Integrated Bioinformatic Analysis Identifies TIPIN as a Prognostic Biomarker in Hepatocellular Carcinoma

BACKGROUND: Gene expression and DNA methylation analyses have long been used to identify cancer markers. However, a combination analysis of the gene expression and DNA methylation has yet to be performed to identify potential biomarkers of hepatocellular carcinoma (HCC). METHODS: By matching gene expression profiles and promoter methylation data in The Cancer Genome Atlas (TCGA), genes with discrepant expression as well as genes with differential promoter methylation were identified. High-expression genes with low promoter methylation were defined as epigenetically induced (EI), while low-expression genes with high promoter methylation were defined as epigenetically suppressed (ES). The human protein interaction network was further integrated to construct the EI/ES gene interaction network, and the key genes in the subnet were identified as potential HCC biomarkers. The expression differences and prognostic values were verified in TCGA and Gene Expression Omnibus (GEO) databases, as well as with tissue chip technology. RESULTS: Four key genes were identified: TIPIN, RBM15B, DUSP28, and TRIM31, which demonstrated the differential gene expression and prognostic value in TCGA and GEO databases. Tissue microarray analysis (TMA) revealed that TIPIN levels were altered in HCC. The upregulated TIPIN expression was associated with worse overall survival. Univariate and multivariate analyses showed that the TIPIN expression was an independent predictor of HCC. CONCLUSION: TIPIN might be a potential novel prognostic biomarker for HCC.