Abstract 3988: Identifying prognostic biomarkers of hepatocellular carcinoma by weighted gene coexpression network analysis

Abstract

Abstract Purpose: Exploring the molecular mechanisms of prognosis in patients with hepatocellular carcinoma (HCC) could assist in identifying novel biomarkers for effective therapy against this deadly disease. Hence, this study was designed to determine the prognostic biomarkers of HCC and to investigate potential mechanisms. Experimental Design: The RNA-Seq data as well as clinical data were downloaded from The Cancer Genome Atlas (TCGA) database, aiming at identifying differentially expressed genes (DEGs) between nontumorous tissues and HCC. Then, weighted gene coexpression network analysis (WGCNA) was performed for determining significant modules associated with overall survival (OS). Results: The mRNA expression profiles from 374 HCC patients in TCGA were included to determine 3270 DEGs. Then, WGCNA was carried out on the 3270 DEGs, and 10 coexpressed gene modules were determined. Pearson’s correlation analysis revealed that the turquoise module significantly positively correlated with OS and the blue module significantly negatively correlated with OS, followed by seven hub genes with high connectivity were identified in these two modules. Based on the Kaplan-Meier (K-M) survival curves and receiver operating characteristic (ROC) curves, the seven hub genes could predict prognosis for patients with HCC well, and the results were validated by GSE54236 dataset contained 78 HCC patients. Additionally, the univariate and multivariate Cox regression analyses showed that the seven hub genes were independent prognostic factors for patients with HCC. Conclusions: In conclusion, the current results provide novel insights into the prognostic biomarkers of HCC, which may contribute to the development of molecular targeted therapy for HCC. Citation Format: Yi Bai, Junyu Long, Jianzhen Lin, Xu Yang, Dongxu Wang, Xiaobo Yang, Xinting Sang, Jiahui Liu, Haitao Zhao. Identifying prognostic biomarkers of hepatocellular carcinoma by weighted gene coexpression network analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3988.