Communications Medicine (May 2024)

Molecular analysis for ovarian cancer detection in patient-friendly samples

  • Birgit M. M. Wever,
  • Mirte Schaafsma,
  • Maaike C. G. Bleeker,
  • Yara van den Burgt,
  • Rianne van den Helder,
  • Christianne A. R. Lok,
  • Frederike Dijk,
  • Ymke van der Pol,
  • Florent Mouliere,
  • Norbert Moldovan,
  • Nienke E. van Trommel,
  • Renske D. M. Steenbergen

DOI
https://doi.org/10.1038/s43856-024-00517-8
Journal volume & issue
Vol. 4, no. 1
pp. 1 – 9

Abstract

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Abstract Background High ovarian cancer mortality rates motivate the development of effective and patient-friendly diagnostics. Here, we explored the potential of molecular testing in patient-friendly samples for ovarian cancer detection. Methods Home-collected urine, cervicovaginal self-samples, and clinician-taken cervical scrapes were prospectively collected from 54 patients diagnosed with a highly suspicious ovarian mass (benign n = 25, malignant n = 29). All samples were tested for nine methylation markers, using quantitative methylation-specific PCRs that were verified on ovarian tissue samples, and compared to non-paired patient-friendly samples of 110 age-matched healthy controls. Copy number analysis was performed on a subset of urine samples of ovarian cancer patients by shallow whole-genome sequencing. Results Three methylation markers are significantly elevated in full void urine of ovarian cancer patients as compared to healthy controls (C2CD4D, P = 0.008; CDO1, P = 0.022; MAL, P = 0.008), of which two are also discriminatory in cervical scrapes (C2CD4D, P = 0.001; CDO1, P = 0.004). When comparing benign and malignant ovarian masses, GHSR shows significantly elevated methylation levels in the urine sediment of ovarian cancer patients (P = 0.024). Other methylation markers demonstrate comparably high methylation levels in benign and malignant ovarian masses. Cervicovaginal self-samples show no elevated methylation levels in patients with ovarian masses as compared to healthy controls. Copy number changes are identified in 4 out of 23 urine samples of ovarian cancer patients. Conclusions Our study reveals increased methylation levels of ovarian cancer-associated genes and copy number aberrations in the urine of ovarian cancer patients. Our findings support continued research into urine biomarkers for ovarian cancer detection and highlight the importance of including benign ovarian masses in future studies to develop a clinically useful test.