biostudies-literatureUnknown30(6)Zhang LLung adenocarcinoma (LUAD) is the most prevalent and lethal subtype of lung cancer worldwide and despite advances in diagnostic and therapeutic strategies, its prognosis remains poor. The present study aimed to identify key genes in LUAD through bioinformatics approaches. Transcriptomic data from the Gene Expression Omnibus and The Cancer Genome Atlas databases were analyzed using differential expression analysis, weighted gene co-expression network analysis, protein-protein interaction network construction and machine learning algorithms, and were validated using reverse transcription-quantitative PCR. Gene set enrichment analysis (GSEA) was performed to explore potential mechanisms associated with the involvement of key genes in LUAD, and single-cell transcriptomic data, collected from tExperimental and therapeutic medicine241https://www.ebi.ac.uk/biostudies/studies/S-EPMC12569745biostudies-literatureIdentification of CAV1 and CDH5 as potential diagnostic and prognostic biomarkers in lung adenocarcinoma.PMC12569745Liu YLi YWang CZhang LWang YWang LfalseIdentification of CAV1 and CDH5 as potential diagnostic and prognostic biomarkers in lung adenocarcinoma.Lung adenocarcinoma (LUAD) is the most prevalent and lethal subtype of lung cancer worldwide and despite advances in diagnostic and therapeutic strategies, its prognosis remains poor. The present study aimed to identify key genes in LUAD through bioinformatics approaches. Transcriptomic data from the Gene Expression Omnibus and The Cancer Genome Atlas databases were analyzed using differential expression analysis, weighted gene co-expression network analysis, protein-protein interaction network construction and machine learning algorithms, and were validated using reverse transcription-quantitative PCR. Gene set enrichment analysis (GSEA) was performed to explore potential mechanisms associated with the involvement of key genes in LUAD, and single-cell transcriptomic data, collected from t2025-01-01T00:00:00Z2025 Dec2026-06-05T09:23:14.843Z2026-05-15T03:12:48.453ZS-EPMC125697454117039310.3892/etm.2025.12991