title: Assessment of 54 biomarkers for biopsy-detectable prostate cancer.
abstract: OBJECTIVE
  We analyzed the association of 54 biomarkers from seven classes including adipokines, immune response metalloproteinases, adhesion molecules, and growth factors with prostate cancer risk adjusting for the Prostate Cancer Prevention Trial (PCPT) risk score.
  
  
  METHODS
  A total of 123 incident prostate cancer cases and 127 age-matched controls were selected from subjects in the San Antonio Center for Biomarkers of Risk of Prostate Cancer cohort study. Prediagnostic serum concentrations were measured in the sample collected at baseline using LabMAP technology. The odds ratios (OR) of prostate cancer risk associated with serum concentrations of 54 markers were estimated using univariate conditional logistic regression before and after adjustment for the PCPT risk score. Two-way hierarchical unsupervised clustering techniques were used to evaluate whether the 54-marker panel distinguished cases from controls.
  
  
  RESULTS
  Vascular endothelial growth factor, resistin, interleukin 1Ra (IL-1Ra), granulocyte colony-stimulating factor, matrix metalloproteinase-3, plasminogen activator inhibitor, and kallikrein-8 were statistically significantly (P < 0.05) underexpressed in prostate cancer cases, and alpha-fetoprotein was statistically significantly overexpressed in prostate cancer cases, but all had area underneath the receiver-operating characteristic curve <60%; none were statistically significant adjusting for multiple comparisons (P < 0.0008) or after adjustment for the PCPT risk score. Statistical clustering of patients by the marker panel did not distinguish a separate group of cases from controls.
  
  
  CONCLUSIONS
  This age-matched case-control study did not support findings of increased diagnostic potential from a 54-marker panel when compared with the conventional risk factors incorporated in the PCPT risk calculator. Future discovery of new biomarkers should always be tested and compared against conventional risk factors before applying them in clinical practice.
authors.affiliation: Department of Urology, University of Texas Health Sciences Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78284-7802, USA. parekhd@uthscsa.edu
authors.forename: Dipen J
authors.initials: DJ
authors.lastname: Parekh
authors.forename: Donna Pauler
authors.initials: DP
authors.lastname: Ankerst
authors.forename: Jacques
authors.initials: J
authors.lastname: Baillargeon
authors.forename: Betsy
authors.initials: B
authors.lastname: Higgins
authors.forename: Elizabeth A
authors.initials: EA
authors.lastname: Platz
authors.forename: Dean
authors.initials: D
authors.lastname: Troyer
authors.forename: Javier
authors.initials: J
authors.lastname: Hernandez
authors.forename: Robin J
authors.initials: RJ
authors.lastname: Leach
authors.forename: Anna
authors.initials: A
authors.lastname: Lokshin
authors.forename: Ian M
authors.initials: IM
authors.lastname: Thompson
mesh_terms: D054392:Adipokines / Q000097:blood; D015415:Biomarkers / Q000097:blood*; D001706:Biopsy; D016022:Case-Control Studies; D015815:Cell Adhesion Molecules / Q000097:blood; D016000:Cluster Analysis; D015331:Cohort Studies; D006801:Humans; D036341:Intercellular Signaling Peptides and Proteins / Q000097:blood; D008297:Male; D045726:Metalloproteases / Q000097:blood; D011237:Predictive Value of Tests; D011446:Prospective Studies; D011467:Prostate / Q000473:pathology; D011471:Prostatic Neoplasms / Q000097:blood / Q000175:diagnosis* / Q000473:pathology / Q000517:prevention & control; D018570:Risk Assessment; D012307:Risk Factors; D013781:Texas
chemical_list: D054392:Adipokines; D015415:Biomarkers; D015815:Cell Adhesion Molecules; D036341:Intercellular Signaling Peptides and Proteins; D045726:Metalloproteases