title: Protein deep sequencing applied to biobank samples from patients with pancreatic cancer.
abstract: OBJECTIVE
  Pancreatic cancer is commonly detected at advanced stages when the tumor is no longer amenable to surgical resection. Therefore, finding biomarkers for early stage disease is urgent. Here, we show that high-definition mass spectrometry (HDMS(E)) can be used to identify serum protein alterations associated with early stage pancreatic cancer.
  
  
  METHODS
  We analyzed serum samples from patients with resectable pancreatic cancer, benign pancreatic disease, and healthy controls. The SYNAPT G2-Si platform was used in a data-independent manner coupled with ion mobility. The dilution of the samples with yeast alcohol dehydrogenase tryptic digest of known concentration allowed the estimated amounts of each identified protein to be calculated (Silva et al. in Anal Chem 77:2187-2200, 2005; Silva et al. in Mol Cell Proteomics 5:144-156, 2006). A global protein expression comparison of the three study groups was made using label-free quantification and bioinformatic analyses.
  
  
  RESULTS
  Two-way unsupervised hierarchical clustering revealed 134 proteins that successfully classified pancreatic cancer patients from the controls, and identified 40 proteins that showed a significant up-regulation in the pancreatic cancer group. This discrimination reliability was further confirmed by principal component analysis. The differentially expressed candidates were aligned with protein network analyses and linked to biological pathways related to pancreatic tumorigenesis. Pancreatic disease link associations could be made for BAZ2A, CDK13, DAPK1, DST, EXOSC3, INHBE, KAT2B, KIF20B, SMC1B, and SPAG5, by pathway network linkages to p53, the most frequently altered tumor suppressor in pancreatic cancer.
  
  
  CONCLUSIONS
  These pancreatic cancer study candidates may provide new avenues of research for a noninvasive blood-based diagnosis for pancreatic tumor stratification.
authors.affiliation: Department of Surgery, Clinical Sciences Lund, Lund University, Skåne University Hospital, 221 85, Lund, Sweden.
authors.forename: Daniel
authors.initials: D
authors.lastname: Ansari
authors.forename: Roland
authors.initials: R
authors.lastname: Andersson
authors.forename: Monika P
authors.initials: MP
authors.lastname: Bauden
authors.forename: Bodil
authors.initials: B
authors.lastname: Andersson
authors.forename: Joanne B
authors.initials: JB
authors.lastname: Connolly
authors.forename: Charlotte
authors.initials: C
authors.lastname: Welinder
authors.forename: Agata
authors.initials: A
authors.lastname: Sasor
authors.forename: György
authors.initials: G
authors.lastname: Marko-Varga
mesh_terms: D000368:Aged; D018070:Biological Specimen Banks; D014408:Biomarkers, Tumor / Q000378:metabolism*; D001798:Blood Proteins / Q000378:metabolism*; D016022:Case-Control Studies; D019295:Computational Biology; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010179:Pancreas / Q000378:metabolism*; D010190:Pancreatic Neoplasms / Q000378:metabolism*; D011379:Prognosis; D040901:Proteomics / Q000379:methods*; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
chemical_list: D014408:Biomarkers, Tumor; D001798:Blood Proteins