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Identification of hepatitis B virus and liver cancer bridge molecules based on functional module network
The potential role of chronic inflammation in the development of cancer has been widely recognized. However, there has been little research fully and thoroughly exploring the molecular link between hepatitis B virus (HBV) and hepatocellular carcinoma (HCC). To elucidate the molecular links between H...
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Published in: | World journal of gastroenterology : WJG 2019-09, Vol.25 (33), p.4921-4932 |
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creator | Huang, Xiao-Bing He, Yong-Gang Zheng, Lu Feng, Huan Li, Yu-Ming Li, Hong-Yan Yang, Feng-Xia Li, Jing |
description | The potential role of chronic inflammation in the development of cancer has been widely recognized. However, there has been little research fully and thoroughly exploring the molecular link between hepatitis B virus (HBV) and hepatocellular carcinoma (HCC).
To elucidate the molecular links between HBV and HCC through analyzing the molecular processes of HBV-HCC using a multidimensional approach.
First, maladjusted genes shared between HBV and HCC were identified by disease-related differentially expressed genes. Second, the protein-protein interaction network based on dysfunctional genes identified a series of dysfunctional modules and significant crosstalk between modules based on the hypergeometric test. In addition, key regulators were detected by pivot analysis. Finally, targeted drugs that have regulatory effects on diseases were predicted by modular methods and drug target information.
The study found that 67 genes continued to increase in the HBV-HCC process. Moreover, 366 overlapping genes in the module network participated in multiple functional blocks. It could be presumed that these genes and their interactions play an important role in the relationship between inflammation and cancer. Correspondingly, significant crosstalk constructed a module level bridge for HBV-HCC molecular processes. On the other hand, a series of non-coding RNAs and transcription factors that have potential pivot regulatory effects on HBV and HCC were identified. Among them, some of the regulators also had persistent disorders in the process of HBV-HCC including microRNA-192, microRNA-215, and microRNA-874, and early growth response 2, FOS, and Kruppel-like factor 4. Therefore, the study concluded that these pivots are the key bridge molecules outside the module. Last but not least, a variety of drugs that may have some potential pharmacological or toxic side effects on HBV-induced HCC were predicted, but their mechanisms still need to be further explored.
The results suggest that the persistent inflammatory environment of HBV can be utilized as an important risk factor to induce the occurrence of HCC, which is supported by molecular evidence. |
doi_str_mv | 10.3748/wjg.v25.i33.4921 |
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fullrecord | <record><control><sourceid>pubmed_cross</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6737318</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>31543683</sourcerecordid><originalsourceid>FETCH-LOGICAL-c396t-895ea588270e03f09285e224bc5e40793c9ab464c0e0251812e638ab98a847da3</originalsourceid><addsrcrecordid>eNpVkF1LwzAUhoMobk7vvZL8gdYkJ22TG0HFj8HAG70OaZpumV07krbDf2_GdOjVOfDyvIfzIHRNSQoFF7e79TIdWZY6gJRLRk_QlDEqEyY4OUVTSkiRSGDFBF2EsCaEAWTsHE2AZhxyAVO0mle27V3tjO5d1-Kuxiu7jXvvAn7Ao_NDwLqtcONG67HRrYmj9K5aWrzpGmuGxgZc6mArHPl6aM2-SDcxrWKGW9vvOv95ic5q3QR79TNn6OP56f3xNVm8vcwf7xeJAZn3iZCZ1ZkQrCCWQE0kE5lljJcms5wUEozUJc-5iTHLqKDM5iB0KYUWvKg0zNDdoXc7lBtbmfid143aerfR_kt12qn_SetWatmNKi-gACpiATkUGN-F4G19ZClRe-sqWlfRuorW1d56RG7-3jwCv5rhGzsvgZ0</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Identification of hepatitis B virus and liver cancer bridge molecules based on functional module network</title><source>PubMed Central</source><creator>Huang, Xiao-Bing ; He, Yong-Gang ; Zheng, Lu ; Feng, Huan ; Li, Yu-Ming ; Li, Hong-Yan ; Yang, Feng-Xia ; Li, Jing</creator><creatorcontrib>Huang, Xiao-Bing ; He, Yong-Gang ; Zheng, Lu ; Feng, Huan ; Li, Yu-Ming ; Li, Hong-Yan ; Yang, Feng-Xia ; Li, Jing</creatorcontrib><description>The potential role of chronic inflammation in the development of cancer has been widely recognized. However, there has been little research fully and thoroughly exploring the molecular link between hepatitis B virus (HBV) and hepatocellular carcinoma (HCC).
