Retinol-driven Gene Signatures Predict Lung Adenocarcinoma Outcomes and Highlight PAICS as a Therapeutic Opportunity.

Retinol, a pivotal regulator of cellular growth and apoptosis, has garnered substantial attention for its intricate involvement in cancer development. To explore Vitamin A's impact on lung adenocarcinoma (LUAD), we utilized comprehensive datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) to dissect the intricate role of retinol in cancer progression. The unsupervised clustering analysis, grounded on retinol metabolism gene sets, divided patients into two distinct clusters, with cluster 1 exhibiting significantly inferior survival outcomes. Through differential analysis, we uncovered 349 differentially mutated and 394 differentially expressed genes between these clusters. Leveraging these discoveries, we built a seven-gene signature model that precisely predicted poorer survival for patients with a higher risk score, which was subsequently validated in four independent GEO cohorts, demonstrating its robustness and reliability. Our drug sensitivity analysis further revealed that high-risk patients were more susceptible to gefitinib and erlotinib. Notably, leveraging gene dependency scores and RNA-seq data from LUAD cell lines, we identified Supplementary Information: The online version contains supplementary material available at 10.1007/s43657-025-00223-y.