title: PSGR and PCA3 as biomarkers for the detection of prostate cancer in urine.
abstract: BACKGROUND
  Several studies have demonstrated the usefulness of monitoring an RNA transcript in urine, such as PCA3, for prostate cancer (PCa) diagnosis. PCa screening would benefit from additional biomarkers of higher specificity and could be used in conjunction with prostate-specific antigen (PSA) testing, in order to better determine biopsy candidates.
  
  
  METHODS
  We used urine sediments after prostate massage (PM) from 215 consecutive patients, who presented for prostate biopsy. We tested whether prostate-specific G-protein coupled receptor (PSGR), a biomarker previously described to be over-expressed in PCa tissue, could also be detected by quantitative real-time PCR in post-PM urine sediment. We combined these findings with prostate cancer gene 3 (PCA3), the current gold standard for PCa diagnosis in urine, to test if a combination of both biomarkers could improve the sensitivity of PCA3 alone.
  
  
  RESULTS
  By univariate analysis we found that PSGR and PCA3 were significant predictors of PCa. Receiver operator characteristic curve analysis and its multivariate extension, multivariate ROC (MultiROC), were used to assess the outcome predictive values of the individual and the paired biomarkers. We obtained the following area under the curve values: PSA (0.602), PSGR (0.681), PCA3 (0.656), and PSGRvPCA3 (0.729). Then, we tested whether a combination of PSGR and PCA3 could improve specificity by fixing the sensitivity at 95%. We obtained specificities of 15% (PSGR), 17% (PCA3), and 34% (PSGRvPCA3).
  
  
  CONCLUSIONS
  A multiplexed model including PSGR and PCA3 improves the specificity for the detection of PCa, especially in the area of high sensitivity. This could be clinically useful for determining which patients should undergo biopsy.
authors.affiliation: Biomedical Research Unit, Research Institute, Vall d'Hebron UniversityHospital, Barcelona, Spain.
authors.forename: Marina
authors.initials: M
authors.lastname: Rigau
authors.forename: Juan
authors.initials: J
authors.lastname: Morote
authors.forename: Maria Carmen
authors.initials: MC
authors.lastname: Mir
authors.forename: Carlos
authors.initials: C
authors.lastname: Ballesteros
authors.forename: Israel
authors.initials: I
authors.lastname: Ortega
authors.forename: Alex
authors.initials: A
authors.lastname: Sanchez
authors.forename: Eva
authors.initials: E
authors.lastname: Colás
authors.forename: Marta
authors.initials: M
authors.lastname: Garcia
authors.forename: Anna
authors.initials: A
authors.lastname: Ruiz
authors.forename: Miguel
authors.initials: M
authors.lastname: Abal
authors.forename: Jacques
authors.initials: J
authors.lastname: Planas
authors.forename: Jaume
authors.initials: J
authors.lastname: Reventós
authors.forename: Andreas
authors.initials: A
authors.lastname: Doll
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000951:Antigens, Neoplasm / Q000235:genetics / Q000652:urine*; D015415:Biomarkers / Q000652:urine; D014408:Biomarkers, Tumor / Q000235:genetics / Q000652:urine*; D006801:Humans; D008297:Male; D008875:Middle Aged; D009363:Neoplasm Proteins / Q000652:urine*; D016133:Polymerase Chain Reaction; D011237:Predictive Value of Tests; D011467:Prostate / Q000033:anatomy & histology; D017430:Prostate-Specific Antigen / Q000097:blood; D011471:Prostatic Neoplasms / Q000175:diagnosis* / Q000453:epidemiology / Q000652:urine; D012334:RNA, Neoplasm / Q000235:genetics; D018035:Receptors, Odorant / Q000652:urine*; D018570:Risk Assessment; D014158:Transcription, Genetic
chemical_list: D000951:Antigens, Neoplasm; D015415:Biomarkers; D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins; C417566:OR51E2 protein, human; D012334:RNA, Neoplasm; D018035:Receptors, Odorant; C479341:prostate cancer antigen 3, human; D017430:Prostate-Specific Antigen