Systematic profiling of ferroptosis gene signatures predicts prognostic factors in esophageal squamous cell carcinoma

We developed a predictive model associated with ferroptosis to provide a more comprehensive view of esophageal squamous cell carcinoma (ESCC) immunotherapy. Gene expression data and corresponding clinical outcomes were obtained from the GEO and The Cancer Genome Atlas (TCGA) databases, and a ferroptosis-related gene set was obtained from the FerrDb database. We identified 45 ferroptosis-related genes that were differentially expressed, including enrichment in genes involved in the immune system process. We established a ferroptosis-related gene-based prognostic model based on the results of univariate Cox regression and multivariate Cox regression analyses, with an area under the curve (AUC) of 0.76 (3 years). We found that the patients with low-risk scores showed a higher proportion of CD8(+) T cells, CD4(+) memory activated T cells, etc. Finally, a predictive ferroptosis-related prognostic nomogram, which included the predictive values of age, gender, grade, TNM stage, and risk score, was established to predict overall survival. In sum, we developed a ferroptosis-related gene-based prognostic model that provides novel insights into the prediction of ESCC prognosis and identifies the relevance of the immune microenvironment for patient outcomes.

Automated summary

A predictive model associated with ferroptosis was developed to provide a comprehensive view of esophageal squamous cell carcinoma (ESCC) immunotherapy. The model identified 45 differentially expressed ferroptosis-related genes and established a prognostic model based on Cox regression analyses, with a predictive nomogram for overall survival. Low-risk patients showed a higher proportion of activated immune system genes and demonstrated the relevance of immune microenvironment for patient outcomes.