Risk characteristics with seven epithelial-mesenchymal transition-related genes are used to predict the prognosis of patients with hepatocellular carcinoma

• Published in: Journal of gastrointestinal oncology Vol. 12; no. 4; pp. 1884 - 1894
• Main Authors: Shi, Xianqing, Tu, Shuhuan, Zhu, Liqun
• Format: Journal Article
• Language: English
• Published: China AME Publishing Company 01.08.2021
• Subjects: Original; Gene Genome Map; epithelial-mesenchymal transition-related gene (EAG); Kaplan-Meier curve; prognosis; Hepatocellular carcinoma (HCC)
• ISSN: 2078-6891; 2219-679X
• DOI: 10.21037/jgo-21-394

Epithelial-mesenchymal transition (EMT)-related genes (ERGs) have been shown to play an important role in cancer invasion, tumor resistance, and tumor metastasis of hepatocellular carcinoma. This study sought to examine the prognostic value of ERGs and other pre-hepatoma genes. Relevant data from The Cancer Genome Atlas (TCGA) were analyzed and synthesized. Specifically, 1,014 ERGs were downloaded and subject to a gene set enrichment analysis; 318 different EAG expressions were found, and the possible molecular mechanism of EAG was predicted by GO analysis and KEGG analysis. To determine the prediction of ERGS, a Cox regression model was used to establish a risk hypothesis. Based on risk patterns, patients were divided into high- or low-risk groups. Kaplan-Meier and receiver operating characteristic (ROC) curves confirmed the predictive value of the model. Seven prognostically relevant ERGs (i.e., ECT2, EZH2, MYCN, ROR2, SPP1, SQSTM1, and STC2) were identified. Using Cox's regression analysis method, appropriate cases were selected to establish a new risk prediction model. Under the risk model, the overall survival rate of the low-risk group samples was higher than that of the high-risk group samples (P<0.00001). In short, we developed a risk model for liver cancer based on ERGs terminology. This model improve the postpartum treatment of patients with liver cancer.