鉴定cAMP通路相关基因与胃癌的预后价值以及与免疫浸润的关系

Identification of cAMP pathway-related genes with prognostic value and correlation with immune infiltration in gastric cancer

目的 基于环磷酸腺苷(cAMP)通路基因构建与胃癌预后相关的风险模型,并研究预后特异性和免疫特征。方法选用TCGA数据库下载的胃腺癌和正常组织的转录组以及临床数据,采用加权基因共表达网络分析(WGCNA)、单因素Cox回归和迭代多因素Cox回归分析构建最佳的cAMP通路相关的胃癌预后模型,并在GEO数据中进行验证。用Kaplan-Meier生存分析、单因素和多因素研究模型的预后特征。采用基因集富集分析(GESA)分析探索高低危人群的差异表达信号通路。用免疫CIBERSORT算法探讨风险评分与肿瘤免疫微环境的关系。利用TIDE评分估计高低风险胃癌患者的免疫治疗反应。结果用WGCNA筛选出51个模块基因,最终构建了最佳的双基因(EDNRA和GNAI1)胃癌预后模型。多因素Cox回归分析表明,预后风险模型可作为一个独立预后因素(HR=2.641,P=6.33×10^(-4))。GSEA发现高风险组主要在心肌病、细胞-基质黏附通路中富集,低风险组在DNA复制和氧化磷酸化通路中富集。免疫细胞浸润结果揭示了高危人群与静息记忆CD4+T细胞、单核细胞和静息肥大细胞等多种免疫细胞密切相关。高风险组中的TIDE、T细胞排除率和T细胞功能障碍评分显著高于低风险组。结论 我们成功构建了双基因的预后模型,为胃癌患者的预后诊断以及基因靶向治疗发挥重要作用。

Objective This study aimed to construct a risk signature related to gastric cancer(GC) prognosis based on cAMP pathway genes and investigate its prognostic specificity and immune characteristics.Methods Transcriptomic data and clinical information for gastric adenocarcinoma and normal tissues were obtained from the TCGA database.Weighted gene co-expression network analysis(WGCNA),univariate Cox regression,and iterative multivariable Cox regression were employed to construct the optimal cAMP pathway-related gastric cancer prognosis signature,which was further validated in an independent GEO dataset.Kaplan-Meier survival analysis,univariate Cox regression analyses and multivariate Cox regression analyses were used to explore the prognostic features of the signature.Gene set enrichment analysis(GSEA) was performed to investigate differentially expressed signaling pathways between high and low-risk groups in GC.The immune CIBERSORT algorithm was performed to explore the relationship between the risk score and the tumor immune microenvironment.The TIDE score was conducted to estimate the immunotherapeutic response of high and low-risk gastric cancer patients.Results Using WGCNA,we identified 51 modules of genes,ultimately constructing the optimal dual-gene(EDNRA and GNAI1) gastric cancer prognosis signature.Multivariable Cox regression analysis revealed that the prognostic risk signature could serve as an independent prognostic factor(HR=2.641,P=6.33×10^(-4)).GSEA identified the key pathways including cardiomyopathy and cell-matrix adhesion were enriched in high and DNA replication and oxidative phosphorylation were enriched in low-risk groups.The immune cell infiltration analysis revealed close associations of the high-risk group with immune cells such as resting memory CD4^(+) T cells,monocytes,and resting mast cells.The high-risk group exhibited significantly higher TIDE,T cell exclusion score,and T cell dysfunction score compared to the low-risk group.Conclusion We successfully developed a dual-gene prognosis signature,which holds significant implications for prognosis diagnosis and gene-targeted therapy in gastric cancer patients.