Abstract
Ferroptosis and iron-metabolism have been widely reported to play an important role in cancer. Long non-coding RNAs (lncRNAs) are increasingly recognized as the crucial mediators in the regulation of ferroptosis and iron metabolism. A systematic understanding of ferroptosis and iron-metabolism related lncRNAs (FIRLs) in esophageal squamous cell carcinoma (ESCC) is essential for prognosis prediction. Herein, Pearson's correlation analysis was carried out between ferroptosis and iron-metabolism-related genes (FIRGs) and all lncRNAs to derive the FIRLs. Based on weighted gene co-expression network exploration (WCGNA), least absolute shrinkage and selection operator (LASSO) regression and Cox regression analysis, a risk stratification system, including 3 FIRLs (LINC01068, TMEM92-AS1, AC243967.2), was established. According to Kaplan-Meier analysis, receiver operating characteristic (ROC) curve analysis, and univariate and multivariate Cox regression analyses, the risk stratification system had excellent predictive ability and clinical relevance. The validity of the established prognostic signature was further examined in TCGA (training set) and GEO (validation set) cohorts. A nomogram with enhanced precision for forecasting OS was set up on basis of the independent prognostic elements. Functional enrichment analysis revealed that three FIRLs took part in various cellular functions and signaling pathways, and the immune status was varied in the high-risk and low-risk groups. In the end, the oncogenic effects of LINC01068 was explored using in vitro researches. Overall, a risk stratification system of three FIRLs was found to have significant prognostic value for ESCC and may serve as a ferroptosis-associated therapeutic target in the clinic.