Background

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.

Methods

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.

Results

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.

Conclusion

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.

中文翻译：

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基于特征性铁死亡相关基因的肝细胞癌患者预后模型

背景

考虑到 HCC 患者数量的增加，预测患者的生存率至关重要。尽管铁死亡与 HCC 进展密切相关，但通过铁死亡相关基因预测 HCC 患者的存活率具有挑战性。

方法

分析TCGA数据库中HCC的RNA-seq和临床数据建立预后模型，并使用ICGC和GSE14520数据进行验证。风险评分由通过单变量和 LASSO Cox 回归分析确定的 5 个基因构建。通过单变量和多变量Cox回归分析，结合风险评分、TNM分期和肝硬化构建列线图。

结果

从 70 个与铁死亡相关的 DEG 中鉴定出的 5 个基因用于构建预测 TCGA 队列中 HCC 患者存活率的基因特征。PCA 和热图显示不同评分组的患者之间存在明显差异。接下来，将风险评分、TNM 分期和肝硬化结合在列线图中，用于预测总生存期。生存分析表明，低危组的总生存期明显高于高危组。来自 GSE14520 队列的数据证实了令人满意的列线图性能。此外，KEGG 和 GO 功能富集分析表明，风险组之间总生存率的差异与免疫相关通路密切相关。

结论

基于铁死亡相关基因的列线图在预测HCC患者预后方面表现出良好的性能。该模型可为靶向铁死亡评估HCC患者提供参考。