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Towards Objective Anal Cancer Screening: From Swab-Based Genome-Wide Methylation Marker Discovery to Novel Test Development

Anal high-grade squamous intraepithelial lesions (HSIL-AIN2/3) are precursors to anal cancer, and early detection and treatment through screening is crucial for effective cancer prevention. Current guidelines recommend anal swab-based screening and highlight the need for objective biomarkers to improve risk stratification. While DNA methylation markers have shown strong potential in anal biopsies, their performance in anal swabs is reduced, likely due to sample-type dependency. This study aimed to identify a DNA methylation classifier specifically derived from anal swabs of men who have sex with men living with HIV (MSMLWH) to enhance diagnostic accuracy. Genome-wide methylation profiling was performed on anal swabs from 36 HSIL-AIN3 cases, 34 controls (<low-grade squamous intraepithelial lesions (<LSIL)), and 7 anal cancer patients using the 850K Infinium MethylationEPIC BeadChip (Illumina). Candidate CpG sites were selected via logistic regression with adaptive multi-group ridge penalties using co-data and an empirical Bayes approach (ecpc). The top candidate markers were validated using quantitative methylation-specific PCR (qMSP) on an independent series of 204 swabs to identify an optimal methylation classifier. Ecpc analysis identified 50 CpG sites with a combined area-under-the-curve (AUC) of 0.80. All ten candidate markers evaluated by qMSP showed significant increases in methylation levels associated with disease severity (p<0.001). From these, a 3-gene methylation classifier was identified, demonstrating excellent performance with an AUC of 0.80 (95% confidence interval:0.72-0.88) in distinguishing HSIL-AIN3+ from ≤LSIL. This study identified a robust 3-gene methylation classifier with strong potential for detecting HSIL-AIN3 and anal cancer when applied to anal swabs from MSMLWH.

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Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID Description Technology Samples
EGAD00010002832 Illumina Infinium MethylationEPIC 850K BeadChip 86