CYBB identified as a key immune hub gene linking lung cancer and atrial fibrillation.

IF 1.5 4区医学 Q3 CARDIAC & CARDIOVASCULAR SYSTEMS

Journal of Cardiothoracic Surgery Pub Date : 2025-06-18 DOI:10.1186/s13019-025-03510-x

Tong Lang, Lingbing Meng

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引用次数: 0

Abstract

Background: The proportion of patients with lung cancer complicated by atrial fibrillation (AF) is increasing. Identifying shared molecular targets between these two conditions may provide important prognostic insights for patients with comorbidities.

Methods: The GSE8569 and GSE41177 datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differential expression analysis was performed using the limma package in R. Weighted gene co-expression network analysis (WGCNA) was conducted to identify significant gene modules. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, along with gene set enrichment analysis (GSEA), were used to explore biological functions. Clinical survival data for lung cancer were obtained from The Cancer Genome Atlas (TCGA), and receiver operating characteristic (ROC) analysis was conducted using the R package ROC (version 1.17.0.1).

Results: A total of 598 differentially expressed genes (DEGs) were identified. These DEGs were primarily enriched in cell proliferation, inflammatory responses, non-small cell lung cancer, the p53 signaling pathway, and the cell cycle. Three core genes (CYBB, ITGB2, FCER1G) were identified. Notably, CYBB was downregulated in lung cancer compared to normal tissue. Patients in the low-risk group had significantly better survival outcomes. Heatmap visualization showed that expression of CYBB decreased with increasing risk scores, suggesting a protective role.

Conclusion: CYBB expression may influence lung cancer prognosis and contribute to the pathogenesis of AF. Further research is needed to clarify CYBB's role in patients with both conditions.

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CYBB被确定为连接肺癌和房颤的关键免疫枢纽基因。

背景：肺癌合并心房颤动（AF）的患者比例呈上升趋势。确定这两种疾病之间的共同分子靶点可能为合并症患者提供重要的预后见解。方法：从Gene Expression Omnibus （GEO）数据库下载GSE8569和GSE41177数据集。差异表达分析采用R. limma软件包进行。加权基因共表达网络分析（WGCNA）鉴定显著基因模块。基因本体（GO）和京都基因与基因组百科全书（KEGG）分析以及基因集富集分析（GSEA）用于探索生物功能。肺癌患者的临床生存数据来自The cancer Genome Atlas (TCGA)，采用R包（1.17.0.1版）进行受试者工作特征（ROC）分析。结果：共鉴定出598个差异表达基因（deg）。这些deg主要富集于细胞增殖、炎症反应、非小细胞肺癌、p53信号通路和细胞周期。鉴定出三个核心基因（CYBB、ITGB2、FCER1G）。值得注意的是，与正常组织相比，CYBB在肺癌中下调。低危组患者的生存结果明显更好。热图可视化显示，CYBB的表达随着风险评分的增加而降低，表明其具有保护作用。结论：CYBB表达可能影响肺癌预后，参与房颤的发病机制，CYBB在两种疾病中的作用有待进一步研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Cardiothoracic Surgery 医学-心血管系统

CiteScore

2.50

自引率

6.20%

发文量

286

审稿时长

4-8 weeks

期刊介绍： Journal of Cardiothoracic Surgery is an open access journal that encompasses all aspects of research in the field of Cardiology, and Cardiothoracic and Vascular Surgery. The journal publishes original scientific research documenting clinical and experimental advances in cardiac, vascular and thoracic surgery, and related fields. Topics of interest include surgical techniques, survival rates, surgical complications and their outcomes; along with basic sciences, pediatric conditions, transplantations and clinical trials. Journal of Cardiothoracic Surgery is of interest to cardiothoracic and vascular surgeons, cardiothoracic anaesthesiologists, cardiologists, chest physicians, and allied health professionals.