To elucidate the molecular links between HBV and HCC through analyzing the molecular processes of HBV-HCC using a multidimensional approach.
First, maladjusted genes shared between HBV and HCC were identified by disease-related differentially expressed genes. Second, the protein-protein interaction network based on dysfunctional genes identified a series of dysfunctional modules and significant crosstalk between modules based on the hypergeometric test. In addition, key regulators were detected by pivot analysis. Finally, targeted drugs that have regulatory effects on diseases were predicted by modular methods and drug target information.
The study found that 67 genes continued to increase in the HBV-HCC process. Moreover, 366 overlapping genes in the module network participated in multiple functional blocks. It could be presumed that these genes and their interactions play an important role in the relationship between inflammation and cancer. Correspondingly, significant crosstalk constructed a module level bridge for HBV-HCC molecular processes. On the other hand, a series of non-coding RNAs and transcription factors that have potential pivot regulatory effects on HBV and HCC were identified. Among them, some of the regulators also had persistent disorders in the process of HBV-HCC including microRNA-192, microRNA-215, and microRNA-874, and early growth response 2, FOS, and Kruppel-like factor 4. Therefore, the study concluded that these pivots are the key bridge molecules outside the module. Last but not least, a variety of drugs that may have some potential pharmacological or toxic side effects on HBV-induced HCC were predicted, but their mechanisms still need to be further explored.
The results suggest that the persistent inflammatory environment of HBV can be utilized as an important risk factor to induce the occurrence of HCC, which is supported by molecular evidence.</description><identifier>ISSN: 1007-9327</identifier><identifier>EISSN: 2219-2840</identifier><identifier>DOI: 10.3748/wjg.v25.i33.4921</identifier><identifier>PMID: 31543683</identifier><language>eng</language><publisher>United States: Baishideng Publishing Group Inc</publisher><subject>Basic Study ; Carcinoma, Hepatocellular - drug therapy ; Carcinoma, Hepatocellular - epidemiology ; Carcinoma, Hepatocellular - etiology ; Datasets as Topic ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic - drug effects ; Gene Expression Regulation, Neoplastic - immunology ; Gene Regulatory Networks - drug effects ; Gene Regulatory Networks - immunology ; Hepatitis B virus - immunology ; Hepatitis B, Chronic - immunology ; Hepatitis B, Chronic - pathology ; Hepatitis B, Chronic - virology ; Host-Pathogen Interactions - genetics ; Host-Pathogen Interactions - immunology ; Humans ; Immunoglobulin G - pharmacology ; Immunoglobulin G - therapeutic use ; Liver Neoplasms - drug therapy ; Liver Neoplasms - epidemiology ; Liver Neoplasms - etiology ; Melphalan - pharmacology ; Melphalan - therapeutic use ; MicroRNAs - antagonists & inhibitors ; MicroRNAs - metabolism ; Protein Interaction Mapping ; Protein Interaction Maps - drug effects ; Protein Interaction Maps - genetics ; Protein Interaction Maps - immunology ; Risk Factors ; Transcription Factors - antagonists & inhibitors ; Transcription Factors - metabolism</subject><ispartof>World journal of gastroenterology : WJG, 2019-09, Vol.25 (33), p.4921-4932</ispartof><rights>The Author(s) 2019. Published by Baishideng Publishing Group Inc. All rights reserved. 2019</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c396t-895ea588270e03f09285e224bc5e40793c9ab464c0e0251812e638ab98a847da3</citedby><cites>FETCH-LOGICAL-c396t-895ea588270e03f09285e224bc5e40793c9ab464c0e0251812e638ab98a847da3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6737318/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6737318/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31543683$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Huang, Xiao-Bing</creatorcontrib><creatorcontrib>He, Yong-Gang</creatorcontrib><creatorcontrib>Zheng, Lu</creatorcontrib><creatorcontrib>Feng, Huan</creatorcontrib><creatorcontrib>Li, Yu-Ming</creatorcontrib><creatorcontrib>Li, Hong-Yan</creatorcontrib><creatorcontrib>Yang, Feng-Xia</creatorcontrib><creatorcontrib>Li, Jing</creatorcontrib><title>Identification of hepatitis B virus and liver cancer bridge molecules based on functional module network</title><title>World journal of gastroenterology : WJG</title><addtitle>World J Gastroenterol</addtitle><description>The potential role of chronic inflammation in the development of cancer has been widely recognized. However, there has been little research fully and thoroughly exploring the molecular link between hepatitis B virus (HBV) and hepatocellular carcinoma (HCC).
