ArticleTranslational cancer research2026
Identification of a novel signature for prognostic stratification and integrative analyses in lung adenocarcinoma.
Article in Translational cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Recently, research has revealed that the Golgi apparatus is involved in the development process of cancer; however, the specific effect of Golgi apparatus-related genes (GAGs) in lung adenocarcinoma (LUAD) remains unclear. This study aims to construct a more concise and practical risk model in LUAD using GAG. Methods: The gene expression profiles of patients with LUAD were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and GAGs were downloaded from the Gene Set Enrichment Analysis (GSEA) database. Univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses were performed to identify the prognostic GAG signature. Kaplan-Meier and receiver operating characteristic (ROC) curves were plotted to validate the predictive effect of the prognostic signatures. The correlation between the risk model and the immune landscape was examined using CIBERSORT and TIDE analyses. Also, the genes in the signature were assessed by single-cell RNA sequencing (scRNA-seq). Results: A prognostic signature comprising 5 GAG genes ( Conclusions: The risk model based on GAGs can effectively stratify the prognosis of patients and predict immunotherapy responses in LUAD.
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