Identification and validation of ferroptosis-related prognostic risk model and immune landscape in hepatocellular carcinoma

Abstract

BackgroundFerroptosis has been paid much more attention on account of the correlation withtumorigenesis and development. However, the molecular characteristics and immune landscape of ferroptosis regulators in hepatocellular carcinoma (HCC) have not been fully elucidated. MethodsRNA-sequencing data and matched clinical data were collected from The Cancer Genome Atlas (TCGA) database, then underwent gene expression, genetic variations, prognostic risk model, and immune characterization analyses. An independent cohort from Gene Expression Omnibus (GEO) database was utilized to validate ferroptosis-related prognostic risk model. ResultsWe first identified the differentially expressed ferroptosis regulators between the tumor tissues and normal controls in HCC. Furthermore, the prognostic risk model based on ferroptosis regulators was constructed, of which the high risk group presented poor clinical outcomes compared to the low risk group. Importantly, the ferroptosis-related prognostic risk model consistently presented excellent prediction ability in recognizing the high and low risk patients according to the validation from an independent cohort. Subsequently, immune landscape analysis uncovered that most of ferroptosis regulatory genes were significantly associated with the infiltration of multiple immune cells and the expression of immune checkpoints in HCC. Moreover, the correlations of risk score with immune cells infiltration and immune checkpoints were determined in HCC. ConclusionOur study developed a prognostic risk model based on ferroptosis regulatory genes, which could accurately predict the patients’ prognosis. Immune characteristics analysisrevealed that ferroptosis regulatory genes were associated with immune cells infiltration and immune checkpoints in HCC.