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  • 1
    Publication Date: 2012-07-20
    Description: Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations, and large numbers of somatic genomic alterations, associated with a predisposition to cancer. However, it remains difficult to distinguish background, or 'passenger', cancer mutations from causal, or 'driver', mutations in these data sets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. Here we test the hypothesis that genomic variations and tumour viruses may cause cancer through related mechanisms, by systematically examining host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways, such as Notch signalling and apoptosis, that go awry in cancer. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on a par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches increase the specificity of cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate the prioritization of cancer-causing driver genes to advance the understanding of the genetic basis of human cancer.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3408847/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3408847/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Rozenblatt-Rosen, Orit -- Deo, Rahul C -- Padi, Megha -- Adelmant, Guillaume -- Calderwood, Michael A -- Rolland, Thomas -- Grace, Miranda -- Dricot, Amelie -- Askenazi, Manor -- Tavares, Maria -- Pevzner, Samuel J -- Abderazzaq, Fieda -- Byrdsong, Danielle -- Carvunis, Anne-Ruxandra -- Chen, Alyce A -- Cheng, Jingwei -- Correll, Mick -- Duarte, Melissa -- Fan, Changyu -- Feltkamp, Mariet C -- Ficarro, Scott B -- Franchi, Rachel -- Garg, Brijesh K -- Gulbahce, Natali -- Hao, Tong -- Holthaus, Amy M -- James, Robert -- Korkhin, Anna -- Litovchick, Larisa -- Mar, Jessica C -- Pak, Theodore R -- Rabello, Sabrina -- Rubio, Renee -- Shen, Yun -- Singh, Saurav -- Spangle, Jennifer M -- Tasan, Murat -- Wanamaker, Shelly -- Webber, James T -- Roecklein-Canfield, Jennifer -- Johannsen, Eric -- Barabasi, Albert-Laszlo -- Beroukhim, Rameen -- Kieff, Elliott -- Cusick, Michael E -- Hill, David E -- Munger, Karl -- Marto, Jarrod A -- Quackenbush, John -- Roth, Frederick P -- DeCaprio, James A -- Vidal, Marc -- F32 GM095284/GM/NIGMS NIH HHS/ -- F32GM095284/GM/NIGMS NIH HHS/ -- K08 CA122833/CA/NCI NIH HHS/ -- K08 HL098361/HL/NHLBI NIH HHS/ -- K08HL098361/HL/NHLBI NIH HHS/ -- K25 HG006031/HG/NHGRI NIH HHS/ -- K25HG006031/HG/NHGRI NIH HHS/ -- P01 CA050661/CA/NCI NIH HHS/ -- P01CA050661/CA/NCI NIH HHS/ -- P50 HG004233/HG/NHGRI NIH HHS/ -- P50HG004233/HG/NHGRI NIH HHS/ -- R01 CA047006/CA/NCI NIH HHS/ -- R01 CA063113/CA/NCI NIH HHS/ -- R01 CA066980/CA/NCI NIH HHS/ -- R01 CA081135/CA/NCI NIH HHS/ -- R01 CA085180/CA/NCI NIH HHS/ -- R01 CA093804/CA/NCI NIH HHS/ -- R01 CA131354/CA/NCI NIH HHS/ -- R01 HG001715/HG/NHGRI NIH HHS/ -- R01CA047006/CA/NCI NIH HHS/ -- R01CA063113/CA/NCI NIH HHS/ -- R01CA066980/CA/NCI NIH HHS/ -- R01CA081135/CA/NCI NIH HHS/ -- R01CA085180/CA/NCI NIH HHS/ -- R01CA093804/CA/NCI NIH HHS/ -- R01CA131354/CA/NCI NIH HHS/ -- R01HG001715/HG/NHGRI NIH HHS/ -- T32 HL007208/HL/NHLBI NIH HHS/ -- T32HL007208/HL/NHLBI NIH HHS/ -- U01 CA141583/CA/NCI NIH HHS/ -- U01CA141583/CA/NCI NIH HHS/ -- England -- Nature. 2012 Jul 26;487(7408):491-5. doi: 10.1038/nature11288.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Genomic Analysis of Network Perturbations Center of Excellence in Genomic Science, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/22810586" target="_blank"〉PubMed〈/a〉
