of 10 mL. Before colposcopy or LLETZ, the clinician collected a CS using a Cervex-Brush Combi (Rovers Medical Devices, Oss, The Netherlands) which was directly rinsed in 20 mL Thinprep PreservCyt medium (Hologic, Inc., Bedford, Massachusetts, USA) 5 . Upon arrival in the laboratory, the FVU samples and the ThinPrep PreservCyt vial with the cervical cells were vortexed for 20 seconds and subsequently stored at 4°C for maximum 24 hours before being aliquoted into secondary tubes (2 mL for HPV analysis and 4 mL for methylation analysis) 5 . Afterwards, the aliquots were stored at -80°C until HPV and DNA methylation testing. For both samples (200 µL), DNA extraction was performed using STARMag Universal Cartridge kit on the STARLET IVD platform (Hamilton, USA) followed by PCR amplification on a CFX96™ real-time thermocycler (Bio-Rad, USA) according to the manufacturer’s instructions. HPV DNA testing was performed using the real-time PCR-based Allplex HR HPV detection assay (Seegene, Korea) which detects 14 individual HPV types: HPV16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, and 68 38 . For both CS and FVU, we used the manufacturer’s predefined absolute threshold for HPV positivity in cervical samples (all HPV genotypes: Ct ≤ 43) 5 . Histological results were reported using the CIN classification 39 and grouped as ≤ CIN1 (normal including inflammation and non-specific reactive features, and CIN1), CIN2+ (CIN2, CIN3, adenocarcinoma in situ (AIS), and cancer), and CIN3+ (CIN3, AIS, and cancer). Histological results were obtained from the Danish Pathology Databank 40 . DNA extraction and ASCL1/LHX8 methylation analysis The FVU and CS aliquots were thawed overnight at 4°C before the methylation analysis. On the day of the methylation analysis, the FVU sediment was obtained by centrifugation of 4 mL FVU at 3,000xg for 15 minutes while the cervical sediment was obtained by centrifugation of 4 mL Thinprep vial at 3,400xg for 10 minutes. DNA was extracted from FVU sediment using the Quick-DNA Urine kit (Zymo Research, Irvine, CA, USA) and from CS sediment using QIAamp DNA mini kit (Qiagen, Hilden, Germany). DNA concentration measurements were performed using the Qubit fluorometer (ThermoFischer Scientific, Waltham, MA, USA). Extracted DNA (200 ng) was bisulphite converted using the EZ DNA Methylation-Lightning Kit (D5030, Zymo Research, Irvine, CA, USA). All procedures were performed according to the instructions of the manufacturers. Bisulphite-converted DNA (5.0 uL) was subsequently used as input for the quantitative methylation specific PCR (qMSP) analysis of the genes ASCL1 and LHX8 using the PreCursor-M Gold Assay (RUO) (Self-screen BV, Amsterdam, The Netherlands), which also included the ACTB reference gene for quantification and quality control. DNA methylation testing was performed on the Rotor-Gene Q MDx 5plex HRM instrument (QIAGEN, Hilden, Germany) by laboratory technicians blinded for all study outcomes. The quantification cycle (Cq) values were measured at fixed thresholds for fluorescence. The methylation levels of ASCL1 and LHX8 (i.e. Cq ratios) were calculated by comparing the target Cq values to the Cq values of ACTB (2 –ΔCq x 100) 41 . A Cq threshold of ≤ 28 for ACTB indicated sufficient DNA, DNA quality, and adequate bisulphite conversion. Invalid samples were retested once, and the second result was defined definitive. Neither the methylation nor the extended genotyping results had an influence on the clinical management. Statistical analysis Age was summarized using medians and interquartile ranges (IQR) with group differences tested via the Mann-Whitney U-test. All statistical analyses and visualizations were conducted on log2-transformed ΔCq ratios for the individual methylation markers ASCL1 , LHX8 and predicted probabilities for the ASCL1/LHX8 marker panel. Differences in DNA methylation levels across cervical disease categories were presented by boxplots and assessed using the Kruskal-Wallis test. In both sample types, post-hoc pairwise comparisons of DNA methylation levels between controls (≤ CIN1), CIN2, CIN3/AIS, and cancer as well as between CIN2 and CIN3/AIS were performed using the Mann-Whitney U-test with Bonferroni correction for four simultaneous comparisons (α = 0.0125). The log2-transformed ΔCq ratios for the methylation markers were incorporated into a predefined logistic regression model for FVU developed by Van Keer et al (in revision), based on healthy controls and a referral population, including cancer patients. This model estimated predicted probabilities (ranging from 0 to 1) representing the likelihood of CIN3 + given the DNA methylation outcome of a sample. Model development excluded CIN2 due to the heterogenous nature of this morphological diagnosis 42 . Predicted probabilities were used to construct Receiver Operating Characteristic (ROC) curves and the discriminative performance was quantified by Area Under the Curve (AUC) including 95% confidence intervals (CIs). Discriminative performance was interpreted using Hosmer and Lemeshow thresholds: Acceptable (0.7 ≤ AUC < 0.8); excellent (0.8 ≤ AUC < 0.9); and outstanding (AUC ≥ 0.9) 43 . Predicted probabilities were also used to calculate detection rates, sensitivities for CIN3 + and CIN2+, and specificity for ≤ CIN1, along with 95% CIs and stratification by age group and referral status. Main analyses applied predefined methylation positivity thresholds set at 70% specificity for ≤ CIN1 established by Van Keer et al (in revision) for FVU and Griffioen et al for CS (submitted). Supplementary analyses used thresholds targeting 80% specificity for ≤ CIN1, also predefined by Van Keer et al (in revision) and Griffioen et al (submitted). Performance differences between paired samples were tested using the McNemar (McN) test and unpaired proportions were compared using a two-sample proportion test. In HPV-positive FVU samples, performance for detecting CIN3+, CIN2+, and ≤ CIN1 was evaluated using five strategies: (1) ASCL1/LHX8 methylation test; (2) HPV16/18 genotyping; (3) extended HPV genotyping (HPV16/18/31/33/52) 44 ; (4) combined HPV16/18 genotyping with ASCL1/LHX8 methylation test; and (5) combined extended genotyping with ASCL1/LHX8 methylation test. Data was stored and entered in REDCap 45 and all statistical analyses were performed in STATA version 18. Unless otherwise stated, statistical significance was defined as P < 0.05. Results Study population The study population consisted of 286 women referred for colposcopy or LLETZ who had a positive HPV test result on their FVU sample (Table 1 ). The median age was 35 years (IQR: 29–45 years) and the study population included 123 controls (≤ CIN1) and 163 cases (CIN2+). 114 out of 286 women (39.9%) reported to be HPV vaccinated (data not tabulated). No differences in median age (p = 0.28) and self-reported HPV vaccination status (p = 0.46) were seen between controls and cases. Referral for LLETZ was significantly higher among cases compared to controls (61.4% vs 8.1%, p < 0.01). Among the 125 CIN3 + cases, 64.8% (n = 81/125) were referred for LLETZ and 35.2% (n = 44/125) for colposcopy (data not tabulated). The majority of women testing HPV-positive on FVU were also HPV positive on their paired CS (n = 264, 92.3%). Twenty-two discordant cases, HPV positive only in FVU and negative in CS, were excluded from the paired comparison (four CIN3 and 18 controls (14 no dysplasia and four CIN1)). All HPV-positive samples were tested for the DNA methylation markers ( ASCL1 and LHX8 ), with all FVU and CS valid for the qMSP. Table 1 Characteristics of study population Total study population (n = 286) Controls (≤ CIN1) n = 123 Cases (CIN2+) n = 163 p-value Median age at time of inclusion , years (IQR) 35 (29–45) 34 (26–48) 36 (30–45) 0.28 Age groups n (%) 23–29 128 (44.8) 60 (48.8) 68 (41.7) 0.16 30–36 80 (28.0) 26 (21.4) 54 (33.1) 37–43 47 (16.4) 23 (18.7) 24 (14.7) 44–64 31 (10.8) 14 (11.4) 17 (10.4) Referred for colposcopy or LLETZ n (%) Colposcopy 176 (61.5) 113 (91.9) 63 (38.7) 0.001 LLETZ 110 (38.5) 10 (8.1) 100 (61.4) Histology results No dysplasia 65 (22.7) - CIN1 58 (20.3) CIN2 38 (13.3) CIN3 112 (39.2) AIS 11 (3.9) Cervical cancer 2 (0.7) LLETZ: Large Loop Excision of the Transformation Zone. IQR: interquartile range, n: number, % (column percentage). CIN: Cervical Intraepithelial Neoplasia, grade 1 to 3, AIS: Adenocarcinoma in situ. Controls (women with no dysplasia or CIN grade 1). Cases: CIN2, CIN3, AIS, and cancer. DNA methylation analysis in first-void urine For all HPV-positive FVU (n = 286), both markers showed a significant increase in DNA methylation levels with increasing cervical disease severity (p < 0.001) (Fig. 1 ). Compared to controls (≤ CIN1), both DNA methylation markers ( ASCL1 and LHX8 ), were significantly increased in cervical cancer and CIN3/AIS (p < 0.001) as well as CIN2 compared to CIN3/AIS (p-values: 0.005–0.007). ASCL1 was also significantly increased in CIN2 compared to controls (p = 0.006). The ability of the ASCL1/LHX8 methylation test to discern CIN3+ (n = 125) and CIN2+ (n = 163) from controls (n = 123) in HPV-positive FVU samples resulted in AUCs of 0.76 (95% CI: 0.70–0.82) and 0.73 (95% CI: 0.67–0.79), respectively (Fig. 2 ). At the predefined test threshold of 70% specificity (Van Keer et al), sensitivities of 79.2% (95% CI: 71.0-85.9%) for CIN3 + and 75.5% (95% CI: 68.1–81.9%) for CIN2 + with corresponding specificity of 57.0% (95% CI: 47.8–65.8%) for ≤ CIN1 were obtained (Table 2 ). Sensitivities for detecting CIN3 + and CIN2 + in the stratified analyses by age and referral status were comparable to the main analysis, while specificity in women aged ≥ 30 was significantly lower (42.5% vs 57.0%, p = 0.04) (Table S2 supplementary table). The performance data of the ASCL1/LHX8 methylation test using a predefined 80% specificity threshold are reported in Table S2 , supplementary table. Table 2 Clinical performance of the ASCL1/LHX8 methylation test in HPV-positive first-void urine samples (n = 286). ASCL1/LHX8 methylation n/N % (95% CI) CIN3 + sensitivity 99/125 79.2 (71.0-85.9) CIN2 + sensitivity 123/163 75.5 (68.1–81.9) ≤CIN1 specificity 70/123 57.0 (47.8–65.8) Detection rate ASCL1/LHX8 positive* n (%) ASCL1/LHX8 negative n (%) Cervical cancer (n = 2) 2 (100) - CIN3/AIS (n = 123) 97 (78.9) 26 (21.1) CIN2 (n = 38) 24 (63.2) 14 (36.8) Controls (≤ CIN1) (n = 123) 53 (43.1) 70 (56.9) CIN: Cervical Intraepithelial Neoplasia (CIN), grade 1 to 3; Controls: women with no dysplasia or CIN grade 1 (≤ CIN1), CIN2: CIN grade 2, CIN3: CIN grade 3, AIS: adenocarcinoma in situ. CIN3+: CIN3, AIS, and cancer. CIN2+: CIN2, CIN3, AIS, and Cancer. n/N: CIN3 + sensitivity: True positive/total CIN3 + cases, CIN2 + sensitivity: True positive/total CIN2 + cases, ≤CIN1 specificity: True negative/total ≤ CIN1. *) ASCL1/LHX8 methylation positivity threshold in first-void urine was set at predefined 70% specificity for ≤ CIN1 (Van Keer et al., in revision). DNA methylation analysis in paired HPV-positive cervical samples Next, methylation performance in HPV-positive paired CS was determined (n = 264) and compared to FVU. In CS, the ASCL1 and LHX8 methylation levels increased significantly with disease severity (p < 0.001) (Figure S1 , supplementary figure). In CS, the ROC curves demonstrated AUCs of 0.84 (95% CI: 0.79–0.89) for CIN3 + vs controls and 0.80 (95% CI: 0.75–0.85) for CIN2 + vs controls for ASCL1/LHX8 methylation (Figure S3, A-B, supplementary figure). At a predefined threshold of 70% specificity (based on a screening population), CIN3 + and CIN2 + sensitivities of 88.4% and 86.2%, respectively were obtained at 45.7% specificity. Comparison of methylation results between first-void urine and cervical samples Median methylation levels of both markers were significantly higher in CS than in paired FVU across disease categories (p < 0.001) (Figure S2 , supplementary figure). AUCs were likewise higher in CS versus FVU (n = 264) for CIN3+ (0.84, 95% CI: 0.79–0.89 vs 0.75, 95% CI: 0.69–0.82) and CIN2+ (0.80, 95% CI: 0.75–0.85 vs 0.73, 95% CI:0.67–0.79) (Figure S3 A-D, supplementary figure). When applying the predefined test thresholds, the CIN3 + and CIN2 + sensitivities in CS were significantly higher compared to FVU (CIN3+: 88.4% vs 79.0%, p = 0.02 and CIN2+: 86.2% vs 74.8%, p < 0.01), while specificity was significantly higher in FVU compared to CS (59.0% vs 45.7%, p = 0.04). Both cancers were detected in all instances (Table 3 ). Among the 157 CIN2/CIN3 cases, concordant results were obtained for 125 (79,6%) cases, with 110 (70.0%) testing methylation positive in both sample types and 15 (10.0%) (seven CIN2 and eight CIN3) testing methylation negative in both sample types. Seven cases (4.4%) (one CIN2 and six CIN3) tested methylation negative on CS only and 25 cases (16.0%) (seven CIN2, 18 CIN3) tested methylation negative in FVU only (data not tabulated). In the stratified analyses, no differences in CIN3 + sensitivity was detected between samples in women aged ≥ 30 (81.0% vs 89.4, p = 0.09) and women referred for LLETZ (81.0% vs 87.3%, p = 0.30) (Table S3, supplementary table). The difference in specificity between samples became non-significant in the stratified analyses (p-values between 0.09–0.39). Performance data using a predefined 80% specificity threshold for the methylation analysis were reported in Table 3 S, supplementary table. Table 3 Comparison of clinical performance of the ASCL1/LHX8 methylation test in paired HPV-positive first-void urine and cervical samples (n = 264) First-void urine samples Cervical samples ASCL1/LHX8 methylation* ASCL1/LHX8 methylation # n/N % (95% CI) n/N % (95% CI) CIN3 + sensitivity 