Performance of PCDHGB7 Methylation as a Triage Tool for Cervical Cancer Screening in Non- hrHPV16/18-Positive Women

Performance of PCDHGB7 Methylation as a Triage Tool for Cervical Cancer Screening in Non- hrHPV16/18-Positive Women | 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 PCDHGB7 Methylation as a Triage Tool for Cervical Cancer Screening in Non- hrHPV16/18-Positive Women Xuechuan Han, Qiaorui Zhang, Yang Fan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8556133/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Objective The implementation of high-risk human papillomavirus (hrHPV)-based screening has greatly reduced the incidence and mortality of cervical cancer. However, an effective, noninvasive triage strategy that is independent of subjective pathological interpretation is urgently required to decrease unnecessary colposcopy referrals in non hrHPV16/18-positive women. Materials and methods A total of 1038 non HPV16/18-positive women aged 30–80 years (median = 40 years) were enrolled from Ningxia People’s Hospital. The performance of PCDHGB7 methylation level detection as a triage tool for identifying cervical cancer and high-grade precancerous lesions was evaluated. Results PCDHGB7 hypermethylation efficiently distinguished cervical intraepithelial neoplasia grade 2 or worse (CIN2+) from CIN1 or normal histology (CIN1-), demonstrating high sensitivity (69.2%) and excellent specificity (96.9%). Notably, PCDHGB7 hypermethylation show strong triage performance in non-HPV16/18-positive women with abnormal cytology, including ASC-US (sensitivity 45.8%, specificity 97.7%) and LSIL (sensitivity 65.0%, specificity 95.1%). Furthermore, favourable performance was observed in women ASC-H (sensitivity 65.0%, specificity 95.1%) and HSIL (sensitivity 81.3%, specificity 95.2%). Conclusions PCDHGB7 hypermethylation detection represents a promising triage strategy for non-hrHPV16/18-positive women, offering high specificity and reliable sensitivity for CIN2 + detection. Its application may substantially reduce unnecessary colposcopy-referrals and improve the efficiency of cervical cancer screening programs. PCDHGB7 DNA hypermethylation non-16/18 hrHPV Triage Cervical Cancer screening Introduction Cervical cancer (CxCa) remains one of the most prevalent gynecological malignancies and the fourth leading cause of cancer-related mortality among women worldwide, accounting for approximately 6.5% of newly diagnosed cancers annually[1]. China bears a substantial proportion of this burden, with an approximately 110,000 new cases and 60,000 deaths annually, representing nearly 18% and 17% of the global incidence and mortality, highlighting persistent challenges in prevention and early detection [2]. Progression from high-grade squamous intraepithelial lesions (HSIL) to invasive CxCa is typically slow, creating a clinically actionable window for early intervention. Current screening guidelines worldwide recommend a combination of ThinPrep Cytologic Test (TCT) and human papillomavirus (hr-HPV) testing as the most widely adopted screening strategy. HPV testing, increasingly used as primary screening modality, offers high sensitivity and strong objectivity, with negative results reliably excluding CxCa risk. However, its limited specificity compromises clinical precision, as it frequently detects transient, self-limiting infections [4]. Moreover, HPV testing cannot distinguish active viral replication from residual viral DNA, nor do they directly identify cervical lesions, resulting in high colposcopy referral rates and the need for additional cytological or histological evaluation [5-7]. By contrast, TCT enables direct assessment of cellular morphology and exhibits higher specificity, thereby reducing false-positive results. Its sensitivity, however, is suboptimal, increasing the risk of missed diagnoses, and its performance is heavily dependent on operator expertise. This subjectivity contributes to substantial interinstitutional variability, particularly in low- and middle-income settings. Together, these limitations highlight the urgent need for novel screening and triage strategies that combine high sensitivity, high specificity, and robust objectivity. Aberrant DNA methylation is a hallmark of carcinogenesis and occurs early in malignant transformation, rendering it an attractive diagnostic[8,9], prognostic, and predictive biomarker across multiple cancer types, including CxCa [10]. Despite this potential, only a limited number of methylation-based biomarkers have been systematic clinical validation. PCDHGB7 , a member of the protocadherin gamma gene cluster involved in neuronal connectivity, has recently identified by Dong et al . as a novel universal cancer-only marker (UCOM), highlighting its potential utility in cancer detection [11]. In this study, we aimed to further validate the diagnostic performance of a PCDHGB7 methylation assay and to explore its application as a triage strategy for women with non-16/18 hrHPV positivity. By addressing a critical gap in current screening algorithms, this work seeks to improve risk stratification and reduce unnecessary invasive procedures in CxCa screening. Materials and Methods Participants Patients meeting the following inclusion criteria were recruited from the outpatient department of Ningxia People’s Hospital between January 1, 2023, and December 31, 2023: (1) aged ≥30 years; (2) underwent HPV and cytology testing in our institution and were non–16/18 hrHPV-positive; and (3) agreed to use their remaining HPV testing samples for this study. Patients missing cytology information were excluded. Cervical brush samples were collected with written informed consent. All participants were referred for colposcopy, and their remaining samples were anonymized before methylation testing. Additional exclusion criteria included: (1) failed quality control (remaining sample volume <400 μl), (2) failed assay, (3) lost to follow-up without a colposcopy visit, (4) diagnosis of other cancers (e.g., endometrial or ovarian cancer), (5) vaginal or vulvar intraepithelial neoplasia grade 2 or worse, and (6) history of CIN2+. Methylation results and clinical data of eligible patients were included in the analysis. Institutional Review Board approval was obtained from the Ethics Committee of Ningxia People’s Hospital. Gene methylation detection Methylation testing was performed on the remaining cervical brush samples from HPV testing. A 400 μl volume was used for genomic DNA extraction using the EP Genomic DNA Kit (Epiprobe Biotech, K-21) and an automated nucleic acid extraction system. Subsequently, 100 ng of genomic DNA was used for methylation-sensitive restriction enzyme qPCR (MSRE-qPCR), as described previously. Unlike bisulfite PCR, MSRE-qPCR is based on selective digestion of DNA by methylation-sensitive enzymes, followed by qPCR with primers flanking the enzyme cutting site. CpG sites of PCDHGB7 were detected, and GAPDH was used for normalization. Methylation levels were evaluated using ΔCt = Ct_ PCDHGB7 − Ct_ GAPDH . CerMe detection was performed by a dedicated laboratory. HPV testing Cervical brush samples were collected by gynecologists and tested using the Roche Cobas 4800 HPV real-time PCR assay, following the manufacturer’s protocol. Samples positive for HPV16 or HPV18 were classified as HPV16/18 positive. Samples negative for HPV16/18 but positive for any of the other 12 high-risk types (31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, and 68) were classified as non–16/18 hrHPV-positive. All samples were collected by qualified gynecologists and tested by certified laboratory personnel. Cytology testing Cytological samples were collected using broom-type cervical smears (Cervex-Brush®, Rovers Medical Devices) and preserved in SurePath™ Preservative Fluid. The ThinPrep® 2000 System was used for automated slide preparation and reading. Cytology was classified using the 2001 Bethesda System as follows: (1) no intraepithelial lesion or malignancy (NILM); (2) ASCUS; (3) atypical glandular cells (AGC); (4) atypical squamous cells, cannot exclude HSIL (ASC-H); (5) LSIL; (6) HSIL; (7) squamous cell carcinoma (SCC); and (8) adenocarcinoma (AC). Colposcopy biopsy All non–16/18 hrHPV-positive women underwent colposcopy within 2 months of enrollment. Procedures were performed by certified colposcopy specialists and included acetic acid and iodine staining. Guidelines from the ASCCP and CSCCP were followed. Women with all of the following low-risk features could be classified as normal without biopsy: (1) completely normal colposcopic impression, (2) type 1 transformation zone, (3) age <40 years, (4) <HSIL cytology, and (5) no HPV16/18 infection. Others underwent 2–4 targeted biopsies and, when indicated, endocervical curettage (ECC). Histopathology results were categorized as: (1) normal, (2) CIN1, (3) CIN2/3 (including CIN2, CIN2–3, CIN3), and (4) cervical cancer (including AC, SCC, or cervical sarcoma). CIN1− included normal and CIN1; CIN2+ included CIN2/3 and cancer. Colposcopists were blinded to methylation results. Statistical analysis Statistical analyses were performed using GraphPad Prism 9 and Microsoft Excel. ROC curves were used to quantify diagnostic performance using the hybrid Wilson/Brown method. Differences in methylation levels between CIN1− and CIN2+ were compared using a two-tailed unpaired parametric test. A P value <0.05 was considered statistically significant (* P < 0.05, ** P < 0.01, *** P < 0.001, **** P < 0.0001). Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated using 2 × 2 contingency tables. Missing data were excluded from analysis. Results A total of 1,038 patients were high-risk HPV-positive (non-HPV16/18). The ThinPrep Cytology Test (TCT) results were as follows: NILM, 129 cases (12.4%, 129/1038); ASC-US, 339 cases (32.7%, 339/1038); ASC-H, 105 cases (10.1%, 105/1038); LSIL, 297 cases (28.6%, 297/1038); AGC, 6 cases (0.6%, 6/1038); SCC, 15 cases (1.4%, 15/1038); AIS, 6 cases (0.6%, 6/1038); and HSIL, 141 cases (13.6%, 141/1038). Among these, the 6 cases of AGC and 6 cases of AIS were ultimately diagnosed as cervical adenocarcinoma. Due to the limited sample size, AGC and AIS cases were not included in subgroup comparative analyses or performance evaluations. Comparison of diagnostic performance between TCT and PCDHGB7 gene methylation Among the 1,038 patients, 909 (87.6%) had positive TCT results. Colposcopy-guided biopsy, used as the gold standard, yielded positive results in 351 cases (33.8%) and negative results in 687 cases (66.2%). PCDHGB7 methylation was positive in 264 cases (25.4%) and negative in 774 cases (74.6%). The accuracy of TCT was 43.1%, with a sensitivity of 95.7% and a specificity of 16.5%. The Kappa value for agreement between TCT and the gold standard was 0.088 (P < 0.01), indicating statistically significant but slight agreement. These results demonstrate that PCDHGB7 DNA methylation testing showed stronger agreement with the gold standard than TCT. Table 1. Comparison of TCT and DNA Methylation Results [n (%)] Histological Diagnosis TCT Detection DNA Methylation Detection Positive Negative Positive Negative ≥CIN2 336 (95.7) 15 (4.3) 243 (69.2) 108 (30.8) <CIN2 573 (83.5) 114 (16.5) 21 (3.1) 666 (96.9) Values represent n (%). Percentages are calculated using the total number within each histological diagnosis group as the denominator. Table 2. Comparison of Diagnostic Performance Between ThinPrep Cytologic Test (TCT) and PCDHGB7 DNA Methylation Testing (%) Test Method Sensitivity Specificity Positive Predictive Value (PPV) Negative Predictive Value (NPV) Accuracy ThinPrep Cytologic Test (TCT) 95.7 16.5 36.8 88.4 43.1 PCDHGB7 DNA Methylation Testing 69.2 96.9 92.0 86.0 87.6 *Performance metrics were calculated using colposcopy-guided biopsy as the reference standard (gold standard). Sensitivity and specificity were calculated for the detection of histologically confirmed ≥CIN2 lesions. PPV, NPV, and accuracy were calculated based on the total study population (n=1038).* Comparison of diagnostic performance between TCT and PCDHGB7 gene methylation across stratified subgroups The diagnostic performance of the two testing methods was compared against the histopathological diagnosis (used as the gold standard) across stratified cytological subgroups. Diagnostic validity metrics—including accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV)—were evaluated. The specific results are presented below. ASC-US The cohort included 468 patients: 339 with ASC-US and 129 with NILM on the TCT. PCDHGB7 DNA methylation testing was positive in 42 cases and negative in 426 cases. The accuracy of TCT was 36.5%, with a sensitivity of 79.2% and a specificity of 28.8%. The agreement between TCT results and histological diagnosis, assessed using the Kappa statistic, was 0.032 (P > 0.1), indicating no statistically significant agreement. In contrast, the accuracy of PCDHGB7 DNA methylation testing was 89.7%, with a sensitivity of 45.8% and a specificity of 97.7%. The corresponding Kappa value was 0.525 (P < 0.01), indicating statistically significant agreement. As detailed in Tables 3 and 4 (presented below), PCDHGB7 DNA methylation testing demonstrated superior diagnostic performance compared to TCT within the ASC-US subgroup. Table 3. Comparison of TCT Results and PCDHGB7 DNA Methylation Testing Results in the ASC-US Subgroup [n (%)] Histological Diagnosis TCT Detection PCDHGB7 DNA Methylation Testing Positive Negative Positive Negative ≥CIN2 57 (79.2) 15 (20.8) 33 (45.8) 39 (54.2) <CIN2 282 (71.2) 114 (28.8) 9 (2.3) 387 (97.7) *Percentages represent row-wise proportions. Denominators: ≥CIN2 (n=72), <CIN2 (n=396). CIN: cervical intraepithelial neoplasia.* Table 4. Comparison of Diagnostic Performance Between ThinPrep Cytologic Test (TCT) and PCDHGB7 DNA Methylation Testing in the ASC-US Subgroup (%) Test Method Sensitivity Specificity Positive Predictive Value (PPV) Negative Predictive Value (NPV) Accuracy ThinPrep Cytologic Test (TCT) 79.2 28.8 16.8 88.4 36.5 PCDHGB7 DNA Methylation Testing 45.8 97.7 78.6 90.8 89.7 *Performance metrics were calculated using colposcopy-guided biopsy as the reference standard (gold standard) for the detection of histologically confirmed ≥CIN2 lesions within the ASC-US subgroup (n=468). Sensitivity and Specificity calculations were based on 72 ≥CIN2 cases and 396 <CIN2 cases, respectively. PPV, NPV, and accuracy were calculated using the total ASC-US subgroup cohort.* LSIL As shown in Tables 5 and 6, the cohort comprised 426 patients: 297 with LSIL and 129 with NILM, based on the TCT. PCDHGB7 DNA methylation testing was positive in 57 cases and negative in 369 cases. The accuracy of TCT was 37.3%, with a sensitivity of 75.0% and a specificity of 31.1%. The agreement between TCT results and the histological diagnosis, assessed using the Kappa statistic, was 0.023 (P > 0.5), indicating no statistically significant agreement. In contrast, the accuracy of PCDHGB7 DNA methylation testing was 90.8%, with a sensitivity of 65.0% and a specificity of 95.1%. The corresponding Kappa value was 0.614 (P < 0.01), indicating statistically significant agreement. Within the LSIL subgroup, PCDHGB7 DNA methylation testing demonstrated superior diagnostic performance compared to TCT. Table 5. Comparison of TCT Results and PCDHGB7 DNA Methylation Testing Results in the LSIL Subgroup [n (%)] Histological Diagnosis TCT Detection PCDHGB7 DNA Methylation Testing Positive Negative Positive Negative ≥CIN2 45 (75) 15 (25) 39 (65) 21 (35) <CIN2 252 (68.9) 114 (31.1) 18 (4.9) 348 (95.1) *Percentages represent row-wise proportions. Denominators: ≥CIN2 (n=60), <CIN2 (n=366). CIN: cervical intraepithelial neoplasia.* Table 6. Comparison of Diagnostic Performance Between ThinPrep Cytologic Test (TCT) and PCDHGB7 DNA Methylation Testing in the LSIL Subgroup (%) Test Method Sensitivity Specificity Positive Predictive Value (PPV) Negative Predictive Value (NPV) Accuracy ThinPrep Cytologic Test (TCT) 75 31.1 15.2 88.4 37.3 PCDHGB7 DNA Methylation Testing 65 95.1 68.4 94.3 90.8 *Performance metrics were calculated using colposcopy-guided biopsy as the reference standard (gold standard) for the detection of histologically confirmed ≥CIN2 lesions within the LSIL subgroup (n=426). Sensitivity and specificity calculations were based on 60 ≥CIN2 and 366 <CIN2 cases, respectively. PPV, NPV, and accuracy were calculated using the total LSIL subgroup cohort.* ASC-H As shown in Tables 7 and 8, the cohort comprised 234 patients: 105 with ASC-H and 129 with NILM, as determined by the TCT. PCDHGB7 DNA methylation testing was positive in 60 cases and negative in 174 cases. The accuracy of TCT was 82.1%, with a sensitivity of 83.9% and a specificity of 80.9%. The agreement between TCT results and histological diagnosis, assessed using the Kappa statistic, was 0.633 (P < 0.01), indicating statistically significant substantial agreement. In comparison, the accuracy of PCDHGB7 DNA methylation testing was 80.8%, with a sensitivity of 58.1% and a specificity of 95.7%. The corresponding Kappa value was 0.573 (P < 0.01), indicating statistically significant moderate agreement. Within the ASC-H subgroup, PCDHGB7 DNA methylation testing demonstrated a high degree of concordance with histological diagnosis, although slightly lower than that of TCT. Table 7. Comparison of TCT Results and PCDHGB7 DNA Methylation Testing Results in the ASC-H Subgroup [n (%)] Histological Diagnosis TCT Detection PCDHGB7 DNA Methylation Testing Positive Negative Positive Negative ≥CIN2 78 (83.8) 15 (16.2) 54 (58.1) 39 (41.9) <CIN2 27 (19.1) 114 (80.9) 6 (4.3) 135 (95.7) *Percentages represent row-wise proportions. Denominators: ≥CIN2 (n=93), <CIN2 (n=141). CIN: cervical intraepithelial neoplasia. ASC-H: atypical squamous cells, cannot exclude high-grade squamous intraepithelial lesions.