Work

The cervico‐vaginal DNA methylation WID ‐ qEC test: An epigenetic marker associated with ovarian cancer in the absence of endometrial and cervical cancer

Year: 2026

Type: article

Abstract: The DNA methylation-based WID-qEC test, applied to cervico-vaginal samples, has been validated for the accurate detection of endometrial and cervical cancers. However, a small proportion of women test positive despite the absence of these cancers. The aim of this study was to explore the biological and clinical characteristics associated with such WID-qEC-positive cases to inform potential follow-up strategies. We analyzed 1269 cervico-vaginal samples from women without endometrial or cervical cancer, including healthy controls (n = 624), women with benign gynecological conditions (n = 324), and ovarian cancer cases (n = 321). Of the 80 WID-qEC-positive results, 43 (54%) were from women with ovarian cancer. WID-qEC positivity was associated with the presence of ovarian cancer (adjusted odds ratio [OR] 2.93; 95% CI 1.75-4.95) and with a higher number of lifetime ovulatory cycles (adjusted OR 2.67; 95% CI 1.06-7.50), a known ovarian cancer risk factor. Both associations were independent of age, menopausal status, hormone replacement therapy usage, or family history of breast or ovarian cancer. Our findings suggest that in the absence of endometrial or cervical cancer, WID-qEC positivity may indicate an elevated risk or presence of ovarian cancer. While the standalone positive predictive value (PPV) for ovarian cancer detection remains low in the general population, we outline how WID-qEC could be used in a two-step triage approach. In women presenting with abnormal bleeding, combining WID-qEC positivity with a highly specific plasma-based cell-free DNA methylation test (e.g., with 60%-80% sensitivity and ~98.4% specificity) could theoretically yield a PPV of around 30%-40%. This hypothetical modeling is intended solely to illustrate how WID-qEC positivity might inform future triage research, rather than to propose a clinical diagnostic algorithm.

Source: International Journal of Cancer

DOI: 10.1002/ijc.70354