Lian Lian, Teng Shi-Bing, Xia You-You, Shen Xiao-Ming, Zheng Yan, Han Shu-Guang, Wang Wen-Jie, Xu Xue-Fei, Zhou Chong
Department of Oncology, Suzhou Xiangcheng People's Hospital, Suzhou, China.
Department of Thoracic Surgery, Suzhou Xiangcheng People's Hospital, Suzhou, China.
J Gastrointest Oncol. 2022 Apr;13(2):462-477. doi: 10.21037/jgo-22-69.
Esophageal cancer is one of the most common gastrointestinal malignancies worldwide, with high morbidity and mortality in China. The clinical importance of the interaction between hypoxia and immune status in the tumor microenvironment has been established in esophageal squamous cell carcinoma (ESCC). This study aims to develop a new hypoxia- and immune-based gene signature to predict the survival of ESCC patients.
The RNA-sequencing and clinical data of 173 cases of ESCC and 271 normal tissues were obtained from The Cancer Genome Atlas (TCGA) data portal and the Genotype-Tissue Expression (GTEx) database. Hypoxia-related genes (HRGs) and immune-related genes (IRGs) were retrieved from publicly shared data. Differentially expressed gene (DEG) analyses were carried out by the DESeq2 method using the edgeR package in R. Based on the intersection of the DEGs and HRGs/IRGs, differentially expressed HRGs (DEHRGs) and differentially expressed IRGs (DEIRGs) were obtained. DEHRGs and DEIRGs associated with prognosis were evaluated using univariate Cox proportional hazards analysis. A prognostic risk score model was constructed according to the genes acquired through Cox regression. Univariate analysis and Cox proportional hazards analysis were used to determine the independent prognostic factors related to prognosis. A nomogram was developed to predict the 1-, 2-, and 3-year overall survival (OS) probability.
A total of 73 intersecting genes were obtained as DEHRGs and a total of 548 intersecting genes were obtained as DEIRGs. The risk score was established using 8 genes (, , , , , , ) acquired from univariate Cox analysis. Based on this 8-gene-based risk score, a risk prognosis classifier was constructed to classify the samples into high- and low-risk groups according to the median risk score. The nomogram model was constructed to predict the OS of ESCC patients.
The hypoxia- and immune-based gene signature might serve as a prognostic classifier for clinical decision-making regarding individualized management, follow-up plans, and treatment strategies for ESCC patients.
食管癌是全球最常见的胃肠道恶性肿瘤之一,在中国发病率和死亡率都很高。肿瘤微环境中缺氧与免疫状态之间相互作用的临床重要性在食管鳞状细胞癌(ESCC)中已得到证实。本研究旨在开发一种基于缺氧和免疫的新基因特征,以预测ESCC患者的生存情况。
从癌症基因组图谱(TCGA)数据门户和基因型-组织表达(GTEx)数据库中获取173例ESCC病例和271例正常组织的RNA测序及临床数据。从公开共享的数据中检索缺氧相关基因(HRGs)和免疫相关基因(IRGs)。使用R语言中的edgeR包,通过DESeq2方法进行差异表达基因(DEG)分析。基于DEGs与HRGs/IRGs的交集,获得差异表达的HRGs(DEHRGs)和差异表达的IRGs(DEIRGs)。使用单变量Cox比例风险分析评估与预后相关的DEHRGs和DEIRGs。根据通过Cox回归获得的基因构建预后风险评分模型。使用单变量分析和Cox比例风险分析确定与预后相关的独立预后因素。开发了一种列线图来预测1年、2年和3年总生存(OS)概率。
共获得73个相交基因作为DEHRGs,共获得548个相交基因作为DEIRGs。使用从单变量Cox分析中获得的8个基因(,,,,,,)建立风险评分。基于这个基于8个基因的风险评分,构建了一个风险预后分类器,根据中位风险评分将样本分为高风险和低风险组。构建列线图模型以预测ESCC患者的OS。
基于缺氧和免疫的基因特征可能作为一种预后分类器,用于ESCC患者个体化管理、随访计划和治疗策略的临床决策。