* Table 8. Comparison of Diagnostic Performance Between ThinPrep Cytologic Test (TCT) and PCDHGB7 DNA Methylation Testing in the ASC-H Subgroup (%) Test Method Sensitivity Specificity Positive Predictive Value (PPV) Negative Predictive Value (NPV) Accuracy ThinPrep Cytologic Test (TCT) 83.8 80.9 74.3 88.4 37.3 PCDHGB7 DNA Methylation Testing 65 95.1 68.4 94.3 90.8 *Performance metrics were calculated using colposcopy-guided biopsy as the reference standard (gold standard) for the detection of histologically confirmed ≥CIN2 lesions within the ASC-H subgroup (n=234). Sensitivity and Specificity calculations were based on 93 ≥CIN2 cases and 141 <CIN2 cases, respectively. PPV, NPV, and accuracy were calculated using the total ASC-H subgroup cohort. ASC-H: atypical squamous cells, cannot exclude high-grade squamous intraepithelial lesions.* HSIL As shown in Tables 9 and 10, the cohort comprised 270 patients: 141 with HSIL and 129 with NILM, as determined by the TCT. PCDHGB7 DNA methylation testing was positive in 123 cases and negative in 147 cases. The accuracy of TCT was 90.0%, with a sensitivity of 89.6% and a specificity of 90.5%. The agreement between TCT results and histological diagnosis, measured by the Kappa statistic, was 0.799 (P < 0.01), indicating statistically significant near-perfect agreement. PCDHGB7 DNA methylation testing demonstrated an accuracy of 87.8%, with a sensitivity of 81.3% and a specificity of 95.2%. The corresponding Kappa value was 0.757 (P < 0.01), indicating statistically significant substantial agreement. Within the HSIL subgroup, PCDHGB7 DNA methylation testing showed strong concordance with histological diagnosis, comparable to that of TCT. Table 9. Comparison of TCT Results and PCDHGB7 DNA Methylation Testing Results in the HSIL Subgroup [n (%)] Histological Diagnosis TCT Detection PCDHGB7 DNA Methylation Testing Positive Negative Positive Negative ≥CIN2 129 (89.6) 15 (10.4) 117 (81.3) 27 (18.7) <CIN2 12 (9.5) 114 (90.5) 6 (4.8) 120 (95.2) *Percentages represent row-wise proportions. Denominators: ≥CIN2 (n=144), <CIN2 (n=126). CIN: cervical intraepithelial neoplasia; HSIL: high-grade squamous intraepithelial lesion.* Table 10. Comparison of Diagnostic Performance Between ThinPrep Cytologic Test (TCT) and PCDHGB7 DNA Methylation Testing in the HSIL Subgroup (%) Test Method Sensitivity Specificity Positive Predictive Value (PPV) Negative Predictive Value (NPV) Accuracy ThinPrep Cytologic Test (TCT) 89.6 90.5 91.5 88.4 90 PCDHGB7 DNA Methylation Testing 81.3 95.2 95.1 81.6 87.8 *Performance metrics were calculated using colposcopy-guided biopsy as the reference standard for detection of histologically confirmed ≥CIN2 lesions within the HSIL subgroup (n=270). Sensitivity and specificity calculations were based on 144 ≥CIN2 and 126 <CIN2 cases, respectively. PPV, NPV, and accuracy were calculated using the total HSIL subgroup cohort. HSIL: high-grade squamous intraepithelial lesion.* Discussion In this study, we developed a bisulfite-free detection method based on PCDHGB7 methylation level for the triage of non-hrHPV16/18-positive women, with the goal of reducing unnecessary referrals for colposcopy. We further evaluated the diagnostic performance of this methylation-based method across different cytological categories, demonstrating its strength in diverse clinical scenarios. Although DNA methylation has been widely recognized as a promising target for cancer biomarker development, its translation into clinical practice has been limited by the technical complexity of existing detection techniques. To date, only a few methylation biomarkers have been successfully implemented in clinical settings. For instance, FAM19A4/miR124-2 methylation demonstrated a sensitivity of 68.0% and specificity of 78.3% for detecting CIN2+ in a large multicenter cohort study [12]. By contrast, our PCDHGB7 methylation assay showed superior diagnostic performance, with a sensitivity of 69.2% and a notably higher specificity of 96.9% for CIN2+. Several other epigenetic markers, including CADM1, MAL, EPB41L3, POU4F3, PAX1, JAM3, C13ORF18, and TERT, are currently under investigation[13,14]. However, accurate detection of these methylation markers typically relies on advanced techniques such as next-generation sequencing, real-time quantitative methylation-specific PCR, or methylation microarrays. These methods usually require bisulfite treatment, which can cause DNA degradation and loss of genomic complexity, thereby compromising analytical sensitivity. In contrast, the novel bisulfite-free approach adopted in this study targets specific PCDHGB7 hypermethylation sites, offering several advantages over conventional methods. This technique is more stable, convenient, rapid, and cost-effective, making it particularly suitable for large-scale screening and application in resource-limited settings [15,16]. In clinical practice, hrHPV-based screening provides approximately 60-70% greater protection against invasive cervical cancer than cytology alone [17,18]. However, in younger women, especially those infected with non-HPV16/18 genotypes, HPV testing alone may be suboptimal because it cannot reliably distinguish transient infections from those that are persistent and clinically significant. PCDHGB7 methylation detection, as a molecular-based assay, offers high sensitivity and is independent of subjective pathological interpretation. The use of objective and standardized diagnostic criteria reduces interobserver variability and enhances the reproducibility of test results. Colposcopy remains a cornerstone in the diagnostic workup and management of abnormal cervical screening results. However, its diagnostic accuracy is highly dependent on the expertise of the colposcopist [19], with reported sensitivities for CIN2+ detection ranging widely from 65% to 100% [20–25]. In resource-constrained regions, the limited availability of experienced colposcopists further increases the risk of misdiagnosis and inappropriate management [26,27]. Our findings demonstrated that women with positive PCDHGB7 methylation exhibited the highest incidence of CIN2+ lesions, suggesting that this subgroup warrants prioritized clinical attention. Longitudinal studies with extended follow-up are needed to further validate the utility of PCDHGB7 methylation as an effective triage tool to guide colposcopy referral decisions. Despite the promising findings, several limitations of this study should be noted. First, the single-center study may limit the generalizability of the results; validation in multicenter cohorts is therefore warranted. Second, the relatively modest sample size constrained the statistical power of certain subgroup analyses. Additionally, although the diagnostic model demonstrated strong performance, minor refinements may be necessary before widespread clinical implementation. Future studies should enroll larger and more diverse populations, including participants from community-based screening programs, to more comprehensively evaluate the performance of this method. Finally, the absence of long-term follow-up data precluded evaluation of the predictive value of PCDHGB7 methylation for CIN3+ progression risk, which should be addressed in future longitudinal research. Conclusions PCDHGB7 methylation detection represents an effective, noninvasive, and objective triage strategy for women who are hrHPV-positive but not infected with HPV16 or 18. It reduces unnecessary referrals for colposcopy and may serve as an important adjunct to future cervical cancer screening guidelines. Declarations Ethics approval and consent to participant. This study adhered to the Declaration of Helsinki in the ‘Ethics approval andconsent to participate’ section of the Declarations. . This research was written with Ningxia people hospital of Medical Science Ethics Committee approval ([2021]-ZDYF-012). Availability of data and materials Original data are available and can be accessed by contacting Xuechuan Han.All the patient records were identified before been obtained for analysis. The analysis outcomes of all available data were reported in the article. Conflict of interest: Hereby, authors declare no conflict of interest Authors’ contribution: All of the authors contributed to writing and preparing the manuscript. informed consent: Written consent form was obtained from the patient. Funding: This study was funded by the National Key R&D Program of Ningxia Hui Autonomous Region (grant 2022BEG01003). References Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global cancer statistics 2020: GLOBOCAN Estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209-249. 