A Novel Epithelial-Mesenchymal Transition Gene Signature Correlated With Prognosis, and Immune Infiltration in Hepatocellular Carcinoma

Background: Although many genes related to epithelial-mesenchymal transition (EMT) have been explored in hepatocellular carcinoma (HCC), their prognostic significance still needs further analysis. Methods: 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. Results: 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. Conclusion: The nomogram based on the EMT risk score can reliably predict the survival outcome of HCC patients, thereby providing benefits for medical decisions.