Detection of CADM1, MAL, and PAX1 Methylation by ddPCR for Triage of HPV-Positive Cervical Lesions - Maria Anisimova; Mark Jain; Liya Shcherbakova; Liana Aminova; Andrey Bugerenko; Natalia Novitskaya; Larisa Samokhodskaya; Vladislav Kokarev; Victoria Inokenteva; Olga Panina (Biomedicines, 2025)
The aberrant DNA methylation of tumour suppressor genes, including CADM1, MAL, and PAX1, is implicated in cervical carcinogenesis. Objectives: This pilot study aimed to evaluate the methylation levels of these genes in HPV-positive women and assess their diagnostic performance for detecting histologic high-grade squamous intraepithelial lesions (HSILs) and carcinoma. Methods: Cervical samples from 73 HPV-positive women were analyzed using droplet digital PCR (ddPCR) to quantify methylation levels of CADM1, MAL, and PAX1. The methylation levels were further compared across cytological and histological classifications. A control group of 26 HPV-negative women with negative cytology was also included. The diagnostic performance was assessed through receiver operating characteristic (ROC) analysis, as well as sensitivity and specificity calculations for individual genes and gene panels. Results: MAL methylation was absent in NILM, LSIL, and HSIL samples but was significantly elevated in carcinoma. PAX1 methylation was observed in both high-grade and some low-grade lesions. CADM1 methylation remained low or undetectable in the NILM, LSIL, and HSIL groups, with a significant increase observed in carcinoma cases. The CADM1/MAL panel demonstrated the highest diagnostic accuracy, with an area under the curve (AUC) of 0.912, 70% sensitivity, and 100% specificity. ddPCR exhibited superior analytical sensitivity compared to real-time PCR. Conclusions: The CADM1/MAL methylation panel, assessed by ddPCR, may serve as a specific biomarker for the triage of HPV-positive women at risk of HSIL and carcinoma. However, this study’s limited sample size and single-centre design necessitate cautious interpretation. Further validation in larger, population-based cohorts is necessary to confirm its clinical utility.