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Kim SI, Kim SJ, Suh DH, Kim K, No JH, Kim YB. Pathologic discrepancies between colposcopy-directed biopsy and loop electrosurgical excision procedure of the uterine cervix in women with cytologic high-grade squamous intraepithelial lesions. J Gynecol Oncol. 2020;31(2):e13. Li X, Zhao Y, Xiang F, Zhang X, Chen Z, Zhang M, Kang X, Wu R. Evaluation of the diagnostic performance of colposcopy in the detection of cervical high-grade squamous intraepithelial lesions among women with transformation zone type 3. BMC Cancer. 2024;24(1):381. Wentzensen N, Walker JL, Gold MA, Smith KM, Zuna RE, Mathews C, Dunn ST, Zhang R, Moxley K, Bishop E, Tenney M, Nugent E, Graubard BI, Wacholder S, Schiffman M. Multiple biopsies and detection of cervical cancer precursors at colposcopy. J Clin Oncol. 2015;33(1):83-89. Dorji N, Tshering S, Choden S, Chhetri M, Bhujel D, Wangden T, Pradhan B, Bhutia PC, Tshomo U. Evaluation of the diagnostic performance of colposcopy in the diagnosis of histologic cervical intraepithelial neoplasia 2+ (CIN2+). BMC Cancer. 2022;22(1):930. Qin D, Bai A, Xue P, Seery S, Wang J, Mendez MJG, Li Q, Jiang Y, Qiao Y. Colposcopic accuracy in diagnosing squamous intraepithelial lesions: a systematic review and meta-analysis of the International Federation of Cervical Pathology and Colposcopy 2011 terminology. BMC Cancer. 2023;23(1):187. Bai A, Wang J, Li Q, Seery S, Xue P, Jiang Y. Assessing colposcopic accuracy for high-grade squamous intraepithelial lesion detection: a retrospective, cohort study. BMC Womens Health. 2022;22(1):9. Wei B, Zhang B, Xue P, Seery S, Wang J, Li Q, Jiang Y, Qiao Y. Improving colposcopic accuracy for cervical precancer detection: a retrospective multicenter study in China. BMC Cancer. 2022;22(1):388. Gustafson LW, Tranberg M, Christensen PN, Brøndum R, Wentzensen N, Clarke MA, Andersen B, Petersen LK, Bor P, Hammer A. Clinical utility of p16/Ki67 dual-stain cytology for detection of cervical intraepithelial neoplasia grade two or worse in women with a transformation zone type 3: a cross-sectional study. BJOG. 2023;130(2):202-209. Booth BB, Tranberg M, Gustafson LW, Christiansen AG, Lapirtis H, Krogh LM, Hjorth IMD, Hammer A. Risk of cervical intraepithelial neoplasia grade 2 or worse in women aged ≥ 69 referred to colposcopy due to an HPV-positive screening test. BMC Cancer. 2023;23(1):405. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 13 Feb, 2026 Editor assigned by journal 13 Feb, 2026 Editor invited by journal 23 Jan, 2026 Submission checks completed at journal 22 Jan, 2026 First submitted to journal 22 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8556133","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":593391149,"identity":"06d057ff-d382-4f3d-86ae-8d221cc598b1","order_by":0,"name":"Xuechuan Han","email":"","orcid":"","institution":"People’s Hospital of Ningxia Hui Autonomous Region, Ningxia Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xuechuan","middleName":"","lastName":"Han","suffix":""},{"id":593391150,"identity":"99eaae02-ea1d-4d1b-8f6c-975b09aa1e57","order_by":1,"name":"Qiaorui Zhang","email":"","orcid":"","institution":"People’s Hospital of Ningxia Hui Autonomous Region, Ningxia Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qiaorui","middleName":"","lastName":"Zhang","suffix":""},{"id":593391152,"identity":"bd42efaa-4196-475a-a388-3a435bd131de","order_by":2,"name":"Yang Fan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0ElEQVRIiWNgGAWjYLCCCgMbHnn2xsYHH4jWcqYiTc6w53Cz4QzitZw5bMxwI71NmoMY1QbHzx5+cbAtLbFx5sMGaQYGOzndBkJazuSlWRxss0lsl05sMC5gSDY2O0BIy4EcM+OPIFtmJzYkz2A4kLiNoJbzb8wMDrYdTmy4ebDhMA9RWm7kGD84APY+Y2MzUVokb7wxYzgADuTEZsYZBkT4he98jvGHA+CoPP78x4cKOzmCWhQOMLBJILmTgHIQkG9gYCY+mYyCUTAKRsHIBAAIsU8zqZwmzwAAAABJRU5ErkJggg==","orcid":"","institution":"People’s Hospital of Ningxia Hui Autonomous Region, Ningxia Medical University","correspondingAuthor":true,"prefix":"","firstName":"Yang","middleName":"","lastName":"Fan","suffix":""}],"badges":[],"createdAt":"2026-01-09 02:53:38","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8556133/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8556133/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103049954,"identity":"304d5f2d-6d24-4207-a7aa-89f1b6b0e74b","added_by":"auto","created_at":"2026-02-20 07:47:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1086590,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8556133/v1/1837ce10-8ab9-4529-8ea7-c2cedbf57b70.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Performance of PCDHGB7 Methylation as a Triage Tool for Cervical Cancer Screening in Non- hrHPV16/18-Positive Women","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCervical cancer (CxCa) remains one of the most prevalent gynecological malignancies and the fourth leading cause of cancer-related mortality among women worldwide, accounting for approximately 6.5% of newly diagnosed cancers annually[1]. China bears a substantial proportion of this burden, with an approximately 110,000 new cases and 60,000 deaths annually, representing nearly 18% and 17% of the global incidence and mortality, highlighting persistent challenges in prevention and early detection [2].\u003c/p\u003e\n\u003cp\u003eProgression from high-grade squamous intraepithelial lesions (HSIL) to invasive CxCa is typically slow, creating a clinically actionable window for early intervention. Current screening guidelines worldwide recommend a combination of ThinPrep Cytologic Test (TCT) and human papillomavirus (hr-HPV) testing as the most widely adopted screening strategy. HPV testing, increasingly used as primary screening modality, offers high sensitivity and strong objectivity, with negative results reliably excluding CxCa risk. However, its limited specificity compromises clinical precision, as it frequently detects transient, self-limiting infections [4]. Moreover, HPV testing cannot distinguish active viral replication from residual viral DNA, nor do they directly identify cervical lesions, resulting in high colposcopy referral rates and the need for additional cytological or histological evaluation [5-7].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBy contrast, TCT enables direct assessment of cellular morphology and exhibits higher specificity, thereby reducing false-positive results. Its sensitivity, however, is suboptimal, increasing the risk of missed diagnoses, and its performance is heavily dependent on operator expertise. This subjectivity contributes to substantial interinstitutional variability, particularly in low- and middle-income settings. Together, these limitations highlight the urgent need for novel screening and triage strategies that combine high sensitivity, high specificity, and robust objectivity.\u003c/p\u003e\n\u003cp\u003eAberrant DNA methylation is a hallmark of carcinogenesis and occurs early in malignant transformation, rendering it an attractive diagnostic[8,9], prognostic, and predictive biomarker across multiple cancer types, including CxCa [10]. Despite this potential, only a limited number of methylation-based biomarkers have been systematic clinical validation.\u003cem\u003e\u0026nbsp;PCDHGB7\u003c/em\u003e, a member of the protocadherin gamma gene cluster involved in neuronal connectivity, has recently identified by Dong\u0026nbsp;\u003cem\u003eet al\u003c/em\u003e. as\u0026nbsp;a novel universal cancer-only marker (UCOM), highlighting its potential utility in cancer detection\u0026nbsp;[11].\u003c/p\u003e\n\u003cp\u003eIn this study, we aimed to further validate the diagnostic performance of a \u003cem\u003ePCDHGB7\u003c/em\u003e methylation assay and to explore its application as a triage strategy for women with non-16/18 hrHPV positivity. By addressing a critical gap in current screening algorithms, this work seeks to improve risk stratification and reduce unnecessary invasive procedures in CxCa screening.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eParticipants\u003c/p\u003e\n\u003cp\u003ePatients meeting the following inclusion criteria were recruited from the outpatient department of Ningxia People\u0026rsquo;s Hospital between January 1, 2023, and December 31, 2023: (1) aged \u0026ge;30 years; (2) underwent HPV and cytology testing in our institution and were non\u0026ndash;16/18 hrHPV-positive; and (3) agreed to use their remaining HPV testing samples for this study. Patients missing cytology information were excluded. Cervical brush samples were collected with written informed consent. All participants were referred for colposcopy, and their remaining samples were anonymized before methylation testing. Additional exclusion criteria included: (1) failed quality control (remaining sample volume \u0026lt;400 \u0026mu;l), (2) failed assay, (3) lost to follow-up without a colposcopy visit, (4) diagnosis of other cancers (e.g., endometrial or ovarian cancer), (5) vaginal or vulvar intraepithelial neoplasia grade 2 or worse, and (6) history of CIN2+. Methylation results and clinical data of eligible patients were included in the analysis. Institutional Review Board approval was obtained from the Ethics Committee of Ningxia People\u0026rsquo;s Hospital.