Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
Department of Hepatic Oncology, Zhongshan Hospital, Fudan University, Shanghai, China.
Sci Rep. 2024 Jul 24;14(1):17055. doi: 10.1038/s41598-024-68054-x.
It has been believed that immunosenescence plays a crucial role in tumorigenesis and cancer therapy. Nevertheless, there is still a lack of understanding regarding its role in determining clinical outcomes and therapy selection for gastric cancer patients, due to the lack of a feasible immunosenescence signature. Therefore, this research aims to develop a gene signature based on immunosenescence, which is used for stratification of gastric cancer. By integrative analysis of bulk transcriptome and single-cell data, we uncovered immunosenescence features in gastric cancer. Random forest algorithm was used to select hub genes and multivariate Cox algorithm was applied to construct a scoring system to evaluate the prognosis and the response to immunotherapy and chemotherapy. The Cancer Genome Atlas of Stomach Adenocarcinoma (TCGA-STAD) cohort was implemented as the training cohort and two independent cohorts from the Gene Expression Omnibus (GEO) database were used for validation. The model was further tested by our Fudan cohort. In this study, immunosenescence was identified as a hallmark of gastric cancer that is linked with transcriptomic features, genomic variations, and distinctive tumor microenvironment (TME). Four immunosenescence genes, including APOD, ADIPOR2, BRAF, and C3, were screened out to construct a gene signature for risk stratification. Higher risk scores indicated strong predictive power for poorer overall survival. Notably, the risk score signature could reliably predict response to chemotherapy and immunotherapy, with patients with high scores benefiting from immunotherapy and patients with low scores responding to chemotherapy. We report immunosenescence as a hitherto unheralded hallmark of gastric cancer that affects prognosis and treatment efficiency.
人们一直认为免疫衰老在肿瘤发生和癌症治疗中起着关键作用。然而，由于缺乏可行的免疫衰老特征，对于其在确定胃癌患者的临床结果和治疗选择中的作用，仍缺乏了解。因此，本研究旨在开发一种基于免疫衰老的基因特征，用于胃癌的分层。通过对批量转录组和单细胞数据的综合分析，我们揭示了胃癌中的免疫衰老特征。随机森林算法用于选择枢纽基因，多元 Cox 算法用于构建评分系统，以评估预后以及对免疫治疗和化学治疗的反应。癌症基因组图谱胃癌（TCGA-STAD）队列被用作训练队列，来自基因表达数据库（GEO）的两个独立队列用于验证。该模型还通过我们的复旦队列进行了测试。在这项研究中，免疫衰老被确定为与转录组特征、基因组变异和独特的肿瘤微环境（TME）相关的胃癌标志。筛选出 4 个免疫衰老基因，包括 APOD、ADIPOR2、BRAF 和 C3，用于构建风险分层的基因特征。较高的风险评分表明总体生存率的预测能力较强。值得注意的是，风险评分特征可以可靠地预测对化疗和免疫治疗的反应，高分患者受益于免疫治疗，低分患者对化疗有反应。我们报告免疫衰老作为胃癌一个迄今为止尚未被认识的标志，影响预后和治疗效率。