95/121 79.0 (70.1–85.5) 107/121 88.4 (81.3–93.5) CIN2 + sensitivity 119/159 74.8 (67.3–81.4) 137/159 86.2 (80.0–91.0) ≤CIN1 specificity 62/105 59.0 (49.0-68.5) 48/105 45.7 (36.0-55.7) Detection rate ASCL1/LHX8 positive* n (%) ASCL1/LHX8 negative n (%) ASCL1/LHX8 positive** n (%) ASCL1/LHX8 negative n (%) Cervical cancer (n = 2) 2 (100) - 2 (100) - CIN3/AIS (n = 119) 93 (78.2) 26 (22.0) 105 (88.2) 14 (11.8) CIN2 (n = 38) 24 (63.2) 14 (37.0) 30 (79.0) 8 (21.1) Controls (≤ CIN1) (n = 105) 43 41.0) 62 (59.0) 57 (54.3) 48 (45.7) CIN: cervical intraepithelial neoplasia, grade 1 to 3; Controls: women with no dysplasia or CIN grade 1 (≤ CIN1), CIN2: CIN grade 2, CIN3: CIN grade 3, AIS: adenocarcinoma in situ. CIN3+: CIN3, AIS, and cancer. CIN2+: CIN2, CIN3, AIS, and cancer. n/N: CIN3 + sensitivity: True positive/total CIN3 + cases. CIN2 + sensitivity: True positive/total CIN2 + cases. ≤CIN1 specificity: true negative/total ≤ CIN1. *) ASCL1/LHX8 methylation positivity threshold in first-void urine was set at predefined 70% specificity for ≤ CIN1 as defined by Van Keer et al (in revision). **) ASCL1/LHX8 methylation positivity threshold in cervical samples was set at predefined 70% specificity for ≤ CIN1 as defined by Griffioen et al (submitted). Methylation testing versus HPV-genotyping in HPV-positive first-void urine For all HPV-positive FVU (n = 286), the ASCL1/LHX8 methylation positivity did not differ across the HPV genotypes for controls (p-values: 0.21 to 0.90) and CIN2 cases (p-values: 0.15 to 0.86), while among women with CIN3 + a significant increase in methylation positivity was observed for HPV16/18 versus non-alpha-7/9 types (HPV51, 56, 66) (90.2% vs 70.3%, p = 0.02) (Figure S4, supplementary figure). Compared to HPV16/18 genotyping, methylation testing showed a significantly higher sensitivity for CIN3+ (40.8% vs 79.2%, p < 0.01) and CIN2+ (38.7% vs 75.5%, p < 0.01), but lower specificity (88.6% vs 57.0%, p < 0.01) (Table 4 ). When comparing to extended HPV genotyping, methylation testing had a virtually equal sensitivity for CIN3+ (73.6% vs 79.2%, p = 0.35) and CIN2+ (71.0% vs 75.5%, p = 0.35) and specificity for ≤ CIN1 (57.0% vs 59.3%, p = 0.80). The sensitivity of combined methylation testing and HPV16/18 genotyping was significantly higher as compared to HPV16/18 genotyping alone for CIN3+ (83.2% vs 40.8%, p < 0.01) and CIN2+ (80.0% vs 38.7%, p < 0.01) with significantly lower specificity (52.0% vs 88.6%, p < 0.01). Higher sensitivities for CIN3+ (92.8% vs 73.6%, p < 0.01) and CIN2+ (90.2% vs 71.0%, p < 0.01) with lower specificity (34.1% vs 59.3%, p < 0.01) were observed for combined methylation testing and extended HPV genotyping as compared to extended HPV genotyping alone. Similar observations occurred for the strategies when using a predefined 80% specificity threshold for the ASCL1/LHX8 marker panel (Table S4, supplementary table). Table 4 Performance of ASCL1/LHX8 methylation versus HPV genotyping testing in HPV-positive first void urine samples (n = 286) CIN3 + sensitivity CIN2 + sensitivity ≤CIN1 specificity Triage strategies n a % (95% CI) n b % (95% CI) n c % (95% CI) ASCL1/LHX8 * methylation 99/125 79.2 (71.0-85.9) 123/163 75.5 (68.1–81.9) 70/123 57.0 (48.0-65.8) HPV16/18 genotyping ** 51/125 40.8 (32.1–50.0) 63/163 38.7 (31.1–46.6) 109/123 88.6 (81.6–93.6) Extended HPV genotyping*** 92/125 73.6 (65.0-81.1) 115/163 71.0 (62.9–77.4) 73/123 59.3 (50.1–68.1) HPV16/18 genotyping and/or ASCL1/LHX8 methylation**** 104/125 83.2 (75.4–89.2) 130/163 80.0 (72.8–85.6) 64/123 52.0 (42.8–61.1) Extended HPV genotyping and/or ASCL1/LHX8 methylation***** 116/125 92.8 (86.8–97.0) 147/163 90.2 (85.4–94.3) 42/123 34.1 (25.8–43.2) CIN: Cervical Intraepithelial Neoplasia grade 1 to 3, CIN3+: CIN3, AIS, and cancer, CIN2+: CIN2, CIN3, AIS, and cancer. ≤CIN1: No dysplasia or CIN grade 1. n/N: CIN3 + sensitivity: True positive/total CIN3 + cases. CIN2 + sensitivity: True positive/total CIN2 + cases. ≤CIN1 specificity: true negative/total ≤ CIN1. *) ASCL1/LHX8 methylation positivity (test threshold set at 70% specificity (Van Keer et al, in revision)). **) HPV16/18 genotyping: Labelled positive if HPV16 and/or HPV18 were present. ***) Extended HPV genotyping: Labelled positive if HPV16, HPV18, HPV31, HPV33, and/or HPV52 were detected.****) HPV16/18 genotyping combined with ASCL1/LHX8 methylation (test threshold set at 70% specificity (Van Keer et al, in revision)).*****) Extended HPV genotyping combined with ASCL1/LHX8 methylation (test threshold set at 70% specificity (Van Keer et al, in revision)). Discussion This study demonstrated that ASCL1 and LHX8 DNA methylation levels in FVU samples from HPV-positive women correlated with increased cervical disease severity. The ASCL1/LHX8 methylation test showed acceptable discriminative performance for CIN3 + and CIN2 + versus ≤ CIN1 in HPV-positive FVU samples, and excellent performance in HPV-positive CS from the referral population. While methylation testing in FVU had somewhat lower sensitivity for detecting CIN3+/CIN2 + than paired CS, specificity was higher. Among women aged ≥ 30 years, similar CIN3 + sensitivity and specificity was seen between FVU and CS. Methylation test positivity was higher in CIN3 + cases with HPV16/18 versus other alpha-7/9 genotypes consistent with the greater severity and cancer risk associated with these infections. In controls and CIN2 cases, the methylation test positivity was consistent across genotypes, indicating limited genotype influence in low-grade lesions and controls. Methylation testing in HPV-positive FVU was virtually equal to extended HPV genotyping and demonstrated superior sensitivity but lower specificity compared to HPV16/18 genotyping. Consistent with previous findings 32 , the ASCL1 and LHX8 methylation levels in HPV-positive FVU samples increased with cervical disease severity, peaking in cancer. These data support previous findings on CS and cervico-vaginal self-samples that methylation detects CIN2/CIN3 lesions with a higher potential of progression to cancer 23 , 24 . However, prospective longitudinal data on FVU are needed to investigate this further. While our AUC for CIN3+ (0.76) was acceptable, but somewhat lower than previous studies (AUC: 0.83 for CIN3 + vs healthy controls and CIN3 + vs ≤ CIN1, respectively) 32,Van Keer et al (in revision) , this difference likely reflects the lower proportion of cancers and the absence of healthy controls in the present study. With fewer advanced cases, the accuracy of any test will automatically decrease. The AUC for CIN2+ (AUC = 0.73) on the other hand matched findings by Van Keer et al (in revision) who used the same marker panel and threshold for methylation positivity in FVU. This supports the robustness of ASCL1/LHX8 (PreCursor-M Gold) methylation test and the clinical threshold for methylation positivity in FVU across referral settings. Moreover, the CIN3 + sensitivity (79.2%) achieved by the ASCL1/LHX8 methylation test in FVU was reassuring, especially when compared to the pooled CIN3 + sensitivity of 71% at a predefined 70% specificity reported in a meta-analysis of DNA methylation tests in CS 18 . Despite small numbers, the ASCL1/LHX8 methylation test was able to detect both cervical cancers (n = 2, 100%) in FVU and detected 78.9% of the CIN3/AIS lesions and 63.2% of the CIN2 lesions in FVU. Interestingly, our methylation test positivity exceeded those reported by Van den Helder 32 (68% for CIN3 and 58% for CIN2), probably explained by differences in study populations, pre-analytical processing methods, previous use of a non-commercial methylation assay, and another urine collection device. Methylation testing in HPV-positive FVU samples showed lower sensitivity for detecting CIN3+/ CIN2 + but slightly higher specificity compared to CS. The lower specificity in CS may reflect the methylation positivity threshold being derived from a screening cohort (Griffioen et al, submitted), whereas the FVU threshold was trained in healthy controls and CIN-Cancer cases (a referral population) (Van Keer et al, in revision) . Applying the screening-derived CS threshold to our HPV-positive referral population was already anticipated to reduce specificity to some degree. Discrepant methylation results (FVU-/CS+) in 16% of the CIN2/CIN3 cases may reflect differences in background DNA in FVU as compared to CS and/or variations in shedding of the cancerous cells into FVU 27 , 46 . The latter was supported by our data showing lower methylation levels in FVU compared to CS across all disease categories. This aligns with previous studies reporting reduced methylation levels in self-collected vaginal and urine samples versus paired CS, regardless of the target populations and methylation markers analyzed 33 , 47 . Importantly, among women aged ≥ 30, those targeted for HPV-based screening 3 , the CIN3 + sensitivity and specificity did not differ significantly between sample types, possibly due to more advanced, highly methylated lesions in this age group 21 , 48 – 50 . In younger women (< 30 years), CIN2/3 lesions are often smaller and less methylated 51 which may hamper detection in FVU. Lower methylation levels in younger women with cervical neoplasia likely reflect shorter HPV infection duration and higher CIN2 regression rates, reported at up to 60–66% 21 52, 53 . HPV vaccination may further complicate the detectability of DNA methylation in FVU, as extremely low methylation levels have been reported in CS from vaccinated women with CIN3 lesions 54 . Our study could not fully evaluate this effect due to reliance on self-reported vaccination status lacking details on time of vaccination, vaccine type, and dosage. In HPV-positive FVU, the ASCL1/LHX8 methylation test performed similarly to extended genotyping and outperformed HPV16/18 genotyping in terms of sensitivity for CIN3+/CIN2 + but had lower specificity. Combining ASCL1/LHX8 methylation with HPV16/18 or extended genotyping further increased CIN3+/CIN2 + sensitivity, but at the cost of reduced specificity. These robust findings support the potential value of methylation testing as a direct and even single triage test to enhance risk stratification in women testing HPV-positive in FVU for onward colposcopy referral. This approach would eliminate the need for an extra clinician-collected CS for triage testing which may ensure higher compliance to follow-up for un(der)-screened women. The lower CIN3 + sensitivity of HPV16/18 genotyping in our study (40.8%) likely reflected the lower prevalence of HPV16/18 (26.9%) compared to the 47.9% reported by Van Keer et al (in revision), who observed equal CIN3 + sensitivity between methylation and HPV16/18 genotyping with slightly higher specificity for genotyping. From a laboratory perspective, triage testing in HPV-positive FVU samples should ideally be delivered at a single time point, as a single test. While both HPV16/18 and extended HPV genotyping meet this requirement, methylation analysis currently requires some extra handling, though automated and high-throughput assays are under development 55 56 . The study’s strengths included use of paired FVU and CS collected before the colposcopy or LLETZ procedure, enabling direct and accurate comparison of methylation results within the same HPV-infected woman. The paired design also reduced the risk of confounding by using each woman as her own control. Samples were tested using a commercial methylation test (PreCursor-M Gold) derived from a genome-wide discovery study on self-collected vaginal samples 34 and included a histological endpoint. The risk of verification bias of the histological endpoint was considered low as women had multiple cervical biopsies collected regardless of colposcopy findings or had LLETZ performed 5 . Limitations included that FVU was collected at the colposcopy clinics under relatively controlled clinical circumstances, which is not representative of its intended use in a home-based setting 5 . Moreover, women recruited at colposcopy clinics are not representative of the un(der)-screened populations for whom FVU sampling is primarily intended. Likewise, our sensitivity endpoints may be overestimated due to the risk of spectrum bias 57 , while our specificity was likely underestimated given the higher HPV and CIN3 + prevalence in our referral population 58 compared to un(der)-screened populations. Therefore, our findings cannot be extrapolated directly to un(der)-screened populations. Finally, some of the stratified analyses have relatively wide CIs, so these results should be interpreted with caution. In conclusion, the ASCL1/LHX8 methylation test constituted a feasible and promising method to detect underlying CIN3 + in HPV-positive FVU samples. While its sensitivity for detecting CIN3 + in FVU was somewhat lower than in paired CS in the overall population, no such difference was found among women aged ≥ 30 years. The comparable performance of methylation analysis for CIN3 + relative to extended HPV genotyping supports its potential clinical utility as a direct and single triage method in HPV-positive FVU samples. This approach could eliminate the need for clinician-collected CS for risk assessment and reduce loss to follow-up. Further validation of DNA methylation analysis in HPV-positive FVU samples from un(der)-screened populations is warranted. Abbreviations ASCL1 achaete-scute family BHLH transcription factor 1 LHX8 LIM homeobox 8 AUC Area under the curve ROC Receiver Operating characteristics HPV High-risk human papillomavirus FVU First-void urine CIN Cervical intraepithelial neoplasia CIN2+ Cervical intraepithelial neoplasia grade 2 or worse CIN3+ Cervical intraepithelial