Liver Disease Center, The Affiliated Hospital of Qingdao University, No. 59 Haier Road, Qingdao, 266003, China.
Qingdao University, No. 308 Ningxia Road, Qingdao, 266071, China.
J Transl Med. 2021 Apr 29;19(1):183. doi: 10.1186/s12967-021-02846-x.
Growing attention have been paid to the relationship between TP53 and tumor immunophenotype, but there are still lacking enough search on the field of gastric cancer (GC).
We identified differential expressed immune-related genes (DEIRGs) between the TP53-altered GC samples (n = 183) and without TP53-altered GC samples (n = 192) in The Cancer Genome Atlas and paired them. In the TCGA cohort (n = 350), a risk score was determined through univariate and multivariate cox regression and Lasso regression analysis. Patients were divided into two groups, high-risk and low-risk, based on the median risk score. Four independent cohorts (GSE84437,n = 431; GSE62254, n = 300; GSE15459, n = 191; GSE26901, n = 100) from the Gene Expression Omnibus (GEO) database were used to validate the reliability and universal applicability of the model.
The signature contained 11 gene pairs showed good performance in predicting progression-free survival (PFS), disease-free survival (DFS), disease special survival (DSS), and the overall survival (OS) for GC patients in the TCGA cohort. The subgroup analysis showed that the signature was suitable for GC patients with different characteristics. The signature could capable of distinguish GC patients with good prognosis and poor prognosis in all four independent external validation cohorts. The high- and low-risk groups differed significantly in the proportion of several immune cell infiltration, especially for the T cells memory resting, T cells memory activated and follicular helper, and Macrophage M0, which was also related to the prognosis of GC patients.
The present work proposed an innovative system for evaluating the prognosis of gastric cancer. Considering its stability and general applicability, which may become a widely used tool in clinical practice.
TP53 与肿瘤免疫表型之间的关系受到越来越多的关注，但在胃癌（GC）领域的研究仍然不足。
我们在癌症基因组图谱（TCGA）中鉴定了 TP53 改变的 GC 样本（n=183）和未改变的 GC 样本（n=192）之间差异表达的免疫相关基因（DEIRGs），并对其进行了配对。在 TCGA 队列（n=350）中，通过单因素和多因素 Cox 回归以及 Lasso 回归分析确定风险评分。根据中位风险评分将患者分为高风险和低风险两组。我们从基因表达综合数据库（GEO）中选取了四个独立的队列（GSE84437，n=431；GSE62254，n=300；GSE15459，n=191；GSE26901，n=100）来验证模型的可靠性和普遍适用性。
该特征包含 11 对基因，在 TCGA 队列中对 GC 患者的无进展生存期（PFS）、无病生存期（DFS）、疾病特异性生存期（DSS）和总生存期（OS）的预测具有良好的性能。亚组分析表明，该特征适用于具有不同特征的 GC 患者。该特征能够区分来自四个独立外部验证队列中预后良好和预后不良的 GC 患者。高低风险组在几种免疫细胞浸润的比例上存在显著差异，尤其是 T 细胞记忆静息、T 细胞记忆激活和滤泡辅助以及 M0 巨噬细胞，这也与 GC 患者的预后有关。
本研究提出了一种评估胃癌预后的新方法。考虑到其稳定性和普遍适用性，它可能成为临床实践中广泛使用的工具。
