Abstract
Aberrant activation of DNA repair is frequently associated with tumor progression and response to therapy in hepatocellular carcinoma (HCC). Bioinformatics analyses of HCC data in the Cancer Genome Atlas (TCGA) were performed to define DNA repair based molecular classification that could predict the prognosis of patients with HCC. Furthermore, we tested its predictive performance in 120 independent cases. Four molecular subgroups were identified on the basis of coordinate DNA repair cluster (CDRC) comprising 15 genes in TCGA dataset. Increasing expression of CDRC genes were significantly associated with TP53 mutation. High CDRC was significantly correlated with advanced tumor grades, advanced pathological stage and increased vascular invasion rate. Multivariate Cox regression analysis indicated that the molecular subgrouping was an independent prognostic parameter for both overall survival (p = 0.004, hazard ratio (HR): 2.989) and tumor-free survival (p = 0.049, HR: 3.366) in TCGA dataset. Similar results were also obtained by analyzing the independent cohort. These data suggest that distinct dysregulation of DNA repair constituents based molecular classes in HCC would be useful for predicting prognosis and designing clinical trials for targeted therapy.
Highlights
Hepatocellular carcinoma (HCC) is the leading cause of cancer death worldwid with dismal prognosis[1]
We investigated the possibility that the expression pattern of the hepatocellular carcinoma (HCC) associated DNA repair genes obtained at diagnosis would permit the identification of distinct subclasses of HCC patients with different prognosis in the Cancer Genome Atlas (TCGA) dataset
Molecular subgroups based on DNA repair genes in hepatocellular carcinoma
Summary
Hepatocellular carcinoma (HCC) is the leading cause of cancer death worldwid with dismal prognosis[1]. Genomic information from tumor tissue will refine the prognostic prediction of HCC patients, and facilitate the identification of genetic determinants that are components of the specific regulatory pathways altered in cancers, providing the opportunity to precision medicine[5]. A thorough understanding of the DNA repair genes expression pattern in tumors would be of utmost importance in HCC prognostic prediction and improving therapy and in achieving the best therapeutic response[17]. We investigated the possibility that the expression pattern of the HCC associated DNA repair genes obtained at diagnosis would permit the identification of distinct subclasses of HCC patients with different prognosis in the Cancer Genome Atlas (TCGA) dataset. We tested the expression pattern of co-regulated cluster of DNA repair genes at both protein and mRNA level to explore the relationship with prognosis of HCC patients in another separate cohort
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