neoplasia grade 3 or worse LLETZ Large Loop Electrosurgical Excision of the Transformation Zone qMSP Quantitative Methylation Specific PCR CI confidence interval PCR poly-chain reaction DNA Deoxyribo nucleic acid McN McNemars test Declarations Acknowledgements The authors thank all women participating in the study. They acknowledge the contribution and clinical support of medical staff at the Depts. of Gynecological at Randers, Horsens, and Gødstrup Regional Hospitals.We gratefully acknowledge the laboratory staff at Department of Pathology, Randers Regional Hospital, for their collaboration and persistent efforts in the laboratory during this study. We would also like to thank Bo Søborg and Marianne Rævsbæk Pedersen, University Research Clinic for Cancer Screening, Dept. of Public Health Programmes, Randers Regional Hospital for their valuable help with data management and packing the self-sampling kits. Finally, the first author (Mette Tranberg) The first author (Mette Tranberg) would like to express her sincere gratitude to Annemie De Smet and Eef Van Den Borst from the Centre for the Evaluation of Vaccination, Vaccine & Infectious Disease Institute, Faculty of Medicine and Health Sciences, University of Antwerp, Belgium, for their valuable guidance and support in the implementation of DNA methylation analyses in the Danish laboratory. Author's contributions MT: scientific PI and study coordinator and was responsible for conducting the study overall and received funding. MT, SVK, LWG, AV and RS conceived the original idea. PN and RB: refinement of the technical details for sample handling, archiving of the samples, and performing all HPV and DNA methylation analyses. ATH supervised the implementation, execution, quality assurance, and interpretation of the DNA methylation analyses. CW supervised the execution and interpretation of the statistical analyses. LWG, PB, AH, CB, and KOB were responsible for patient enrollment, colposcopy procedures, biopsy taking, and cervical excision. SVK and RS: elaboration of handling and DNA methylation testing on urine. MT was the first author and drafted the first version of this article with support of RS, which was subsequently further developed by all authors who also reviewed and approved this version for submission. All authors read and approved the final manuscript. Funding The study was fully funded by Independence Research Fund Denmark (grant no: 1057-00018b) and the Danish Cancer Society (grant no: R351-A20092). The funders had no role in study design, data collection, and analysis, decision to publish, or preparation of the manuscript. Availability of data and materials: The dataset used in this study contains personal information and is not publicly available. An anonymized dataset is available from the corresponding author upon reasonable request and with permissions from relevant Danish Authorities. The authors declare that all data supporting the findings of this study are available within the article and its supplementary files. Ethics approval and consent to participate The project was listed in the record of processing activities for research projects in the Central Denmark Region (j.no. 1-16-02-313-21) and approved by the Ethics Committee in the Central Denmark Region (j. no: 1-10-72-246-21). All participants provided written informed consent. Consent for publication Not applicable. Competing interests Seegenesponsors the Allplex HR HPV assays for the study. According to the contract between Seegene and the University Research Clinic for Cancer Screening and Dept. of Pathology, Randers Regional Hospital, Seegene had no influence on the scientific process and no editorial rights pertaining to this manuscript. The authors retained the right to submit the manuscript.MT have participated in other studies with HPV test kits sponsored by Roche. MT has received honoraria fee from Roche Diagnostics and AstraZeneca for lectures on HPV self-sampling and HPV triage-methods, respectively. SVK is supported by a senior postdoctoral fellowship of the Research Foundation – Flanders (grant no: 12AHX26N). LWG and AH: Have outside this project, received free-of-charge test kits from Roche Diagnostics and AH has received honoraria fee from Exeltis. PN, RB, PB, KOB, and CB: No competing interests. ATH is an employee of Self-screen BV. AV is co-founder of and former board member of Novosanis (Subsidiary of OraSure Technologies Inc, Wijnegem, Belgium), a spin-off company of the University of Antwerp, and was minority shareholder until January 2019. RS is a minority shareholder of Self-screen BV and received consultancy fees form AstraZeneca paid to her institution. Authors details 1) UNICCA- University Research Clinic for Cancer Screening, Dept. of Public Health Programmes, Randers Regional Hospital, Central Denmark Region, Randers, Denmark 2) Dept. of Pathology, Randers Regional Hospital, Central Denmark Region, Randers, Denmark 3) Dept. of Clinical Medicine, Aarhus University, Aarhus, Denmark 4)Centre for the Evaluation of Vaccination, Vaccine & Infectious Disease Institute, Faculty of Medicine and Health Sciences, University of Antwerp, Belgium. 5) Self-screen B.V, Amsterdam, The Netherlands 6) Dept. of Clinical Medicine, Southern University of Denmark, Odense, Denmark 7) Dept. of Obstetrics and Gynaecology, Odense University Hospital, Odense, Denmark 8) Dept. of Obstetrics and Gynaecology, Aarhus University Hospital, Aarhus, Denmark 9) Dept. of Obstetrics and Gynecology, Gødstrup Hospital, Herning, Denmark 10) Dept. of Obstetrics and Gynecology, Horsens Regional Hospital, Horsens, Denmark 11) Dept. of Pathology, Amsterdam UMC location VU University, Amsterdam, The Netherlands 12) Cancer Center Amsterdam, Imaging and biomarkers, Amsterdam, The Netherlands References Landy R, Pesola F, Castañón A, Sasieni P. 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Stark A, Pisanic TR 2nd, Herman JG, Wang TH. High-throughput sample processing for methylation analysis in an automated, enclosed environment. SLAS Technol. 2022;27(3):172–9. Brentnall AR, Cuschieri K, Sargent A, Berkhof J, Rebolj M. Staged design recommendations for validating relative sensitivity of self-sample human papillomavirus tests for cervical screening. J Clin Epidemiol. 2024;166:111227. Giorgi-Rossi P, Franceschi S, Ronco G. HPV prevalence and accuracy of HPV testing to detect high-grade cervical intraepithelial neoplasia. Int J Cancer. 2012;130(6):1387–94. Additional Declarations Competing interest reported. Seegene sponsors the Allplex HR HPV assays for the study. According to the contract between Seegene and the University Research Clinic for Cancer Screening and Dept. of Pathology, Randers Regional Hospital, Seegene had no influence on the scientific process and no editorial rights pertaining to this manuscript. The authors retained the right to submit the manuscript. MT have participated in other studies with HPV test kits sponsored by Roche. MT has received honoraria fee from Roche Diagnostics and AstraZeneca for lectures on HPV self-sampling and HPV triage-methods, respectively. SVK is supported by a senior postdoctoral fellowship of the Research Foundation – Flanders (grant no: 12AHX26N). LWG and AH: Have outside this project, received free-of-charge test kits from Roche Diagnostics and AH has received honoraria fee from Exeltis. PN, RB, PB, KOB, and CB: No competing interests. ATH is an employee of Self-screen BV. AV is co-founder of and former board member of Novosanis (Subsidiary of OraSure Technologies Inc, Wijnegem, Belgium), a spin-off company of the University of Antwerp, and was minority shareholder until January 2019. RS is a minority shareholder of Self-screen BV and received consultancy fees form AstraZeneca paid to her institution. 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13:35:50","extension":"xml","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":160921,"visible":true,"origin":"","legend":"","description":"","filename":"680a4fa7495b4c5fa33e914816eae9101structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8249226/v1/fcd6e4888c5506cf3988030e.xml"},{"id":98425051,"identity":"24f21891-9629-44be-aeda-50e84a1b7b61","added_by":"auto","created_at":"2025-12-17 16:34:14","extension":"html","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":171347,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8249226/v1/3f2c1f4806d772318af4f1e3.html"},{"id":98424296,"identity":"dfe3c16c-79dc-4547-89c8-3fa07b308722","added_by":"auto","created_at":"2025-12-17 16:33:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":210299,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplots of DNA methylation levels of ASCL1 and LHX8 (log2-transformed ΔCq ratios; y-axis) in HPV-positive first-void urine (A-B, n=286) relative to reference gene ACTB according to cervical disease categories (x-axis). Boxplots show medians with lower and upper quartiles and range whickers. A P value, after Bonferroni correction for multiple testing of 0.0125 was considered to be significant. Abbreviations: ns: non-significant, CIN: cervical intraepithelial neoplasia (CIN); CNTRL: women with no dysplasia or CIN1 (≤ CIN1), CIN2: CIN grade 2, CIN3: CIN grade 3, AIS: adenocarcinoma in situ. CC: cervical cancer.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8249226/v1/4b82f53814753da6c93d66b6.png"},{"id":97984828,"identity":"84f5300a-1d79-4235-a67b-079262a6c78c","added_by":"auto","created_at":"2025-12-11 13:35:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":60432,"visible":true,"origin":"","legend":"\u003cp\u003eROC curves illustrating the performance of DNA methylation marker panel \u003cem\u003eASCL1\u003c/em\u003e and \u003cem\u003eLHX8\u003c/em\u003e in HPV-positive first-void urine (n=286) to discern CIN3+ vs ≤CIN1 (A) and CIN2+ vs ≤CIN1 (B). \u0026nbsp;Receiver Operating Characteristic (ROC) curves and corresponding area under the curves (AUCs) with corresponding 95% CIs are shown. CIN: Cervical Intraepithelial Neoplasia (CIN), grade 1 to 3. CNTRL: women with no dysplasia or CIN grade 1 (≤ CIN1). CIN3+: CIN grade 3, AIS: adenocarcinoma in situ, and cancer. CIN2+: CIN grade 2, CIN3, AIS, and Cancer.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8249226/v1/d3ef29da12b5fa7e937f9c72.png"},{"id":106808763,"identity":"06323ec4-17e8-40fa-970e-5fd3b357661d","added_by":"auto","created_at":"2026-04-13 16:01:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1383793,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8249226/v1/7d54f72f-4133-4bed-b7f3-0cb845958805.pdf"},{"id":97984833,"identity":"349cb7a6-8bfa-4818-b298-ef3bb6dc509a","added_by":"auto","created_at":"2025-12-11 13:35:50","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":747086,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigures01122025.docx","url":"https://assets-eu.researchsquare.com/files/rs-8249226/v1/1a2c456bc2f7c2f2f45652f9.docx"},{"id":97984829,"identity":"38572b95-e553-48b8-b59d-e7f29948fdb3","added_by":"auto","created_at":"2025-12-11 13:35:50","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":34464,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables01122025.docx","url":"https://assets-eu.researchsquare.com/files/rs-8249226/v1/e6efc89feed9b5106502927e.docx"}],"financialInterests":"Competing interest reported. Seegene sponsors the Allplex HR HPV assays for the study. According to the contract between Seegene and the University Research Clinic for Cancer Screening and Dept. of Pathology, Randers Regional Hospital, Seegene had no influence on the scientific process and no editorial rights pertaining to this manuscript. The authors retained the right to submit the manuscript. MT have participated in other studies with HPV test kits sponsored by Roche. MT has received honoraria fee from Roche Diagnostics and AstraZeneca for lectures on HPV self-sampling and HPV triage-methods, respectively. SVK is supported by a senior postdoctoral fellowship of the Research Foundation – Flanders (grant no: 12AHX26N). LWG and AH: Have outside this project, received free-of-charge test kits from Roche Diagnostics and AH has received honoraria fee from Exeltis. PN, RB, PB, KOB, and CB: No competing interests. ATH is an employee of Self-screen BV. AV is co-founder of and former board member of Novosanis (Subsidiary of OraSure Technologies Inc, Wijnegem, Belgium), a spin-off company of the University of Antwerp, and was minority shareholder until January 2019. RS is a minority shareholder of Self-screen BV and received consultancy fees form AstraZeneca paid to her institution.","formattedTitle":"Performance of ASLC1/LHX8 DNA methylation and extended HPV genotyping in first-void urine for high-grade cervical intraepithelial neoplasia detection in an HPV-positive referral population - a cross-sectional study","fulltext":[{"header":"Background","content":"\u003cp\u003eWith the shift from cytology-based to the more sensitive high-risk human papillomavirus (HPV)-based cervical cancer screening, several countries have adopted HPV vaginal self-sampling in routine screening to improve coverage among un(der)-screened women who have the highest cancer risk \u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. However, translating the benefits of vaginal self-sampling into real-world settings has proven surprisingly difficult \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Therefore, urinary HPV testing, particulary using first-void urine (FVU), for early detection of high-grade cervical intraepithelial neoplasia and cancer (CIN2\u0026thinsp;+\u0026thinsp;and CIN3+) has been suggested as a promising, accurate, non-invasive, and easier-to-use screening option\u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Primary