Detection of Novel Genomic Markers for Predicting Prognosis in Hepatocellular Carcinoma Patients by Integrative Analysis of Copy Number Aberrations and Gene Expression Profiles: Results from a Long-Term Follow-Up

Abstract

The aim of this study was to explore novel genomic biomarkers predicting hepatocellular carcinoma (HCC) prognosis by integrative analysis of DNA copy number aberrations (CNAs) and gene expression profiles. Array comparative genomic hybridization and expression array were performed on 45 and 31 HCC samples, respectively. To identify functionally important genes, concordant results of DNA copy number and gene expression were retrieved by integrative analysis. Cox regression analysis indicated that the CNAs in 192 genomic regions were significantly associated with overall survival (OS: p < 0.05). Integrative analysis capturing concordant results demonstrated that the low expression of TLE4 (p = 0.041) and XPA (p = 0.006) was associated with poor OS. In the analysis of tumor recurrence, 514 genomic regions with CNAs were associated with recurrence. Integrative analysis revealed that the overexpression of 16 genes, including FGR (p = 0.003), RELA (p = 0.049), LTBP3 (p = 0.050), and RIN1 (p = 0.023), was significantly associated with shorter time to tumor recurrence. On multivariate analysis, FGR and XPA were independent risk factors of early recurrence and poor OS, respectively. Integrated analysis of CNAs and gene expression profiles correlated with long-term follow-up data successfully identified potential prognostic markers predicting survival and tumor recurrence in patients with HCC who underwent surgical resection.