Triage of human papillomavirus infected women by methylation analysis in first-void urine

Abstract Host cell DNA methylation analysis in urine provides promising triage markers for women diagnosed with a high-risk (HR) human papillomavirus (HPV) infection. In this study, we have investigated a panel of six host cell methylation markers (GHSR, SST, ZIC1, ASCL1, LHX8, ST6GALNAC5) in cervic...

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Autores principales: Severien Van Keer, Annina P. van Splunter, Jade Pattyn, Annemie De Smet, Sereina A. Herzog, Xaveer Van Ostade, Wiebren A. A. Tjalma, Margareta Ieven, Pierre Van Damme, Renske D. M. Steenbergen, Alex Vorsters
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/8720320d3a7b43a68e2ef7b124fc4592
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Sumario:Abstract Host cell DNA methylation analysis in urine provides promising triage markers for women diagnosed with a high-risk (HR) human papillomavirus (HPV) infection. In this study, we have investigated a panel of six host cell methylation markers (GHSR, SST, ZIC1, ASCL1, LHX8, ST6GALNAC5) in cervicovaginal secretions collected within the first part of the urine void (FVU) from a referral population. Cytology, histology, and HPV DNA genotyping results on paired FVU and cervical samples were available. Urinary median methylation levels from HR-HPV (n = 93) positive women were found to increase for all markers with severity of underlying disease. Significantly elevated levels were observed for GHSR and LHX8 in relation to high-grade cervical intraepithelial neoplasia (CIN2 +; n = 33), with area under de curve values of 0.80 (95% Confidence Interval (CI) 0.59–0.92) and 0.76 (95% CI 0.58–0.89), respectively. These findings are the first to support the assertion that methylation analysis of host cell genes is feasible in FVU and holds promise as molecular, triage strategy to discern low- from high-grade cervical disease in HR-HPV positive women. Molecular testing on FVU may serve to increase cervical cancer screening attendance in hard-to-reach populations whilst reducing loss to follow-up and await further optimization and validation studies.