摘　要：内质网应激（ERS）是影响癌症发生发展的重要因素之一。本研究的目的在于通过生物信息学方法探讨内质网应激基因在胃癌（STAD）中的表达及预测预后的价值。从癌症基因组图谱数据库（TCGA）和基因表达综合数据库（GEO）获取STAD样本，“ConsensusClusterPlus”R包用于识别胃癌内质网应激相关分子亚型（C1、C2），Kaplan-Meier分析比较分型间生存差异，并进行基于GEO队列的外部验证。基因本体论（GO）富集和京都基因与基因组百科全书（KEGG）通路分析比较其差异基因富集通路差异。使用“limma”R包识别分型间差异基因，通过LASSO回归分析构建预后模型，依照风险值中位数将TCGA训练集分为两组，评估免疫细胞浸润显著差异。生存分析显示，C1的生存结局较C2更好。差异分析确定了6个与分型相关的内质网应激基因，GO富集和KEGG通路分析揭示了亚型间差异基因参与了多种细胞和生物学功能。通过LASSO回归分析构建了一个8基因预后模型，Kaplan-Meier分析表明高风险组患者较低风险组生存时间短，ROC分析验证了预测模型在STAD预后预测中的准确性，免疫分析揭示了两组之间免疫细胞浸润差异显著。本研究基于内质网应激基因对STAD患者进行分型，并构建了新的预后模型，具有预测STAD患者预后的作用，并可为个性化治疗提供一些参考。
关键词：胃癌；内质网应激；分子亚型；免疫细胞浸润；预后模型
中图分类号：R735.2；R730.7                   文献标志码：A               DOI：10.3969/j.issn.1007-7146.2022.05.011

Abstract: Endoplasmic reticulum stress (ERS) is one of the important factors that affect cancer development. The purpose of this study is using bioinformatics method to explore the ERS gene expression in gastric cancer (STAD) and the value of predicting prognosis. The STAD samples were obtained from TCGA database and GEO database. “ConsensusClusterPlus” R package was used to identify ERS-related classification of STAD (C1, C2)，external validation based on GEO queue is performed. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to compare the differences of the differential gene enrichment pathways. The “limma” R package was used to identify differentially expressed genes between molecular subtypes. The prognostic model was established by LASSO regression analysis. TCGA training set was divided into two groups according to the median risk value to evaluate significant differences in immune cell infiltration. Survival analysis showed that C1 had a better survival outcome than C2. Six ERS genes related to typing were identified by differential analysis. GO enrichment and KEGG pathway analysis revealed that differentially expressed genes were involved in various cellular and biological functions among subtypes. An 8-gene prognostic model was constructed by LASSO regression analysis, Kaplan-Meier analysis showed that patients in the high-risk group had a shorter survival time than those in the low-risk group, and ROC analysis verified the accuracy of the prediction model in predicting the prognosis of STAD. Immunoassay revealed significant differences in immune cell infiltration between the two groups. In this study, patients with STAD were classified based on ERS genes and a new prognostic model was constructed, which can predict the prognosis of STAD patients and provide some reference for personalized treatment.
Key words: stomach cancer; endoplasmic reticulum stress; molecular subtypes; immune cell infiltration; prognostic model
（Acta Laser Biology Sinica, 2022, 31(5): 461-470）