Gene Expression Signature in Urine for Diagnosing and Assessing Aggressiveness of Bladder Urothelial Carcinoma — Clinical Cancer Research

De izq. a dcha, Eva Martín Becerra (FINA BIOTECH), Dr. Humberto Villavicencio, Dr. Antonio Alcaraz y Dra. Lourdes Mengual (Dep. Urología Hosp. Clínic

Gene Expression Signature in Urine for Diagnosing and Assessing Aggressiveness of Bladder Urothelial Carcinoma
Lourdes Mengual1,2, Moisès Burset1,3, María José Ribal1, Elisabet Ars2, Mercedes Marín-Aguilera1,2, Manuel Fernández2, Mercedes Ingelmo-Torres1, Humberto Villavicencio2, and Antonio Alcaraz1
+ Author Affiliations

Authors' Affiliations:1Laboratory and Department of Urology, Hospital Clínic, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, 2Molecular Biology Laboratory and Department of Urology, Fundació Puigvert, Universitat Autònoma de Barcelona, and 3Department of Statistics, Faculty of Biology, University of Barcelona, Barcelona, Spain

Corresponding Author:
Lourdes Mengual, Laboratory of Urology, Urology Department, Hospital Clínic, Villarroel, 170, 08036 Barcelona, Spain. Phone: 34-93-2275545; Fax: 34-93-2275545; E-mail: lmengual@ub.edu.
L. Mengual and M. Burset contributed equally to this work.

Abstract
Purpose: To develop an accurate and noninvasive method for bladder cancer diagnosis and prediction of disease aggressiveness based on the gene expression patterns of urine samples.

Experimental Design: Gene expression patterns of 341 urine samples from bladder urothelial cell carcinoma (UCC) patients and 235 controls were analyzed via TaqMan Arrays. In a first phase of the study, three consecutive gene selection steps were done to identify a gene set expression signature to detect and stratify UCC in urine. Subsequently, those genes more informative for UCC diagnosis and prediction of tumor aggressiveness were combined to obtain a classification system of bladder cancer samples. In a second phase, the obtained gene set signature was evaluated in a routine clinical scenario analyzing only voided urine samples.

Results: We have identified a 12+2 gene expression signature for UCC diagnosis and prediction of tumor aggressiveness on urine samples. Overall, this gene set panel had 98% sensitivity (SN) and 99% specificity (SP) in discriminating between UCC and control samples and 79% SN and 92% SP in predicting tumor aggressiveness. The translation of the model to the clinically applicable format corroborates that the 12+2 gene set panel described maintains a high accuracy for UCC diagnosis (SN = 89% and SP = 95%) and tumor aggressiveness prediction (SN = 79% and SP = 91%) in voided urine samples.

Conclusions: The 12+2 gene expression signature described in urine is able to identify patients suffering from UCC and predict tumor aggressiveness. We show that a panel of molecular markers may improve the schedule for diagnosis and follow-up in UCC patients. Clin Cancer Res; 16(9); 2624–33. ©2010 AACR.

Footnotes
Note: Supplementary data for this article are available at Clinical Cancer Research Online (http://clincancerres.aacrjournals.org/).

Received December 24, 2009. Revision received March 2, 2010. Accepted March 8, 2010.

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Gene Expression Signature in Urine for Diagnosing and Assessing Aggressiveness of Bladder Urothelial Carcinoma — Clinical Cancer Research