CervicalMethDx - A Precision DNA Methylation Test to Identify Risk of High-Grade Intraepithelial Lesions in Cervical Cancer Screening Algorithms

Sep 23, 2026

Uploaded by Mimi

CervicalMethDx is a precision DNA methylation classifier designed to triage women with HPV-positive samples in cervical cancer screening algorithms. 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).

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages10

Reading Time25 min

AccessFree to download

Introduction

Validation study overview

Performance results

Prevention relevance

Future evaluation needs

CervicalMethDx: A Precision DNA Methylation Test to Identify Risk of High-Grade Intraepithelial Lesions in Cervical Cancer Screening Algorithms Laura 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, Ashley Ramos-Lopez5, Josefina Romaguera6, Bruce J. Trock7, Teresa D´ıaz-Montes8, David Sidransky1,3, Mariana Brait1,3, and Rafael Guerrero-Preston5,9 | | | | A | | B | S | | T | R | | A | | C | T | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 􀀶 | | 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.
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. | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | In

FAQs

What clinical role does the CervicalMethDx test target in screening algorithms?

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.

How was CervicalMethDx validated and what assay was used?

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.

What classification performance did CervicalMethDx show for CIN2 and CIN3?

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.

Sep 23, 2026

Uploaded by Mimi