Kong Weihao, Mao Zhongxiang, Han Chen, Ding Zhenxing, Yuan Qianqian, Zhang Gaosong, Li Chong, Wu Xuesheng, Chen Jia, Guo Manyu, Hong Shaocheng, Yu Feng, Liu Rongqiang, Wang Xingyu, Zhang Jianlin
Department of Emergency Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Registration Review Department, Anhui Center for Drug Evaluation & Inspection, Hefei, China.
Front Pharmacol. 2022 Apr 20;13:863750. doi: 10.3389/fphar.2022.863750. eCollection 2022.
Although many genes related to epithelial-mesenchymal transition (EMT) have been explored in hepatocellular carcinoma (HCC), their prognostic significance still needs further analysis. Differentially expressed EMT-related genes were obtained through the integrated analysis of 4 Gene expression omnibus (GEO) datasets. The univariate Cox regression and Lasso Cox regression models are utilized to determine the EMT-related gene signature. Based on the results of multivariate Cox regression, a predictive nomogram is established. Time-dependent ROC curve and calibration curve are used to show the distinguishing ability and consistency of the nomogram. Finally, we explored the correlation between EMT risk score and immune immunity. We identified a nine EMT-related gene signature to predict the survival outcome of HCC patients. Based on the EMT risk score's median, HCC patients in each dataset were divided into high and low-risk groups. The survival outcomes of HCC patients in the high-risk group were significantly worse than those in the low-risk group. The prediction nomogram based on the EMT risk score has better distinguishing ability and consistency. High EMT risk score was related to immune infiltration. The nomogram based on the EMT risk score can reliably predict the survival outcome of HCC patients, thereby providing benefits for medical decisions.
尽管在肝细胞癌（HCC）中已经探索了许多与上皮-间质转化（EMT）相关的基因，但其预后意义仍需进一步分析。通过对4个基因表达综合数据库（GEO）数据集的综合分析，获得了差异表达的EMT相关基因。利用单变量Cox回归和Lasso Cox回归模型来确定EMT相关基因特征。基于多变量Cox回归结果，建立了预测列线图。采用时间依赖性ROC曲线和校准曲线来展示列线图的区分能力和一致性。最后，我们探讨了EMT风险评分与免疫的相关性。我们鉴定出一个由9个EMT相关基因组成的特征，用于预测HCC患者的生存结局。根据EMT风险评分的中位数，将每个数据集中的HCC患者分为高风险组和低风险组。高风险组HCC患者的生存结局明显比低风险组差。基于EMT风险评分的预测列线图具有更好的区分能力和一致性。高EMT风险评分与免疫浸润相关。基于EMT风险评分的列线图能够可靠地预测HCC患者的生存结局，从而为医疗决策提供帮助。
