Methylation analysis in urine fractions for optimal CIN3 and cervical cancer detection

INTRODUCTION: Urine sampling is an interesting solution for CIN3 and cervical cancer detection. Urine can be separated in different fractions: full void urine, urine sediment and urine supernatant. We aimed to determine which urine fraction is most competent for CIN3 and cervical cancer detection by methylation analysis. METHODS: Urine samples (27 controls, 30 CIN3 and 17 cervical cancer) were processed into 3 fractions and tested for 5 methylation markers (ASCL1, GHSR, LHX8, SST, ZIC1). We determined Spearman correlation coefficients between fractions, compared methylation levels and calculated AUCs for CIN3 and cancer detection. RESULTS: In general strong correlations (r > 0.60) were found between urine fractions. Methylation levels increased significantly with severity of underlying disease in all urine fractions. CIN3 and controls differed significantly for 2 markers in full void urine, 4 markers in urine sediment and 1 marker in urine supernatant, with AUCs of 0.55-0.79. Comparison of cancer to controls was highly significant for all markers in all fractions, yielding AUCs of 0.87-0.99. CONCLUSION: Methylation analysis performs excellent in all urine fractions for cervical cancer detection. Our results indicate the potential of CIN3 detection by urinary methylation analysis, and demonstrate that urine sediment performs best to detect CIN3

DNA methylation testing for endometrial cancer detection in urine, cervicovaginal self-samples and cervical scrapes

Endometrial cancer incidence is rising and current diagnostics often require invasive biopsy procedures. DNA methylation marker analysis of minimally- and non-invasive sample types could provide an easy-to-apply and patient-friendly alternative to determine cancer risk. Here, we compared the performance of DNA methylation markers to detect endometrial cancer in urine, cervicovaginal self-samples and clinician-taken cervical scrapes. Paired samples were collected from 103 patients diagnosed with stage I to IV endometrial cancer. Urine and self-samples were collected at home. All samples were tested for nine DNA methylation markers using quantitative methylation-specific PCR. Methylation levels measured in endometrial cancer patients were compared to unpaired samples of 317 healthy controls. Diagnostic performances were evaluated by univariable and multivariable logistic regression analysis, followed by leave-one-out cross-validation. Each methylation marker showed significantly higher methylation levels in all sample types of endometrial cancer patients compared to healthy controls (P <.01). Optimal three-marker combinations demonstrated excellent diagnostic performances with area under the receiver operating curve values of 0.95 (95% CI: 0.92-0.98), 0.94 (0.90-0.97) and 0.97 (0.96-0.99), for endometrial cancer detection in urine, self-samples and scrapes, respectively. Sensitivities ranged from 89% to 93% at specificities of 90% to 92%. Virtually equal performances were obtained after cross-validation and excellent diagnostic performances were maintained for stage I endometrial cancer detection. Our study shows the value of methylation analysis in patient-friendly sample types for endometrial cancer detection of all stages. This approach has great potential to screen patient populations at risk for endometrial cancer