Application of serum proteomic patterns by ProteinChip SELDI system in diagnosis of gastric cancer

Abstract

10559 Background: Gastric cancer is one of the most common malignancy in the world and one of the leading causes of cancer related death in Korea. Most treatments for advanced gastric cancer have limited efficacy. So early detection of gastric cancer could have profound impact on the successful treatment. Application of multiple biomarkers may improve the diagnostic prediction to distinguish cancer from non-cancer. ProteinChip Surface-Enhanced Laser Desorption/Ionization Time-of-flight Mass Spectrometry (SELDI-TOF-MS) system is one of the currently used techniques to identify biomarkers for cancers. In this study, we have explored whether the serum proteomic patterns by ProteinChip SELDI system can differentiate gastric cancers from non-cancer cohorts. Methods: We have screened protein profiles of 100 serum samples obtained from 60 gastric cancer patients and 40 healthy individuals. Protein expression profiles were expressed on ProteinChip Array and analyzed by PreoteinChip Reader. Peak intensities were normalized by total ion currency and analyzed by the Biomarker Wizard Software to identify the peaks showing significantly different intensities between normal and cancer groups. Classification analysis and construction of decision trees were done with the Biomarker Pattern Software. Results: SELDI -TOF-MS by averaging 50 laser spots collected at a laser intensity setting of 160, a detector sensitivity of 6, and mean mass range of 30 kDa. Seventeen protein peaks shown significant differences between two groups were chosen to make a protein biomarker pattern. The decision tree which gives the highest discrimination included four peaks at 5,919, 8,583, 10,286, and 13,758 as splitters. The sensitivity and the specificity for classification of with the decision tree giving the highest discrimination were 96.7% (58/60) and 97.5% (39/40), respectively. When the protein biomarker pattern was tested with the blinded test set including 30 gastric cancer patients and 20 healthy individuals and, it yielded a sensitivity of 93.3% (28/30) and a specificity of 90% (18/20). Conclusions: These results suggest that serum-protein profiling pattern by SELDI system may distinguish gastric cancer patients from normal counterparts with relatively high sensitivity and specificity. No significant financial relationships to disclose.