\u003c/p\u003e\n\u003cp\u003eGene\u0026nbsp;methylation detection\u003c/p\u003e\n\u003cp\u003eMethylation testing\u0026nbsp;was performed\u0026nbsp;on\u0026nbsp;the remaining cervical brush samples\u0026nbsp;from\u0026nbsp;HPV testing. A 400 \u0026mu;l volume\u0026nbsp;was used for genomic DNA extraction\u0026nbsp;using the\u0026nbsp;EP Genomic DNA Kit (Epiprobe Biotech, K-21)\u0026nbsp;and\u0026nbsp;an automated nucleic acid extraction\u0026nbsp;system. Subsequently, 100 ng of genomic\u0026nbsp;DNA was used for methylation-sensitive restriction enzyme qPCR (MSRE-qPCR),\u0026nbsp;as described previously.\u0026nbsp;Unlike\u0026nbsp;bisulfite PCR, MSRE-qPCR is based on selective digestion of DNA by methylation-sensitive\u0026nbsp;enzymes,\u0026nbsp;followed by qPCR with primers\u0026nbsp;flanking\u0026nbsp;the \u0026nbsp;enzyme\u0026nbsp;cutting site. CpG sites\u0026nbsp;of\u0026nbsp;\u003cem\u003ePCDHGB7\u0026nbsp;\u003c/em\u003ewere detected,\u0026nbsp;and \u003cem\u003eGAPDH\u0026nbsp;\u003c/em\u003ewas used for normalization.\u0026nbsp;Methylation levels were\u0026nbsp;evaluated\u0026nbsp;using\u0026nbsp;\u0026Delta;Ct = Ct_\u003cem\u003ePCDHGB7\u0026nbsp;\u003c/em\u003e\u0026minus; Ct_\u003cem\u003eGAPDH\u003c/em\u003e.\u0026nbsp;CerMe detection was performed by\u0026nbsp;a\u0026nbsp;dedicated laboratory.\u003c/p\u003e\n\u003cp\u003eHPV testing\u003c/p\u003e\n\u003cp\u003eCervical brush samples were collected by gynecologists and tested using the Roche Cobas 4800 HPV real-time PCR assay, following the manufacturer\u0026rsquo;s protocol. Samples positive for HPV16 or HPV18 were classified as HPV16/18 positive. Samples negative for HPV16/18 but positive for any of the other 12 high-risk types (31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, and 68) were classified as non\u0026ndash;16/18 hrHPV-positive. All samples were collected by qualified gynecologists and tested by certified laboratory personnel.\u003c/p\u003e\n\u003cp\u003eCytology testing\u003c/p\u003e\n\u003cp\u003eCytological samples were collected using broom-type cervical smears (Cervex-Brush\u0026reg;, Rovers Medical Devices) and preserved in SurePath\u0026trade; Preservative Fluid. The ThinPrep\u0026reg; 2000 System was used for automated slide preparation and reading. Cytology was classified using the 2001 Bethesda System as follows: (1) no intraepithelial lesion or malignancy (NILM); (2) ASCUS; (3) atypical glandular cells (AGC); (4) atypical squamous cells, cannot exclude HSIL (ASC-H); (5) LSIL; (6) HSIL; (7) squamous cell carcinoma (SCC); and (8) adenocarcinoma (AC).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eColposcopy biopsy\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll non\u0026ndash;16/18 hrHPV-positive women underwent colposcopy within 2 months of enrollment. Procedures were performed by certified colposcopy specialists and included acetic acid and iodine staining. Guidelines from the ASCCP and CSCCP were followed. Women with all of the following low-risk features could be classified as normal without biopsy: (1) completely normal colposcopic impression, (2) type 1 transformation zone, (3) age \u0026lt;40 years, (4) \u0026lt;HSIL cytology, and (5) no HPV16/18 infection. Others underwent 2\u0026ndash;4 targeted biopsies and, when indicated, endocervical curettage (ECC). Histopathology results were categorized as: (1) normal, (2) CIN1, (3) CIN2/3 (including CIN2, CIN2\u0026ndash;3, CIN3), and (4) cervical cancer (including AC, SCC, or cervical sarcoma). CIN1\u0026minus; included normal and CIN1; CIN2+ included CIN2/3 and cancer. Colposcopists were blinded to methylation results.\u003c/p\u003e\n\u003cp\u003eStatistical analysis\u003c/p\u003e\n\u003cp\u003eStatistical analyses were performed using GraphPad Prism 9 and Microsoft Excel. ROC curves were used to quantify diagnostic performance using the hybrid Wilson/Brown method. Differences in methylation levels between CIN1\u0026minus; and CIN2+ were compared using a two-tailed unpaired parametric test. A \u003cem\u003eP\u0026nbsp;\u003c/em\u003evalue \u0026lt;0.05 was considered statistically significant (*\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05, **\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.01, ***\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.001, ****\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.0001). Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated using 2 \u0026times; 2 contingency tables. Missing data were excluded from analysis.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 1,038 patients were high-risk HPV-positive (non-HPV16/18). The ThinPrep Cytology Test (TCT) results were as follows: NILM, 129 cases (12.4%, 129/1038); ASC-US, 339 cases (32.7%, 339/1038); ASC-H, 105 cases (10.1%, 105/1038); LSIL, 297 cases (28.6%, 297/1038); AGC, 6 cases (0.6%, 6/1038); SCC, 15 cases (1.4%, 15/1038); AIS, 6 cases (0.6%, 6/1038); and HSIL, 141 cases (13.6%, 141/1038). Among these, the 6 cases of AGC and 6 cases of AIS were ultimately diagnosed as cervical adenocarcinoma. Due to the limited sample size, AGC and AIS cases were not included in subgroup comparative analyses or performance evaluations.\u003c/p\u003e\n\u003cp\u003eComparison of diagnostic performance between TCT and PCDHGB7 gene methylation\u003c/p\u003e\n\u003cp\u003eAmong the 1,038 patients, 909 (87.6%) had positive TCT results. Colposcopy-guided biopsy, used as the gold standard, yielded positive results in 351 cases (33.8%) and negative results in 687 cases (66.2%). PCDHGB7 methylation was positive in 264 cases (25.4%) and negative in 774 cases (74.6%). The accuracy of TCT was 43.1%, with a sensitivity of 95.7% and a specificity of 16.5%. The Kappa value for agreement between TCT and the gold standard was 0.088 (P \u0026lt; 0.01), indicating statistically significant but slight agreement. These results demonstrate that PCDHGB7 DNA methylation testing showed stronger agreement with the gold standard than TCT.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Comparison of TCT and DNA Methylation Results [n (%)]\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistological\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eDiagnosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 39px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTCT Detection\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDNA Methylation Detection\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026ge;CIN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e336 (95.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e15 (4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e243 (69.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e108 (30.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u0026lt;CIN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e573 (83.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e114 (16.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e21 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e666 (96.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eValues represent n (%). Percentages are calculated using the total number within each histological diagnosis group as the denominator.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Comparison of Diagnostic Performance Between ThinPrep Cytologic Test (TCT) and PCDHGB7 DNA Methylation Testing (%)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTest Method\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003ePositive Predictive Value (PPV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eNegative Predictive Value (NPV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eAccuracy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eThinPrep Cytologic Test (TCT)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e95.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e16.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e36.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e88.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e43.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003ePCDHGB7 DNA Methylation Testing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e69.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e96.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e92.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e86.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e87.