Data Files Used for Construction of an Extracellular Matrix-related Gene Model for Predicting Prognosis and Immune Features in Gastric Cancer

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.

细胞外基质（extracellular matrix, ECM）是肿瘤微环境（tumor microenvironment）的核心组成部分，可调控肿瘤的发生、增殖、侵袭及血管生成。然而，目前针对ECM与胃癌（gastric cancer, GC）预后相关性的已发表研究仍较为有限，且尚无专门基于ECM相关基因的胃癌患者预后风险预测模型。我们基于癌症基因组图谱（The Cancer Genome Atlas, TCGA）数据库，筛选正常胃组织与胃癌组织之间的差异表达基因（differentially expressed genes, DEGs），选取其中的ECM相关DEGs并开展LASSO Cox回归分析，最终构建了基于5个ECM相关基因的预后风险模型。基于风险评分（RiskScore）与临床特征，我们进一步构建了临床辅助诊断用列线图（nomogram）。结果显示，风险评分较低的胃癌患者相较于风险评分较高的患者，其生存预后更佳。受试者工作特征曲线（receiver operating characteristic, ROC）证实了该预后特征的准确性，该预后风险模型的性能在两个外部验证数据集中得到了进一步验证。