%0 Journal Article %1 Yuan2013Comparative %A Yuan, Weilan %A Huang, Tao %A Yu, Jian %A Zeng, Lingyao %A Lian, Baofeng %A He, Qinwen %A Li, Yixue %A Zhang, Xiaoyan %A Zhou, Fengli %A Xie, Lu %D 2013 %J Biochimica et biophysica acta %K comparative-analysis protein-protein-interactions %R 10.1016/j.bbapap.2013.06.002 %T Comparative analysis of viral protein interaction networks in Hepatitis B Virus and Hepatitis C Virus infected HCC. %U http://dx.doi.org/10.1016/j.bbapap.2013.06.002 %X Previously, the different mechanisms of HBV infection and HCV infection were studied experimentally. Multiple studies also compared the differential network between HBV induced HCC and HCV induced HCC based on gene expression data. However network level comparison combining viral-human interaction network and dysfunctional protein interaction network for HBV and HCV-HCC has rarely been done before. In this work we did some pioneer job in construction of HBV/HCV viral dysfunctional network in HCC, in hope of investigating viral infection impact on the change of genome expression and eventually, the development of HCC. We found that HBx, the main HBV viral protein, directly acted on the gene groups of cell cycle, which could perfectly explain the dominant cell proliferation effect shown in the dysfunctional network of HBV-HCC. On the other hand, multiple important HCV viral proteins including CORE, NS3 and NS5A were found to target very important cancer related proteins such as TP53 and SMAD3, but no direct targeting to major immune response or inflammation related proteins. Therefore the dominant activation of immune response and inflammation related pathways shown in dysfunctional network of HCV-HCC might not be a direct effect of HCV infection. They might have been an indirect demonstration of activated cancer promoting pathways. Similar approaches may as well be applied to other important virus infection caused human diseases to help elucidate the mechanisms of virus-host interaction, and even help with investigations on anti-virus based therapies. This article is part of a Special Issue entitled: Computational Proteomics, Systems Biology & Clinical Implications. Copyright \copyright 2013. Published by Elsevier B.V.

@article{Yuan2013Comparative, abstract = { Previously, the different mechanisms of {HBV} infection and {HCV} infection were studied experimentally. Multiple studies also compared the differential network between {HBV} induced {HCC} and {HCV} induced {HCC} based on gene expression data. However network level comparison combining viral-human interaction network and dysfunctional protein interaction network for {HBV} and {HCV}-{HCC} has rarely been done before. In this work we did some pioneer job in construction of {HBV}/{HCV} viral dysfunctional network in {HCC}, in hope of investigating viral infection impact on the change of genome expression and eventually, the development of {HCC}. We found that {HBx}, the main {HBV} viral protein, directly acted on the gene groups of cell cycle, which could perfectly explain the dominant cell proliferation effect shown in the dysfunctional network of {HBV}-{HCC}. On the other hand, multiple important {HCV} viral proteins including {CORE}, {NS3} and {NS5A} were found to target very important cancer related proteins such as {TP53} and {SMAD3}, but no direct targeting to major immune response or inflammation related proteins. Therefore the dominant activation of immune response and inflammation related pathways shown in dysfunctional network of {HCV}-{HCC} might not be a direct effect of {HCV} infection. They might have been an indirect demonstration of activated cancer promoting pathways. Similar approaches may as well be applied to other important virus infection caused human diseases to help elucidate the mechanisms of virus-host interaction, and even help with investigations on anti-virus based therapies. This article is part of a Special Issue entitled: Computational Proteomics, Systems Biology \& Clinical Implications. Copyright {\copyright} 2013. Published by Elsevier {B.V}. }, added-at = {2018-12-02T16:09:07.000+0100}, author = {Yuan, Weilan and Huang, Tao and Yu, Jian and Zeng, Lingyao and Lian, Baofeng and He, Qinwen and Li, Yixue and Zhang, Xiaoyan and Zhou, Fengli and Xie, Lu}, biburl = {https://www.bibsonomy.org/bibtex/2d9098358e15c234f3b6bdf4c08b522f5/karthikraman}, citeulike-article-id = {12475428}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.bbapap.2013.06.002}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/23774196}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=23774196}, day = 14, doi = {10.1016/j.bbapap.2013.06.002}, interhash = {12596ef52b075c67e1a161b8ccaaee0a}, intrahash = {d9098358e15c234f3b6bdf4c08b522f5}, issn = {0006-3002}, journal = {Biochimica et biophysica acta}, keywords = {comparative-analysis protein-protein-interactions}, month = jun, pmid = {23774196}, posted-at = {2013-09-02 09:49:02}, priority = {2}, timestamp = {2018-12-02T16:09:07.000+0100}, title = {Comparative analysis of viral protein interaction networks in Hepatitis B Virus and Hepatitis C Virus infected {HCC}.}, url = {http://dx.doi.org/10.1016/j.bbapap.2013.06.002}, year = 2013 }