Gene Expression Signature in Urine for Diagnosing and Assessing Aggressiveness of Bladder Urothelial Carcinoma

• Published in: Clinical cancer research Vol. 16; no. 9; pp. 2624 - 2633
• Main Authors: MENGUAL, Lourdes, BURSET, Moisès, RIBAL, Maria José, ARS, Elisabet, MARIN-AGUILERA, Mercedes, FERNANDEZ, Manuel, INGELMO-TORRES, Mercedes, VILLAVICENCIO, Humberto, ALCARAZ, Antonio
• Format: Journal Article
• Language: English
• Published: Philadelphia, PA American Association for Cancer Research 01-05-2010
• Subjects: Aged; Antineoplastic agents; Biological and medical sciences; Cluster Analysis; Female; Gene Expression Profiling; Gene Expression Regulation, Neoplastic; Humans; Male; Medical sciences; Middle Aged; Nephrology. Urinary tract diseases; Oligonucleotide Array Sequence Analysis - methods; Pharmacology. Drug treatments; Reverse Transcriptase Polymerase Chain Reaction; RNA, Neoplasm - genetics; RNA, Neoplasm - isolation & purification; RNA, Neoplasm - urine; Sensitivity and Specificity; Tumors of the urinary system; Urinary Bladder Neoplasms - diagnosis; Urinary Bladder Neoplasms - genetics; Urinary Bladder Neoplasms - urine; Urinary system involvement in other diseases. Miscellaneous; Urinary tract. Prostate gland; Urothelium - metabolism; Urothelium - pathology; Urine; Biological fluid; Urinary system disease; Malignancy; Urinary tract disease; Malignant tumor; Gene expression; Baldder transitional cell carcinoma; Gene expression profile; Bladder disease; Diagnosis; Cancer; Aggressiveness
• ISSN: 1078-0432; 1557-3265
• DOI: 10.1158/1078-0432.CCR-09-3373

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.
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.
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.
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.