CAV1 and gastric cancer: In this study, we integrated GEO and TCGA databases, using bioinformatics analysis methods, to mine and analyze high-throughput data to conduct module and centrality analysis of the PPI network, which helped us screen out key genes (MYLK, MYL9, LUM, and CAV1) that have an important impact on the prognosis of GC patients and can be considered as a biomarker and potential therapeutic target for GC prognosis.