The identification of molecular markers for diagnosis, treatment, and prognosis is a significant issue in the management of patients with gastric cancer. We compared the expression profiles of 23 gastric cancers and 22 normal gastric tissues using cDNA microarrays. We divided the samples into two sets, 11 pairs as a training set and 12 unpaired gastric cancer and 11 unpaired normal gastric tissues as a test set. We selected significant genes in the training set and validated the significance of the genes in the test set. We obtained 238 classifier genes that showed a maximum cross-validation probability and clear hierarchical clustering pattern in the training set, and showed excellent class prediction probability in the independent test set. The classifier genes consisted of known genes related to the biological features of cancer and 28% unknown genes. We obtained genome-wide molecular signatures of gastric cancer, which provides preliminary exploration data for the pathophysiology of gastric cancer.