Disulfidptosis-related lncRNA signatures predict prognosis and immune relevance of lung adenocarcinoma

Abstract Purpose: Lung adenocarcinoma (LUAD) remains the most common malignancy and has a poor prognosis. Disulfidptosis was identified as a novel type of cell death. Long non-coding RNAs (lncRNAs) play an important role in regulating cell death and LUAD progression. However, the role of disulfidptosis-related lncRNAs (DRLs) in LUAD has not been studied. Methods: Disulfidptosis-related genes (DRGs) were performed for differential expression, mutation, GO, KEGG, and survival analyses. The univariate Cox regression and least absolute shrinkage and selection operator regression (Lasso) were used to screening the prognostic value of DRLs. Independent prognostic analysis, receiver operating characteristic (ROC) analysis, a nomogram, survival analysis, progression-free survival analysis, Principal Component Analysis (PCA), and tumor mutation difference analysis were used to validate the predictive efficacy of the signature. In addition, the CIBERSORT algorithm was used to assess the differences in immune cells and their immune function. Results: A total of 21 DRGs differ, and functional enrichment analysis revealed that these 23 DRGs are mainly involved in the structural composition of the cytoskeleton involved in the binding and activation of actin in LUAD. Pearson correlation analysis identified 140 DRLs, LASSO regression analysis obtained 10 DRLs associated with the prognosis of LUAD patients and multifactorial Cox regression analysis was performed to construct a signature consisting of 5 DRLs with independent prognostic significance (LINC01352, AC093673.1, AL606834.1, AL365181.2, MHENCR) to form a prognostic signature. The K-M survival curves showed that the prognosis of patients in the high-risk group was poor, and the ROC curves showed that the area under the curve for the 1, 3, and 5-year survival rates were 0.695, 0.676, and 0.681, respectively, indicating that the signature had the excellent predictive ability. Univariate and multifactorial Cox regression analyses showed that the risk score was an independent prognostic factor. There was a significant correlation between risk score and tumor microenvironment, tumor mutational load, TIDE, and tumor cell stemness. The results of the drug sensitivity analysis showed that patients in the high-risk group had lower semi-inhibitory concentration values for Trametinib, Savolitinib, Ulixertinib, and Crizotinib compared to patients in the low-risk group, while the opposite was true for Tozasertib, Leflunomide, and Ribociclib. Conclusions: We identified a prognostic signature of disulfidptosis‑related lncRNAs by comprehensive and systematic bioinformatics analysis of LUAD patients. Our developed risk-based signature outperforms standard clinicopathological parameters in predicting survival and prognosis and provided novel insights into the treatment of LUAD.