Gastric cancer (GC) remains one of the most common malignant tumours worldwide, with extremely high morbidity and mortality rates. An in-depth understanding of the pathogenesis of GC is key to the future diagnosis and treatment of GC. In this study, we analysed the differentially expressed genes (DEGs) in gastric carcinoma (GC) through GEO database and their clinical implications, with the aim of providing clinical reference and guidance. We selected the GSE118916 dataset for bioinformatics analysis and identified a total of 3231 DEGs. Keywords, including extracellular region, vesicle, protein digestion and absorption, ECM-receptor interaction, etc., of DEGs can be seen by the GO and KEGG enrichment analysis. The online database determined up-regulated CST1 in GC and some other tumors, as well as a close connection between CST1 with patient prognosis. Subsequently, we collected a number of GC clinical cases and examined the expression of CST1, which was seen to be highly expressed in GC, with a favorable diagnostic effect on the occurrence of GC (P<0.05) and a strong correlation with TNM stage, tumor invasion, tumor diameter and differentiation (P<0.05). In other words, CST1 is closely related to the occurrence and development of GC, and has the potential to be a breakthrough in the diagnosis and treatment of GC in the future.