ABSTRACT: A new sequencing-based women's health assay combining self-sampling, HPV detection and genotyping, STI detection, and vaginal microbiome analysis
Project description:Background: Offering self-sampling of cervico-vaginal material for human papillomavirus (HPV) testing is an effective method to increase the coverage in cervical screening programmes. Molecular triage directly on HPV-positive self-samples for colposcopy referral opens the way to full molecular cervical screening. Here, we set out to identify a methylation classifier for detection of precancer (CIN3) or cancer, applicable to self-samples obtained by different devices. Findings: Genome-wide DNA methylation profiling of HPV-positive self-samples revealed 12 methylation targets for CIN3 detection. Multiplex quantitative methylation-specific PCR of these targets yielded a 3-gene methylation classifier (ASCL1, LHX8 and ST6GALNAC5), showing a very good clinical performance for CIN3 detection in both lavage (AUC=0.88; sensitivity=74%; specificity=79%) and brush (AUC=0.90; sensitivity=88%; specificity=81%) self-samples in the validation set. All self-samples from women with cervical cancer scored methylation-positive. Conclusion: By genome-wide DNA methylation profiling on self-samples, we identified a highly effective 3-gene methylation classifier for direct triage on self-samples from HPV-positive women.
Project description:Cervical cancer is the fourth most common cancer among women worldwide and screening pro-grams increase detection rate and survivability. Molecular screening of presence of human papil-loma viruses (HPV) as alternatives to physical examinations offers cost-efficient solutions and can be performed on self-collected samples. A persistent infection with HPV is necessary but not sufficient to develop cancer and additional biomarkers are needed to increase the precision. We have analyzed protein biomarkers found in self-collected dried cervico-vaginal fluid (CVF) from both controls and women with cervical cancer pre-stages.
Project description:Offering self-sampling for HPV testing improves the effectiveness of current cervical screening programs. Molecular triage markers directly applicable on self-samples are needed to further stratify HPV-positive women at risk of cervical cancer (so-called triage) and to avoid over-referral and overtreatment. MicroRNAs (miRNAs) deregulation has been implicated in the development of cervical cancer, and represents a potential class of triage markers. However, it is unknown whether deregulated miRNA expression is reflected in self-samples. This study is the first to establish genome-wide miRNA profiles in HPV-positive self-samples to identify miRNAs that can predict the presence of CIN3 and cervical cancer in self-samples. Small RNA sequencing (sRNA-Seq) was conducted to determine genome-wide miRNA expression profiles in 73 HPV-positive self-samples of women with and without cervical precancer (CIN3). The optimal miRNA marker panel for CIN3 detection was determined by GRidge, a penalized method on logistic regression. Classification of sRNA-Seq data yielded a panel of 9 miRNAs with a combined Area Under the Curve (AUC) of 0.89 for CIN3 detection. Six out of nine miRNAs were validated by qPCR in 165 independent HPV-positive self-samples and resulted in a combined AUC of 0.72 for CIN3+ detection. This study shows that deregulated miRNA expression associated with CIN3 and cervical cancer development can be detected in HPV-positive self-samples using genome-wide miRNA profiling. Further validation by qPCR indicates that miRNA expression analysis offers a promising novel molecular triage strategy for CIN3 and cervical cancer detection applicable to self-samples.
Project description:TOP1cc-seq assay was performed for the quantitative detection of the transient DNA-protein covalent interactions upon acute stimulations.
