Evaluation of Urinary Circulating Tumor DNA to Detect Minimal Residual Disease in Patients with High-Risk Non-Muscle Invasive Bladder Cancer
Year: 2026
Type: preprint
Study design: Observational Study
Abstract: Purpose: Restaging transurethral resection of bladder tumor (reTURBT) is the standard-of-care for some patients with high-risk non-muscle invasive bladder cancer (NMIBC). However, it may lead to complications and biomarkers to avoid unnecessary reTURBT are needed. Materials and Methods: Patients with high-risk NMIBC undergoing reTURBT were prospectively enrolled. Whole-exome sequencing along with low-pass whole-genome sequencing were performed on index TURBT samples to generate mutational profiles and copy number variation. Up to 50 personalized mutations and a fixed panel of 500 hotspot mutations were used for detecting variants from urine samples collected prior to reTURBT. Using a prespecified algorithm, tumor fraction (TF) and copy number burden (CNB) score were used to measure minimal residual disease and correlated with reTURBT pathology. Results: Overall, 72/76 urine samples collected from patients with high-risk NMIBC prior to reTURBT passed quality check. From the indext TURBT specimens, a median of 39 personalized variants from the index TURBT were used for disease tracking. Overall, median TF was 0.206 vs. 0.001 in patients with and without residual tumor, respectively (p<0.001). Similarly, CNB score was elevated (7.34 vs. 4.02, p<0.001). utDNA achieved sensitivity of 97.8% and specificity of 69.2%, with area under the curve (AUC) of 0.932 in predicting disease found on reTURBT. Analyses of the index and reTURBT tissue and urine mutational profiles provided evidence for underdiagnosis of subclinical disease at the time of reTURBT. Conclusion: Paired personalized and panel utDNA can be used to accurately detect residual disease in patients with high-risk NMIBC with potentially wide-ranging clinical applications.
Source: medRxiv
Authors: Roger Li, Joshua Linscott, Prithvi Murthy, Kyle Rose, Young Pak, Frank Zhang, Yong Huang, G. Daniel Grass, Jonathan Chatzkel, Noah M. Hahn, David J. McConkey, Joshua J. Meeks, Siamak Daneshmand, Thomas W. Flaig, Seth P. Lerner, Logan Zemp, Michael A. Poch, Philippe E. Spiess, Wade J. Sexton, Scott M. Gilbert, Hongzhi Xu, Pan Du, Shidong Jia, Xuefeng Wang
Institutions: Moffitt Cancer Center, Johns Hopkins University, Sidney Kimmel Comprehensive Cancer Center, Northwestern University, University of Southern California, USC Norris Comprehensive Cancer Center, University of Colorado Anschutz, Baylor College of Medicine, Dan L Duncan Comprehensive Cancer Center
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7212357248