title: Serum biomarker panels for the detection of pancreatic cancer.
abstract: OBJECTIVE
  Serum-biomarker based screening for pancreatic cancer could greatly improve survival in appropriately targeted high-risk populations.
  
  
  METHODS
  Eighty-three circulating proteins were analyzed in sera of patients diagnosed with pancreatic ductal adenocarcinoma (PDAC, n = 333), benign pancreatic conditions (n = 144), and healthy control individuals (n = 227). Samples from each group were split randomly into training and blinded validation sets prior to analysis. A Metropolis algorithm with Monte Carlo simulation (MMC) was used to identify discriminatory biomarker panels in the training set. Identified panels were evaluated in the validation set and in patients diagnosed with colon (n = 33), lung (n = 62), and breast (n = 108) cancers.
  
  
  RESULTS
  Several robust profiles of protein alterations were present in sera of PDAC patients compared to the Healthy and Benign groups. In the training set (n = 160 PDAC, 74 Benign, 107 Healthy), the panel of CA 19-9, ICAM-1, and OPG discriminated PDAC patients from Healthy controls with a sensitivity/specificity (SN/SP) of 88/90%, while the panel of CA 19-9, CEA, and TIMP-1 discriminated PDAC patients from Benign subjects with an SN/SP of 76/90%. In an independent validation set (n = 173 PDAC, 70 Benign, 120 Healthy), the panel of CA 19-9, ICAM-1 and OPG demonstrated an SN/SP of 78/94% while the panel of CA19-9, CEA, and TIMP-1 demonstrated an SN/SP of 71/89%. The CA19-9, ICAM-1, OPG panel is selective for PDAC and does not recognize breast (SP = 100%), lung (SP = 97%), or colon (SP = 97%) cancer.
  
  
  CONCLUSIONS
  The PDAC-specific biomarker panels identified in this investigation warrant additional clinical validation to determine their role in screening targeted high-risk populations.
authors.affiliation: Division of Gastroenterology, Hepatology and Nutrition, University of Pittsburgh and University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
authors.forename: Randall E
authors.initials: RE
authors.lastname: Brand
authors.forename: Brian M
authors.initials: BM
authors.lastname: Nolen
authors.forename: Herbert J
authors.initials: HJ
authors.lastname: Zeh
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Allen
authors.forename: Mohamad A
authors.initials: MA
authors.lastname: Eloubeidi
authors.forename: Michael
authors.initials: M
authors.lastname: Goldberg
authors.forename: Eric
authors.initials: E
authors.lastname: Elton
authors.forename: Juan P
authors.initials: JP
authors.lastname: Arnoletti
authors.forename: John D
authors.initials: JD
authors.lastname: Christein
authors.forename: Selwyn M
authors.initials: SM
authors.lastname: Vickers
authors.forename: Christopher J
authors.initials: CJ
authors.lastname: Langmead
authors.forename: Douglas P
authors.initials: DP
authors.lastname: Landsittel
authors.forename: David C
authors.initials: DC
authors.lastname: Whitcomb
authors.forename: William E
authors.initials: WE
authors.lastname: Grizzle
authors.forename: Anna E
authors.initials: AE
authors.lastname: Lokshin
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000097:blood*; D001798:Blood Proteins / Q000378:metabolism*; D021441:Carcinoma, Pancreatic Ductal / Q000175:diagnosis* / Q000378:metabolism; D016022:Case-Control Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D025202:Molecular Diagnostic Techniques / Q000379:methods* / Q000706:statistics & numerical data; D015999:Multivariate Analysis; D010190:Pancreatic Neoplasms / Q000175:diagnosis* / Q000378:metabolism; D012372:ROC Curve; D012680:Sensitivity and Specificity; D055815:Young Adult
chemical_list: D014408:Biomarkers, Tumor; D001798:Blood Proteins