In:
Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 23, No. 14 ( 2017-07-15), p. 3700-3710
Abstract:
Purpose: The majority of bladder cancer patients present with localized disease and are managed by transurethral resection. However, the high rate of recurrence necessitates lifetime cystoscopic surveillance. Developing a sensitive and specific urine-based test would significantly improve bladder cancer screening, detection, and surveillance. Experimental Design: RNA-seq was used for biomarker discovery to directly assess the gene expression profile of exfoliated urothelial cells in urine derived from bladder cancer patients (n = 13) and controls (n = 10). Eight bladder cancer specific and 3 reference genes identified by RNA-seq were quantitated by qPCR in a training cohort of 102 urine samples. A diagnostic model based on the training cohort was constructed using multiple logistic regression. The model was further validated in an independent cohort of 101 urines. Results: A total of 418 genes were found to be differentially expressed between bladder cancer and controls. Validation of a subset of these genes was used to construct an equation for computing a probability of bladder cancer score (PBC) based on expression of three markers (ROBO1, WNT5A, and CDC42BPB). Setting PBC = 0.45 as the cutoff for a positive test, urine testing using the three-marker panel had overall 88% sensitivity and 92% specificity in the training cohort. The accuracy of the three-marker panel in the independent validation cohort yielded an AUC of 0.87 and overall 83% sensitivity and 89% specificity. Conclusions: Urine-based molecular diagnostics using this three-marker signature could provide a valuable adjunct to cystoscopy and may lead to a reduction of unnecessary procedures for bladder cancer diagnosis. Clin Cancer Res; 23(14); 3700–10. ©2017 AACR.
Type of Medium:
Online Resource
ISSN:
1078-0432
,
1557-3265
DOI:
10.1158/1078-0432.CCR-16-2610
Language:
English
Publisher:
American Association for Cancer Research (AACR)
Publication Date:
2017
detail.hit.zdb_id:
1225457-5
detail.hit.zdb_id:
2036787-9
