Identification of a Novel Epithelial-to-mesenchymal-related Gene Signature in Predicting Survival of Patients with Hepatocellular Carcinoma.

Abstract

Epithelial-mesenchymal transformation (EMT) promotes cancer metastasis, including hepatocellular carcinoma. Therefore, EMT-related gene signature was explored. The present study was designed to develop an EMT-related gene signature for predicting the prognosis of patients with hepatocellular carcinoma.. An integrated gene expression analysis based on tumor data of the patients with hepatocellular carcinoma from The Cancer Genome Atlas (TCGA), HCCDB18, and GSE14520 dataset was conducted. An EMT-related gene signature was constructed by the least absolute shrinkage and selection operator (LASSO) and COX regression analysis of univariate and multivariate survival. A 3-EMT gene signature was developed and validated based on gene expression profiles of hepatocellular carcinoma from three microarray platforms. Patients with a high-risk score had significantly worse overall survival (OS) than those with low-risk scores. The EMT-related gene signature showed a high performance in accurately predicting prognosis and examining the clinical characteristics and immune score analysis. Univariate and multivariate Cox regression analyses confirmed that the EMT-related gene signature was an independent prognostic factor for predicting survival in hepatocellular carcinoma patients. Compared with the existing models, our EMTrelated gene signature reached a higher area under the curve (AUC). Our findings provide novel insight into understanding EMT and help identify hepatocellular carcinoma patients with poor prognosis.