HPV screening requires triage testing to distinguish HPV-positive women with clinically relevant disease from those with irrelevant, transient HPV infections\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Since cytology, the most evidenced triage tool, is not applicable to urine samples, women testing HPV-positive on a FVU sample would require recall for clinician-based cervical sampling for onward referral\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. This approach risks loss to follow-up and delays in diagnosis \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. In contrast, HPV genotyping and DNA methylation testing can be performed directly on FVU samples\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Each high-risk HPV genotype has varying oncogenic potential\u003csup\u003e\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e and genotyping provides insight into a woman\u0026rsquo;s individual risk of developing CIN2+. A disadvantage of HPV genotyping is that it cannot differentiate between transient and persistent infections associated with the development of CIN2\u0026thinsp;+\u0026thinsp;\u003csup\u003e11\u003c/sup\u003e. DNA hypermethylation in the promoter regions of human tumor suppressor genes is a frequent molecular epigenetic change during the early stages of (cervical) carcinogenesis\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Detection of hypermethylated host-cell DNA in FVU is biologically explained by the local shedding of cervical (pre)cancerous cells into genital secretions that are subsequently excreted in the urine\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. In the presence of cancer, detection of hypermethylated DNA may also result from transrenal excretion of tumor-related circulating cell-free DNA fragments \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. DNA methylation levels have been demonstrated to increase with CIN severity, peaking in cervical cancer across both clinician-collected cervical samples (CS) and self-collected samples (vaginal and urine)\u003csup\u003e\u003cspan additionalcitationids=\"CR19 CR20 CR21\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Accordingly, methylation testing has been proposed as a tool to predict disease development or progression in HPV-positive women\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Furthermore, as nearly all cervical cancers are methylation-positive (98.3%), a negative methylation result is suggested to effectively rule out cancer in HPV-positive women\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Following feasibility studies on the DNA methylation status of host-cell and/or viral genes in urine, including FVU \u003csup\u003e\u003cspan additionalcitationids=\"CR28 CR29 CR30\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, two prospective studies revealed promising results of the host-cell \u003cem\u003eASCL1/LHX8\u003c/em\u003e bi-marker panel in urine samples for the detection of CIN3 and cervical cancer\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e Van Keer (in revision)\u003c/sup\u003e. While good triage performance of \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation testing in HPV-positive vaginal self-samples and CS has been shown \u003csup\u003e\u003cspan additionalcitationids=\"CR34 CR35\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, data on its performance in HPV-positive FVU either or not combined with partial genotyping for HPV16/18 and extended HPV genotyping is sparse. In an HPV-positive referral population, this study investigated the clinical performance of the \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation test (PreCursor-M Gold, Self-screen BV, Amsterdam, The Netherlands) for CIN2+/CIN3\u0026thinsp;+\u0026thinsp;detection in HPV-positive FVU and paired HPV-positive CS. Additionally, methylation test performance was compared to HPV16/18 and extended HPV genotyping to detect high-grade cervical disease in HPV-positive FVU samples.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eSetting and study design and population\u003c/h2\u003e\u003cp\u003eIn Denmark, women aged 23\u0026ndash;64 are invited for cervical cancer screening at their general practitioner with vaginal self-sampling offered to non-attenders. This cross-sectional study included 325 women aged 23\u0026ndash;64 years scheduled for 1) colposcopy (due to abnormal cervical cancer screening result or post-coital bleeding or 2) large loop excision of the transformation zone (LLETZ) at public colposcopy clinics in Randers, Horsens, and G\u0026oslash;dstrup Hospitals, Central Denmark Region from October 2021 to February 2023 as previously described\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Women provided paired FVU and clinician-collected CS for HPV DNA testing followed by a histological reference test (cervical biopsies or LLETZ) for disease verification. Of note, in Denmark, all women referred for colposcopy have a minimum of four cervical biopsies collected, irrespective of the colposcopic impression \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. After sampling, women completed a short questionnaire on sampling acceptability and HPV vaccination status (vaccinated/unvaccinated)\u003csup\u003e5\u003c/sup\u003e. Women were included if they tested HPV DNA positive in the FVU and/or CS and had DNA methylation analysis performed at the Dept. of Pathology, Randers Regional Hospital, Central Denmark Region.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSample collection, storage, HPV DNA testing, and histological outcomes\u003c/h3\u003e\n\u003cp\u003eAfter obtaining informed consent, the women collected a FVU sample in the clinics using the 10 mL Colli-Pee device (Novosanis Colli-Pee\u0026reg; Small Volumes UCM FV-5010, N00327, part of the Orasure Technologies, Inc. Group, Pennsylvania, USA). The Colli-Pee device collects approximately 7 mL of the FVU, whilst immediately mixing the urine with a DNA preservative (UCM, DNA Genotek, Ottawa, Canada), reaching a total volume of 10 mL. Before colposcopy or LLETZ, the clinician collected a CS using a Cervex-Brush Combi (Rovers Medical Devices, Oss, The Netherlands) which was directly rinsed in 20 mL Thinprep PreservCyt medium (Hologic, Inc., Bedford, Massachusetts, USA)\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Upon arrival in the laboratory, the FVU samples and the ThinPrep PreservCyt vial with the cervical cells were vortexed for 20 seconds and subsequently stored at 4\u0026deg;C for maximum 24 hours before being aliquoted into secondary tubes (2 mL for HPV analysis and 4 mL for methylation analysis)\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Afterwards, the aliquots were stored at -80\u0026deg;C until HPV and DNA methylation testing. For both samples (200 \u0026micro;L), DNA extraction was performed using STARMag Universal Cartridge kit on the STARLET IVD platform (Hamilton, USA) followed by PCR amplification on a CFX96\u0026trade; real-time thermocycler (Bio-Rad, USA) according to the manufacturer\u0026rsquo;s instructions. HPV DNA testing was performed using the real-time PCR-based Allplex HR HPV detection assay (Seegene, Korea) which detects 14 individual HPV types: HPV16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, and 68 \u003csup\u003e38\u003c/sup\u003e. For both CS and FVU, we used the manufacturer\u0026rsquo;s predefined absolute threshold for HPV positivity in cervical samples (all HPV genotypes: Ct\u0026thinsp;\u0026le;\u0026thinsp;43)\u003csup\u003e5\u003c/sup\u003e. Histological results were reported using the CIN classification\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e and grouped as \u0026le;\u0026thinsp;CIN1 (normal including inflammation and non-specific reactive features, and CIN1), CIN2+ (CIN2, CIN3, adenocarcinoma \u003cem\u003ein situ\u003c/em\u003e (AIS), and cancer), and CIN3+ (CIN3, AIS, and cancer). Histological results were obtained from the Danish Pathology Databank\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDNA extraction and\u003c/b\u003e \u003cb\u003eASCL1/LHX8\u003c/b\u003e \u003cb\u003emethylation analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe FVU and CS aliquots were thawed overnight at 4\u0026deg;C before the methylation analysis. On the day of the methylation analysis, the FVU sediment was obtained by centrifugation of 4 mL FVU at 3,000xg for 15 minutes while the cervical sediment was obtained by centrifugation of 4 mL Thinprep vial at 3,400xg for 10 minutes. DNA was extracted from FVU sediment using the Quick-DNA Urine kit (Zymo Research, Irvine, CA, USA) and from CS sediment using QIAamp DNA mini kit (Qiagen, Hilden, Germany). DNA concentration measurements were performed using the Qubit fluorometer (ThermoFischer Scientific, Waltham, MA, USA). Extracted DNA (200 ng) was bisulphite converted using the EZ DNA Methylation-Lightning Kit (D5030, Zymo Research, Irvine, CA, USA). All procedures were performed according to the instructions of the manufacturers. Bisulphite-converted DNA (5.0 uL) was subsequently used as input for the quantitative methylation specific PCR (qMSP) analysis of the genes \u003cem\u003eASCL1\u003c/em\u003e and \u003cem\u003eLHX8\u003c/em\u003e using the PreCursor-M Gold Assay (RUO) (Self-screen BV, Amsterdam, The Netherlands), which also included the \u003cem\u003eACTB\u003c/em\u003e reference gene for quantification and quality control.\u003c/p\u003e\u003cp\u003eDNA methylation testing was performed on the Rotor-Gene Q MDx 5plex HRM instrument (QIAGEN, Hilden, Germany) by laboratory technicians blinded for all study outcomes. The quantification cycle (Cq) values were measured at fixed thresholds for fluorescence. The methylation levels of \u003cem\u003eASCL1\u003c/em\u003e and \u003cem\u003eLHX8\u003c/em\u003e (i.e. Cq ratios) were calculated by comparing the target Cq values to the Cq values of ACTB (2 \u003csup\u003e\u0026ndash;ΔCq\u003c/sup\u003e x 100) \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. A Cq threshold of \u0026le;\u0026thinsp;28 for ACTB indicated sufficient DNA, DNA quality, and adequate bisulphite conversion. Invalid samples were retested once, and the second result was defined definitive. Neither the methylation nor the extended genotyping results had an influence on the clinical management.\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eAge was summarized using medians and interquartile ranges (IQR) with group differences tested via the Mann-Whitney U-test. All statistical analyses and visualizations were conducted on log2-transformed ΔCq ratios for the individual methylation markers \u003cem\u003eASCL1\u003c/em\u003e, \u003cem\u003eLHX8\u003c/em\u003e and predicted probabilities for the \u003cem\u003eASCL1/LHX8\u003c/em\u003e marker panel. Differences in DNA methylation levels across cervical disease categories were presented by boxplots and assessed using the Kruskal-Wallis test. In both sample types, \u003cem\u003epost-hoc\u003c/em\u003e pairwise comparisons of DNA methylation levels between controls (\u0026le;\u0026thinsp;CIN1), CIN2, CIN3/AIS, and cancer as well as between CIN2 and CIN3/AIS were performed using the Mann-Whitney U-test with Bonferroni correction for four simultaneous comparisons (α\u0026thinsp;=\u0026thinsp;0.0125).\u003c/p\u003e\u003cp\u003eThe log2-transformed ΔCq ratios for the methylation markers were incorporated into a predefined logistic regression model for FVU developed by Van Keer et al (in revision), based on healthy controls and a referral population, including cancer patients. This model estimated predicted probabilities (ranging from 0 to 1) representing the likelihood of CIN3\u0026thinsp;+\u0026thinsp;given the DNA methylation outcome of a sample. Model development excluded CIN2 due to the heterogenous nature of this morphological diagnosis\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Predicted probabilities were used to construct Receiver Operating Characteristic (ROC) curves and the discriminative performance was quantified by Area Under the Curve (AUC) including 95% confidence intervals (CIs). Discriminative performance was interpreted using Hosmer and Lemeshow thresholds: Acceptable (0.7\u0026thinsp;\u0026le;\u0026thinsp;AUC\u0026thinsp;\u0026lt;\u0026thinsp;0.8); excellent (0.8\u0026thinsp;\u0026le;\u0026thinsp;AUC\u0026thinsp;\u0026lt;\u0026thinsp;0.9); and outstanding (AUC\u0026thinsp;\u0026ge;\u0026thinsp;0.9)\u003csup\u003e43\u003c/sup\u003e. Predicted probabilities were also used to calculate detection rates, sensitivities for CIN3\u0026thinsp;+\u0026thinsp;and CIN2+, and specificity for \u0026le;\u0026thinsp;CIN1, along with 95% CIs and stratification by age group and referral status. Main analyses applied predefined methylation positivity thresholds set at 70% specificity for \u0026le;\u0026thinsp;CIN1 established by Van Keer et al (in revision) for FVU and Griffioen et al for CS (submitted). Supplementary analyses used thresholds targeting 80% specificity for \u0026le;\u0026thinsp;CIN1, also predefined by Van Keer et al (in revision) and Griffioen et al (submitted). Performance differences between paired samples were tested using the McNemar \u003csub\u003e(McN)\u003c/sub\u003e test and unpaired proportions were compared using a two-sample proportion test. In HPV-positive FVU samples, performance for detecting CIN3+, CIN2+, and \u0026le;\u0026thinsp;CIN1 was evaluated using five strategies: (1) \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation test; (2) HPV16/18 genotyping; (3) extended HPV genotyping (HPV16/18/31/33/52)\u003csup\u003e44\u003c/sup\u003e; (4) combined HPV16/18 genotyping with \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation test; and (5) combined extended genotyping with \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation test. Data was stored and entered in REDCap\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e and all statistical analyses were performed in STATA version 18. Unless otherwise stated, statistical significance was defined as \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eStudy population\u003c/h2\u003e\u003cp\u003eThe study population consisted of 286 women referred for colposcopy or LLETZ who had a positive HPV test result on their FVU sample (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The median age was 35 years (IQR: 29\u0026ndash;45 years) and the study population included 123 controls (\u0026le;\u0026thinsp;CIN1) and 163 cases (CIN2+). 