title: Diagnosis of gastric cancer by serum proteomic fingerprinting.
abstract: OBJECTIVE
  Accurate serum biomarkers for gastric cancer currently are lacking. We attempted to identify potential diagnostic serum markers for gastric cancer with the use of the surface-enhanced laser desorption/ionization ProteinChip technology.
  
  
  METHODS
  The study was divided into 3 phases: (1) discovery of potential diagnostic markers using sera of gastric cancer patients and controls, (2) development of a diagnostic model, and (3) independent validation of the diagnostic model using a different cohort of gastric cancer and control patients. The serum proteins/peptides were analyzed with 2 types of ProteinChip arrays, IMAC30 arrays loaded with copper (II) ion and CM10 (weak cation exchange) arrays.
  
  
  RESULTS
  In the discovery set, peak intensities of 31 surface-enhanced laser desorption/ionization proteomic features were significantly higher in gastric cancer patients. The tumor-specific nature of 6 proteomic features with the mass/charge (m/z) values of 5098, 8592, 8610, 11,468, 11,804, and 50,140 was verified by their lower peak intensities in postoperative sera. After excluding the sodium adduct peak (8610 m/z) of the 8592 m/z protein, the peak intensities of the tumor-specific proteomic features were used to develop a linear regression model for calculating a diagnostic index. The area under the receiver operating characteristic curve of the corresponding diagnostic index was 0.92 (95% confidence interval, 0.85-0.99) in the independent validation set. At a specificity of 95%, the sensitivity for gastric cancer detection was 83%.
  
  
  CONCLUSIONS
  A unique serum proteomic fingerprint can be detected in the sera of gastric cancer patients, which may be useful in the noninvasive diagnosis of gastric cancer.
authors.affiliation: Institute of Digestive Diseases of the Chinese University of Hong Kong, Hong Kong, Special Administrative Region, The People's Republic of China.
authors.forename: Terence C W
authors.initials: TC
authors.lastname: Poon
authors.forename: Joseph J Y
authors.initials: JJ
authors.lastname: Sung
authors.forename: Shuk M
authors.initials: SM
authors.lastname: Chow
authors.forename: Enders K W
authors.initials: EK
authors.lastname: Ng
authors.forename: Alex C W
authors.initials: AC
authors.lastname: Yu
authors.forename: Eagle S H
authors.initials: ES
authors.lastname: Chu
authors.forename: Angela M Y
authors.initials: AM
authors.lastname: Hui
authors.forename: Wai K
authors.initials: WK
authors.lastname: Leung
mesh_terms: D000328:Adult; D000368:Aged; D016022:Case-Control Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D010449:Peptide Mapping; D011336:Probability; D040081:Protein Array Analysis; D040901:Proteomics / Q000379:methods*; D012372:ROC Curve; D012680:Sensitivity and Specificity; D018709:Statistics, Nonparametric; D013274:Stomach Neoplasms / Q000175:diagnosis* / Q000235:genetics*