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Performance metrics were calculated using colposcopy-guided biopsy as the reference standard (gold standard). Sensitivity and specificity were calculated for the detection of histologically confirmed \u0026ge;CIN2 lesions. PPV, NPV, and accuracy were calculated based on the total study population (n=1038).*\u003c/p\u003e\n\u003cp\u003eComparison of diagnostic performance between TCT and PCDHGB7 gene methylation across stratified subgroups\u003c/p\u003e\n\u003cp\u003eThe diagnostic performance of the two testing methods was compared against the histopathological diagnosis (used as the gold standard) across stratified cytological subgroups. Diagnostic validity metrics\u0026mdash;including accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV)\u0026mdash;were evaluated. The specific results are presented below.\u003c/p\u003e\n\u003cp\u003eASC-US\u003c/p\u003e\n\u003cp\u003eThe cohort included 468 patients: 339 with ASC-US and 129 with NILM on the TCT. PCDHGB7 DNA methylation testing was positive in 42 cases and negative in 426 cases. The accuracy of TCT was 36.5%, with a sensitivity of 79.2% and a specificity of 28.8%. The agreement between TCT results and histological diagnosis, assessed using the Kappa statistic, was 0.032 (P \u0026gt; 0.1), indicating no statistically significant agreement. In contrast, the accuracy of PCDHGB7 DNA methylation testing was 89.7%, with a sensitivity of 45.8% and a specificity of 97.7%. The corresponding Kappa value was 0.525 (P \u0026lt; 0.01), indicating statistically significant agreement. As detailed in Tables 3 and 4 (presented below), PCDHGB7 DNA methylation testing demonstrated superior diagnostic performance compared to TCT within the ASC-US subgroup.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Comparison of TCT Results and PCDHGB7 DNA Methylation Testing Results in the ASC-US Subgroup [n (%)]\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 95px;\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eHistological Diagnosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTCT Detection\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCDHGB7 DNA Methylation Testing\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026ge;CIN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e57 (79.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e15 (20.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e33 (45.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e39 (54.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026lt;CIN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e282 (71.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e114 (28.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e9 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e387 (97.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Percentages represent row-wise proportions. Denominators: \u0026ge;CIN2 (n=72), \u0026lt;CIN2 (n=396). CIN: cervical intraepithelial neoplasia.*\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. Comparison of Diagnostic Performance Between ThinPrep Cytologic Test (TCT) and PCDHGB7 DNA Methylation Testing in the ASC-US Subgroup (%)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eTest Method\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003ePositive Predictive Value (PPV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eNegative Predictive Value (NPV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eAccuracy\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eThinPrep Cytologic Test (TCT)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e79.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e28.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e16.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e88.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e36.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003ePCDHGB7 DNA Methylation Testing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e45.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e97.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e78.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e90.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e89.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Performance metrics were calculated using colposcopy-guided biopsy as the reference standard (gold standard) for the detection of histologically confirmed \u0026ge;CIN2 lesions within the ASC-US subgroup (n=468). Sensitivity and Specificity calculations were based on 72 \u0026ge;CIN2 cases and 396 \u0026lt;CIN2 cases, respectively. PPV, NPV, and accuracy were calculated using the total ASC-US subgroup cohort.*\u003c/p\u003e\n\u003cp\u003eLSIL\u003c/p\u003e\n\u003cp\u003eAs shown in Tables 5 and 6, the cohort comprised 426 patients: 297 with LSIL and 129 with NILM, based on the TCT. PCDHGB7 DNA methylation testing was positive in 57 cases and negative in 369 cases. The accuracy of TCT was 37.3%, with a sensitivity of 75.0% and a specificity of 31.1%. The agreement between TCT results and the histological diagnosis, assessed using the Kappa statistic, was 0.023 (P \u0026gt; 0.5), indicating no statistically significant agreement. In contrast, the accuracy of PCDHGB7 DNA methylation testing was 90.8%, with a sensitivity of 65.0% and a specificity of 95.1%. The corresponding Kappa value was 0.614 (P \u0026lt; 0.01), indicating statistically significant agreement. Within the LSIL subgroup, PCDHGB7 DNA methylation testing demonstrated superior diagnostic performance compared to TCT.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5. Comparison of TCT Results and PCDHGB7 DNA Methylation Testing Results in the LSIL Subgroup [n (%)]\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistological Diagnosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTCT Detection\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCDHGB7 DNA Methylation Testing\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026ge;CIN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e45 (75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e15 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e39 (65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e21 (35)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026lt;CIN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e252 (68.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e114 (31.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e18 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e348 (95.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Percentages represent row-wise proportions. Denominators: \u0026ge;CIN2 (n=60), \u0026lt;CIN2 (n=366). CIN: cervical intraepithelial neoplasia.*\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6. Comparison of Diagnostic Performance Between ThinPrep Cytologic Test (TCT) and PCDHGB7 DNA Methylation Testing in the LSIL Subgroup (%)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTest Method\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003ePositive Predictive Value (PPV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eNegative Predictive Value (NPV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eAccuracy\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eThinPrep Cytologic Test (TCT)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e31.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e15.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e88.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e37.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003ePCDHGB7 DNA Methylation Testing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e95.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e68.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e94.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e90.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Performance metrics were calculated using colposcopy-guided biopsy as the reference standard (gold standard) for the detection of histologically confirmed \u0026ge;CIN2 lesions within the LSIL subgroup (n=426). Sensitivity and specificity calculations were based on 60 \u0026ge;CIN2 and 366 \u0026lt;CIN2 cases, respectively. PPV, NPV, and accuracy were calculated using the total LSIL subgroup cohort.*\u003c/p\u003e\n\u003cp\u003eASC-H\u003c/p\u003e\n\u003cp\u003eAs shown in Tables 7 and 8, the cohort comprised 234 patients: 105 with ASC-H and 129 with NILM, as determined by the TCT. PCDHGB7 DNA methylation testing was positive in 60 cases and negative in 174 cases. The accuracy of TCT was 82.1%, with a sensitivity of 83.9% and a specificity of 80.9%. The agreement between TCT results and histological diagnosis, assessed using the Kappa statistic, was 0.633 (P \u0026lt; 0.01), indicating statistically significant substantial agreement. In comparison, the accuracy of PCDHGB7 DNA methylation testing was 80.8%, with a sensitivity of 58.1% and a specificity of 95.7%. The corresponding Kappa value was 0.573 (P \u0026lt; 0.01), indicating statistically significant moderate agreement. Within the ASC-H subgroup, PCDHGB7 DNA methylation testing demonstrated a high degree of concordance with histological diagnosis, although slightly lower than that of TCT.