Department of General Surgery, First People's Hospital of Linping District, Hangzhou 311100, China.
First People's Hospital of Linping District.
J Environ Pathol Toxicol Oncol. 2024;43(3):81-93. doi: 10.1615/JEnvironPatholToxicolOncol.2024050455.
Gastric cancer (GC) is the fifth most prevalent malignancy worldwide, characterized by poor prognosis. Apoptosis is interacted with hypoxia in tumorigenesis. This study attempted to delineate potential value of apoptosis and hypoxia-related genes (AHRGs) in prognosis of gastric cancer. Differential expression analysis was performed on GC transcriptomic data from TCGA. Apoptosis-related genes (ARGs) and hypoxia-related genes (HRGs) were obtained from MSigDB, followed by intersecting them with differentially expressed genes (DEGs) in GC. A prognostic model was constructed using univariate, LASSO, and multivariate regression analyses. The model was validated using a Gene Expression Omnibus dataset. DEGs between risk groups were subjected to enrichment analysis. A nomogram was plotted by incorporating clinical information. Non-negative matrix factorization based on core prognostic genes from the multifactorial model was employed to cluster tumor samples. The subsequent analyses involved immunophenoscore, immune landscape, Tumor Immune Dysfunction and Exclusion (TIDE) score, and chemosensitivity for distinct subtypes. A prognostic model based on AHRGs was established, and its predictive capability was verified in external cohorts. Riskscore was determined as an independent prognostic factor, and it was used, combined with other clinical features, to plot a prognostic nomogram. Patients were clustered into cluster1 and cluster2 based on prognostic model genes. Cluster2 showed poorer prognosis and IPS scores, higher immune cell infiltration, immune function and TIDE scores than cluster1. Distinct therapeutic potential for various chemotherapeutic agents was observed between the two clusters. The developed AHRG scoring introduced a novel and effective avenue for predicting GC prognosis and identifying potential targets for further investigation.
胃癌（GC）是全球第五大常见恶性肿瘤，预后较差。细胞凋亡与肿瘤发生中的缺氧相互作用。本研究试图描绘细胞凋亡和缺氧相关基因（AHRGs）在胃癌预后中的潜在价值。对 TCGA 的 GC 转录组数据进行差异表达分析。从 MSigDB 中获取与细胞凋亡相关的基因（ARGs）和与缺氧相关的基因（HRGs），然后与 GC 中的差异表达基因（DEGs）进行交集。使用单变量、LASSO 和多变量回归分析构建预后模型。使用基因表达综合数据集验证该模型。对风险组之间的 DEGs 进行富集分析。通过纳入临床信息绘制列线图。基于多因素模型中的核心预后基因的非负矩阵分解用于对肿瘤样本进行聚类。随后的分析包括免疫表型评分、免疫景观、肿瘤免疫功能障碍和排除（TIDE）评分以及不同亚型的化疗敏感性。建立了基于 AHRGs 的预后模型，并在外部队列中验证了其预测能力。风险评分被确定为独立的预后因素，并与其他临床特征一起绘制预后列线图。根据预后模型基因将患者聚类为 cluster1 和 cluster2。cluster2 比 cluster1 预后更差，IPS 评分更高，免疫细胞浸润更多，免疫功能和 TIDE 评分更高。两个聚类之间观察到不同的化疗药物治疗潜力。开发的 AHRG 评分为预测 GC 预后和确定进一步研究的潜在靶点提供了一种新的有效途径。