114 out of 286 women (39.9%) reported to be HPV vaccinated (data not tabulated). No differences in median age (p\u0026thinsp;=\u0026thinsp;0.28) and self-reported HPV vaccination status (p\u0026thinsp;=\u0026thinsp;0.46) were seen between controls and cases. Referral for LLETZ was significantly higher among cases compared to controls (61.4% vs 8.1%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Among the 125 CIN3\u0026thinsp;+\u0026thinsp;cases, 64.8% (n\u0026thinsp;=\u0026thinsp;81/125) were referred for LLETZ and 35.2% (n\u0026thinsp;=\u0026thinsp;44/125) for colposcopy (data not tabulated). The majority of women testing HPV-positive on FVU were also HPV positive on their paired CS (n\u0026thinsp;=\u0026thinsp;264, 92.3%). Twenty-two discordant cases, HPV positive only in FVU and negative in CS, were excluded from the paired comparison (four CIN3 and 18 controls (14 no dysplasia and four CIN1)). All HPV-positive samples were tested for the DNA methylation markers (\u003cem\u003eASCL1\u003c/em\u003e and \u003cem\u003eLHX8\u003c/em\u003e), with all FVU and CS valid for the qMSP.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCharacteristics of study population\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal study population (n\u0026thinsp;=\u0026thinsp;286)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eControls (\u0026le;\u0026thinsp;CIN1)\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;123\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCases\u003c/p\u003e\u003cp\u003e(CIN2+) \u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;163\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMedian age at time of inclusion\u003c/b\u003e, years (IQR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35 (29\u0026ndash;45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34 (26\u0026ndash;48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36 (30\u0026ndash;45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge groups\u003c/b\u003e n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e23\u0026ndash;29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e128 (44.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60 (48.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e68 (41.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e30\u0026ndash;36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e80 (28.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26 (21.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54 (33.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e37\u0026ndash;43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47 (16.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23 (18.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24 (14.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e44\u0026ndash;64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e31 (10.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (11.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17 (10.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eReferred for colposcopy or LLETZ n (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eColposcopy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e176 (61.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e113 (91.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e63 (38.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLLETZ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e110 (38.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10 (8.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100 (61.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHistology results\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo dysplasia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e65 (22.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCIN1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58 (20.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCIN2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38 (13.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCIN3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e112 (39.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAIS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11 (3.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCervical cancer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (0.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eLLETZ: Large Loop Excision of the Transformation Zone. IQR: interquartile range, n: number, % (column percentage).\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eCIN: Cervical Intraepithelial Neoplasia, grade 1 to 3, AIS: Adenocarcinoma in situ. Controls (women with no dysplasia or CIN grade 1). Cases: CIN2, CIN3, AIS, and cancer.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eDNA methylation analysis in first-void urine\u003c/h2\u003e\u003cp\u003eFor all HPV-positive FVU (n\u0026thinsp;=\u0026thinsp;286), both markers showed a significant increase in DNA methylation levels with increasing cervical disease severity (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Compared to controls (\u0026le;\u0026thinsp;CIN1), both DNA methylation markers (\u003cem\u003eASCL1\u003c/em\u003e and \u003cem\u003eLHX8\u003c/em\u003e), were significantly increased in cervical cancer and CIN3/AIS (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) as well as CIN2 compared to CIN3/AIS (p-values: 0.005\u0026ndash;0.007). \u003cem\u003eASCL1\u003c/em\u003e was also significantly increased in CIN2 compared to controls (p\u0026thinsp;=\u0026thinsp;0.006).\u003c/p\u003e\u003cp\u003eThe ability of the \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation test to discern CIN3+ (n\u0026thinsp;=\u0026thinsp;125) and CIN2+ (n\u0026thinsp;=\u0026thinsp;163) from controls (n\u0026thinsp;=\u0026thinsp;123) in HPV-positive FVU samples resulted in AUCs of 0.76 (95% CI: 0.70\u0026ndash;0.82) and 0.73 (95% CI: 0.67\u0026ndash;0.79), respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). At the predefined test threshold of 70% specificity (Van Keer et al), sensitivities of 79.2% (95% CI: 71.0-85.9%) for CIN3\u0026thinsp;+\u0026thinsp;and 75.5% (95% CI: 68.1\u0026ndash;81.9%) for CIN2\u0026thinsp;+\u0026thinsp;with corresponding specificity of 57.0% (95% CI: 47.8\u0026ndash;65.8%) for \u0026le;\u0026thinsp;CIN1 were obtained (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Sensitivities for detecting CIN3\u0026thinsp;+\u0026thinsp;and CIN2\u0026thinsp;+\u0026thinsp;in the stratified analyses by age and referral status were comparable to the main analysis, while specificity in women aged\u0026thinsp;\u0026ge;\u0026thinsp;30 was significantly lower (42.5% vs 57.0%, p\u0026thinsp;=\u0026thinsp;0.04) (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e supplementary table). The performance data of the \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation test using a predefined 80% specificity threshold are reported in Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e, supplementary table.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClinical performance of the \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation test in HPV-positive first-void urine samples (n\u0026thinsp;=\u0026thinsp;286).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003en/N\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e% (95% CI)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCIN3\u0026thinsp;+\u0026thinsp;sensitivity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e99/125\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e79.2 (71.0-85.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCIN2\u0026thinsp;+\u0026thinsp;sensitivity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e123/163\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e75.5 (68.1\u0026ndash;81.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026le;CIN1 specificity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70/123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e57.0 (47.8\u0026ndash;65.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDetection rate\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eASCL1/LHX8\u003c/b\u003e \u003cb\u003epositive* \u003c/b\u003e\u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eASCL1/LHX8\u003c/b\u003e \u003cb\u003enegative \u003c/b\u003e\u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCervical cancer (n\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCIN3/AIS (n\u0026thinsp;=\u0026thinsp;123)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e97 (78.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26 (21.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCIN2 (n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24 (63.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (36.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eControls (\u0026le;\u0026thinsp;CIN1) (n\u0026thinsp;=\u0026thinsp;123)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e53 (43.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e70 (56.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003eCIN: Cervical Intraepithelial Neoplasia (CIN), grade 1 to 3; Controls: women with no dysplasia or CIN grade 1 (\u0026le;\u0026thinsp;CIN1), CIN2: CIN grade 2, CIN3: CIN grade 3, AIS: adenocarcinoma in situ. CIN3+: CIN3, AIS, and cancer. CIN2+: CIN2, CIN3, AIS, and Cancer. n/N: CIN3\u0026thinsp;+\u0026thinsp;sensitivity: True positive/total CIN3\u0026thinsp;+\u0026thinsp;cases, CIN2\u0026thinsp;+\u0026thinsp;sensitivity: True positive/total CIN2\u0026thinsp;+\u0026thinsp;cases, \u0026le;CIN1 specificity: True negative/total\u0026thinsp;\u0026le;\u0026thinsp;CIN1. *) \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation positivity threshold in first-void urine was set at predefined 70% specificity for \u0026le;\u0026thinsp;CIN1 (Van Keer et al., in revision).\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eDNA methylation analysis in paired HPV-positive cervical samples\u003c/h3\u003e\n\u003cp\u003eNext, methylation performance in HPV-positive paired CS was determined (n\u0026thinsp;=\u0026thinsp;264) and compared to FVU. In CS, the \u003cem\u003eASCL1\u003c/em\u003e and \u003cem\u003eLHX8\u003c/em\u003e methylation levels increased significantly with disease severity (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, supplementary figure). In CS, the ROC curves demonstrated AUCs of 0.84 (95% CI: 0.79\u0026ndash;0.89) for CIN3\u0026thinsp;+\u0026thinsp;vs controls and 0.80 (95% CI: 0.75\u0026ndash;0.85) for CIN2\u0026thinsp;+\u0026thinsp;vs controls for \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation (Figure S3, A-B, supplementary figure). At a predefined threshold of 70% specificity (based on a screening population), CIN3\u0026thinsp;+\u0026thinsp;and CIN2\u0026thinsp;+\u0026thinsp;sensitivities of 88.4% and 86.2%, respectively were obtained at 45.7% specificity.\u003c/p\u003e\n\u003ch3\u003eComparison of methylation results between first-void urine and cervical samples\u003c/h3\u003e\n\u003cp\u003eMedian methylation levels of both markers were significantly higher in CS than in paired FVU across disease categories (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e, supplementary figure). AUCs were likewise higher in CS versus FVU (n\u0026thinsp;=\u0026thinsp;264) for CIN3+ (0.84, 95% CI: 0.79\u0026ndash;0.89 vs 0.75, 95% CI: 0.69\u0026ndash;0.82) and CIN2+ (0.80, 95% CI: 0.75\u0026ndash;0.85 vs 0.73, 95% CI:0.67\u0026ndash;0.79) (Figure S3 A-D, supplementary figure). When applying the predefined test thresholds, the CIN3\u0026thinsp;+\u0026thinsp;and CIN2\u0026thinsp;+\u0026thinsp;sensitivities in CS were significantly higher compared to FVU (CIN3+: 88.4% vs 79.0%, p\u0026thinsp;=\u0026thinsp;0.02 and CIN2+: 86.2% vs 74.8%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), while specificity was significantly higher in FVU compared to CS (59.0% vs 45.7%, p\u0026thinsp;=\u0026thinsp;0.04). Both cancers were detected in all instances (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among the 157 CIN2/CIN3 cases, concordant results were obtained for 125 (79,6%) cases, with 110 (70.0%) testing methylation positive in both sample types and 15 (10.0%) (seven CIN2 and eight CIN3) testing methylation negative in both sample types. Seven cases (4.4%) (one CIN2 and six CIN3) tested methylation negative on CS only and 25 cases (16.0%) (seven CIN2, 18 CIN3) tested methylation negative in FVU only (data not tabulated). In the stratified analyses, no differences in CIN3\u0026thinsp;+\u0026thinsp;sensitivity was detected between samples in women aged\u0026thinsp;\u0026ge;\u0026thinsp;30 (81.0% vs 89.4, p\u0026thinsp;=\u0026thinsp;0.09) and women referred for LLETZ (81.0% vs 87.3%, p\u0026thinsp;=\u0026thinsp;0.30) (Table S3, supplementary table). The difference in specificity between samples became non-significant in the stratified analyses (p-values between 0.09\u0026ndash;0.39). Performance data using a predefined 80% specificity threshold for the methylation analysis were reported in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003eS, supplementary table.