Identification of a novel ferroptosis-related gene signature in hepatocellular carcinoma: clinical significance, tumor microenvironment, drug sensitivity, and gene landscape analysis.

Hepatocellular carcinoma (HCC) continues to be a major factor associated with cancer incidence and mortality. Traditional treatments used for HCC have limited efficacy. Ferroptosis plays a key role in cancer occurrence and development. Therefore, the present work focused on screening ferroptosis-related genes (FRGs) and using these FRGs to establish a prognosis prediction model. Sixty-seven FRGs were screened through a differential analysis of the TCGA-LIHC data, and 10 core genes were identified through univariate and multivariate Cox regression analyses along with LASSO regression. These findings were further validated using the ICGC-LIHC cohort as an independent validation dataset. All included patients were classified into Low or High groups according to their risk score, and the prognostic efficacy was evaluated based on time-dependent ROC curves. The AUC value of the 10 FRGs was 0.991, indicating high predictive ability. A prognostic nomogram was also constructed by incorporating FRGs and patient clinical factors. According to the results of the clinical analysis, High group had unfavorable survival. Tumor microenvironment analysis revealed significant differences in the immune scores and stromal scores between the two groups. Drug sensitivity analyses revealed that the High group presented increased sensitivity to drugs such as sorafenib. Gene landscape and mutation analysis revealed that High group had an increased frequency of TP53 mutation, whereas Low group had an increased frequency of CTNNB1 mutation. In summary, a prognostic prediction signature was established based on the 10 FRGs and evaluated for its potential application value in HCC prognosis for the investigation of the tumor microenvironment, drug sensitivity, and the gene mutation landscape.