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      Identification of key genes and pathways in hepatocellular carcinoma : A preliminary bioinformatics analysis

      research-article
      , PhD a , , PhD a , , PhD b , , , PhD a , b ,
      Medicine
      Wolters Kluwer Health
      computational biology, genes, hepatocellular carcinoma

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          Abstract

          Background:

          Hepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide. However, the precise mechanisms of the development and progression of HCC remain unclear. The present study attempted to identify and functionally analyze the differentially expressed genes between HCC and cirrhotic tissues by using comprehensive bioinformatics analyses.

          Methods:

          The GSE63898 gene expression profile was downloaded from the Gene Expression Omnibus (GEO) and analyzed using the online tool GEO2R to identify differentially expressed genes (DEGs). Gene ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the DEGs were performed in DAVID. The STRING database was used to evaluate the interactions of DEGs and to construct a protein-protein interaction (PPI) network using Cytoscape software. Hub genes were selected using the cytoHubba plugin and were validated with the cBioPortal database.

          Results:

          A total of 301 DEGs were identified between HCC and cirrhotic tissues. The GO analysis results showed that these DEGs were significantly enriched in certain biological processes including negative regulation of growth and cell chemotaxis. Several significant pathways, including the p53 signaling pathway, were identified as being closely associated with these DEGs. The top 12 hub genes were screened and included TTK, NCAPG, TOP2A, CCNB1, CDK1, PRC1, RRM2, UBE2C, ZWINT, CDKN3, AURKA, and RACGAP1. The cBioPortal analysis found that alterations in hub genes could result in significantly reduced disease-free survival in HCC.

          Conclusion:

          The present study identified a series of key genes and pathways that may be involved in the tumorigenicity and progression of HCC, providing a new understanding of the underlying molecular mechanisms of carcinogenesis in HCC.

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          Most cited references39

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          Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal.

          The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.
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            Phosphorylation of beta-catenin by AKT promotes beta-catenin transcriptional activity.

            Increased transcriptional activity of beta-catenin resulting from Wnt/Wingless-dependent or -independent signaling has been detected in many types of human cancer, but the underlying mechanism of Wnt-independent regulation is poorly understood. We have demonstrated that AKT, which is activated downstream from epidermal growth factor receptor signaling, phosphorylates beta-catenin at Ser552 in vitro and in vivo. AKT-mediated phosphorylation of beta-catenin causes its disassociation from cell-cell contacts and accumulation in both the cytosol and the nucleus and enhances its interaction with 14-3-3zeta via a binding motif containing Ser552. Phosphorylation of beta-catenin by AKT increases its transcriptional activity and promotes tumor cell invasion, indicating that AKT-dependent regulation of beta-catenin plays a critical role in tumor invasion and development.
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              International trends in liver cancer incidence, overall and by histologic subtype, 1978-2007.

              Primary liver cancer, the most common histologic types of which are hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC), is the second leading cause of cancer death worldwide. While rising incidence of liver cancer in low-risk areas and decreasing incidence in some high-risk areas has been reported, trends have not been thoroughly explored by country or by histologic type. We examined liver cancer incidence overall and by histology by calendar time and birth cohort for selected countries between 1978 and 2007. For each successive 5-year period, age-standardized incidence rates were calculated from volumes V-IX of the Cancer Incidence in Five Continents electronic database (CI5plus) and the newly released CI5X (volume X) database. Wide global variations persist in liver cancer incidence. Rates of liver cancer remain highest in Asian countries, specifically Eastern and South-Eastern Asian countries. While rates in most of these high-risk countries have been decreasing in recent years, rates in India and several low-risk countries of Africa, Europe, the Americas, and Oceania have been on the rise. Liver cancer rates by histologic type tend to convey a similar temporal profile. However, in Thailand, France, and Italy, ICC rates have increased while HCC rates have declined. We expect rates in high-risk countries to continue to decrease, as the population seroprevalence of hepatitis B virus (HBV) continues to decline. In low-risk countries, targeted screening and treatment of the hepatitis C virus (HCV), treatment of diabetes and primary prevention of obesity, will be key in reducing future liver cancer incidence.
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                Author and article information

                Journal
                Medicine (Baltimore)
                Medicine (Baltimore)
                MEDI
                Medicine
                Wolters Kluwer Health
                0025-7974
                1536-5964
                February 2019
                01 February 2019
                : 98
                : 5
                : e14287
                Affiliations
                [a ]Department of General surgery
                [b ]Beijing Institute of Hepatology, Beijing Youan Hospital, Capital Medical University, Beijing, China.
                Author notes
                []Correspondence: Ning Li, Aiying Zhang, Beijing Institute of Hepatology, Beijing Youan Hospital, Capital Medical University, 8 Xitoutiao, Youanmenwai, Fengtai District, Beijing 100069, China (e-mails: liningya@ 123456ccmu.edu.cn , zhangaiying1996@ 123456outlook.com ).
                Article
                MD-D-18-04477 14287
                10.1097/MD.0000000000014287
                6380748
                30702595
                12cfde54-cd3b-452c-82fd-227b6319cfc2
                Copyright © 2019 the Author(s). Published by Wolters Kluwer Health, Inc.

                This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0

                History
                : 28 June 2018
                : 3 December 2018
                : 26 December 2018
                Categories
                5700
                Research Article
                Clinical Trial/Experimental Study
                Custom metadata
                TRUE

                computational biology,genes,hepatocellular carcinoma

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