Use of urinary cell-free DNA fragmentomics in urothelial carcinoma diagnosis.

Abstract

846 Background: Traditional diagnostic procedures for urothelial carcinoma (UC) are often limited by patient burden and reduced sensitivity, impacting diagnostic accuracy. Liquid biopsy-based molecular detection, particularly through fragmentomics analysis, offers a promising supplement to clinical applications. Fragmentomics, which examines the unique fragmentation patterns of tumor DNA, can provide crucial insights into tumor origin and behavior. This study aims to leverage urinary cell-free DNA (ucfDNA) fragmentomics patterns to enhance the diagnostic capabilities for urothelial carcinoma. Methods: We conducted a case-control study to investigate cfDNA fragment size distributions in urine samples. The study included patients diagnosed with malignant UC (cases) and individuals with benign conditions (controls). High-throughput sequencing was used to identify distinct fragmentomics patterns, including variations in fragment size, end motifs, and genomic coverage at transcription factor binding sites. Diagnostic performance was evaluated using sensitivity, precision, and the area under the curve (AUC). Results: UC patients exhibited distinct fragmentation patterns, characterized by a shift towards shorter cfDNA fragments compared to controls. Analysis of fragment size and genomic coverage provided additional diagnostic insights when combined with methylation data, significantly improving early-stage UC detection. Fragmentomics combined with methylation markers achieved an AUC of 86.25%, with a sensitivity of 89.3% and a precision of 75.76%, demonstrating substantial improvements in diagnostic accuracy. Conclusions: Urinary cfDNA fragmentomics provides valuable complementary information to traditional molecular markers for detecting urothelial carcinoma. This innovative approach enhances diagnostic precision and shows potential for improving early detection strategies, with promising applications in non-invasive cancer screening and monitoring.