Scholarlink

Background <p>Obstructive sleep apnea (OSA) affects nearly 1 billion adults worldwide, and it is relatively common in patients with lung adenocarcinoma (LUAD). This study aimed to identify potential shared transcriptomic signatures and explore pathways linking OSA and LUAD.</p> Methods <p>Transcriptomic data were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Weighted gene co-expression network analysis (WGCNA) and protein–protein interaction (PPI) network analysis were used to identify hub genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to investigate the functional pathways associated with differentially expressed genes (DEGs). Univariate Cox regression and least absolute shrinkage and selection operator (LASSO)-Cox regression analyses were conducted to identify prognostic genes and construct a prognostic signature for LUAD.</p> Results <p>A total of 986 shared DEGs were identified between OSA and LUAD. Among them, 117 hub genes were selected based on the PPI network. A 12-gene signature was constructed and validated in an independent LUAD cohort. The risk score stratified LUAD patients into distinct risk groups and showed associations with estimated immune infiltration patterns. In addition, intermittent hypoxia exposure was associated with expression changes in a subset of signature genes in A549 cells.</p> Conclusions <p>This study identified shared transcriptomic features and highlighted immune-related pathways that may represent potential biological associations between OSA and LUAD.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Correlating obstructive sleep apnea and lung adenocarcinoma using hub gene signatures and molecular mechanisms

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月12日

查看全文
  • Li Zhang,
  • Lei Yang,
  • Gang Chen,
  • Xuemei Yang,
  • Dongchang Wang

摘要

Background

Obstructive sleep apnea (OSA) affects nearly 1 billion adults worldwide, and it is relatively common in patients with lung adenocarcinoma (LUAD). This study aimed to identify potential shared transcriptomic signatures and explore pathways linking OSA and LUAD.

Methods

Transcriptomic data were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Weighted gene co-expression network analysis (WGCNA) and protein–protein interaction (PPI) network analysis were used to identify hub genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to investigate the functional pathways associated with differentially expressed genes (DEGs). Univariate Cox regression and least absolute shrinkage and selection operator (LASSO)-Cox regression analyses were conducted to identify prognostic genes and construct a prognostic signature for LUAD.

Results

A total of 986 shared DEGs were identified between OSA and LUAD. Among them, 117 hub genes were selected based on the PPI network. A 12-gene signature was constructed and validated in an independent LUAD cohort. The risk score stratified LUAD patients into distinct risk groups and showed associations with estimated immune infiltration patterns. In addition, intermittent hypoxia exposure was associated with expression changes in a subset of signature genes in A549 cells.

Conclusions

This study identified shared transcriptomic features and highlighted immune-related pathways that may represent potential biological associations between OSA and LUAD.