Application of serum proteomic pattern on diagnosis of early gastric cancer

Objective:To establish serum proteomic pattern for the early diagnosis of gastric cancer.Methods: PBSⅡ/C type protein spectrometer and CM10 protein chip were performed to detect mass spectrogram of patients with gastric cancer and contrast persons for serum protein signature analysis to build and test ANN model.Results: Four specific protein peaks(M/Z as 2502.3±3.2,3085.5±2.8,4130.6±2.1,8691.4±1.7) which were chosen to develop the artificial neural network diagnostic model had significant difference in gastric cancer compared with the control group.The sensitivity,specificity,negative predictive value,positive predictive value were 95%,98.33%,98.33%,95%,97.5%.Conclusion: Serum proteomic pattern established by this study was valuable to the early diagnosis of gastric cancer.