Development and Validation of the UriMee Model: A Methylation-based Diagnostic Tool for Early Diagnosis of Urothelial Carcinoma.

Abstract

Background and objective: Urothelial carcinoma (UC) is a common malignancy that imposes a significant health care burden. Current diagnostic methods are limited by their invasiveness and low sensitivity, particularly for detecting low-grade tumors. Noninvasive, accurate, and reliable diagnostic tests for an early diagnosis of UC are urgently needed.

Methods: UC-specific DNA methylation biomarkers were identified by combining public datasets from The Cancer Genome Atlas and Gene Expression Omnibus with a cohort from Renji Hospital (n = 50). Using the Least Absolute Shrinkage and Selection Operator regression, we developed a diagnostic model, termed the UriMee model, by selecting key biomarkers from a model cohort (n = 322) and subsequently validating it in an independent cohort (n = 131). The diagnostic performance of the assay was evaluated and compared with that of urine cytology.

Key findings and limitations: At 30% threshold probability, the UriMee model demonstrated high sensitivity (92%) and specificity (92%) in distinguishing UC cases, with particularly strong performance in early-stage tumors (83% sensitivity for Ta, 93% for T1, and 100% for Tis). It significantly outperformed urine cytology, offering greater sensitivity (90% vs 25%, p < 0.001) while maintaining comparable specificity. Additionally, the model was highly effective in identifying upper tract urothelial carcinoma (UTUC), achieving sensitivity of 96%. The study's limitations include the necessity for larger multicenter studies and long-term follow-up to validate the findings and assess the test's effectiveness across diverse populations, as well as its utility in monitoring disease progression and recurrence.

Conclusions: The UriMee test demonstrated high sensitivity and specificity, particularly in detecting early-stage tumors and UTUC, significantly outperforming traditional methods.