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A blinded retrospective study assessed DNA methylation in three gene promoters (ZNF516, FKBP6, INTS1) plus a control gene (β-actin) using quantitative real-time methylation-specific PCR and machine learning. The test achieved 95% classification of CIN2 with 91% sensitivity and 100% specificity (AUC 0.96), and 94% for CIN3 with 90% sensitivity and 100% specificity (AUC 0.96). It also classified combined CIN2/CIN3 at 94% (93% sensitivity, 97% specificity, AUC 0.96).",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/cervicalmethdx-a-precision-dna-methylation-test-to-identify-risk-of-high-grade-intraepithelial-lesions-in-cervical-cancer-screening-algorithms/372660/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/cervicalmethdx-a-precision-dna-methylation-test-to-identify-risk-of-high-grade-intraepithelial-lesions-in-cervical-cancer-screening-algorithms/372660.png","ImageObject",300,407,{"name":92,"@type":93},"Mimi","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-29","2026-09-23",true,{"@type":102,"interactionType":103,"userInteractionCount":52},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What clinical role does the CervicalMethDx test target in screening algorithms?","Question",{"text":112,"@type":113},"CervicalMethDx is intended as a reflex test for women with HPV-positive samples to help identify risk of high-grade intraepithelial lesions and support referral decisions for colposcopy and biopsy.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How was CervicalMethDx validated and what assay was used?",{"text":117,"@type":113},"Validation used a blinded retrospective study of PreservCyt samples, measuring DNA methylation in ZNF516, FKBP6, and INTS1 plus β-actin using quantitative real-time methylation-specific PCR (qMSP) combined with machine learning.",{"name":119,"@type":110,"acceptedAnswer":120},"What classification performance did CervicalMethDx show for CIN2 and CIN3?",{"text":121,"@type":113},"For CIN2, the test correctly classified 95% of samples with 91% sensitivity, 100% specificity, and AUC 0.96. For CIN3, it correctly classified 94% with 90% sensitivity, 100% specificity, and AUC 0.96.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},372660,1790247080,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":52,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":52,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":144},2336477974920,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","CervicalMethDx: A Precision DNA Methylation Test to Identify Risk of High-Grade Intraepithelial Lesions in Cervical Cancer Screening Algorithms  \nLaura Palmieri1,2,3, Fernando T. Zamuner1,3, Dieila Giomo de Lima1,3,4, Keerthana Gosala1, Eli Winkler1, Yash Prashar1, Ana Purcell-Wiltz5, Amanda Garc´ıa-Negrn5,  \nAshley Ramos-Lopez5, Josefina Romaguera6, Bruce J. Trock7, Teresa D´ıaz-Montes8, David Sidransky1,3, Mariana Brait1,3, and Rafael Guerrero-Preston5,9  \n|  |  |  | A |  | B | S |  | T | R |  | A |  | C | T |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |\n| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |\n| 􀀶 |  | Cervical cancer is one of the most common cancers in women. Despite progress in prevention and success in early detection through cytologic screening and human papillomavirus (HPV) detection, there remains a challenge in triaging women appropriately to colposcopy and biopsy. We sought to validate the CervicalMethDx test, a precision DNA methylation classifier for cervical cancer detection, as a reflex test in women with HPV-positive samples. A blinded retrospective study was performed on well-characterized samples in PreservCyt media from a large referral clinical laboratory in the United States. DNA methylation was assessed in three gene promoters (ZNF516, FKBP6, and INTS1) and a control gene (β-actin) by quantitative realtime methylation-specific PCR (qMSP) analysis, using machine learning algorithms. We compared DNA methylation levels in HPV-positive patients presenting with lesions in the Pap test and cervical intraepithelial neoplasia grade 2 (CIN2) or CIN3 histologic diagnosis with DNA methylation levels in HPV-positive patients with lesions in the Pap test but no intraepithelial lesion or malignancy. The CervicalMethDx test correctly classified 95% of the CIN2 samples (n ¼ 210), |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | with 91% sensitivity, 100% specificity, and an area under the ROC curve (AUC) of 0.96, and 94% of CIN3 samples (n ¼ 141), with 90% sensitivity, 100% specificity, and an AUC of 0.96. Moreover, the CervicalMethDx test correctly classified 94% of combined CIN2/CIN3 samples (n ¼ 351), with 93% sensitivity, 97% specificity, and an AUC of 0.96. CervicalMethDx demonstrated strong discriminatory power for identifying CIN2/CIN3 risk and may complement current triage strategies for colposcopy referral. Prospective, population-based studies, including those in low-resource settings, are needed for further evaluation.\u003Cbr>Prevention Relevance: The CervicalMethDx test integrates DNA methylation analysis and machine learning to improve early detection of high-grade cervical lesions (high-grade squamous intraepithelial lesions), offering anoninvasive, cost-effective screening tool. Enhanced risk stratification and overtreatment reduction expand equitable access to precision prevention programs. Further validation will clarify CervicalMethDx’s alignment with global cervical cancer prevention strategies. |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |\n\nIn","cbCaihmZ0sM0WIOY","https://ap.wps.com/l/cbCaihmZ0sM0WIOY","pdf",1693192,"English","# Introduction\n## Validation study overview\n## Performance results\n## Prevention relevance\n## Future evaluation needs","[{\"question\":\"What clinical role does the CervicalMethDx test target in screening algorithms?\",\"answer\":\"CervicalMethDx is intended as a reflex test for women with HPV-positive samples to help identify risk of high-grade intraepithelial lesions and support referral decisions for colposcopy and biopsy.\"},{\"question\":\"How was CervicalMethDx validated and what assay was used?\",\"answer\":\"Validation used a blinded retrospective study of PreservCyt samples, measuring DNA methylation in ZNF516, FKBP6, and INTS1 plus β-actin using quantitative real-time methylation-specific PCR (qMSP) combined with machine learning.\"},{\"question\":\"What classification performance did CervicalMethDx show for CIN2 and CIN3?\",\"answer\":\"For CIN2, the test correctly classified 95% of samples with 91% sensitivity, 100% specificity, and AUC 0.96. For CIN3, it correctly classified 94% with 90% sensitivity, 100% specificity, and AUC 0.96.\"}]","CervicalMethDx - A Precision DNA Methylation Test to Identify Risk of High-Grade Intraepithelial Lesions in Cervical Cancer Screening Algorithms | PDF",1790195060,25]