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of clinical performance of the \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation test in paired HPV-positive first-void urine and cervical samples (n\u0026thinsp;=\u0026thinsp;264)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eFirst-void urine samples\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eCervical samples\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation*\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003en/N\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e% (95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003en/N\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e% (95% CI)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCIN3\u0026thinsp;+\u0026thinsp;sensitivity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e95/121\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e79.0 (70.1\u0026ndash;85.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e107/121\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e88.4 (81.3\u0026ndash;93.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCIN2\u0026thinsp;+\u0026thinsp;sensitivity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e119/159\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e74.8 (67.3\u0026ndash;81.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e137/159\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e86.2 (80.0\u0026ndash;91.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026le;CIN1 specificity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e62/105\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e59.0 (49.0-68.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48/105\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e45.7 (36.0-55.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDetection rate\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eASCL1/LHX8\u003c/em\u003e positive* \u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eASCL1/LHX8\u003c/em\u003e negative \u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eASCL1/LHX8\u003c/em\u003e positive**\u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eASCL1/LHX8\u003c/em\u003e negative \u003c/p\u003e\u003cp\u003en (%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCervical cancer (n\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (100)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCIN3/AIS (n\u0026thinsp;=\u0026thinsp;119)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e93 (78.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26 (22.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e105 (88.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14 (11.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCIN2 (n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24 (63.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (37.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30 (79.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8 (21.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eControls (\u0026le;\u0026thinsp;CIN1) (n\u0026thinsp;=\u0026thinsp;105)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43 41.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e62 (59.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e57 (54.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e48 (45.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eCIN: cervical intraepithelial neoplasia, grade 1 to 3; Controls: women with no dysplasia or CIN grade 1 (\u0026le;\u0026thinsp;CIN1), CIN2: CIN grade 2, CIN3: CIN grade 3, AIS: adenocarcinoma in situ. CIN3+: CIN3, AIS, and cancer. CIN2+: CIN2, CIN3, AIS, and cancer. n/N: CIN3\u0026thinsp;+\u0026thinsp;sensitivity: True positive/total CIN3\u0026thinsp;+\u0026thinsp;cases. CIN2\u0026thinsp;+\u0026thinsp;sensitivity: True positive/total CIN2\u0026thinsp;+\u0026thinsp;cases. \u0026le;CIN1 specificity: true negative/total\u0026thinsp;\u0026le;\u0026thinsp;CIN1. *) \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation positivity threshold in first-void urine was set at predefined 70% specificity for \u0026le;\u0026thinsp;CIN1 as defined by Van Keer et al (in revision). **) \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation positivity threshold in cervical samples was set at predefined 70% specificity for \u0026le;\u0026thinsp;CIN1 as defined by Griffioen et al (submitted).\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eMethylation testing versus HPV-genotyping in HPV-positive first-void urine\u003c/h2\u003e\u003cp\u003eFor all HPV-positive FVU (n\u0026thinsp;=\u0026thinsp;286), the \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation positivity did not differ across the HPV genotypes for controls (p-values: 0.21 to 0.90) and CIN2 cases (p-values: 0.15 to 0.86), while among women with CIN3\u0026thinsp;+\u0026thinsp;a significant increase in methylation positivity was observed for HPV16/18 versus non-alpha-7/9 types (HPV51, 56, 66) (90.2% vs 70.3%, p\u0026thinsp;=\u0026thinsp;0.02) (Figure S4, supplementary figure). Compared to HPV16/18 genotyping, methylation testing showed a significantly higher sensitivity for CIN3+ (40.8% vs 79.2%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and CIN2+ (38.7% vs 75.5%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), but lower specificity (88.6% vs 57.0%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). When comparing to extended HPV genotyping, methylation testing had a virtually equal sensitivity for CIN3+ (73.6% vs 79.2%, p\u0026thinsp;=\u0026thinsp;0.35) and CIN2+ (71.0% vs 75.5%, p\u0026thinsp;=\u0026thinsp;0.35) and specificity for \u0026le;\u0026thinsp;CIN1 (57.0% vs 59.3%, p\u0026thinsp;=\u0026thinsp;0.80). The sensitivity of combined methylation testing and HPV16/18 genotyping was significantly higher as compared to HPV16/18 genotyping alone for CIN3+ (83.2% vs 40.8%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and CIN2+ (80.0% vs 38.7%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) with significantly lower specificity (52.0% vs 88.6%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Higher sensitivities for CIN3+ (92.8% vs 73.6%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and CIN2+ (90.2% vs 71.0%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) with lower specificity (34.1% vs 59.3%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) were observed for combined methylation testing and extended HPV genotyping as compared to extended HPV genotyping alone. Similar observations occurred for the strategies when using a predefined 80% specificity threshold for the \u003cem\u003eASCL1/LHX8\u003c/em\u003e marker panel (Table S4, supplementary table).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePerformance of \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation versus HPV genotyping testing in HPV-positive first void urine samples (n\u0026thinsp;=\u0026thinsp;286)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eCIN3\u0026thinsp;+\u0026thinsp;sensitivity \u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eCIN2\u0026thinsp;+\u0026thinsp;sensitivity\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e\u0026le;CIN1 specificity\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTriage strategies\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003en\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e% (95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003en\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e% (95% CI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003en\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e% (95% CI)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eASCL1/LHX8\u003c/em\u003e* methylation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e99/125\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e79.2 \u003c/p\u003e\u003cp\u003e(71.0-85.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e123/163\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e75.5\u003c/p\u003e\u003cp\u003e(68.1\u0026ndash;81.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e70/123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e57.0\u003c/p\u003e\u003cp\u003e(48.0-65.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHPV16/18 genotyping\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e51/125\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.8\u003c/p\u003e\u003cp\u003e(32.1\u0026ndash;50.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e63/163\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e38.7 \u003c/p\u003e\u003cp\u003e(31.1\u0026ndash;46.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e109/123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e88.6 \u003c/p\u003e\u003cp\u003e(81.6\u0026ndash;93.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExtended HPV genotyping***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e92/125\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e73.6\u003c/p\u003e\u003cp\u003e(65.0-81.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e115/163\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e71.0 \u003c/p\u003e\u003cp\u003e(62.9\u0026ndash;77.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e73/123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e59.3 \u003c/p\u003e\u003cp\u003e(50.1\u0026ndash;68.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHPV16/18 genotyping and/or \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation****\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e104/125\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e83.2\u003c/p\u003e\u003cp\u003e(75.4\u0026ndash;89.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e130/163\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e80.0\u003c/p\u003e\u003cp\u003e(72.8\u0026ndash;85.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e64/123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e52.0\u003c/p\u003e\u003cp\u003e(42.8\u0026ndash;61.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExtended HPV genotyping and/or \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation*****\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e116/125\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e92.8\u003c/p\u003e\u003cp\u003e(86.8\u0026ndash;97.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e147/163\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e90.2\u003c/p\u003e\u003cp\u003e(85.4\u0026ndash;94.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e42/123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e34.1\u003c/p\u003e\u003cp\u003e(25.8\u0026ndash;43.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003eCIN: Cervical Intraepithelial Neoplasia grade 1 to 3, CIN3+: CIN3, AIS, and cancer, CIN2+: CIN2, CIN3, AIS, and cancer. \u0026le;CIN1: No dysplasia or CIN grade 1. n/N: CIN3\u0026thinsp;+\u0026thinsp;sensitivity: True positive/total CIN3\u0026thinsp;+\u0026thinsp;cases. CIN2\u0026thinsp;+\u0026thinsp;sensitivity: True positive/total CIN2\u0026thinsp;+\u0026thinsp;cases. \u0026le;CIN1 specificity: true negative/total\u0026thinsp;\u0026le;\u0026thinsp;CIN1. *) \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation positivity (test threshold set at 70% specificity (Van Keer et al, in revision)). **) HPV16/18 genotyping: Labelled positive if HPV16 and/or HPV18 were present. ***) Extended HPV genotyping: Labelled positive if HPV16, HPV18, HPV31, HPV33, and/or HPV52 were detected.****) HPV16/18 genotyping combined with \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation (test threshold set at 70% specificity (Van Keer et al, in revision)).*****) Extended HPV genotyping combined with \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation (test threshold set at 70% specificity (Van Keer et al, in revision)).\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study demonstrated that \u003cem\u003eASCL1\u003c/em\u003e and \u003cem\u003eLHX8\u003c/em\u003e DNA methylation levels in FVU samples from HPV-positive women correlated with increased cervical disease severity. The \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation test showed acceptable discriminative performance for CIN3\u0026thinsp;+\u0026thinsp;and CIN2\u0026thinsp;+\u0026thinsp;versus \u0026le;\u0026thinsp;CIN1 in HPV-positive FVU samples, and excellent performance in HPV-positive CS from the referral population. While methylation testing in FVU had somewhat lower sensitivity for detecting CIN3+/CIN2\u0026thinsp;+\u0026thinsp;than paired CS, specificity was higher. Among women aged\u0026thinsp;\u0026ge;\u0026thinsp;30 years, similar CIN3\u0026thinsp;+\u0026thinsp;sensitivity and specificity was seen between FVU and CS. Methylation test positivity was higher in CIN3\u0026thinsp;+\u0026thinsp;cases with HPV16/18 versus other alpha-7/9 genotypes consistent with the greater severity and cancer risk associated with these infections. In controls and CIN2 cases, the methylation test positivity was consistent across genotypes, indicating limited genotype influence in low-grade lesions and controls. Methylation testing in HPV-positive FVU was virtually equal to extended HPV genotyping and demonstrated superior sensitivity but lower specificity compared to HPV16/18 genotyping.