    Keywords: Adenoviridae/genetics/metabolism/pathogenicity ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Genes, Neoplasm/*genetics ; Genome, Human/*genetics ; Herpesvirus 4, Human/genetics/metabolism/pathogenicity ; *Host-Pathogen Interactions/genetics ; Humans ; Neoplasms/*genetics/*metabolism/pathology ; Oncogenic Viruses/genetics/metabolism/*pathogenicity ; Open Reading Frames/genetics ; Papillomaviridae/genetics/metabolism/pathogenicity ; Polyomavirus/genetics/metabolism/pathogenicity ; Receptors, Notch/metabolism ; Signal Transduction ; Two-Hybrid System Techniques ; Viral Proteins/genetics/*metabolism
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
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  • 2
    Publication Date: 2008-08-23
    Description: Current yeast interactome network maps contain several hundred molecular complexes with limited and somewhat controversial representation of direct binary interactions. We carried out a comparative quality assessment of current yeast interactome data sets, demonstrating that high-throughput yeast two-hybrid (Y2H) screening provides high-quality binary interaction information. Because a large fraction of the yeast binary interactome remains to be mapped, we developed an empirically controlled mapping framework to produce a "second-generation" high-quality, high-throughput Y2H data set covering approximately 20% of all yeast binary interactions. Both Y2H and affinity purification followed by mass spectrometry (AP/MS) data are of equally high quality but of a fundamentally different and complementary nature, resulting in networks with different topological and biological properties. Compared to co-complex interactome models, this binary map is enriched for transient signaling interactions and intercomplex connections with a highly significant clustering between essential proteins. Rather than correlating with essentiality, protein connectivity correlates with genetic pleiotropy.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2746753/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2746753/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Yu, Haiyuan -- Braun, Pascal -- Yildirim, Muhammed A -- Lemmens, Irma -- Venkatesan, Kavitha -- Sahalie, Julie -- Hirozane-Kishikawa, Tomoko -- Gebreab, Fana -- Li, Na -- Simonis, Nicolas -- Hao, Tong -- Rual, Jean-Francois -- Dricot, Amelie -- Vazquez, Alexei -- Murray, Ryan R -- Simon, Christophe -- Tardivo, Leah -- Tam, Stanley -- Svrzikapa, Nenad -- Fan, Changyu -- de Smet, Anne-Sophie -- Motyl, Adriana -- Hudson, Michael E -- Park, Juyong -- Xin, Xiaofeng -- Cusick, Michael E -- Moore, Troy -- Boone, Charlie -- Snyder, Michael -- Roth, Frederick P -- Barabasi, Albert-Laszlo -- Tavernier, Jan -- Hill, David E -- Vidal, Marc -- HG003224/HG/NHGRI NIH HHS/ -- R01 HG001715/HG/NHGRI NIH HHS/ -- R01 HG001715-06/HG/NHGRI NIH HHS/ -- R01 HG003224/HG/NHGRI NIH HHS/ -- R01 HG003224-04/HG/NHGRI NIH HHS/ -- R01-HG001715/HG/NHGRI NIH HHS/ -- U01 AI070499-01/AI/NIAID NIH HHS/ -- U01-A1070499-01/PHS HHS/ -- U56 CA113004/CA/NCI NIH HHS/ -- U56 CA113004-03/CA/NCI NIH HHS/ -- U56-CA113004/CA/NCI NIH HHS/ -- New York, N.Y. -- Science. 2008 Oct 3;322(5898):104-10. doi: 10.1126/science.1158684. Epub 2008 Aug 21.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA 02115, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/18719252" target="_blank"〉PubMed〈/a〉
    Keywords: Computational Biology ; Gene Regulatory Networks ; Mass Spectrometry ; Metabolic Networks and Pathways ; Protein Array Analysis ; Protein Binding ; *Protein Interaction Mapping/methods/standards ; Proteome/metabolism ; Proteomics ; Saccharomyces cerevisiae/genetics/*metabolism ; Saccharomyces cerevisiae Proteins/genetics/isolation & purification/*metabolism ; Signal Transduction ; Transcription Factors/metabolism ; Two-Hybrid System Techniques
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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