Bioinformatics analysis based on ferroptosis-related lncRNAs: construction of a clinical prognostic model for nasopharyngeal carcinoma and correlation analysis.

Background: A prognostic model of ferroptosis associated with long non-coding RNAs (lncRNAs) in nasopharyngeal carcinoma was established by using The Cancer Genome Atlas (TCGA) database, and immune correlation analysis was conducted for patients classified into high- and low-risk groups by the model. Nasopharyngeal carcinoma is associated with many lncRNA gene mutations, and tumors are often closely related to metabolism, accompanied by obvious characteristics of immune infiltration. Methods: Gene expression data and clinical data of nasopharyngeal carcinoma tissues and normal tissues were obtained from TCGA database, and differential lncRNAs related to ferroptosis were screened out. Univariate and multivariate Cox risk regression models were used to screen and establish the lncRNA prognostic risk prediction model. Patients were scored according to the model. The immune-related functions of the high-risk and low-risk groups were compared to obtain immune-related differences between the groups. In this study, the prognostic model was constructed by the intersection of genes related to nasopharyngeal cancer prognosis and genes related to iron death metabolism through Cox regression analysis and R-packet screening, and the area under curve (AUC) was further used to predict and verify the model. Results: In this study, a total of 14 differential lncRNAs related to the prognosis of ferroptosis were obtained. Immune correlation analysis showed that the high- and low-risk groups had significant differences in the following factors: dendritic cells, B cells, mast cells, and other immune cells (P=0.0001); anaphase-promoting complex (APC) co-inhibition, chemotactic factor receptor, immune checkpoint, and other immune functions (P=0.002); glutamate cysteine ligase catalytic (GCLC), human endogenous retrovirus-H long terminal repeat-associating protein 2 (HHLA2), cluster of differentiation (CD276), B and T-lymphocyte attenuator (BTLA), and other immune checkpoint related genes (P<0.001). GCLC was highly expressed in NP69/DDP cells (P=0.04). DDP can activate ferroptosis in NP69/DDP cells can inhibit GCLC expression, and the AUC curve (AUC =0.899) indicates that the model has good prediction and accuracy. Conclusions: The prognostic model based on 16 ferroptosis-related lncRNAs can predict the prognosis of nasopharyngeal carcinoma patients, and the ferroptosis-related lncRNAs involved in the construction of the model obtained in this study may be related to the level of immune infiltration, and may even become new targets for immune checkpoint inhibitor therapy.