FeRGs生物信息学分析及肺腺癌预后模型构建

CONSTRUCTION OF A PROGNOSTIC MODEL OF LUNG ADENOCARCINOMA BASED ON BIOINFORMATICS ANALYSIS OF FERROPTOSIS-RELATED GENES

目的研究铁死亡相关基因(FeRGs)在肺腺癌(LUAD)中的预后价值。方法从癌症基因组图谱下载LUAD病人的RNA-seq表达数据及相应的临床数据,筛选出肿瘤组织与癌旁组织之间差异表达的FeRGs。用单因素Cox回归分析筛选出与LUAD预后相关的FeRGs,用LASSO回归构建预后模型,并用模型将病人分为高、低风险两组。应用主成分分析(PCA)、t-分布随机邻近插入(t-SNE)分析和独立预后分析等评估模型的性能;进行免疫细胞浸润和免疫相关功能分析,以了解模型与免疫的关系。结果构建了由ALOX15、ATP5MC3、CISD1、DPP4、FANCD2、GLS2、GSS、PHKG2、ACSL3、PEBP1和PGD共11个FeRGs组成的预后模型,该模型可较准确区分高、低风险病人,并且可独立于其他变量作为LUAD总生存率的预测因子。结论本文研究构建了FeRGs预后模型,可为临床评估LUAD病人的预后提供参考。

Objective To study the prognostic value of ferroptosis-related genes(FeRGs)in lung adenocarcinoma(LUAD).Methods The RNA-seq expression data and corresponding clinical data of LUAD patients were downloaded from the Cancer Genome Atlas.The differentially expressed FeRGs between tumor tissues and adjacent tissues were screened.FeRGs related to the prognosis of LUAD were screened using the univariate Cox regression analysis.Then,a prognostic model was constructed using the LASSO regression.Patients were divided into high-and low-risk groups based on the model.The performance of the mo-del was evaluated using the principal component analysis,t-distributed stohastic neighbor embedding analysis,and independent prognostic analysis.Immune cell infiltration and immune-related function analysis were conducted to explore the relationship between the model and immunity.Results A prognostic model consisting of 11 FeRGs(ALOX15,ATP5MC3,CISD1,DPP4,FANCD2,GLS2,GSS,PHKG2,ACSL3,PEBP1,and PGD)was constructed,by which,patients at high and low risks could be accurately distinguished,and the model could be used as an independent predictor of overall LUAD survival from other variables.Conclusion This study constructed a prognostic model based on FeRGs,which can provide a reference for clinical evaluation of the prognosis of LUAD patients.