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7. Comparison of TCT Results and PCDHGB7 DNA Methylation Testing Results in the ASC-H Subgroup [n (%)]\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistological Diagnosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTCT Detection\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCDHGB7 DNA Methylation Testing\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026ge;CIN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e78 (83.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e15 (16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e54 (58.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e39 (41.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026lt;CIN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e27 (19.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e114 (80.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e6 (4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e135 (95.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Percentages represent row-wise proportions. Denominators: \u0026ge;CIN2 (n=93), \u0026lt;CIN2 (n=141). CIN: cervical intraepithelial neoplasia. ASC-H: atypical squamous cells, cannot exclude high-grade squamous intraepithelial lesions.*\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 8. Comparison of Diagnostic Performance Between ThinPrep Cytologic Test (TCT) and PCDHGB7 DNA Methylation Testing in the ASC-H Subgroup (%)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTest Method\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003ePositive Predictive Value (PPV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eNegative Predictive Value (NPV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eAccuracy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eThinPrep Cytologic Test (TCT)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e83.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e80.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e74.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e88.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e37.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003ePCDHGB7 DNA Methylation Testing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e95.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e68.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e94.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e90.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Performance metrics were calculated using colposcopy-guided biopsy as the reference standard (gold standard) for the detection of histologically confirmed \u0026ge;CIN2 lesions within the ASC-H subgroup (n=234). Sensitivity and Specificity calculations were based on 93 \u0026ge;CIN2 cases and 141 \u0026lt;CIN2 cases, respectively. PPV, NPV, and accuracy were calculated using the total ASC-H subgroup cohort. ASC-H: atypical squamous cells, cannot exclude high-grade squamous intraepithelial lesions.*\u003c/p\u003e\n\u003cp\u003eHSIL\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs shown in Tables 9 and 10, the cohort comprised 270 patients: 141 with HSIL and 129 with NILM, as determined by the TCT. PCDHGB7 DNA methylation testing was positive in 123 cases and negative in 147 cases. The accuracy of TCT was 90.0%, with a sensitivity of 89.6% and a specificity of 90.5%. The agreement between TCT results and histological diagnosis, measured by the Kappa statistic, was 0.799 (P \u0026lt; 0.01), indicating statistically significant near-perfect agreement. PCDHGB7 DNA methylation testing demonstrated an accuracy of 87.8%, with a sensitivity of 81.3% and a specificity of 95.2%. The corresponding Kappa value was 0.757 (P \u0026lt; 0.01), indicating statistically significant substantial agreement. Within the HSIL subgroup, PCDHGB7 DNA methylation testing showed strong concordance with histological diagnosis, comparable to that of TCT.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 9. Comparison of TCT Results and PCDHGB7 DNA Methylation Testing Results in the HSIL Subgroup [n (%)]\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistological Diagnosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTCT Detection\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePCDHGB7 DNA Methylation Testing\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026ge;CIN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e129 (89.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e15 (10.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e117 (81.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e27 (18.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e\u0026lt;CIN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e12 (9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e114 (90.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e6 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 95px;\"\u003e\n \u003cp\u003e120 (95.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Percentages represent row-wise proportions. Denominators: \u0026ge;CIN2 (n=144), \u0026lt;CIN2 (n=126). CIN: cervical intraepithelial neoplasia; HSIL: high-grade squamous intraepithelial lesion.*\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 10. Comparison of Diagnostic Performance Between ThinPrep Cytologic Test (TCT) and PCDHGB7 DNA Methylation Testing in the HSIL Subgroup (%)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTest Method\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003ePositive Predictive Value (PPV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eNegative Predictive Value (NPV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eAccuracy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eThinPrep Cytologic Test (TCT)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e89.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e90.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e91.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e88.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003ePCDHGB7 DNA Methylation Testing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e81.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e95.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e95.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e81.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e87.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Performance metrics were calculated using colposcopy-guided biopsy as the reference standard for detection of histologically confirmed \u0026ge;CIN2 lesions within the HSIL subgroup (n=270). Sensitivity and specificity calculations were based on 144 \u0026ge;CIN2 and 126 \u0026lt;CIN2 cases, respectively. PPV, NPV, and accuracy were calculated using the total HSIL subgroup cohort. HSIL: high-grade squamous intraepithelial lesion.*\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we developed a bisulfite-free detection method based on PCDHGB7 methylation level for the triage of non-hrHPV16/18-positive women, with the goal of reducing unnecessary referrals for colposcopy. We further evaluated the diagnostic performance of this methylation-based method across different cytological categories, demonstrating its strength in diverse clinical scenarios.\u003c/p\u003e\n\u003cp\u003eAlthough DNA methylation has been widely recognized as a promising target for cancer biomarker development, its translation into clinical practice has been limited by the technical complexity of existing detection techniques. To date, only a few methylation biomarkers have been successfully implemented in clinical settings. For instance, FAM19A4/miR124-2 methylation demonstrated a sensitivity of 68.0% and specificity of 78.3% for detecting CIN2+ in a large multicenter cohort study [12]. By contrast, our PCDHGB7 methylation assay showed superior diagnostic performance, with a sensitivity of 69.2% and a notably higher specificity of 96.9% for CIN2+. Several other epigenetic markers, including CADM1, MAL, EPB41L3, POU4F3, PAX1, JAM3, C13ORF18, and TERT, are currently under investigation[13,14]. However, accurate detection of these methylation markers typically relies on advanced techniques such as next-generation sequencing, real-time quantitative methylation-specific PCR, or methylation microarrays. These methods usually require bisulfite treatment, which can cause DNA degradation and loss of genomic complexity, thereby compromising analytical sensitivity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn contrast, the novel bisulfite-free approach adopted in this study targets specific PCDHGB7 hypermethylation sites, offering several advantages over conventional methods. This technique is more stable, convenient, rapid, and cost-effective, making it particularly suitable for large-scale screening and application in resource-limited settings [15,16].