To elucidate the molecular links between HBV and HCC through analyzing the molecular processes of HBV-HCC using a multidimensional approach.
First, maladjusted genes shared between HBV and HCC were identified by disease-related differentially expressed genes. Second, the protein-protein interaction network based on dysfunctional genes identified a series of dysfunctional modules and significant crosstalk between modules based on the hypergeometric test. In addition, key regulators were detected by pivot analysis. Finally, targeted drugs that have regulatory effects on diseases were predicted by modular methods and drug target information.
The study found that 67 genes continued to increase in the HBV-HCC process. Moreover, 366 overlapping genes in the module network participated in multiple functional blocks. It could be presumed that these genes and their interactions play an important role in the relationship between inflammation and cancer. Correspondingly, significant crosstalk constructed a module level bridge for HBV-HCC molecular processes. On the other hand, a series of non-coding RNAs and transcription factors that have potential pivot regulatory effects on HBV and HCC were identified. Among them, some of the regulators also had persistent disorders in the process of HBV-HCC including microRNA-192, microRNA-215, and microRNA-874, and early growth response 2, FOS, and Kruppel-like factor 4. Therefore, the study concluded that these pivots are the key bridge molecules outside the module. Last but not least, a variety of drugs that may have some potential pharmacological or toxic side effects on HBV-induced HCC were predicted, but their mechanisms still need to be further explored.
The results suggest that the persistent inflammatory environment of HBV can be utilized as an important risk factor to induce the occurrence of HCC, which is supported by molecular evidence.</description><subject>Basic Study</subject><subject>Carcinoma, Hepatocellular - drug therapy</subject><subject>Carcinoma, Hepatocellular - epidemiology</subject><subject>Carcinoma, Hepatocellular - etiology</subject><subject>Datasets as Topic</subject><subject>Gene Expression Profiling</subject><subject>Gene Expression Regulation, Neoplastic - drug effects</subject><subject>Gene Expression Regulation, Neoplastic - immunology</subject><subject>Gene Regulatory Networks - drug effects</subject><subject>Gene Regulatory Networks - immunology</subject><subject>Hepatitis B virus - immunology</subject><subject>Hepatitis B, Chronic - immunology</subject><subject>Hepatitis B, Chronic - pathology</subject><subject>Hepatitis B, Chronic - virology</subject><subject>Host-Pathogen Interactions - genetics</subject><subject>Host-Pathogen Interactions - immunology</subject><subject>Humans</subject><subject>Immunoglobulin G - pharmacology</subject><subject>Immunoglobulin G - therapeutic use</subject><subject>Liver Neoplasms - drug therapy</subject><subject>Liver Neoplasms - epidemiology</subject><subject>Liver Neoplasms - etiology</subject><subject>Melphalan - pharmacology</subject><subject>Melphalan - therapeutic use</subject><subject>MicroRNAs - antagonists & inhibitors</subject><subject>MicroRNAs - metabolism</subject><subject>Protein Interaction Mapping</subject><subject>Protein Interaction Maps - drug effects</subject><subject>Protein Interaction Maps - genetics</subject><subject>Protein Interaction Maps - immunology</subject><subject>Risk Factors</subject><subject>Transcription Factors - antagonists & inhibitors</subject><subject>Transcription Factors - metabolism</subject><issn>1007-9327</issn><issn>2219-2840</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNpVkF1LwzAUhoMobk7vvZL8gdYkJ22TG0HFj8HAG70OaZpumV07krbDf2_GdOjVOfDyvIfzIHRNSQoFF7e79TIdWZY6gJRLRk_QlDEqEyY4OUVTSkiRSGDFBF2EsCaEAWTsHE2AZhxyAVO0mle27V3tjO5d1-Kuxiu7jXvvAn7Ao_NDwLqtcONG67HRrYmj9K5aWrzpGmuGxgZc6mArHPl6aM2-SDcxrWKGW9vvOv95ic5q3QR79TNn6OP56f3xNVm8vcwf7xeJAZn3iZCZ1ZkQrCCWQE0kE5lljJcms5wUEozUJc-5iTHLqKDM5iB0KYUWvKg0zNDdoXc7lBtbmfid143aerfR_kt12qn_SetWatmNKi-gACpiATkUGN-F4G19ZClRe-sqWlfRuorW1d56RG7-3jwCv5rhGzsvgZ0</recordid><startdate>20190907</startdate><enddate>20190907</enddate><creator>Huang, Xiao-Bing</creator><creator>He, Yong-Gang</creator><creator>Zheng, Lu</creator><creator>Feng, Huan</creator><creator>Li, Yu-Ming</creator><creator>Li, Hong-Yan</creator><creator>Yang, Feng-Xia</creator><creator>Li, Jing</creator><general>Baishideng Publishing Group Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>5PM</scope></search><sort><creationdate>20190907</creationdate><title>Identification of hepatitis B virus and liver cancer bridge molecules based on functional module network</title><author>Huang, Xiao-Bing ; He, Yong-Gang ; Zheng, Lu ; Feng, Huan ; Li, Yu-Ming ; Li, Hong-Yan ; Yang, Feng-Xia ; Li, Jing</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c396t-895ea588270e03f09285e224bc5e40793c9ab464c0e0251812e638ab98a847da3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Basic Study</topic><topic>Carcinoma, Hepatocellular - drug therapy</topic><topic>Carcinoma, Hepatocellular - epidemiology</topic><topic>Carcinoma, Hepatocellular - etiology</topic><topic>Datasets as Topic</topic><topic>Gene Expression Profiling</topic><topic>Gene Expression Regulation, Neoplastic - drug effects</topic><topic>Gene Expression Regulation, Neoplastic - immunology</topic><topic>Gene Regulatory Networks - drug effects</topic><topic>Gene Regulatory Networks - immunology</topic><topic>Hepatitis B virus - immunology</topic><topic>Hepatitis B, Chronic - immunology</topic><topic>Hepatitis B, Chronic - pathology</topic><topic>Hepatitis B, Chronic - virology</topic><topic>Host-Pathogen Interactions - genetics</topic><topic>Host-Pathogen Interactions - immunology</topic><topic>Humans</topic><topic>Immunoglobulin G - pharmacology</topic><topic>Immunoglobulin G - therapeutic use</topic><topic>Liver Neoplasms - drug therapy</topic><topic>Liver Neoplasms - epidemiology</topic><topic>Liver Neoplasms - etiology</topic><topic>Melphalan - pharmacology</topic><topic>Melphalan - therapeutic use</topic><topic>MicroRNAs - antagonists & inhibitors</topic><topic>MicroRNAs - metabolism</topic><topic>Protein Interaction Mapping</topic><topic>Protein Interaction Maps - drug effects</topic><topic>Protein Interaction Maps - genetics</topic><topic>Protein Interaction Maps - immunology</topic><topic>Risk Factors</topic><topic>Transcription Factors - antagonists & inhibitors</topic><topic>Transcription Factors - metabolism</topic><toplevel>online_resources</toplevel><creatorcontrib>Huang, Xiao-Bing</creatorcontrib><creatorcontrib>He, Yong-Gang</creatorcontrib><creatorcontrib>Zheng, Lu</creatorcontrib><creatorcontrib>Feng, Huan</creatorcontrib><creatorcontrib>Li, Yu-Ming</creatorcontrib><creatorcontrib>Li, Hong-Yan</creatorcontrib><creatorcontrib>Yang, Feng-Xia</creatorcontrib><creatorcontrib>Li, Jing</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>World journal of gastroenterology : WJG</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Huang, Xiao-Bing</au><au>He, Yong-Gang</au><au>Zheng, Lu</au><au>Feng, Huan</au><au>Li, Yu-Ming</au><au>Li, Hong-Yan</au><au>Yang, Feng-Xia</au><au>Li, Jing</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification of hepatitis B virus and liver cancer bridge molecules based on functional module network</atitle><jtitle>World journal of gastroenterology : WJG</jtitle><addtitle>World J Gastroenterol</addtitle><date>2019-09-07</date><risdate>2019</risdate><volume>25</volume><issue>33</issue><spage>4921</spage><epage>4932</epage><pages>4921-4932</pages><issn>1007-9327</issn><eissn>2219-2840</eissn><abstract>The potential role of chronic inflammation in the development of cancer has been widely recognized. However, there has been little research fully and thoroughly exploring the molecular link between hepatitis B virus (HBV) and hepatocellular carcinoma (HCC).
