Abstract
BACKGROUND: Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer, and it has a high incidence and poor prognosis. Disulfidptosis is a novel form of death induced by disulfide stress caused by excessive intracellular cystine accumulation under glucose starvation conditions. This study investigated the significance of disulfidptosis-related long non-coding RNAs (DRlncRNAs) in the risk assessment and prognosis prediction of LUAD. METHODS: RNA sequencing data and clinical information of LUAD patients were obtained from The Cancer Genome Atlas database. Differentially expressed genes associated with disulfidptosis were screened using univariate Cox regression analysis. A prognostic model was constructed using the least absolute shrinkage and selection operator and the Cox regression analysis to classify patients into high- and low-risk groups. Time-dependent receiver operating characteristic, C-index, and Kaplan-Meier curves were plotted and compared to evaluate the predictive ability of the prognostic model. Functional gene set enrichment analysis (GSEA) and single-sample GSEA were used to explore the characteristics of enrichment pathways, immune-related functions, and treatment response in the high- and low-risk groups. RESULTS: A risk prognostic model was constructed consisting of eight DRlncRNAs (ATXN1-AS1, AC018645.3, AC096733.2, AL049836.1, LINC01711, AF131215.5, AC027288.1, and AL606489.1). Univariate and multifactorial Cox analyses showed that the model was a prognostic factor independent of multiple clinicopathologic parameters. CONCLUSIONS: The developed 8-lncRNA prognostic model serves as a valid biomarker for predicting LUAD prognosis and provides potential therapeutic insights. Targeting DRlncRNAs may contribute to improved prognosis and guide future therapeutic strategies.