Researchers have developed a non-invasive test to detect cervical pre-cancer by analysing urine and vaginal samples collected by the women themselves.
Presenting the findings at the 2019 NCRI Cancer Conference in Glasgow, the authors said the test could improve participation in cervical cancer screening programmes.
The team from Queen Mary University of London developed a triage classifier for the detection of cervical intraepithelial neoplasia grade 2+ (CIN2+), based on DNA methylation of HPV16, HPV18, HPV31, and HPV33 and the human gene EPB41L3.
Women attending the colposcopy clinic at The Royal London Hospital following abnormal screening cytology and/or a positive HPV result were recruited as part of the ‘Self-sampling for vaginal HPV’ programme.
In total, 600 women provided self-collected vaginal samples using either Flocked swab and Diagene or HerSwab and Qvintip. DNA was analysed for six S5 markers. Average methylation was calculated to generate the S5 score.
S5 showed significant separation between <CIN2 and CIN2+ samples for both urine and vagina self-samples (P≤0.0001). The area under the ROC curve was 0.7254 (P≤0.0001) for urine samples and 0.7388 (P≤0.0001) for vaginal self-samples.
At the pre-defined cut-off of 0.8, the sensitivity for urine samples was 66% and the specificity was 72% (P≤0.0001) and for vaginal self-samples was 71%, with specificity 6%.
The authors concluded that S5 can be successfully amplified in urine and vaginal self-collected samples and that the classifier is able to correctly identify CIN2+ women. They said the test would be likely to improve participation in screening programmes.