\u003c/p\u003e\u003cp\u003eConsistent with previous findings\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, the \u003cem\u003eASCL1\u003c/em\u003e and \u003cem\u003eLHX8\u003c/em\u003e methylation levels in HPV-positive FVU samples increased with cervical disease severity, peaking in cancer. These data support previous findings on CS and cervico-vaginal self-samples that methylation detects CIN2/CIN3 lesions with a higher potential of progression to cancer \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. However, prospective longitudinal data on FVU are needed to investigate this further. While our AUC for CIN3+ (0.76) was acceptable, but somewhat lower than previous studies (AUC: 0.83 for CIN3\u0026thinsp;+\u0026thinsp;vs healthy controls and CIN3\u0026thinsp;+\u0026thinsp;vs\u0026thinsp;\u0026le;\u0026thinsp;CIN1, respectively)\u003csup\u003e32,Van Keer et al (in revision)\u003c/sup\u003e, this difference likely reflects the lower proportion of cancers and the absence of healthy controls in the present study. With fewer advanced cases, the accuracy of any test will automatically decrease. The AUC for CIN2+ (AUC\u0026thinsp;=\u0026thinsp;0.73) on the other hand matched findings by Van Keer et al (in revision) who used the same marker panel and threshold for methylation positivity in FVU. This supports the robustness of \u003cem\u003eASCL1/LHX8\u003c/em\u003e (PreCursor-M Gold) methylation test and the clinical threshold for methylation positivity in FVU across referral settings. Moreover, the CIN3\u0026thinsp;+\u0026thinsp;sensitivity (79.2%) achieved by the \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation test in FVU was reassuring, especially when compared to the pooled CIN3\u0026thinsp;+\u0026thinsp;sensitivity of 71% at a predefined 70% specificity reported in a meta-analysis of DNA methylation tests in CS\u003csup\u003e18\u003c/sup\u003e. Despite small numbers, the \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation test was able to detect both cervical cancers (n\u0026thinsp;=\u0026thinsp;2, 100%) in FVU and detected 78.9% of the CIN3/AIS lesions and 63.2% of the CIN2 lesions in FVU. Interestingly, our methylation test positivity exceeded those reported by Van den Helder\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e (68% for CIN3 and 58% for CIN2), probably explained by differences in study populations, pre-analytical processing methods, previous use of a non-commercial methylation assay, and another urine collection device. Methylation testing in HPV-positive FVU samples showed lower sensitivity for detecting CIN3+/ CIN2\u0026thinsp;+\u0026thinsp;but slightly higher specificity compared to CS. The lower specificity in CS may reflect the methylation positivity threshold being derived from a screening cohort (Griffioen et al, submitted), whereas the FVU threshold was trained in healthy controls and CIN-Cancer cases (a referral population) \u003csup\u003e(Van Keer et al, in revision)\u003c/sup\u003e. Applying the screening-derived CS threshold to our HPV-positive referral population was already anticipated to reduce specificity to some degree. Discrepant methylation results (FVU-/CS+) in 16% of the CIN2/CIN3 cases may reflect differences in background DNA in FVU as compared to CS and/or variations in shedding of the cancerous cells into FVU \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. The latter was supported by our data showing lower methylation levels in FVU compared to CS across all disease categories. This aligns with previous studies reporting reduced methylation levels in self-collected vaginal and urine samples versus paired CS, regardless of the target populations and methylation markers analyzed\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Importantly, among women aged\u0026thinsp;\u0026ge;\u0026thinsp;30, those targeted for HPV-based screening \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, the CIN3\u0026thinsp;+\u0026thinsp;sensitivity and specificity did not differ significantly between sample types, possibly due to more advanced, highly methylated lesions in this age group \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan additionalcitationids=\"CR49\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. In younger women (\u0026lt;\u0026thinsp;30 years), CIN2/3 lesions are often smaller and less methylated \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e which may hamper detection in FVU. Lower methylation levels in younger women with cervical neoplasia likely reflect shorter HPV infection duration and higher CIN2 regression rates, reported at up to 60\u0026ndash;66%\u003csup\u003e21 52,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. HPV vaccination may further complicate the detectability of DNA methylation in FVU, as extremely low methylation levels have been reported in CS from vaccinated women with CIN3 lesions\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. Our study could not fully evaluate this effect due to reliance on self-reported vaccination status lacking details on time of vaccination, vaccine type, and dosage.\u003c/p\u003e\u003cp\u003eIn HPV-positive FVU, the \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation test performed similarly to extended genotyping and outperformed HPV16/18 genotyping in terms of sensitivity for CIN3+/CIN2\u0026thinsp;+\u0026thinsp;but had lower specificity. Combining \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation with HPV16/18 or extended genotyping further increased CIN3+/CIN2\u0026thinsp;+\u0026thinsp;sensitivity, but at the cost of reduced specificity. These robust findings support the potential value of methylation testing as a direct and even single triage test to enhance risk stratification in women testing HPV-positive in FVU for onward colposcopy referral. This approach would eliminate the need for an extra clinician-collected CS for triage testing which may ensure higher compliance to follow-up for un(der)-screened women. The lower CIN3\u0026thinsp;+\u0026thinsp;sensitivity of HPV16/18 genotyping in our study (40.8%) likely reflected the lower prevalence of HPV16/18 (26.9%) compared to the 47.9% reported by Van Keer et al (in revision), who observed equal CIN3\u0026thinsp;+\u0026thinsp;sensitivity between methylation and HPV16/18 genotyping with slightly higher specificity for genotyping. From a laboratory perspective, triage testing in HPV-positive FVU samples should ideally be delivered at a single time point, as a single test. While both HPV16/18 and extended HPV genotyping meet this requirement, methylation analysis currently requires some extra handling, though automated and high-throughput assays are under development \u003csup\u003e55 56\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe study\u0026rsquo;s strengths included use of paired FVU and CS collected before the colposcopy or LLETZ procedure, enabling direct and accurate comparison of methylation results within the same HPV-infected woman. The paired design also reduced the risk of confounding by using each woman as her own control. Samples were tested using a commercial methylation test (PreCursor-M Gold) derived from a genome-wide discovery study on self-collected vaginal samples\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e and included a histological endpoint. The risk of verification bias of the histological endpoint was considered low as women had multiple cervical biopsies collected regardless of colposcopy findings or had LLETZ performed\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Limitations included that FVU was collected at the colposcopy clinics under relatively controlled clinical circumstances, which is not representative of its intended use in a home-based setting\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Moreover, women recruited at colposcopy clinics are not representative of the un(der)-screened populations for whom FVU sampling is primarily intended. Likewise, our sensitivity endpoints may be overestimated due to the risk of spectrum bias\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e, while our specificity was likely underestimated given the higher HPV and CIN3\u0026thinsp;+\u0026thinsp;prevalence in our referral population\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e compared to un(der)-screened populations. Therefore, our findings cannot be extrapolated directly to un(der)-screened populations. Finally, some of the stratified analyses have relatively wide CIs, so these results should be interpreted with caution.\u003c/p\u003e\u003cp\u003eIn conclusion, the \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation test constituted a feasible and promising method to detect underlying CIN3\u0026thinsp;+\u0026thinsp;in HPV-positive FVU samples. While its sensitivity for detecting CIN3\u0026thinsp;+\u0026thinsp;in FVU was somewhat lower than in paired CS in the overall population, no such difference was found among women aged\u0026thinsp;\u0026ge;\u0026thinsp;30 years. The comparable performance of methylation analysis for CIN3\u0026thinsp;+\u0026thinsp;relative to extended HPV genotyping supports its potential clinical utility as a direct and single triage method in HPV-positive FVU samples. This approach could eliminate the need for clinician-collected CS for risk assessment and reduce loss to follow-up. Further validation of DNA methylation analysis in HPV-positive FVU samples from un(der)-screened populations is warranted.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eASCL1\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eachaete-scute family BHLH transcription factor 1\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLHX8\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eLIM homeobox 8\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAUC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eArea under the curve\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eReceiver Operating characteristics\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHPV\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHigh-risk human papillomavirus\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eFVU\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eFirst-void urine\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCIN\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCervical intraepithelial neoplasia\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCIN2+\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCervical intraepithelial neoplasia grade 2 or worse\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCIN3+\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCervical intraepithelial neoplasia grade 3 or worse\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLLETZ\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eLarge Loop Electrosurgical Excision of the Transformation Zone\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eqMSP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eQuantitative Methylation Specific PCR\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003econfidence interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePCR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003epoly-chain reaction\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDNA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDeoxyribo nucleic acid\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMcN\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMcNemars test\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003cbr\u003e\u003c/strong\u003eThe authors thank all women participating in the study. They acknowledge the contribution and clinical support of medical staff at the Depts. of Gynecological at Randers, Horsens, and G\u0026oslash;dstrup Regional Hospitals.We gratefully acknowledge the laboratory staff at Department of Pathology, Randers Regional Hospital, for their collaboration and persistent efforts in the laboratory during this study. We would also like to thank Bo S\u0026oslash;borg and Marianne R\u0026aelig;vsb\u0026aelig;k Pedersen, University Research Clinic for Cancer Screening, Dept. of Public Health Programmes, Randers Regional Hospital for their valuable help with data management and packing the self-sampling kits.\u0026nbsp;Finally, the first author (Mette Tranberg) The first author (Mette Tranberg) would like to express her sincere gratitude to Annemie De Smet and Eef Van Den Borst from the Centre for the Evaluation of Vaccination, Vaccine \u0026amp; Infectious Disease Institute, Faculty of Medicine and Health Sciences, University of Antwerp, Belgium, for their valuable guidance and support in the implementation of DNA methylation analyses in the Danish laboratory.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026apos;s contributions\u0026nbsp;\u003cbr\u003e\u003c/strong\u003eMT: scientific PI and study coordinator and was responsible for conducting the study overall and received funding. MT, SVK, LWG, AV and RS conceived the original idea. PN and RB: refinement of the technical details for sample handling, archiving of the samples, and performing all HPV and DNA methylation analyses. ATH supervised the implementation, execution, quality assurance, and interpretation of the DNA methylation analyses. CW supervised the execution and interpretation of the statistical analyses. LWG, PB, AH, CB, and KOB were responsible for patient enrollment, colposcopy procedures, biopsy taking, and cervical excision. SVK and RS: elaboration of handling and DNA methylation testing on urine. MT was the first author and drafted the first version of this article with support of RS, which was subsequently further developed by all authors who also reviewed and approved this version for submission. All authors read and approved the final manuscript.