A Promising Esophageal Cancer Prognostic Signature of Ferroptosis-Related LncRNA to Predict Immune Scenery and Immunotherapy Response

Ferroptosis and long non-coding RNA (lncRNA) expression signatures have been associated with the clinical progression and immune-contexture of different solid tumors. The study aimed to identify a prognostic signature of ferroptosis-related lncRNAs (falncRNAs) to forecast the immune scenery and immunotherapy response in esophageal cancer (EC).Gene expression profiles of EC were extracted from The Cancer Genome Atlas (TCGA) database, and ferroptosis-related genes were downloaded from the FerrDb database, which identified differentially expressed falncRNAs (DEfalncRNAs) via differential analysis. DEfalncRNA pairs associated with prognosis were identified by constructing a matrix, univariate and least absolute shrinkage and selection operator (LASSO) analysis. The prognostic signature was constructed by multivariate analysis. We appraised the forecasting capability of prognostic signature in survival, clinicopathological features, immune landscape, efficacy of immunotherapy, and drug sensitivity. The potential molecular mechanism of signature was investigated by gene set enrichment analysis (GSEA).We obtained 18 DEfalncRNA pairs to define a novel prognostic signature that was determined on a discovery cohort of 158 tumor samples and 11 adjacent normal tissues from TCGA and internally validated, with the definition of high- vs low-risk groups based on 3 years overall survival. We demonstrated that the high- vs low-risk groups differed for clinical parameters and computationally predicted drug sensitivity and tumor immune contexture, with the high-risk group having worse survival, more aggressive disease (node involvement, metastasis), reduced drug sensitivity, higher tumor mutation load, and gene signatures of infiltration of pro-tumoral immune cell subsets. The GSEA results revealed that ferroptosis and immunoregulatory pathways were significantly enriched in the high-risk group.The prognostic signature based on falncRNAs has the potential to forecast the survival, immune scenery, efficacy of immunotherapy, and drug sensitivity of EC, which is helpful for clinical prediction and individualized treatment.