利用生物信息学分析肥胖与胃癌的关联

肥胖与胃癌（GC）在全球范围内均为常见疾病。尤其是肥胖患者人数逐年增加，而胃癌的发病率和死亡率居高不下，严重影响个体生活质量。尽管已有证据表明两者之间存在紧密联系，但其共病机制仍不清楚。我们从Gene Expression Omnibus数据库获取了GSE94752和GSE54129的基因表达谱数据。通过基因本体（Gene Ontology）和京都基因与基因组百科全书（KEGG）对肥胖与胃癌共有差异表达基因（DEGs）进行路径富集分析，探讨相关生物过程。随后基于Search Tool for the Retrieval of Interacting Genes (STRING)数据库建立蛋白质-蛋白质相互作用（PPI）网络，并利用Cytoscape插件MCODE筛选核心模块和中心基因。进一步分析这些中心基因的共表达网络及转录因子（TF）、miRNAs与mRNAs的相互作用网络。最后，利用不同数据集进行验证，确认核心基因的意义。共筛选出246个共享差异表达基因（209上调，37下调），功能分析强调炎症和免疫相关途径在两种疾病中的关键作用。利用Cytoscape插件CytoHubba识别出九个核心基因，包括CXCR4、CXCL8、CXCL10、IL6、TNF、CCL4、CXCL2、CD4和CCL2。通过多数据集验证，IL6和CCL4被确认为最终核心基因。TF-miRNA-mRNA调控网络显示，主要关联的转录因子包括RELA和NFKB1，而主要的miRNAs包括hsa-miR-195-5p和hsa-miR-106a-5p。通过生物信息学方法，筛选出与肥胖和胃癌相关的两个核心基因，建构了核心基因、转录因子和miRNAs的网络，揭示了其潜在的共同分子机制。

Obesity and gastric cancer (GC) are prevalent diseases worldwide. In particular, the number of patients with obesity is increasing annually, while the incidence and mortality rates of GC are ranked high. Consequently, these conditions seriously affect the quality of life of individuals. While evidence suggests a strong association between these two conditions, the underlying mechanisms of this comorbidity remain unclear.We obtained the gene expression profiles of GSE94752 and GSE54129 from the Gene Expression Omnibus database. To investigate the associated biological processes, pathway enrichment analyses were conducted using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes for the shared differentially expressed genes in obesity and GC. A protein-protein interaction (PPI) network was subsequently established based on the Search Tool for the Retrieval of Interacting Genes (STRING) database, followed by the screening of the core modules and central genes in this network using Cytoscape plug-in MCODE. Furthermore, we scrutinized the co-expression network and the interplay network of transcription factors (TFs), miRNAs, and mRNAs linked to these central genes. Finally, we conducted further analyses using different datasets to validate the significance of the hub genes.A total of 246 shared differentially expressed genes (209 upregulated and 37 downregulated) were selected for ensuing analyses. Functional analysis emphasized the pivotal role of inflammation and immune-associated pathways in these two diseases. Using the Cytoscape plug-in CytoHubba, nine hub genes were identified, namely, CXCR4, CXCL8, CXCL10, IL6, TNF, CCL4, CXCL2, CD4, and CCL2. IL6 and CCL4 were confirmed as the final hub genes through validation using different datasets. The TF-miRNA-mRNA regulatory network showed that the TFs primarily associated with the hub genes included RELA and NFKB1, while the predominantly associated miRNAs included has-miR-195-5p and has-miR-106a-5p.Using bioinformatics methods, we identified two hub genes from the Gene Expression Omnibus datasets for obesity and GC. In addition, we constructed a network of hub genes, TFs, and miRNAs, and identified the major related TFs and miRNAs. These factors may be involved in the common molecular mechanisms of obesity and GC.