\u003cbr\u003e\u003cstrong\u003eFunding\u003cbr\u003e\u0026nbsp;\u003c/strong\u003eThe study was fully funded by Independence Research Fund Denmark (grant no: 1057-00018b) and the Danish Cancer Society (grant no: R351-A20092). The funders had no role in study design, data collection, and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003cbr\u003e\u003c/strong\u003eThe dataset used in this study contains personal information and is not publicly available. An anonymized dataset is available from the corresponding author upon reasonable request and with permissions from relevant Danish Authorities. The authors declare that all data supporting the findings of this study are available within the article and its supplementary files.\u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003e\u003cstrong\u003eEthics approval and consent to participate\u003cbr\u003e\u003c/strong\u003eThe project was listed in the record of processing activities for research projects in the Central Denmark Region (j.no. 1-16-02-313-21) and approved by the Ethics Committee in the Central Denmark Region (j. no: 1-10-72-246-21). All participants provided written informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Not applicable.\u003cbr\u003e \u003cstrong\u003eCompeting interests\u0026nbsp;\u003cbr\u003e\u003c/strong\u003eSeegenesponsors the Allplex HR HPV assays for the study. According to the contract between Seegene and the University Research Clinic for Cancer Screening and Dept. of Pathology, Randers Regional Hospital, Seegene had no influence on the scientific process and no editorial rights pertaining to this manuscript. The authors retained the right to submit the manuscript.MT have participated in other studies with HPV test kits sponsored by Roche. MT has received honoraria fee from Roche Diagnostics and AstraZeneca for lectures on HPV self-sampling and HPV triage-methods, respectively.\u0026nbsp;SVK is supported by a senior postdoctoral fellowship of the Research Foundation \u0026ndash; Flanders (grant no:\u0026nbsp;12AHX26N). LWG and AH: Have outside this project, received free-of-charge test kits from Roche Diagnostics and AH has received honoraria fee from Exeltis. PN, RB, PB, KOB, and CB:\u0026nbsp;No competing interests. ATH is an employee of Self-screen BV. AV is co-founder of and former board member of Novosanis (Subsidiary of OraSure Technologies Inc, Wijnegem, Belgium), a spin-off company of the University of Antwerp, and was minority shareholder until January 2019. RS is a minority shareholder of Self-screen BV and received consultancy fees form AstraZeneca paid to her institution.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors details\u003cbr\u003e\u003c/strong\u003e1) UNICCA- University Research Clinic for Cancer Screening, Dept. of Public Health Programmes, Randers Regional Hospital, Central Denmark Region, Randers, Denmark\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;2) Dept. of Pathology, Randers Regional Hospital, Central Denmark Region, Randers, Denmark\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;3) Dept. of Clinical Medicine, Aarhus University, Aarhus, Denmark\u003c/p\u003e\n\u003cp\u003e4)Centre for the Evaluation of Vaccination, Vaccine \u0026amp; Infectious Disease Institute, Faculty of Medicine and Health Sciences, University of Antwerp, Belgium.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;5) Self-screen B.V, Amsterdam, The Netherlands\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;6) Dept. of Clinical Medicine, Southern University of Denmark, Odense, Denmark\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;7) Dept. \u0026nbsp;of Obstetrics and Gynaecology, Odense University Hospital, Odense, Denmark\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;8) Dept. of Obstetrics and Gynaecology, Aarhus University Hospital, Aarhus, Denmark\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;9) Dept. of Obstetrics and Gynecology, G\u0026oslash;dstrup Hospital, Herning, Denmark\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;10) Dept. of Obstetrics and Gynecology, Horsens Regional Hospital, Horsens, Denmark\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;11) Dept. of Pathology, Amsterdam UMC location VU University, Amsterdam, The Netherlands\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;12) Cancer Center Amsterdam, Imaging and biomarkers, Amsterdam, The Netherlands\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLandy R, Pesola F, Casta\u0026ntilde;\u0026oacute;n A, Sasieni P. 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Non-invasive detection of endometrial cancer by DNA methylation analysis in urine. Clin Epigenetics. 2020;12(1):165.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSnoek BC, Splunter APV, Bleeker MCG, et al. Cervical cancer detection by DNA methylation analysis in urine. Sci Rep. 2019;9(1):3088.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBarrett JE, Sundstr\u0026ouml;m K, Jones A, et al. The WID-CIN test identifies women with, and at risk of, cervical intraepithelial neoplasia grade 3 and invasive cervical cancer. Genome Med. 2022;14(1):116.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHansel A, Steinbach D, Greinke C, et al. A promising DNA methylation signature for the triage of high-risk human papillomavirus DNA-positive women. PLoS ONE. 2014;9(3):e91905.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLeeman A, Del Pino M, Marimon L, et al. Reliable identification of women with CIN3\u0026thinsp;+\u0026thinsp;using hrHPV genotyping and methylation markers in a cytology-screened referral population. Int J Cancer. 2019;144(1):160\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVink FJ, Meijer C, Hesselink AT, et al. FAM19A4/miR124-2 Methylation Testing and Human Papillomavirus (HPV) 16/18 Genotyping in HPV-Positive Women Under the Age of 30 Years. Clin Infect Dis. 2023;76(3):e827\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLoopik DL, Bentley HA, Eijgenraam MN, IntHout J, Bekkers RLM, Bentley JR. The Natural History of Cervical Intraepithelial Neoplasia Grades 1, 2, and 3: A Systematic Review and Meta-analysis. J Low Genit Tract Dis. 2021;25(3):221\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTainio K, Athanasiou A, Tikkinen KAO, et al. Clinical course of untreated cervical intraepithelial neoplasia grade 2 under active surveillance: systematic review and meta-analysis. BMJ. 2018;360:k499.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLouvanto K, Verhoef L, Pimenoff V, et al. Low methylation marker levels among human papillomavirus-vaccinated women with cervical high-grade squamous intraepithelial lesions. Int J Cancer. 2024;155(9):1549\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVerhoef L, Floore AN, Doorn S, et al. Direct bisulphite conversion of cervical samples for DNA methylation analysis. Epigenetics. 2022;17(10):1173\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStark A, Pisanic TR 2nd, Herman JG, Wang TH. High-throughput sample processing for methylation analysis in an automated, enclosed environment. SLAS Technol. 2022;27(3):172\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrentnall AR, Cuschieri K, Sargent A, Berkhof J, Rebolj M. Staged design recommendations for validating relative sensitivity of self-sample human papillomavirus tests for cervical screening. J Clin Epidemiol. 2024;166:111227.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGiorgi-Rossi P, Franceschi S, Ronco G. HPV prevalence and accuracy of HPV testing to detect high-grade cervical intraepithelial neoplasia. Int J Cancer. 2012;130(6):1387\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmed","sideBox":"Learn more about [BMC Medicine](http://bmcmedicine.biomedcentral.com/)","snPcode":"12916","submissionUrl":"https://submission.nature.com/new-submission/12916/3","title":"BMC Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"DNA methylation, cervical cancer screening, HPV DNA testing, urinary HPV testing, early detection of cancer/methods","lastPublishedDoi":"10.21203/rs.3.rs-8249226/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8249226/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eFirst-void urine (FVU) collection for high-risk human papillomavirus (HPV) testing is a promising tool to reach un(der)-screened women in cervical cancer screening programs. This cross-sectional study investigated the clinical performance of host-cell DNA methylation markers \u003cem\u003eASCL1 \u003c/em\u003eand \u003cem\u003eLHX8\u003c/em\u003e in HPV-positive FVU to detect high-grade cervical intraepithelial neoplasia and cancer (CIN2+ and CIN3+).\u003c/p\u003e\n\u003cp\u003eSecondly, comparative analysis to paired HPV-positive clinician-collected cervical samples (CS) and HPV genotyping was examined.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003ePaired FVU and CS samples were collected from 286 women aged 23-64 years referred for colposcopy or cervical excision. Histological endpoints included 123 ≤CIN1 (no dysplasia and CIN1), 38 CIN2, and 123 CIN3/AIS and 2 cancers. FVU and CS were tested for HPV DNA and \u003cem\u003eASCL1\u003c/em\u003e/\u003cem\u003eLHX8\u003c/em\u003emethylation. Methylation test performance was evaluated by area under the curve (AUC) and logistic regression analysis. \u0026nbsp;Accuracy differences between paired samples and across methylation, HPV16/18, and extended 16/18/31/33/52 genotyping testing in FVU were tested using McNemar’s test.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003e\u003cem\u003eASCL1\u003c/em\u003e and \u003cem\u003eLHX8\u003c/em\u003e methylation levels in HPV-positive FVU increased significantly with disease severity. Methylation testing yielded an AUC of 0.76 (95% CI: 0.70-0.82) for CIN3+ and 0.73 (95% CI: 0.67-0.79) for CIN2+, with corresponding sensitivities of 79.2% (95% CI: 71.0-85.9%) and 75.5% (95% CI: 68.1-81.9%) and a specificity of 57.0% (95% CI: 47.8-65.8%) for ≤CIN1. In CS, methylation testing yielded an AUC of 0.84 (95% CI: 0.79-0.89) for CIN3+ and 0.80 (95% CI: 0.75-0.85) for CIN2+, corresponding to significantly higher sensitivities (p≤0.02) but lower specificity (p=0.04) compared to FVU. In women aged ≥30 years, CIN3+ sensitivity and specificity for ≤CIN1 were similar between FVU and CS (both p=0.09). Methylation testing in HPV-positive FVU had similar diagnostic accuracy as extended genotyping (p≥0.35), but had a higher sensitivity (p=0.01) and a lower specificity (p=0.01) than HPV16/18 genotyping.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003e\u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation testing in HPV-positive FVU showed promise for detecting high-grade cervical disease. \u003cem\u003eASCL1/LHX8\u003c/em\u003e methylation performance in FVU was similar to extended HPV genotyping and, in women aged ≥30 years, similar to performance in CS. This supports the potential of methylation analysis as a direct and single triage test in urine-based cervical cancer screening, removing the need for follow-up cervical sampling.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial registration:\u003c/strong\u003e Clinicaltrials.gov: NCT05065853\u003c/p\u003e","manuscriptTitle":"Performance of ASLC1/LHX8 DNA methylation and extended HPV genotyping in first-void urine for high-grade cervical intraepithelial neoplasia detection in an HPV-positive referral population - a cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-11 13:35:45","doi":"10.21203/rs.3.rs-8249226/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-15T17:19:15+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-11T09:48:53+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-30T22:07:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"258128005386094176099729611095704257431","date":"2025-12-23T16:56:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"151360391134084985721488575362773254277","date":"2025-12-23T13:52:43+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-13T15:58:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"60742724747583716519959793148372726982","date":"2025-12-11T03:55:46+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-10T09:12:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"173480412329656144065204295549910179388","date":"2025-12-08T23:37:33+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-08T20:42:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-02T05:35:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-02T05:32:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medicine","date":"2025-12-01T10:17:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmed","sideBox":"Learn more about [BMC Medicine](http://bmcmedicine.biomedcentral.com/)","snPcode":"12916","submissionUrl":"https://submission.nature.com/new-submission/12916/3","title":"BMC Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"773ec33a-f4d2-4a69-91c7-f4d838c2bf4e","owner":[],"postedDate":"December 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-04-13T16:00:05+00:00","versionOfRecord":{"articleIdentity":"rs-8249226","link":"https://doi.org/10.1186/s12916-026-04837-5","journal":{"identity":"bmc-medicine","isVorOnly":false,"title":"BMC Medicine"},"publishedOn":"2026-04-10 15:57:17","publishedOnDateReadable":"April 10th, 2026"},"versionCreatedAt":"2025-12-11 13:35:45","video":"","vorDoi":"10.1186/s12916-026-04837-5","vorDoiUrl":"https://doi.org/10.1186/s12916-026-04837-5","workflowStages":[]},"version":"v1","identity":"rs-8249226","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8249226","identity":"rs-8249226","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}