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Investigating the mechanism of hepatocellular carcinoma progression by constructing genetic and epigenetic networks using NGS data identification and big database mining method.

ABSTRACT: The mechanisms leading to the development and progression of hepatocellular carcinoma (HCC) are complicated and regulated genetically and epigenetically. The recent advancement in high-throughput sequencing has facilitated investigations into the role of genetic and epigenetic regulations in hepatocarcinogenesis. Therefore, we used systems biology and big database mining to construct genetic and epigenetic networks (GENs) using the information about mRNA, miRNA, and methylation profiles of HCC patients. Our approach involves analyzing gene regulatory networks (GRNs), protein-protein networks (PPINs), and epigenetic networks at different stages of hepatocarcinogenesis. The core GENs, influencing each stage of HCC, were extracted via principal network projection (PNP). The pathways during different stages of HCC were compared. We observed that extracellular signals were further transduced to transcription factors (TFs), resulting in the aberrant regulation of their target genes, in turn inducing mechanisms that are responsible for HCC progression, including cell proliferation, anti-apoptosis, aberrant cell cycle, cell survival, and metastasis. We also selected potential multiple drugs specific to prominent epigenetic network markers of each stage of HCC: lestaurtinib, dinaciclib, and perifosine against the NTRK2, MYC, and AKT1 markers influencing HCC progression from stage I to stage II; celecoxib, axitinib, and vinblastine against the DDIT3, PDGFB, and JUN markers influencing HCC progression from stage II to stage III; and atiprimod, celastrol, and bortezomib against STAT3, IL1B, and NFKB1 markers influencing HCC progression from stage III to stage IV.

SUBMITTER: Li CW

PROVIDER: S-EPMC5346727 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Investigating the mechanism of hepatocellular carcinoma progression by constructing genetic and epigenetic networks using NGS data identification and big database mining method.

Li Cheng-Wei CW Chang Ping-Yao PY Chen Bor-Sen BS

Oncotarget 20161101 48

The mechanisms leading to the development and progression of hepatocellular carcinoma (HCC) are complicated and regulated genetically and epigenetically. The recent advancement in high-throughput sequencing has facilitated investigations into the role of genetic and epigenetic regulations in hepatocarcinogenesis. Therefore, we used systems biology and big database mining to construct genetic and epigenetic networks (GENs) using the information about mRNA, miRNA, and methylation profiles of HCC p ...[more]

PMID: 27821810

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Project description:Epstein-Barr virus (EBV), also known as human herpesvirus 4, is prevalent in all human populations. EBV mainly infects human B lymphocytes and epithelial cells, and is therefore associated with their various malignancies. To unravel the cellular mechanisms during the infection, we constructed interspecies networks to investigate the molecular cross-talk mechanisms between human B cells and EBV at the first (0-24 hours) and second (8-72 hours) stages of EBV infection. We first constructed a candidate genome-wide interspecies genetic-and-epigenetic network (the candidate GIGEN) by big database mining. We then pruned false positives in the candidate GIGEN to obtain the real GIGENs at the first and second infection stages in the lytic phase by their corresponding next-generation sequencing data through dynamic interaction models, the system identification approach, and the system order detection method. The real GIGENs are very complex and comprise protein-protein interaction networks, gene/microRNA (miRNA)/long non-coding RNA regulation networks, and host-virus cross-talk networks. To understand the molecular cross-talk mechanisms underlying EBV infection, we extracted the core GIGENs including host-virus core networks and host-virus core pathways from the real GIGENs using the principal network projection method. According to the results, we found that the activities of epigenetics-associated human proteins or genes were initially inhibited by viral proteins and miRNAs, and human immune responses were then dysregulated by epigenetic modification. We suggested that EBV exploits viral proteins and miRNAs, such as EBNA1, BPLF1, BALF3, BVRF1 and miR-BART14, to develop its defensive mechanism to defeat multiple immune attacks by the human immune system, promotes virion production, and facilitates the transportation of viral particles by activating the human genes NRP1 and CLIC5. Ultimately, we propose a therapeutic intervention comprising thymoquinone, valpromide, and zebularine to act as inhibitors of EBV-associated malignancies.

Dataset Information

Investigating the mechanism of hepatocellular carcinoma progression by constructing genetic and epigenetic networks using NGS data identification and big database mining method.

Publications

Investigating the mechanism of hepatocellular carcinoma progression by constructing genetic and epigenetic networks using NGS data identification and big database mining method.

Similar Datasets

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