Urothelial Carcinoma Detection Based on Copy Number Profiles of Urinary Cell-Free DNA by Shallow Whole-Genome Sequencing.

Abstract

Current noninvasive assays for urothelial carcinoma (UC) lack clinical sensitivity and specificity. Given the utility of plasma cell-free DNA (cfDNA) biomarkers, the development of urinary cfDNA biomarkers may improve the diagnostic sensitivity. We assessed copy number alterations (CNAs) by shallow genome-wide sequencing of urinary cfDNA in 95 cancer-free individuals and 65 patients with UC, 58 with kidney cancer, and 45 with prostate cancer. We used a support vector machine to develop a diagnostic classifier based on CNA profiles to detect UC (UCdetector). The model was further validated in an independent cohort (52 patients). Genome sequencing data of tumor specimens from 90 upper tract urothelial cancers (UTUCs) and CNA data for 410 urothelial carcinomas of bladder (UCBs) from The Cancer Genome Atlas were used to validate the classifier. Genome sequencing data for urine sediment from 32 patients with UC were compared with cfDNA. To monitor the treatment efficacy, we collected cfDNA from 7 posttreatment patients. Urinary cfDNA was a more sensitive alternative to urinary sediment. The UCdetector could detect UC at a median clinical sensitivity of 86.5% and specificity of 94.7%. UCdetector performed well in an independent validation data set. Notably, the CNA features selected by UCdetector were specific markers for both UTUC and UCB. Moreover, CNA changes in cfDNA were consistent with the treatment effects. Meanwhile, the same strategy could localize genitourinary cancers to tissue of origin in 70.1% of patients. Our findings underscore the potential utility of urinary cfDNA CNA profiles as a basis for noninvasive UC detection and surveillance.