[1]翟 阳,李晶瑾,常琳涵,等.基于TCGA数据库筛选肺腺癌差异表达免疫基因并构建风险预后模型及实验验证[J].现代检验医学杂志,2026,41(03):119-125.[doi:10.3969/j.issn.1671-7414.2026.03.022]
　ZHAI Yang,LI Jingjin,CHANG Linhan,et al.Differential Expression of Immune Genes in Lung Adenocarcinoma Screened Based on the TCGA Database to Construct a Risk Prognosis Model and Verify by Experiment[J].Journal of Modern Laboratory Medicine,2026,41(03):119-125.[doi:10.3969/j.issn.1671-7414.2026.03.022]
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基于TCGA数据库筛选肺腺癌差异表达免疫基因并构建风险预后模型及实验验证()

《现代检验医学杂志》[ISSN:/CN:]

卷:
第41卷
期数:
2026年03期
页码:
119-125
栏目:
论著
出版日期:
2026-05-13

文章信息/Info

Title:
Differential Expression of Immune Genes in Lung Adenocarcinoma Screened Based on the TCGA Database to Construct a Risk Prognosis Model and Verify by Experiment
文章编号:
1671-7414（2026）03-119-07
作者:
翟 阳1，李晶瑾2，常琳涵1，陈 茜2
1.陕西省肿瘤医院肿瘤内科，西安 710061;2.西安交通大学第一附属医院生殖医学科，西安 710061
Author(s):
ZHAI Yang1，LI Jingjin2，CHANG Linhan1，CHEN Qian2
1.Department of Medical Oncology, Shaanxi Provincial Cancer Hospital, Xi’an 710061, China;2.Department of Reproductive Medicine, the First Affiliated Hospital of Xi’an Jiaotong University , Xi’an 710061, China
关键词:
肺腺癌; 竞争性内源RNA网络; 差异表达免疫基因; 预后模型
分类号:
R734.2；R730.43
DOI:
10.3969/j.issn.1671-7414.2026.03.022
摘要:
目的基于癌症基因组图谱（TCGA）数据库筛选肺腺癌（LUAD）差异表达免疫相关基因（DEIGs）并构建风险预后模型及实验验证，为预测LUAD患者预后及优化诊疗方案提供参考依据。方法TCGA数据库下载LUAD的转录组测序技术数据，LUAD免疫相关基因表达数据从InnateDB中获取，采用edgeR和DESeq2算法对DEIGs进行分析。利用Cytoscape构建信使RNA-微小RNA-长链非编码RNA（mRNA-miRNA-lncRNA）网络。利用单因素COX回归筛选与预后相关的基因，多因素COX回归构建疾病预后风险模型。采用受试者操作特征（ROC）曲线方式评价模型的效能。通过免疫组织化学验证模型基因在LUAD患者临床样本的表达水平。结果总共鉴定出1359个DEIGs，构建了由8个lncRNA、7个miRNA和117个DEIGs组成的mRNA-miRNA-lncRNA网络。功能富集分析表明，117个DEIGs参与免疫和炎症反应，并积极参与丝裂原活化蛋白激酶（MAPK）信号通路。利用COX回归构建10个DEIGs（包含ASPH、CAV1、FKBP4、GRIK2、FURIN、SLC6A8、FSCN1、CKAP4、HAPLN2和IL22RA2）的LUAD多基因预后模型。时间相关的ROC曲线表明，该预后模型在TCGA数据集上有较强的预测能力。ASPH、FSCN1、MS4A1、CD40LG的阳性表达与TNM分期、细胞分化及淋巴结转移相关（均P<0.05）。高水平的ASPH和FSCN1，低水平的MS4A1和CD40LG表达均与LUAD患者的总生存率低相关（均P<0.05）。结论该研究的结果确定了具有临床意义的DEIGs，验证了基于DEIGs的LUAD预后预测模型的效果，同时提示ASPH和FSCN1可能是LUAD患者的有效预后标志物，有可能为LUAD的治疗提供新途径。
Abstract:
Objective To screen differentially expressed immune genes (DEIGs) in lung adenocarcinoma (LUAD) based on the Cancer Genome Atlas (TCGA) database and construct a risk-prognosis model for experimental verification, providing a reference basis for predicting the prognosis and optimizing treatment strategies in LUAD patients. Methods The transcriptome sequencing data for LUAD was downloaded from the TCGA database. The expression data of immune-related genes in LUAD were obtained from InnateDB. The edgeR and DESeq2 algorithms were used to analyze DEIGs. The mRNA-miRNA-lncRNA network was constructed using Cytoscape. Univariate COX regression was used to screen out the genes related to prognosis, while multivariate COX regression was used to construct a disease prognosis risk model. The efficacy of the model was evaluated using receiver operating characteristic (ROC) curve. The expression levels of the model genes in clinical samples from LUAD patients were verified by immunohistochemistry. Results A total of 1 359 DEIGs were identified in this study. An mRNA-miRNA-lncRNA network composed of 8 lncRNAs, 7 miRNAs and 117 DEIGs was constructed. Functional enrichment analysis indicated that the 117 DEIGs were involved in immune and inflammatory responses and participated in the MAPK signaling pathway. A COX regression-based polygenic prognostic model for LUAD was constructed using 10 DEIGs (ASPH, CAV1, FKBP4, GRIK2, FURIN, SLC6A8, FSCN1, CKAP4, HAPLN2 and IL22RA2). The time- dependent ROC curves indicated robust redictive ability of this model in the TCGA dataset. Positive expression of ASPH, FSCN1, MS4A1, CD40LG was related to TNM stage, cell differentiation and lymph node metastasis (all P<0.05). High levels of ASPH and FSCN1, and low levels of MS4A1 and CD40LG expression were associated with poor overall survival rate in LUAD patients (all P <0.05). Conclusions This study identified clinically relevant DEIGs, validated the efficacy of a DEIG-based prognostic prediction model for LUAD, and suggested that ASPH and FSCN1 might be effective prognostic markers for LUAD patients, potentially offering new therapeutic avenues for LUAD management.

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备注/Memo

备注/Memo:
基金项目： 陕西省重点研发计划-一般项目-社会发展领域（编号：2023-YBSF-030），希恩科-艾力斯肺癌靶向治疗研究基金项目（编号：Y-2021AST/qn-0005），北京科创医学发展基金会项目（编号：KC2021-JX-0186-22）。
作者简介： 翟阳（1987-），女，硕士研究生，副主任医师，研究方向：肺癌及消化道肿瘤的综合治疗，肿瘤物理微环境相关研究，E-mail：zhaiyang2020@126.com。
更新日期/Last Update: 2026-05-15