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Background: As the major type of esophageal cancer (ESCA), esophageal squamous cell carcinoma (ESCC) is also related to the highest malignant level and low survival rates across the world. Increasing people recognize long non-coding RNAs (lncRNAs) as significant mediators in regulating ferroptosis and iron-metabolism. Determining the prognostic value of ferroptosis and iron-metabolism related lncRNAs (FIRLs) in ESCC is thus critical. Methods: 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 was established. According to Kaplan-Meier analysis, receiver operating characteristic (ROC) curve analysis, and univariate and multivariate Cox regression analyses, the predictive ability and clinical relevance of the risk stratification system were evaluated. 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. Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied for the identification of pathways in which FIRLs significantly enriched. we used cell culture, transfection, CCK-8, and qRT-PCR as in vitro assays. Results: An 3-FIRLs risk stratification system was developed by multivariate Cox regression analysis to divide patients into two risk groups. Patients in the high-risk group had worse prognosis than patients in the low-risk group. Multivariate Cox regression analysis showed the risk stratification system was an independent prognostic indicator. Receiver operating characteristic curve (ROC) analysis proved the predictive accuracy of the signature. The area under time-dependent ROC curve (AUC) reached 0.853 at 1 year, 0.802 at 2 years, 0.740 at 5 years in the training cohort and 0.712 at 1 year, 0.822 at 2 years, 0.883 at 5 years in the validation cohort. Functional enrichment analysis predicted potential associations of 49 possible upstream regulated FIRGs with ferroptosis and iron-metabolism processes and oncological signatures. Analysis of the immune cell infiltration landscape showed that ESCC in the high-risk group tended be immunologically “cold”. In vitro experiments suggested that LINC01068 promoted ESCC cell proliferation. Conclusion: The risk stratification system based on FIRLs could serve as a reliable tool for forecasting the survival of patients with ESCC. |
