title: Gene expression signature in urine for diagnosing and assessing aggressiveness of bladder urothelial carcinoma.
abstract: OBJECTIVE
  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.
  
  
  METHODS
  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.
authors.affiliation: Laboratory and Department of Urology, Hospital Clínic, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Universitat de Barcelona, Barcelona, Spain. lmengual@ub.edu
authors.forename: Lourdes
authors.initials: L
authors.lastname: Mengual
authors.forename: Moisès
authors.initials: M
authors.lastname: Burset
authors.forename: María José
authors.initials: MJ
authors.lastname: Ribal
authors.forename: Elisabet
authors.initials: E
authors.lastname: Ars
authors.forename: Mercedes
authors.initials: M
authors.lastname: Marín-Aguilera
authors.forename: Manuel
authors.initials: M
authors.lastname: Fernández
authors.forename: Mercedes
authors.initials: M
authors.lastname: Ingelmo-Torres
authors.forename: Humberto
authors.initials: H
authors.lastname: Villavicencio
authors.forename: Antonio
authors.initials: A
authors.lastname: Alcaraz
mesh_terms: D000368:Aged; D016000:Cluster Analysis; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008297:Male; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods; D012334:RNA, Neoplasm / Q000235:genetics / Q000302:isolation & purification / Q000652:urine; D020133:Reverse Transcriptase Polymerase Chain Reaction; D012680:Sensitivity and Specificity; D001749:Urinary Bladder Neoplasms / Q000175:diagnosis* / Q000235:genetics* / Q000652:urine; D019459:Urothelium / Q000378:metabolism / Q000473:pathology
chemical_list: D012334:RNA, Neoplasm