\u003c/p\u003e\n\u003cp\u003eIn clinical practice, hrHPV-based screening provides approximately 60-70% greater protection against invasive cervical cancer than cytology alone [17,18]. However, in younger women, especially those infected with non-HPV16/18 genotypes, HPV testing alone may be suboptimal because it cannot reliably distinguish transient infections from those that are persistent and clinically significant.\u0026nbsp;\u003cem\u003ePCDHGB7\u0026nbsp;\u003c/em\u003emethylation detection, as a molecular-based assay, offers high sensitivity and is independent of subjective pathological interpretation. The use of objective and standardized diagnostic criteria reduces interobserver variability and enhances the reproducibility of test results.\u003c/p\u003e\n\u003cp\u003eColposcopy remains a cornerstone in the diagnostic workup and management of abnormal cervical screening results. However, its diagnostic accuracy is highly dependent on the expertise of the colposcopist [19], with reported sensitivities for CIN2+ detection ranging widely from 65% to 100% [20\u0026ndash;25]. In resource-constrained regions, the limited availability of experienced colposcopists further increases the risk of misdiagnosis and inappropriate management [26,27]. Our findings demonstrated that women with positive\u0026nbsp;\u003cem\u003ePCDHGB7\u0026nbsp;\u003c/em\u003emethylation exhibited the highest incidence of CIN2+ lesions, suggesting that this subgroup warrants prioritized clinical attention. Longitudinal studies with extended follow-up are needed to further validate the utility of\u0026nbsp;\u003cem\u003ePCDHGB7\u0026nbsp;\u003c/em\u003emethylation as an effective triage tool to guide colposcopy referral decisions.\u003c/p\u003e\n\u003cp\u003eDespite the promising findings, several limitations of this study should be noted. First, the single-center study may limit the generalizability of the results; validation in multicenter cohorts is therefore warranted. Second, the relatively modest sample size constrained the statistical power of certain subgroup analyses. Additionally, although the diagnostic model demonstrated strong performance, minor refinements may be necessary before widespread clinical implementation. Future studies should enroll larger and more diverse populations, including participants from community-based screening programs, to more comprehensively evaluate the performance of this method. Finally, the absence of long-term follow-up data precluded evaluation of the predictive value of\u0026nbsp;\u003cem\u003ePCDHGB7\u0026nbsp;\u003c/em\u003emethylation for CIN3+ progression risk, which should be addressed in future longitudinal research.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003ePCDHGB7 methylation detection represents an effective, noninvasive, and objective triage strategy for women who are hrHPV-positive but not infected with HPV16 or 18. It reduces unnecessary referrals for colposcopy and may serve as an important adjunct to future cervical cancer screening guidelines.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participant. \u003c/strong\u003eThis study adhered to the Declaration of Helsinki in the \u0026lsquo;Ethics approval andconsent to participate\u0026rsquo; section of the Declarations.\u003cstrong\u003e.\u003c/strong\u003eThis research was written with Ningxia people hospital of Medical Science Ethics Committee approval ([2021]-ZDYF-012).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e Original data are available and can be accessed by contacting Xuechuan Han.All the patient records were identified before been obtained for analysis. The analysis outcomes of all available data were reported in the article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u0026nbsp;\u003c/strong\u003eHereby, authors declare no conflict of interest\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contribution:\u0026nbsp;\u003c/strong\u003eAll of the authors contributed to writing and preparing the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003einformed consent:\u0026nbsp;\u003c/strong\u003eWritten consent form was obtained from the patient.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis study was funded by the National Key R\u0026amp;D Program of Ningxia Hui Autonomous Region (grant 2022BEG01003).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. 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BMC Cancer. 2022;22(1):388.\u003c/li\u003e\n\u003cli\u003eGustafson LW, Tranberg M, Christensen PN, Br\u0026oslash;ndum R, Wentzensen N, Clarke MA, Andersen B, Petersen LK, Bor P, Hammer A. Clinical utility of p16/Ki67 dual-stain cytology for detection of cervical intraepithelial neoplasia grade two or worse in women with a transformation zone type 3: a cross-sectional study. BJOG. 2023;130(2):202-209. \u003c/li\u003e\n\u003cli\u003eBooth BB, Tranberg M, Gustafson LW, Christiansen AG, Lapirtis H, Krogh LM, Hjorth IMD, Hammer A. Risk of cervical intraepithelial neoplasia grade 2 or worse in women aged\u0026thinsp;\u0026ge;\u0026thinsp;69 referred to colposcopy due to an HPV-positive screening test. BMC Cancer. 2023;23(1):405.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"PCDHGB7, DNA hypermethylation, non-16/18 hrHPV, Triage, Cervical Cancer screening","lastPublishedDoi":"10.21203/rs.3.rs-8556133/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8556133/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThe implementation of high-risk human papillomavirus (hrHPV)-based screening has greatly reduced the incidence and mortality of cervical cancer. However, an effective, noninvasive triage strategy that is independent of subjective pathological interpretation is urgently required to decrease unnecessary colposcopy referrals in non hrHPV16/18-positive women.\u003c/p\u003e\u003ch2\u003eMaterials and methods\u003c/h2\u003e \u003cp\u003eA total of 1038 non HPV16/18-positive women aged 30\u0026ndash;80 years (median\u0026thinsp;=\u0026thinsp;40 years) were enrolled from Ningxia People\u0026rsquo;s Hospital. The performance of \u003cem\u003ePCDHGB7\u003c/em\u003e methylation level detection as a triage tool for identifying cervical cancer and high-grade precancerous lesions was evaluated.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e \u003cem\u003ePCDHGB7\u003c/em\u003e hypermethylation efficiently distinguished cervical intraepithelial neoplasia grade 2 or worse (CIN2+) from CIN1 or normal histology (CIN1-), demonstrating high sensitivity (69.2%) and excellent specificity (96.9%). Notably, \u003cem\u003ePCDHGB7\u003c/em\u003e hypermethylation show strong triage performance in non-HPV16/18-positive women with abnormal cytology, including ASC-US (sensitivity 45.8%, specificity 97.7%) and LSIL (sensitivity 65.0%, specificity 95.1%). Furthermore, favourable performance was observed in women ASC-H (sensitivity 65.0%, specificity 95.1%) and HSIL (sensitivity 81.3%, specificity 95.2%).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003e \u003cem\u003ePCDHGB7\u003c/em\u003e hypermethylation detection represents a promising triage strategy for non-hrHPV16/18-positive women, offering high specificity and reliable sensitivity for CIN2\u0026thinsp;+\u0026thinsp;detection. Its application may substantially reduce unnecessary colposcopy-referrals and improve the efficiency of cervical cancer screening programs.\u003c/p\u003e","manuscriptTitle":"Performance of PCDHGB7 Methylation as a Triage Tool for Cervical Cancer Screening in Non- hrHPV16/18-Positive Women","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-19 14:28:12","doi":"10.21203/rs.3.rs-8556133/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-02-13T14:06:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-13T07:59:10+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-24T04:33:28+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-22T23:07:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2026-01-22T23:01:38+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f16c7b7c-a2d0-4eed-b3a2-ab01f8b70a34","owner":[],"postedDate":"February 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-19T14:28:12+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-19 14:28:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8556133","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8556133","identity":"rs-8556133","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}