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）的主要组成成分，可影响肿瘤发生、增殖、侵袭及血管生成进程。然而，目前已发表的关于ECM与胃癌（gastric cancer, GC）预后相关性的研究较为有限，尚无基于ECM相关基因的胃癌患者预后风险预测模型。本研究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间的差异表达基因（differentially expressed genes, DEGs），筛选出其中的ECM相关差异表达基因并对其开展LASSO Cox回归分析，最终构建了包含5个ECM相关基因的预后风险模型。基于风险评分（RiskScore）与临床特征构建了临床诊断用列线图（nomogram）。研究结果显示，风险评分较低的胃癌患者其生存预后优于风险评分较高的患者。受试者工作特征（receiver operating characteristic, ROC）曲线验证了该预后风险特征的准确性，且该预后风险模型的性能在两个外部数据集（external datasets）中得到了进一步验证。

搜集汇总

背景与挑战

背景概述

该数据集包含用于构建胃癌预后和免疫特征预测模型的数据文件，主要基于细胞外基质相关基因的差异表达分析。数据集提供了TCGA数据库的临床和基因表达数据，以及两个外部验证数据集，支持模型的开发和验证。