Exploring the Prognostic Features of Hepatocellular Carcinoma via Text Mining and Data Analysis

Abstract

Transcatheter arterial chemoembolization is one of the interventional treatments for hepatocellular carcinoma (HCC). This treatment is generally used for patients with intermediate to advanced hepatocellular carcinoma, and identifying the role of HCC-related genes can help improve the efficiency of transcatheter arterial chemoembolization. To investigate the role of HCC-related genes and to provide valid evidence for transcatheter arterial chemoembolization treatment, we performed a comprehensive bioinformatics analysis. Through text mining ("hepatocellular carcinoma") and microarray data analysis (GSE104580), we obtained a standard gene set, which was followed by gene ontology and Kyoto Gene and Genome Encyclopedia analysis. The significant 8 genes clustered in protein-protein interactions network were chosen to be used in the follow-up analysis. Through survival analysis low expression of the key genes were found to be strongly associated with survival in HCC patients in this study. The correlation between the expression of the key genes and tumor immune infiltration was assessed by Pearson correlation analysis. As a result, 15 drugs targeting seven of the eight genes have been identified, and therefore can be considered as potential components for transcatheter arterial chemoembolization treatment of HCC.