title: Discovery and validation of new protein biomarkers for urothelial cancer: a prospective analysis.
abstract: BACKGROUND
  Non-invasive methods for diagnosis of urothelial carcinoma have reduced specificity in patients with non-malignant genitourinary disease or other disorders. We aimed to use mass spectrometry and bioinformatics to define and validate a cancer-specific proteomic pattern.
  
  
  METHODS
  We used capillary-electrophoresis-coupled mass spectrometry to obtain polypeptide patterns from urine samples of 46 patients with urothelial carcinoma and 33 healthy volunteers. From signatures of polypeptide mass, we established a model for predicting the presence of cancer. The model was refined further by use of 366 urine samples obtained from other healthy volunteers and patients with malignant and non-malignant genitourinary disease. We estimated the proportion of correct classifications from the refined model by applying it to a masked group containing 31 patients with urothelial carcinoma, 11 healthy individuals, and 138 patients with non-malignant genitourinary disease. We also sequenced several diagnostic polypeptides for urothelial carcinoma.
  
  
  RESULTS
  We identified a diagnostic urothelial-carcinoma pattern of 22 polypeptide masses. On masked assessment, prediction models based on these polypeptides correctly classified all samples of urothelial carcinoma (sensitivity 100% [95% CI 87-100) and all healthy samples (specificity 100% [84-100]). Correct identification of patients with urothelial carcinoma from those with other malignant and non-malignant genitourinary disease ranged from 86% to 100%. A prominent polypeptide from the diagnostic pattern for urothelial carcinoma was identified as fibrinopeptide A-a known biomarker of ovarian cancer and gastric cancer.
  
  
  CONCLUSIONS
  Validation of a highly specific biomarker pattern for urothelial carcinoma in a large group of patients with various urological disorders could be used in the diagnosis of other diseases that are identified in urine samples or in other body fluids.
authors.affiliation: Department of Molecular Physiology, Mellon Prostate Cancer Institute, University of Virginia, Charlottesville, VA, USA. dt9d@virginia.edu
authors.forename: Dan
authors.initials: D
authors.lastname: Theodorescu
authors.forename: Stefan
authors.initials: S
authors.lastname: Wittke
authors.forename: Mark M
authors.initials: MM
authors.lastname: Ross
authors.forename: Michael
authors.initials: M
authors.lastname: Walden
authors.forename: Mark
authors.initials: M
authors.lastname: Conaway
authors.forename: Ingo
authors.initials: I
authors.lastname: Just
authors.forename: Harald
authors.initials: H
authors.lastname: Mischak
authors.forename: Henry F
authors.initials: HF
authors.lastname: Frierson
mesh_terms: D014408:Biomarkers, Tumor / Q000032:analysis*; D002277:Carcinoma / Q000175:diagnosis* / Q000235:genetics / Q000473:pathology*; D016022:Case-Control Studies; D019295:Computational Biology; D003937:Diagnosis, Differential; D019075:Electrophoresis, Capillary; D005260:Female; D006801:Humans; D008297:Male; D013058:Mass Spectrometry; D040901:Proteomics; D012680:Sensitivity and Specificity; D014571:Urologic Neoplasms / Q000175:diagnosis* / Q000235:genetics / Q000473:pathology*; D019459:Urothelium
chemical_list: D014408:Biomarkers, Tumor