主页 文献库文献详情
PMID: 42435294 已发表 · aheadofprint 英语

Seven-gene biomarkers reveal prognostic and immune signatures in lung adenocarcinoma.

Discover oncology ·2026-07-11

Liu Y, Tong R, Li L, Zhang Y, Gong S

摘要

Reliable prognostic biomarkers for lung adenocarcinoma (LUAD) remain limited because of inter-cohort heterogeneity across transcriptomic studies. This study aimed to identify survival-related gene signatures associated with immune characteristics in LUAD. Three independent Gene Expression Omnibus (GEO) datasets were analyzed separately to identify consistently dysregulated genes in LUAD. Functional enrichment, protein-protein interaction network, survival, receiver operating characteristic (ROC) curve analysis, principal component analysis (PCA), expression validation, and immune infiltration analyses were performed. A total of 68 overlapping differentially expressed genes were identified. Functional enrichment analysis showed that these genes were mainly involved in vascular-related biological processes. Network and survival analyses identified seven significantly downregulated genes, including AGER, CAV1, EDNRB, ROBO4, EMCN, TEK, and PTPRB, which were associated with overall survival in LUAD. ROC analysis showed favorable diagnostic performance across the three GEO datasets, with area under the curve (AUC) values ranging from 0.873 to 1.000. In the larger datasets, AUCs ranged from 0.932 to 0.952 in GSE19188 and from 0.873 to 0.949 in GSE30219, with corresponding 95% CI ranges of 0.870-1.000 and 0.710-1.000, respectively. PCA further supported separation between LUAD and normal samples. Immune infiltration analysis showed associations between the seven-gene signature, tumor purity, and multiple immune cell populations. A seven-gene vascular-related signature was associated with prognosis and immune infiltration patterns in LUAD. These findings may support future biomarker development and studies of tumor microenvironment remodeling in LUAD.

关键词
Bioinformatics analysis Differentially expressed genes Immune infiltration Lung adenocarcinoma
文献信息
期刊
Discover oncology
期刊简称
Discov Oncol
ISSN
2730-6011
发表日期
2026-07-11
语言
英语
国家/地区
United States
NLM ID
101775142
分析服务
分析服务

联系地址

山东省济南市章丘区文博路2号

齐鲁师范学院 genelibs生信实验室

山东省济南市高新区舜华路750号

大学科技园北区F座4单元2楼

电话: 0531-88819269

微信公众号

关注微信订阅号,实时查看信息,关注医学生物学动态。


商务邮箱

E-mail: [email protected]