Data Files Used for Construction of an Extracellular Matrix-related Gene Model for Predicting Prognosis and Immune Features in Gastric Cancer|胃癌研究数据集|基因模型数据集

The extracellular matrix (ECM) is a major component of the tumor microenvironment and can influence tumor initiation, proliferation, invasion, and angiogenesis. However, published research on the relationship between ECM and gastric cancer (GC) prognosis is limited. There is currently no ECM-related prognostic risk model to predict the prognosis of GC patients. We screened the differentially expressed genes (DEGs) between normal and GC tissues based on The Cancer Genome Atlas (TCGA) database. ECM-related DEGs were selected and LASSO Cox regression analysis was performed for these DEGs. We established a prognostic risk model based on five ECM-related genes. A nomogram for clinical diagnosis was constructed based on Riskscore and clinical characteristics. The results showed that GC patients with lower RiskScore had better survival outcomes than those with higher RiskScore. The receiver operating characteristic (ROC) curve confirmed the accuracy of the prognostic risk signatures. The performance of the prognostic risk model was further validated in two external datasets.