title: Discovery and validation of urinary biomarkers for detection of renal cell carcinoma.
abstract: BACKGROUND
  Renal cell carcinoma (RCC) is often accompanied by non-specific symptoms. The increase of incidentally discovered small renal masses also presents a diagnostic dilemma. This study investigates whether RCC-specific peptides with diagnostic potential can be detected in urine and whether a combination of such peptides could form a urinary screening tool.
  
  
  METHODS
  For the discovery of RCC-specific biomarkers, we have employed CE-MS to analyze urine samples from patients with RCC (N=40) compared to non-diseased controls (N=68).
  
  
  CONCLUSIONS
  86 peptides were found to be specifically associated to RCC, of which sequence could be obtained for 40. A classifier based on these peptides was evaluated in an independent set of 76 samples, resulting in 80% sensitivity and 87% specificity. The specificity of the marker panel was further validated in a historical dataset of 1077 samples including age-matched controls (N=218), patients with related cancer types and renal diseases (N=859). In silico protease prediction based on the cleavage sites of differentially excreted peptides, suggested modified activity of certain proteases including cathepsins, ADAMTS and kallikreins some of which were previously found to be associated to RCC.
  
  
  CONCLUSIONS
  RCC can be detected with high accuracy based on specific urinary peptides.
  
  
  CONCLUSIONS
  Clear cell renal cell carcinoma (RCC) has the highest incidence among the renal malignancies, often presenting non-specific or no symptoms at all. Moreover, with no diagnostic marker being available so far, almost 30% of the patients are diagnosed with metastatic disease and 30-40% of the patients initially diagnosed with localized tumor relapse. These facts introduce the clinical need of early diagnosis. This study is focused on the investigation of a marker model based on urinary peptides, as a tool for the detection of RCC in selected patients at risk. Upon evaluation of the marker model in an independent blinded set of 76 samples, 80% sensitivity and 87% specificity were reported. An additional dataset of 1077 samples was subsequently employed for further evaluation of the specificity of the classifier.
authors.affiliation: Mosaiques diagnostics GmbH, Hannover, Germany; Biomedical Research Foundation, Academy of Athens, Biotechnology Division, Athens, Greece. Electronic address: frantzi@mosaiques-diagnostics.com.
authors.forename: Maria
authors.initials: M
authors.lastname: Frantzi
authors.affiliation: Mosaiques diagnostics GmbH, Hannover, Germany.
authors.forename: Jochen
authors.initials: J
authors.lastname: Metzger
authors.affiliation: St James's University Hospital, Cancer Research UK Clinical Centre, Clinical and Biomedical Proteomics Group, Leeds, United Kingdom.
authors.forename: Rosamonde E
authors.initials: RE
authors.lastname: Banks
authors.affiliation: University of Glasgow, Institute of Cardiovascular and Medical Sciences, Glasgow, United Kingdom.
authors.forename: Holger
authors.initials: H
authors.lastname: Husi
authors.affiliation: Mosaiques diagnostics GmbH, Hannover, Germany.
authors.forename: Julie
authors.initials: J
authors.lastname: Klein
authors.affiliation: Mosaiques diagnostics GmbH, Hannover, Germany.
authors.forename: Mohammed
authors.initials: M
authors.lastname: Dakna
authors.affiliation: University of Glasgow, Institute of Cardiovascular and Medical Sciences, Glasgow, United Kingdom.
authors.forename: William
authors.initials: W
authors.lastname: Mullen
authors.affiliation: St James's University Hospital, Department of Urology, Leeds, United Kingdom.
authors.forename: Jonathan J
authors.initials: JJ
authors.lastname: Cartledge
authors.affiliation: Inserm, U858/I2MR, Department of Renal and Cardiac Remodeling, Team #5, 1 Avenue Jean Poulhès, BP 84225, 31432 Toulouse Cedex 4, France; Université Toulouse III Paul Sabatier, Institut de Médecine Moléculaire de Rangueil, Toulouse F-31000, France.
authors.forename: Joost P
authors.initials: JP
authors.lastname: Schanstra
authors.affiliation: Hannover Medical School, Institute of Clinical Chemistry, Hannover, Germany.
authors.forename: Korbinian
authors.initials: K
authors.lastname: Brand
authors.affiliation: Hannover Medical School, Department of Urology and Urological Oncology, Hannover, Germany.
authors.forename: Markus A
authors.initials: MA
authors.lastname: Kuczyk
authors.affiliation: Mosaiques diagnostics GmbH, Hannover, Germany; University of Glasgow, Institute of Cardiovascular and Medical Sciences, Glasgow, United Kingdom.
authors.forename: Harald
authors.initials: H
authors.lastname: Mischak
authors.affiliation: Biomedical Research Foundation, Academy of Athens, Biotechnology Division, Athens, Greece.
authors.forename: Antonia
authors.initials: A
authors.lastname: Vlahou
authors.affiliation: University of Colorado, Department of Surgery and Pharmacology, Aurora, CO, USA; University of Colorado Comprehensive Cancer Center, Aurora, CO, USA.
authors.forename: Dan
authors.initials: D
authors.lastname: Theodorescu
authors.affiliation: Hannover Medical School, Department of Urology and Urological Oncology, Hannover, Germany.
authors.forename: Axel S
authors.initials: AS
authors.lastname: Merseburger
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015415:Biomarkers / Q000652:urine*; D002292:Carcinoma, Renal Cell / Q000175:diagnosis / Q000652:urine; D005260:Female; D006801:Humans; D007680:Kidney Neoplasms / Q000175:diagnosis / Q000652:urine; D008297:Male; D008875:Middle Aged; D009363:Neoplasm Proteins / Q000652:urine*; D010455:Peptides / Q000652:urine*
chemical_list: D015415:Biomarkers; D009363:Neoplasm Proteins; D010455:Peptides
keywords: Diagnosis; Protease prediction; Proteomics; Renal cell carcinoma; Urinary peptide markers