A 4-cuproptosis-related lncRNA theragnostic signature predicts survival and immunotherapy response in patients with lung adenocarcinoma.
Lina Lu, Yinyin Qin, Mingdeng Wang, Yanjun Deng, Yuansheng Lin
Abstract
Open AccessLung adenocarcinoma (LUAD), the most prevalent histological subtype of lung cancer worldwide, is associated with poor survival outcomes. Both cuproptosis and long non-coding RNAs (lncRNAs) demonstrate significant prognostic value and play emerging roles in LUAD immunotherapy. The aim of the present study was to identify a cuproptosis-related lncRNA signature for predicting survival and treatment response in patients with LUAD. Cuproptosis-related lncRNAs were screened from The Cancer Genome Atlas-LUAD cohort using Pearson correlation analysis (|R|>0.3, P<0.001) with 19 established cuproptosis genes. To establish a prognostic lncRNA signature for LUAD, univariate Cox regression followed by LASSO and multivariate Cox regression analyses were employed. Validation was performed using Kaplan-Meier survival analysis, principal component analysis, and functional enrichment analysis. A clinical nomogram integrating the signature with clinicopathological features was subsequently developed. The association of the signature with immunotherapy response and chemosensitivity was further assessed. Finally, reverse transcription-quantitative PCR confirmed the differential expression of cuproptosis-related lncRNAs in LUAD tissues. The results revealed that a 4-cuproptosis-related lncRNA signature (AC026355.2, AP000695.1, ARHGEF26-AS1 and AP005137.2) was established, demonstrating its utility as an independent prognostic factor for overall survival in patients with LUAD. In addition, the signature effectively differentiates between patients with different responses to immunotherapy. Finally, candidate compounds targeting the signature were identified. In conclusion, this cuproptosis-related lncRNA signature stratifies LUAD prognosis and immunotherapy response and provides a theragnostic tool for personalized therapy.