Objective: To analyze the alterations of serum proteomic pattern in esophageal squamous cell carcinoma (ESCC) by SELDI-TOF-MS, to establish a diagnostic model of ESCC screening in high incidence area and investigate its clinical value.
Methods: SELDI-TOF-MS and CM10 proteinChip were used to detect the serum proteomic patterns of 36 cases of ESCC and 38 healthy control subjects in high incidence area. The data were analyzed and a diagnostic model was established by using support vector machine (SVM). The diagnostic model was evaluated by leave-one-out cross validation.
Results: At the molecular weight range of 2000 to 20,000, 31 protein peaks were significantly different between ESCC and controls (P < 0.01). A diagnostic model consisting of 4 protein peaks could do the best in diagnosis of ESCC and controls. The accuracy was 85.1%, sensitivity was 86.1%, specificity was 84.2%, and positive value was 83.8%.
Conclusion: The diagnostic model formed by 4 protein peaks, established in this study, can well distinguish ESCC from healthy subjects. It provides a new approach for ESCC screening in high incidence area.