Peng Jing, Yan Qi, Pei Wennan, Jiang Yi, Zhou Li, Li Ruoqing
Department of General Medicine, Chongqing University Central Hospital, Chongqing Emergency Medical Center, Chongqing Key Laboratory of Emergency Medicine, Chongqing, China.
Department of Gastroenterology and Hepatology, Chongqing Emergency Medical Center, Chongqing University Central Hospital, Chongqing, China.
Int J Genomics. 2025 Jan 21;2025:5554610. doi: 10.1155/ijog/5554610. eCollection 2025.
() is associated with the development of various stomach diseases, one of the major risk factors for stomach adenocarcinoma (STAD). The infection score between tumor and normal groups was compared by single-sample gene set enrichment analysis (ssGSEA). The key modules related to infection were identified by weighted gene coexpression network analysis (WGCNA), and functional enrichment analysis was conducted on these module genes. Further, the limma package was used to screen the differentially expressed genes (DEGs) between -positive and -negative STAD. The prognostic genes were obtained to construct the riskscore model, and the performance of the model was validated. The correlation between riskscore and tumor immune microenvironment (TIME) was analyzed by Spearman's method. The single-cell atlas of -positive STAD was delineated. The mRNA expression levels of the prognostic genes were verified using STAD cells, and the migration and invasion capacities of STAD cells were evaluated by using the wound healing assay and transwell assay. The infection score in the tumor group was significantly higher than that in the normal group. The purple and royal blue modules showed higher correlation with infection in STAD, and these module genes were enriched in the immune-related pathway. Further, five prognostic genes (, , , , and ) were screened from the infection-related DEGs, which were utilized for establishing the riskscore model, with good robustness. Riskscore exhibited strong correlation with TIME in STAD. Single-cell atlas of -positive STAD revealed that is highly expressed in Epithelial Cell 1, Epithelial Cell 2, and parietal cells of the tumor group. , , , , and showed high expression in STAD cells, and the silencing of could suppress the migration and invasion of STAD cells. This study established a riskscore model based on infection-related genes, which could provide reference for prognostic prediction and treatment targets of STAD.
（）与各种胃部疾病的发生相关，是胃腺癌（STAD）的主要危险因素之一。通过单样本基因集富集分析（ssGSEA）比较肿瘤组和正常组之间的感染评分。通过加权基因共表达网络分析（WGCNA）确定与感染相关的关键模块，并对这些模块基因进行功能富集分析。此外，使用limma软件包筛选阳性和阴性STAD之间的差异表达基因（DEG）。获得预后基因以构建风险评分模型，并验证该模型的性能。通过Spearman方法分析风险评分与肿瘤免疫微环境（TIME）之间的相关性。描绘了阳性STAD的单细胞图谱。使用STAD细胞验证预后基因的mRNA表达水平，并通过伤口愈合试验和transwell试验评估STAD细胞的迁移和侵袭能力。肿瘤组的感染评分明显高于正常组。紫色和皇家蓝色模块在STAD中与感染显示出更高的相关性，并且这些模块基因在免疫相关途径中富集。此外，从感染相关的DEG中筛选出五个预后基因（、、、、和），用于建立风险评分模型，具有良好的稳健性。风险评分在STAD中与TIME表现出强相关性。阳性STAD的单细胞图谱显示，在肿瘤组的上皮细胞1、上皮细胞2和壁细胞中高表达。、、、、和在STAD细胞中高表达，并且的沉默可以抑制STAD细胞的迁移和侵袭。本研究基于感染相关基因建立了风险评分模型，可为STAD的预后预测和治疗靶点提供参考。