To elucidate the molecular links between HBV and HCC through analyzing the molecular processes of HBV-HCC using a multidimensional approach.
First, maladjusted genes shared between HBV and HCC were identified by disease-related differentially expressed genes. Second, the protein-protein interaction network based on dysfunctional genes identified a series of dysfunctional modules and significant crosstalk between modules based on the hypergeometric test. In addition, key regulators were detected by pivot analysis. Finally, targeted drugs that have regulatory effects on diseases were predicted by modular methods and drug target information.
The study found that 67 genes continued to increase in the HBV-HCC process. Moreover, 366 overlapping genes in the module network participated in multiple functional blocks. It could be presumed that these genes and their interactions play an important role in the relationship between inflammation and cancer. Correspondingly, significant crosstalk constructed a module level bridge for HBV-HCC molecular processes. On the other hand, a series of non-coding RNAs and transcription factors that have potential pivot regulatory effects on HBV and HCC were identified. Among them, some of the regulators also had persistent disorders in the process of HBV-HCC including microRNA-192, microRNA-215, and microRNA-874, and early growth response 2, FOS, and Kruppel-like factor 4. Therefore, the study concluded that these pivots are the key bridge molecules outside the module. Last but not least, a variety of drugs that may have some potential pharmacological or toxic side effects on HBV-induced HCC were predicted, but their mechanisms still need to be further explored.
The results suggest that the persistent inflammatory environment of HBV can be utilized as an important risk factor to induce the occurrence of HCC, which is supported by molecular evidence.</abstract><cop>United States</cop><pub>Baishideng Publishing Group Inc</pub><pmid>31543683</pmid><doi>10.3748/wjg.v25.i33.4921</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Basic Study Carcinoma, Hepatocellular - drug therapy Carcinoma, Hepatocellular - epidemiology Carcinoma, Hepatocellular - etiology Datasets as Topic Gene Expression Profiling Gene Expression Regulation, Neoplastic - drug effects Gene Expression Regulation, Neoplastic - immunology Gene Regulatory Networks - drug effects Gene Regulatory Networks - immunology Hepatitis B virus - immunology Hepatitis B, Chronic - immunology Hepatitis B, Chronic - pathology Hepatitis B, Chronic - virology Host-Pathogen Interactions - genetics Host-Pathogen Interactions - immunology Humans Immunoglobulin G - pharmacology Immunoglobulin G - therapeutic use Liver Neoplasms - drug therapy Liver Neoplasms - epidemiology Liver Neoplasms - etiology Melphalan - pharmacology Melphalan - therapeutic use MicroRNAs - antagonists & inhibitors MicroRNAs - metabolism Protein Interaction Mapping Protein Interaction Maps - drug effects Protein Interaction Maps - genetics Protein Interaction Maps - immunology Risk Factors Transcription Factors - antagonists & inhibitors Transcription Factors - metabolism |
title | Identification of hepatitis B virus and liver cancer bridge molecules based on functional module network |
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