[1]袁颖诗,吴 丽,吴晓枝,等.基于TCGA数据筛选肺腺癌相关胞葬基因和预后模型的构建及与免疫浸润的相关性分析[J].现代检验医学杂志,2026,41(03):126-132.[doi:10.3969/j.issn.1671-7414.2026.03.023]
　YUAN Yingshi,WU Li,WU Xiaozhi,et al.Identification of Efferocytosis-Related Genes in Lung Adenocarcinoma Based on TCGA Data: Construction of a Prognostic Model and Analysis of the Association with Immune Infiltration[J].Journal of Modern Laboratory Medicine,2026,41(03):126-132.[doi:10.3969/j.issn.1671-7414.2026.03.023]
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基于TCGA数据筛选肺腺癌相关胞葬基因和预后模型的构建及与免疫浸润的相关性分析()

《现代检验医学杂志》[ISSN:/CN:]

卷:
第41卷
期数:
2026年03期
页码:
126-132
栏目:
论著
出版日期:
2026-05-13

文章信息/Info

Title:
Identification of Efferocytosis-Related Genes in Lung Adenocarcinoma Based on TCGA Data: Construction of a Prognostic Model and Analysis of the Association with Immune Infiltration
文章编号:
1671-7414（2026）03-126-07
作者:
袁颖诗，吴 丽，吴晓枝，谭鸿霞，郑文婷
中山市小榄人民医院/中山市第五人民医院检验科，广东中山 528415
Author(s):
YUAN Yingshi，WU Li，WU Xiaozhi，TAN Hongxia，ZHENG Wenting
Department of Laboratory Medicine, Xiaolan People’s Hospital of Zhongshan/the Fifth People’s Hospital of Zhongshan, Guangdong Zhongshan 528415, China
关键词:
肺腺癌; 癌症基因组图谱; 胞葬相关基因; 预后模型; 免疫浸润
分类号:
R734.2；R730.43
DOI:
10.3969/j.issn.1671-7414.2026.03.023
文献标志码:
A
摘要:
目的?基于癌症基因组图谱（TCGA）数据库筛选肺腺癌（LUAD）胞葬相关基因（ERGs），构建预后模型，分析其与肿瘤免疫浸润特征的相关性。方法从TCGA下载LUAD转录组数据作为训练集，采用DESeq2包筛选差异表达基因（DEGs），与搜集的ERGs取交集获得胞葬相关差异表达基因（DE-ERGs）。利用Kaplan-Meier（K-M）生存分析联合LASSO回归筛选核心基因并构建胞葬相关预后模型，在GSE31210和GSE13213队列中进行外部验证。通过K-M生存曲线和受试者操作特征（ROC）曲线评估模型性能，多因素COX回归确定LUAD独立预后因素，Estimate和Cibersort算法探讨高、低风险组患者间的免疫浸润差异。结果?基于TCGA鉴定出5个核心DE-ERGs（P2RX1、GAPDH、SFTPD、GPR37、ALDH2），构建胞葬相关LUAD预后模型。高风险组患者总生存期显著缩短（P<0.05）。预后模型在TCGA训练集、GSE31210和GSE13213验证集中均表现出良好的预测性能。1、3、5年ROC曲线下面积分别为：TCGA（0.661、0.674、0.646），GSE31210（0.657、0.621、0.645），GSE13213（0.936、0.722、0.719）。风险评分与病理分期，T、N、M分期显著关联（均P<0.05），是LUAD独立的预后因素（P<0.001）。此外，免疫浸润分析表明高风险组患者免疫浸润水平更低（P<0.001），其中M0和M1巨噬细胞浸润水平更高（均P<0.001），VSIR、CTLA4、TIGIT免疫检查点基因表达上调（均P<0.001）。结论基于TCGA数据构建的胞葬相关模型可有效预测LUAD的预后，并与患者的免疫状态密切相关，这可能为LUAD患者的治疗和预后评估提供潜在的靶点及理论依据。
Abstract:
Objective To identify efferocytosis-related genes (ERGs) in lung adenocarcinoma (LUAD) based on the Cancer Ge-nome Atlas (TCGA) database, construct a prognostic model and investigate its correlation with tumor immune infiltration. Meth-ods Transcriptomic profiles of LUAD were downloaded from TCGA as the training set. Differentially expressed genes (DEGs) were identified using the DESeq2 package and intersected with the ERGs to obtain differentially expressed efferocytosis-related genes (DE-ERGs). Kaplan-Meier (K-M) survival analysis combined with LASSO regression was employed to identify core genes and establish an ERG-associated prognostic model. External validation was performed using the GSE31210 and GSE13213 co-horts. The performance of the prognostic model was evaluated using K-M survival curves and receiver operating characteristic (ROC) curves. Independent prognostic factors for LUAD were identified by multivariate COX regression analyses. Immune in-filtration differences between high- and low-risk groups were assessed using the Estimate and Cibersort algorithms. Results Five core DE-ERGs (P2RX1, GAPDH, SFTPD, GPR37, and ALDH2) were identified based on TCGA data, and an efferocytosis-relat-ed prognostic model for LUAD was constructed. Patients in the high-risk group had significantly shorter overall survival (P<0.05). The prognostic model demonstrated robust predictive performance across all cohorts, including the TCGA training cohort and two validation cohorts (GSE31210 and GSE13213). ROC analysis revealed 1-, 3-, and 5-year area under the curve values were as follows: TCGA cohort (0.661, 0.674, 0.646), GSE31210 cohort (0.657, 0.621, 0.645), and GSE13213 cohort (0.936, 0.722, 0.719). The risk score was significantly associated with pathological stage, T, N, and M staging (all P<0.05), and could serve as an inde-pendent prognostic factor of LUAD (P<0.001). Moreover, immune infiltration analysis revealed reduced immune infiltration in the high-risk group (P<0.001), with elevated M0, M1 macrophages infiltration (all P<0.001) and higher expression of immune check-point genes (VSIR, CTLA4, TIGIT, all P<0.001). Conclusions The efferocytosis-related model developed based on TCGA data effectively predicts the prognosis of LUAD patients and is closely related to immune landscapes, which may provide potential targets and a theoretical basis for the treatment and prognostic assessment of LUAD patients.

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备注/Memo

备注/Memo:
作者简介：袁颖诗（1998-），女，硕士研究生，技师，研究方向：检验标志物挖掘与机制研究，E-mail：1046817404@qq.com。
通讯作者：郑文婷（1983-），女，本科，主任技师，研究方向：检验标志物挖掘与机制研究，E-mail：zhengwenting2018@163.com。
更新日期/Last Update: 2026-05-15