Bioinformatic analysis of the potential common pathogenic mechanisms for gastric precancerous lesions and Helicobacter pylori.

Liufeng Yi, Tiantong Jiang, Siyu Tao, Nachuan Li, Yuan Ding, Meng Li, Shaoli Wang, Zhen Liu
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Abstract

Objective: Gastric precancerous lesions (GPL) represent a critical stage in the progression from gastritis to gastric cancer (GC). Helicobacter pylori (H. pylori) infection is a significant etiological factor exacerbating the inflammatory-cancerous transformation. The host immune status is a central regulatory mechanism for GPL, while persistent H. pylori infection drives changes in the immune microenvironment (IME). However, the potential pathological link between GPL and H. pylori remains unclear. This study aims to identify common differentially expressed genes (DEGs) between GPL and H. pylori using bioinformatics analysis, thereby elucidating their shared pathogenic mechanisms.

Methods: DEGs were extracted from GPL datasets (GSE87666) and H. pylori datasets (GSE60427) sourced from the Gene Expression Omnibus (GEO) database through GEO2R and R software. Protein-protein interaction (PPI) networks were generated using the STRING database and analyzed with Cytoscape software to identify hub genes. The diagnostic value of these hub genes was evaluated through Receiver Operating Characteristic (ROC) curves and Area Under the Curve (AUC) analysis, validated with datasets GSE130823, GSE60662, and GSE5081. Immune infiltration analysis of key genes was conducted using the CIBERSORT algorithm and ssGSEA. Gene mutation analysis was carried out using the cBioPortal database, and small molecule drugs were detected using the Connectivity Map (CMap) database.

Results: The analysis revealed 189 DEGs. Functional enrichment analysis highlighted pathways related to immune system regulation, leukocyte migration and chemotaxis, cytokine-cytokine receptor interaction, and chemokine signaling. Seven hub genes were identified: IL6, FCGR3A, CCL3, CXCR4, CXCL9, CCL4, and CCR1. High AUC values for these hub genes indicated their potential for predicting disease occurrence.

Conclusions: This research identified seven hub genes closely related to GPL and H. pylori, elucidating potential mechanisms of disease progression, particularly emphasizing the roles of the IME and chemokine activity. These findings may provide insights for identifying disease biomarkers, inhibiting the "inflammation-cancer" transformation, and preventing GC. Furthermore, the targets and molecular mechanisms identified in this study require further experimental validation to confirm their therapeutic potential.

胃癌前病变和幽门螺杆菌潜在共同致病机制的生物信息学分析。
目的:胃癌前病变(GPL)是胃炎向胃癌发展的关键阶段。幽门螺杆菌(h.p ylori)感染是加重炎性癌变的重要病因。宿主免疫状态是GPL的中心调控机制,而持续性幽门螺杆菌感染驱动免疫微环境(IME)的变化。然而,GPL和幽门螺杆菌之间潜在的病理联系尚不清楚。本研究旨在通过生物信息学分析鉴定GPL和幽门螺杆菌之间的共同差异表达基因(DEGs),从而阐明它们共同的致病机制。方法:通过GEO2R和R软件分别从基因表达Omnibus (GEO)数据库中的GPL数据集(GSE87666)和幽门螺杆菌数据集(GSE60427)中提取DEGs。利用STRING数据库生成蛋白-蛋白相互作用(PPI)网络,并用Cytoscape软件进行分析,以确定枢纽基因。通过受试者工作特征(ROC)曲线和曲线下面积(AUC)分析评估这些枢纽基因的诊断价值,并使用数据集GSE130823、GSE60662和GSE5081进行验证。采用CIBERSORT算法和ssGSEA对关键基因进行免疫浸润分析。基因突变分析采用cBioPortal数据库,小分子药物检测采用Connectivity Map (CMap)数据库。结果:分析结果为189 deg。功能富集分析强调了与免疫系统调节、白细胞迁移和趋化性、细胞因子-细胞因子受体相互作用和趋化因子信号传导相关的途径。共鉴定出7个枢纽基因:IL6、FCGR3A、CCL3、CXCR4、CXCL9、CCL4和CCR1。这些枢纽基因的高AUC值表明它们有预测疾病发生的潜力。结论:本研究确定了与GPL和幽门螺杆菌密切相关的7个枢纽基因,阐明了疾病进展的潜在机制,特别强调了IME和趋化因子活性的作用。这些发现可能为识别疾病生物标志物、抑制“炎症-癌症”转化和预防胃癌提供见解。此外,本研究确定的靶点和分子机制需要进一步的实验验证以确认其治疗潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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