Abstract

IntroductionCirrhosis is one of the most important risk factors for development of hepatocellular carcinoma (HCC). Recent studies have shown that removal or well control of the underlying cause could reduce but not eliminate the risk of HCC. Therefore, it is important to elucidate the molecular mechanisms that drive the progression of cirrhosis to HCC.Materials and MethodsMicroarray datasets incorporating cirrhosis and HCC subjects were identified from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were determined by GEO2R software. Functional enrichment analysis was performed by the clusterProfiler package in R. Liver carcinogenesis-related networks and modules were established using STRING database and MCODE plug-in, respectively, which were visualized with Cytoscape software. The ability of modular gene signatures to discriminate cirrhosis from HCC was assessed by hierarchical clustering, principal component analysis (PCA), and receiver operating characteristic (ROC) curve. Association of top modular genes and HCC grades or prognosis was analyzed with the UALCAN web-tool. Protein expression and distribution of top modular genes were analyzed using the Human Protein Atlas database.ResultsFour microarray datasets were retrieved from GEO database. Compared with cirrhotic livers, 125 upregulated and 252 downregulated genes in HCC tissues were found. These DEGs constituted a liver carcinogenesis-related network with 272 nodes and 2954 edges, with 65 nodes being highly connected and formed a liver carcinogenesis-related module. The modular genes were significantly involved in several KEGG pathways, such as “cell cycle,” “DNA replication,” “p53 signaling pathway,” “mismatch repair,” “base excision repair,” etc. These identified modular gene signatures could robustly discriminate cirrhosis from HCC in the validation dataset. In contrast, the expression pattern of the modular genes was consistent between cirrhotic and normal livers. The top modular genes TOP2A, CDC20, PRC1, CCNB2, and NUSAP1 were associated with HCC onset, progression, and prognosis, and exhibited higher expression in HCC compared with normal livers in the HPA database.ConclusionOur study revealed a highly connected module associated with liver carcinogenesis on a cirrhotic background, which may provide deeper understanding of the genetic alterations involved in the transition from cirrhosis to HCC, and offer valuable variables for screening and surveillance of HCC in high-risk patients with cirrhosis.

Highlights

  • Cirrhosis is one of the most important risk factors for development of hepatocellular carcinoma (HCC)

  • Association of the top modular genes and HCC grades or prognosis was analyzed by using UALCAN (Chandrashekar et al, 2017), which is an interactive web-portal for exploring the association between tumor subgroup gene expression and survival in TCGA3

  • By performing a series of bioinformatics analyses, we found a highly connected module covering 65 HCC risky genes, which could robustly distinguish cirrhosis from HCC; the top modular genes were highly associated with HCC onset and development and prognosis

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Summary

Introduction

Cirrhosis is one of the most important risk factors for development of hepatocellular carcinoma (HCC). Recent studies have shown that removal or well control of the underlying cause could reduce but not eliminate the risk of HCC. It is important to elucidate the molecular mechanisms that drive the progression of cirrhosis to HCC. Growing clinical evidence shows that removal or control of the injurious factors, such as hepatitis B or C virus, can reduce but not eliminate the risk of HCC (Casado et al, 2013; Marcellin et al, 2013; Xu et al, 2015; Sun et al, 2017). It is important to understand the molecular mechanisms that drive the progression of cirrhosis to HCC. Different studies often yield diverse results and the global view on the landscape of genomic changes is still not very clear

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