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Cervical screening by high-risk HPV (hrHPV) testing requires additional risk stratification (triage), as most infections are transient and only a subset of hrHPV-positive women harbours clinically relevant disease. Molecular triage markers such as microRNAs (miRNAs) and DNA methylation markers are particularly promising, as they can be objectively tested directly on hrHPV-positive scrapes and cervicovaginal self-samples. Here, we evaluated the marker potential of 10 candidate miRNAs in 209 hrHPV-positive scrapes of women with underlying precancer (cervical intraepithelial neoplasia, grade 2–3 (CIN2-3)), cancer, or without disease (CIN0/1). A predictive miRNA classifier for CIN3 detection was built using logistic regression, which was compared to and combined with DNA methylation marker FAM19A4. Markers were correlated to histology parameters and hrHPV genotype. A miRNA classifier consisting of miR-149, miR-20a, and miR-93 achieved an area under the curve (AUC) of 0.834 for CIN3 detection, which was not significantly different to that of FAM19A4 methylation (AUC: 0.862, p = 0.591). Combining miRNA and methylation analysis demonstrated complementarity between both marker types (AUC: 0.939). While the miRNA classifier seemed more predictive for CIN2, FAM19A4 methylation was particularly high in HPV16-positive and histologically advanced CIN3, i.e. CIN3 with high lesion volume. The miRNA classifier, FAM19A4 methylation, and the miRNA/methylation combination were highest in cancer-associated scrapes. In conclusion, a panel of three miRNAs is discriminatory for CIN3 in hrHPV-positive scrapes and can complement DNA methylation analysis for the efficient detection of cervical disease. Combined analysis of the two marker types warrants further evaluation as triage strategy in hrHPV-based screening. [ABSTRACT FROM AUTHOR]

Abstract Objective HPV16/18 genotyping and detection of hypermethylation of human cell genes involved in cervical oncogenesis have shown promising results in triage of high-risk HPV (hrHPV)-screen positive women on cervical smears. These tests can be performed on self-samples, which contain cervical and vaginal cells. We studied whether a self-sample represents the hrHPV type causing the worst cervical lesion and whether any differences in hypermethylation of FAM19A4/miR124-2 exist between CIN lesions caused by different hrHPV types. These results have important implications for reflex triage of self-samples. Methods Correlation between genotype found on self-sample using GP5+/6+-PCR-EIA-LMNX and causative hrHPV genotype in the worst lesion on histology was studied using laser capture microdissection (LCM)-SPF10-PCR (N = 152). Hypermethylation of FAM19A4/miR124-2 in the self-sample was tested in a quantitative methylation specific PCR and compared between lesions caused by HPV16/18 and other hrHPV genotypes. Results Causative hrHPV genotype of the worst lesion (CIN1, CIN2, CIN3, invasive cervical cancer) was detected on self-sample in 93.4%. HPV16 was the most frequently found genotype on self-sampling (39.2%, 73/186) and causative genotype in CIN3+ (51.4%, 38/74, all detected on self-sample). There were no differences in the percentages of positive FAM19A4/miR124-2 methylation assays between lesions caused by HPV16/18 (73.8% in CIN3+) or other hrHPV genotypes (66.7% in CIN3+) (p = 0.538). Conclusions Our results show that hrHPV genotypes found on self-sample were a good representation of hrHPV in the worst CIN lesion and that methylation testing on self-sample for detection of CIN3+ was not significantly different between lesions caused by HPV16/18 and other hrHPV genotypes. Highlights • Genotyping of self-samples finds the causative genotype of the worst underlying lesion in almost all HPV screen-positives. • Hypermethylation of FAM19A4/miR124-2 shows no difference between lesions caused by HPV16/18 or other hrHPV genotypes. • Our results support HPV16/18 genotyping and hypermethylation of FAM19A4/miR124-2 for triage of HPV self-screen-positives. [ABSTRACT FROM AUTHOR]