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. 2009 Mar-Apr;15(3-4):85-94.
doi: 10.2119/molmed.2008.00110. Epub 2008 Dec 15.

Genes involved in viral carcinogenesis and tumor initiation in hepatitis C virus-induced hepatocellular carcinoma

Valeria R Mas  1 , Daniel G Maluf, Kellie J Archer, Kenneth Yanek, Xiangrong Kong, Laura Kulik, Chris E Freise, Kim M Olthoff, Rafik M Ghobrial, Paula McIver, Robert Fisher
Affiliations

Genes involved in viral carcinogenesis and tumor initiation in hepatitis C virus-induced hepatocellular carcinoma

Valeria R Mas et al. Mol Med. 2009 Mar-Apr.

Abstract

The role of chronic hepatitis C virus (HCV) in the pathogenesis of HCV-associated hepatocellular carcinoma (HCC) remains controversial. To understand the transition from benign to malignant, we studied the gene expression patterns in liver tissues at different stages, including normal, cirrhosis, and different HCC stages. We studied 108 liver tissue samples obtained from 88 distinct patients (41 HCV-cirrhotic tissues, 17 HCV-cirrhotic tissues from patients with HCC, and 47 HCV-HCC tissues). Differentially expressed genes (DEG) were studied by use of high-density oligonucleotide arrays. Among probe sets identified as differentially expressed via the F test, all pairwise comparisons were performed. Cirrhotic tissues with and without concomitant HCC were further evaluated, and a classifier was used to predict whether the tissue type was associated with HCC. Differential expression profiles were analyzed using Interaction Networks and Functional Analysis. Characteristic gene signatures were identified when normal tissue was compared with cirrhosis, cirrhosis with early HCC, and normal with HCC. Pathway analysis classified the cellular and biological functions of the DEG as related to cellular growth and proliferation, cell death and inflammatory disease in cirrhosis; cell death, cell cycle, DNA replication, and immune response in early HCCs; and cell death, cell growth and proliferation, cell cycle, and DNA repair in advanced HCCs. Characteristic gene signatures were identified at different stages of HCV-HCC progression. A set of genes were identified to predict whether the cirrhotic tissue was associated with HCC.

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Figures

Figure 1
Figure 1
The gene expression matrix was filtered to include only the 2,262 probe sets represented in the Venn diagram illustrating the number of significant genes for the three pairwise comparisons. Thereafter, agglomerative hierarchical clustering using Ward’s method was applied to the filtered dataset using Pearson’s correlation as the similarity measure. Pink box: Normal livers, Yellow box: HCV-cirrhosis from patients without HCC, orange box: HCV-cirrosis from patients with HCC (non tumor tissues), Blue box: HCV-HCC.
Figure 2
Figure 2. The 2 top-scoring networks of interactions among the differentially expressed genes between HCV-HCC vs. HCV-cirrhotic tissues.
Core analysis was performed to interpret the data set in the context of biological processes, pathways and molecular networks for the 542 probe sets differentially expressed only in the HCV-HCC vs. HCV cirrhosis comparison. The top molecular and cellular functions in the networks were classified as cell morphology, development and cancer (score=41) and gene expression, viral function and cancer (score=32). Interconnections of significant functional networks in HCV cirrhosis are indicated. Spatial location of nodes into their corresponding subcellular locations is also indicated. The meaning of the node shapes and interaction edges is also indicated.
Figure 3
Figure 3
Receiver operating characteristic (ROC) curve.
Figure 4
Figure 4. Validation of microarray results for expression levels of EDF1, TFPI, CDH4, and TNFAIP3 genes using QPCR.
Total RNA from the same RNAs samples that were subjected to microarray study were used in the QPCR validation reactions. Values were expressed as mRNA gene expression level (for each specific gene)/housekeeping gene fold change expression compared to the reference sample. The gene expression of the study genes was identified as significant differentially expressed when comparing different group of tissues samples. Specifically, EDF1 was identified as differentially expressed when HCV cirrhotic tissues from patients with HCC (non-tumor samples) (N=17) were compared with HCV cirrhotic tissues from patients without HCC (N=41) (A). TFPI was differentially expressed in HCV-HCC samples (N=47) when compared with HCV cirrhotic tissues from patients with HCC (N=17) (B). CDH4 and TNFAIP3 were identified as differentially expressed when HCV-HCC samples (N=47) were compared with HCV cirrhotic tissues (N=41) (C).
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