TAF2: A potential oncogene for hepatocellular carcinoma

Astrocyte Elevated Gene 1 (AEG1) is an oncogene for hepatocellular carcinoma (HCC). Its role in HCC pathogenesis has been well studied. A pan cancer analysis of gene expression in multiple databases identified TATA-box binding protein associated factor 2 (TAF2) as the gene that is most frequently co-expressed with AEG1. TAF2 is a protein that is involved in transcription of genes by RNA polymerase II. It is a factor that is dispensable for basal transcription but, required for activated transcription. It has also been shown to be involved in regulating cyclin levels and hence cell cycle progression. Bioinformatic analysis on data from different cancer databases confirmed the positive correlation of TAF2 expression with AEG1 expression, the over expression of TAF2 in HCC patients and poor survival of HCC patients with increasing TAF2. We confirmed the over expression of TAF2 in HCC cell lines using western blotting and HCC liver using immunohistochemistry. We established cell lines with stable knockdown of TAF2 expression. These clones showed significant decrease in their ability to invade and migrate but not their proliferation ability. This is in contrast to what has been observed in previous studies. We hypothesize that the knockdowns do not show any decrease in cellular proliferation since the remaining TAF2 in the cells is sufficient to produce cyclins and keep cell cycle undisturbed. The knockdown of TAF2 causes an increase in E-cadherin level and decrease in Snail protein expression which is a known negative regulator of E-cadherin. Knockdown of TAF2 causes cells to become more epithelial leading to a decrease in their ability to migrate and invade. This study shows that TAF2 is a potential oncogene that needs to be further studied

Dissecting the expression landscape of cytochromes P450 in hepatocellular carcinoma: towards novel molecular biomarkers

Abstract: Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related deaths around the world. Recent advances in genomic technologies have allowed the identification of various molecular signatures in HCC tissues. For instance, differential gene expression levels of various cytochrome P450 genes (CYP450) have been reported in studies performed on limited numbers of HCC tissue samples, or focused on a small subset on CYP450s. In the present study, we monitored the expression landscape of all the members of the CYP450 family (57 genes) in more than 200 HCC tissues using RNA-Seq data from The Cancer Genome Atlas. Using stringent statistical filters and data from paired tissues, we identified significantly dysregulated CYP450 genes in HCC. Moreover, the expression level of selected CYP450s was validated by qPCR on cDNA samples from an independent cohort. Threshold values (sensitivity and specificity) based on dysregulated gene expression were also determined to allow for confident identification of HCC tissues. Finally, a global look at expression levels of the 57 members of the CYP450 family across ten different cancer types revealed specific expression signatures. Overall, this study provides useful information on the transcriptomic landscape of CYP450 genes in HCC and on new potential HCC biomarkers

Functional and Topological Properties in Hepatocellular Carcinoma Transcriptome

Hepatocellular carcinoma (HCC) is a leading cause of global cancer mortality. However, little is known about the precise molecular mechanisms involved in tumor formation and pathogenesis. The primary goal of this study was to elucidate genome-wide molecular networks involved in development of HCC with multiple etiologies by exploring high quality microarray data. We undertook a comparative network analysis across 264 human microarray profiles monitoring transcript changes in healthy liver, liver cirrhosis, and HCC with viral and alcoholic etiologies. Gene co-expression profiling was used to derive a consensus gene relevance network of HCC progression that consisted of 798 genes and 2,012 links. The HCC interactome was further confirmed to be phenotype-specific and non-random. Additionally, we confirmed that co-expressed genes are more likely to share biological function, but not sub-cellular localization. Analysis of individual HCC genes revealed that they are topologically central in a human protein-protein interaction network. We used quantitative RT-PCR in a cohort of normal liver tissue (n = 8), hepatitis C virus (HCV)-induced chronic liver disease (n = 9), and HCC (n = 7) to validate co-expressions of several well-connected genes, namely ASPM, CDKN3, NEK2, RACGAP1, and TOP2A. We show that HCC is a heterogeneous disorder, underpinned by complex cross talk between immune response, cell cycle, and mRNA translation pathways. Our work provides a systems-wide resource for deeper understanding of molecular mechanisms in HCC progression and may be used further to define novel targets for efficient treatment or diagnosis of this disease

Network analysis of hepatocellular carcinoma liquid biopsies augmented by single-cell sequencing data

Liquid biopsy, the analysis of body fluids, represents a promising approach for disease diagnosis and prognosis with minimal intervention. Sequencing cell-free RNA derived from liquid biopsies has been very promising for the diagnosis of several diseases. Cancer research, in particular, has emerged as a prominent candidate since early diagnosis has been shown to be a critical determinant of disease prognosis. Although high-throughput analysis of liquid biopsies has uncovered many differentially expressed genes in the context of cancer, the functional connection between these genes is not investigated in depth. An important approach to remedy this issue is the construction of gene networks which describes the correlation patterns between different genes, thereby allowing to infer their functional organization. In this study, we aimed at characterizing extracellular transcriptome gene networks of hepatocellular carcinoma patients compared to healthy controls. Our analysis revealed a number of genes previously associated with hepatocellular carcinoma and uncovered their association network in the blood. Our study thus demonstrates the feasibility of performing gene co-expression network analysis from cell-free RNA data and its utility in studying hepatocellular carcinoma. Furthermore, we augmented cell-free RNA network analysis with single-cell RNA sequencing data which enables the contextualization of the identified network modules with cell-type specific transcriptomes from the liver

C-terminal truncated hepatitis B virus X protein promotes hepatocellular carcinogenesis through induction of cancer and stem cell-like properties

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Constructing the HBV-human protein interaction network to understand the relationship between HBV and hepatocellular carcinoma

<p>Abstract</p> <p>Background</p> <p>Epidemiological studies have clearly validated the association between hepatitis B virus (HBV) infection and hepatocellular carcinoma (HCC). Patients with chronic HBV infection are at increased risk of HCC, in particular those with active liver disease and cirrhosis.</p> <p>Methods</p> <p>We catalogued all published interactions between HBV and human proteins, identifying 250 descriptions of HBV and human protein interactions and 146 unique human proteins that interact with HBV proteins by text mining.</p> <p>Results</p> <p>Integration of this data set into a reconstructed human interactome showed that cellular proteins interacting with HBV are made up of core proteins that are interconnected with many pathways. A global analysis based on functional annotation highlighted the enrichment of cellular pathways targeted by HBV.</p> <p>Conclusions</p> <p>By connecting the cellular proteins targeted by HBV, we have constructed a central network of proteins associated with hepatocellular carcinoma, which might be to regard as the basis of a detailed map for tracking new cellular interactions, and guiding future investigations.</p

Alcohol-dysregulated microRNAs in hepatitis B virus-related hepatocellular carcinoma

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