Quantitative measurement of L1 HPV16 methylation for the prediction of pre-invasive and invasive cervical disease
File(s)Figure 03 Thresholds for CIN2+ and CIN3+.tif (1.8 MB)
Accepted version
Author(s)
Type
Journal Article
Abstract
Background: Methylation of the HPV DNA has been proposed as a novel biomarker. Here, we correlated the mean methylation level of 12 CpG sites within L1 gene, to the histological grade of cervical precancer and cancer. We assessed whether HPV L1 gene methylation can predict the presence of high-grade disease at histology in women testing positive for HPV 16 genotype.
Methods: Pyrosequencing was used for DNA methylation quantification and 145 women were recruited.
Results: We found that the L1 HPV16 mean methylation (+/-SD) significantly increased with disease severity [CIN3=17.9%(±7.2) vs CIN2=11.6%(±6.5), p<0.001 or vs CIN1 =9.0%(±3.5), p<0.001). Mean methylation was a good predictor of CIN3+ cases; the Area Under the Curve (AUC) was higher for sites 5611 in the prediction of CIN2+ and higher for position 7145 for CIN3+. The evaluation of different methylation thresholds for the prediction of CIN3+, showed that the optimal balance of sensitivity and specificity (75.7% and 77.5%, respectively), PPV and NPV (74.7% and 78.5%, respectively) was achieved for a methylation of 14.0% with overall accuracy of 76.7%.
Conclusion: Elevated methylation level is associated with increased disease severity and has good ability to discriminate HPV16 positive women that have high-grade disease or worse.
Methods: Pyrosequencing was used for DNA methylation quantification and 145 women were recruited.
Results: We found that the L1 HPV16 mean methylation (+/-SD) significantly increased with disease severity [CIN3=17.9%(±7.2) vs CIN2=11.6%(±6.5), p<0.001 or vs CIN1 =9.0%(±3.5), p<0.001). Mean methylation was a good predictor of CIN3+ cases; the Area Under the Curve (AUC) was higher for sites 5611 in the prediction of CIN2+ and higher for position 7145 for CIN3+. The evaluation of different methylation thresholds for the prediction of CIN3+, showed that the optimal balance of sensitivity and specificity (75.7% and 77.5%, respectively), PPV and NPV (74.7% and 78.5%, respectively) was achieved for a methylation of 14.0% with overall accuracy of 76.7%.
Conclusion: Elevated methylation level is associated with increased disease severity and has good ability to discriminate HPV16 positive women that have high-grade disease or worse.
Date Issued
2017-02-07
Date Acceptance
2016-12-22
Citation
Journal of Infectious Diseases, 2017, 215 (5), pp.764-771
ISSN
1537-6613
Publisher
Oxford University Press (OUP)
Start Page
764
End Page
771
Journal / Book Title
Journal of Infectious Diseases
Volume
215
Issue
5
Copyright Statement
© The Author 2017. Published by Oxford University Press for the Infectious Diseases Society
of America. All rights reserved. This is a pre-copy-editing, author-produced PDF of an article accepted for publication in [insert journal title] following peer review. The definitive publisher-authenticated version is available online at: https://academic.oup.com/jid/article-lookup/doi/10.1093/infdis/jiw645
of America. All rights reserved. This is a pre-copy-editing, author-produced PDF of an article accepted for publication in [insert journal title] following peer review. The definitive publisher-authenticated version is available online at: https://academic.oup.com/jid/article-lookup/doi/10.1093/infdis/jiw645
Sponsor
British Society for Colposcopy and Cervical Pathology
Imperial College Healthcare Charity
Genesis Research Trust
Imperial College Healthcare Charity
Grant Number
N/A
7114/R17R
01020
Subjects
Science & Technology
Life Sciences & Biomedicine
Immunology
Infectious Diseases
Microbiology
cervical intraepithelial neoplasia
CIN
HPV L1 gene methylation
pyrosequencing
Human Papillomavirus
LIQUID-BASED CYTOLOGY
16 E6 GENE
DNA METHYLATION
INTRAEPITHELIAL NEOPLASIA
ENDOMETRIAL LESIONS
NUCLEAR MORPHOMETRY
PREGNANCY OUTCOMES
CANCER
WOMEN
RISK
Adult
Aged
Capsid Proteins
Cervical Intraepithelial Neoplasia
CpG Islands
DNA Methylation
DNA, Viral
Female
Genotype
Greece
Human papillomavirus 16
Humans
Linear Models
Middle Aged
Oncogene Proteins, Viral
Papillomavirus Infections
Prospective Studies
Sensitivity and Specificity
United Kingdom
Uterine Cervical Diseases
Young Adult
11 Medical And Health Sciences
06 Biological Sciences
Publication Status
Published