Department of Oncology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China.
Department of Liver Surgery, Renji Hospital, Shanghai Jiao Tong University School of Medicine, China.
Gene. 2024 Nov 30;928:148796. doi: 10.1016/j.gene.2024.148796. Epub 2024 Jul 25.
Angiogenesis significantly correlates with tumor microenvironment remodeling and immunotherapy response. Our study aimed to construct a prognostic angiogenesis-related model for gastric cancer. Using public database, a angiogenetic related five-gene (FGF1, GRB14, PAK3, PDGFRA, and PRKD1) model was identified. The top 25 % of patients were defined as high-risk, and the remaining as low-risk. The area under the curve for 1-, 3-, and 5-year overall survival (OS) were 0.646, 0.711, and 0.793, respectively. Survival analysis showed a better 10-year OS in low-risk patients in the construction (HR = 0.57, p = 0.002) and validation cohorts. GO and GSEA revealed that DEGs were enriched in extracellular matrix receptor interactions, dendritic cell antigen processing/presentation regulation, and angiogenesis pathways. CIBERSORT analysis revealed abundant naïve B cells, resting mast cells, resting CD4 memory T cells, M2 macrophages, and monocytes in high-risk subgroups. The TIMER database showed strong positive correlations between PAK3, FGF1, PRKD1, and PDGFRA expression levels and the infiltration of CD4 T cells and macrophages. The IOBR analysis revealed an immunosuppressive environment in the high-risk subgroup. Low-risk patients show a higher response rate to anti-PD1 treatment. TMA showed that FGF1 overexpression was associated with poor prognosis and CD4 T cells and macrophage infiltration. In vivo study based on the 615 mice indicated that inhibiting FGF1 function could suppress tumor growth and enhance anti-PD1 therapeutic efficacy. In summary, we established a five-angiogenesis-related gene model to predict survival outcomes and immunotherapy responses in patients with gastric cancer and identified FGF1 as a prognostic gene and potential target for improving immune treatment.
血管生成与肿瘤微环境重塑和免疫治疗反应密切相关。我们的研究旨在构建一个用于预测胃癌的预后相关血管生成模型。使用公共数据库，确定了一个与血管生成相关的五个基因（FGF1、GRB14、PAK3、PDGFRA 和 PRKD1）模型。将前 25%的患者定义为高风险，其余为低风险。1、3、5 年总生存期（OS）的曲线下面积分别为 0.646、0.711 和 0.793。生存分析显示，在构建和验证队列中，低风险患者的 10 年 OS 更好（HR=0.57，p=0.002）。GO 和 GSEA 分析显示，DEGs 富集在细胞外基质受体相互作用、树突状细胞抗原处理/呈递调节和血管生成途径中。CIBERSORT 分析显示，高风险亚组中存在丰富的幼稚 B 细胞、静止肥大细胞、静止 CD4 记忆 T 细胞、M2 巨噬细胞和单核细胞。TIMER 数据库显示 PAK3、FGF1、PRKD1 和 PDGFRA 表达水平与 CD4 T 细胞和巨噬细胞浸润之间存在强烈的正相关。IOBR 分析显示高风险亚组存在免疫抑制环境。低风险患者对抗 PD1 治疗的反应率更高。TMA 显示 FGF1 过表达与预后不良和 CD4 T 细胞和巨噬细胞浸润相关。基于 615 只小鼠的体内研究表明，抑制 FGF1 功能可抑制肿瘤生长并增强抗 PD1 治疗效果。总之，我们建立了一个与血管生成相关的五个基因模型，用于预测胃癌患者的生存结果和免疫治疗反应，并确定 FGF1 作为一个预后基因和改善免疫治疗的潜在靶点。
