A Cuproptosis-related lncRNA Signature for Prognostic Stratification and Immunotherapeutic Implications in Lung Adenocarcinoma

BACKGROUND: Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer, and there have been disputes over its prognostic biomarker and clinical outcome. Cuproptosis, a novel form of regulated cell death (RCD), has been insufficiently explored in terms of its potential role in LUAD. METHODS: In this study, we developed a machine learning-based integrative procedure for constructing a consensus cuproptosis-related lncRNA signature (CTLNS) using TCGA data and validated it with external datasets. RESULTS: The CTLNS was identified as an independent predictor of overall survival, showing stable and accurate performance across multiple cohorts. Patients classified into high- and low-risk groups exhibited significant differences in survival outcomes. Functional analyses revealed that the low-risk group was enriched in DNA replication and immune-related pathways, while the high-risk group was associated with oncogenic signaling and cell cycle regulation. Notably, high-risk patients showed increased sensitivity to several chemotherapy agents, including Docetaxel, Cisplatin, Gefitinib, and Paclitaxel, while low-risk patients were more responsive to Nilotinib. CONCLUSION: These findings suggest that CTLNS is a reliable biomarker for prognostic prediction and treatment stratification in LUAD, offering potential utility in personalized therapy.