The use of Human Papillomavirus DNA Methylation in cervical intraepithelial neoplasia: a systematic review and meta-analysis

Background Methylation of viral DNA has been proposed as a novel biomarker for triage of human papillomavirus (HPV) positive women at screening. This systematic review and meta-analysis aims to assess how methylation levels change with disease severity and to determine diagnostic test accuracy (DTA) in detecting high-grade cervical intra-epithelial neoplasia (CIN). Methods We performed searches in MEDLINE, EMBASE and CENTRAL from inception to October 2019. Studies were eligible if they explored HPV methylation levels in HPV positive women. Data were extracted in duplicate and requested from authors where necessary. Random-effects models and a bivariate mixed-effects binary regression model were applied to determine pooled effect estimates. Findings 44 studies with 8819 high-risk HPV positive women were eligible. The pooled estimates for positive methylation rate in HPV16 L1 gene were higher for high-grade CIN (≥CIN2/high-grade squamous intra-epithelial lesion (HSIL) (95% confidence interval (95%CI:72·7% (47·8–92·2))) vs. low-grade CIN (≤CIN1/low-grade squamous intra-epithelial lesion (LSIL) (44·4% (95%CI:16·0–74·1))). Pooled difference in mean methylation level was significantly higher in ≥CIN2/HSIL vs. ≤CIN1/LSIL for HPV16 L1 (11·3% (95%CI:6·5–16·1)). Pooled odds ratio of HPV16 L1 methylation was 5·5 (95%CI:3·5–8·5) for ≥CIN2/ HSIL vs. ≤CIN1/LSIL (p < 0·0001). HPV16 L1/L2 genes performed best in predicting CIN2 or worse (pooled sensitivity 77% (95%CI:63–87), specificity 64% (95%CI:55–71), area under the curve (0·73 (95%CI:0·69–0·77)). Interpretation Higher HPV methylation is associated with increased disease severity, whilst HPV16 L1/L2 genes demonstrated high diagnostic accuracy to detect high-grade CIN in HPV16 positive women. Direct clinical use is limited by the need for a multi-genotype and standardised assays. Next-generation multiplex HPV sequencing assays are under development and allow potential for rapid, automated and low-cost methylation testing