Gastric cancer (GC) is one of the most common malignant tumors worldwide. Many patients diagnosed with GC are already at a late stage. Despite the decrease in mortality rates recently, the prognosis of this cancer is poor. Therefore, it is necessary to explore novel biomarkers with early diagnostic value with GC. In this study, we present a large-scale proteomic analysis of 30 GC tissues and 30 matched normal tissues using label-free global proteome profiling. The results allowed identifying 537 differentially expressed proteins, including 280 upregulated and 257 downregulated proteins. The ingenuity pathway analysis (IPA) results indicated that the sirtuin signaling pathway was the most activated whereas the oxidative phosphorylation was the most inhibited pathway. Moreover, the most activated molecular function was cell movement, including tissue invasion by tumor cell lines. Based on IPA results, 15 hub proteins were screened. Using the receiver operating characteristic curve, most of these hub proteins had a high diagnostic power in distinguishing tumors and normal controls. A four-protein (ATP5B-ATP5O-NDUFB4-NDUFB8) diagnostic signature was built using a random forest model. The area under curve (AUC) of this model was 0.864 in the validation set, suggesting a high diagnostic power. In the testing set of plasma enzyme-linked immune sorbent assay, the results achieved an AUC of 0.778 and accuracy of 71.8% to distinguish GC tissues from healthy controls. In conclusion, this study identified potential biomarkers and help to understand the pathogenesis of GC and provide novel and specific therapeutic targets for this cancer.