A prognostic model for hepatocellular carcinoma patients based on signature ferroptosis-related genes

Considering the increase in the number of HCC patients, it is critical to predict the survival of patients. Although ferroptosis is closely related to HCC progression, predicting the survival of HCC patients through ferroptosis-related genes is challenging.

RNA-seq and clinical data of HCC in the TCGA database were analyzed to establish a prognostic model, and ICGC and GSE14520 data were used for validation. Risk score was constructed with 5 genes identified by univariate and LASSO Cox regression analysis. Risk score, TNM stage and cirrhosis were incorporated to construct a nomogram through univariate and multivariate Cox regression analysis.

Five genes identified from 70 ferroptosis-related DEGs were used to construct a gene signature that predicts survival of HCC patients in the TCGA cohort. PCA and heatmap showed clear differences between patients in different score groups. Next, risk score, TNM stage and cirrhosis were combined in a nomogram for overall survival prediction. Survival analysis indicated that the overall survival of the low-risk group was significantly higher than that of the high-risk group. The data from the GSE14520 cohort confirmed satisfactory nomogram performance. Furthermore, KEGG and GO functional enrichment analyses indicated that the difference in overall survival between risk groups was closely related to immune-related pathways. Further analyses implied that an immune-suppressive tumor microenvironment might contribute to the difference in the prognosis between risk groups.

The nomogram based on ferroptosis-related genes showed good performance for predicting the prognosis of HCC patients. The model may provide a reference for the evaluation of HCC patients by targeting ferroptosis.