Network modeling links breast cancer susceptibility and centrosome dysfunction.

@article{citeulike:1805629, abstract = {Many cancer-associated genes remain to be identified to clarify the underlying molecular mechanisms of cancer susceptibility and progression. Better understanding is also required of how mutations in cancer genes affect their products in the context of complex cellular networks. Here we have used a network modeling strategy to identify genes potentially associated with higher risk of breast cancer. Starting with four known genes encoding tumor suppressors of breast cancer, we combined gene expression profiling with functional genomic and proteomic (or 'omic') data from various species to generate a network containing 118 genes linked by 866 potential functional associations. This network shows higher connectivity than expected by chance, suggesting that its components function in biologically related pathways. One of the components of the network is HMMR, encoding a centrosome subunit, for which we demonstrate previously unknown functional associations with the breast cancer-associated gene BRCA1. Two case-control studies of incident breast cancer indicate that the HMMR locus is associated with higher risk of breast cancer in humans. Our network modeling strategy should be useful for the discovery of additional cancer-associated genes.}, address = {[1] Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute and Department of Genetics, Harvard Medical School, 44 Binney St., Boston, Massachusetts 02115, USA. [2] Department of Cancer Biology, Dana-Farber Cancer Institute and Department of Genetics, Harvard Medical School, 44 Binney St., Boston, Massachusetts 02115, USA. [3] Present addresses: Bioinformatics and Biostatistics Unit, Translational Research Laboratory, Catalan Institute of Oncology, IDIBELL, Gran V\'{i}a km 2.7, L'Hospitalet, Barcelona 08907, Spain (M.A.P.); Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Datun Rd., Beijing 100101, China (J.-D.J.H.); Department of Genome Sciences, University of Washington, 1705 NE Pacific St., Seattle, Washington 98195, USA (L.M.S.); Human Biology Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. North, Seattle, Washington 98109, USA (M.T.); Harvard School of Public Health, Boston, Massachusetts 02115, USA (N.A.-G.); Department of Biomedical Informatics, Ohio State University Medical Center, 460 West 12th Ave., Columbus, Ohio 43210, USA (J.D.P.). [4] These authors contributed equally to this work.}, author = {Pujana, Miguel Angel A. and Han, Jing-Dong J D. and Starita, Lea M M. and Stevens, Kristen N N. and Tewari, Muneesh and Ahn, Jin Sook S. and Rennert, Gad and Moreno, V\'{i}ctor and Kirchhoff, Tomas and Gold, Bert and Assmann, Volker and Elshamy, Wael M M. and Rual, Jean-Fran\c{c}ois F. and Levine, Douglas and Rozek, Laura S S. and Gelman, Rebecca S S. and Gunsalus, Kristin C C. and Greenberg, Roger A A. and Sobhian, Bijan and Bertin, Nicolas and Venkatesan, Kavitha and Ayivi-Guedehoussou, Nono and Sol\'{e}, Xavier and Hern\'{a}ndez, Pilar and L\'{a}zaro, Conxi and Nathanson, Katherine L L. and Weber, Barbara L L. and Cusick, Michael E E. and Hill, David E E. and Offit, Kenneth and Livingston, David M M. and Gruber, Stephen B B. and Parvin, Jeffrey D D. and Vidal, Marc}, citeulike-article-id = {1805629}, doi = {10.1038/ng.2007.2}, issn = {1061-4036}, journal = {Nat Genet}, keywords = {brca, breast\_cancer, network}, month = {October}, posted-at = {2008-01-23 15:35:57}, priority = {0}, title = {Network modeling links breast cancer susceptibility and centrosome dysfunction.}, url = {http://dx.doi.org/10.1038/ng.2007.2}, year = {2007} }

TY - JOUR ID - citeulike:1805629 L3 - citeulike-article-id:1805629 N2 - Many cancer-associated genes remain to be identified to clarify the underlying molecular mechanisms of cancer susceptibility and progression. Better understanding is also required of how mutations in cancer genes affect their products in the context of complex cellular networks. Here we have used a network modeling strategy to identify genes potentially associated with higher risk of breast cancer. Starting with four known genes encoding tumor suppressors of breast cancer, we combined gene expression profiling with functional genomic and proteomic (or 'omic') data from various species to generate a network containing 118 genes linked by 866 potential functional associations. This network shows higher connectivity than expected by chance, suggesting that its components function in biologically related pathways. One of the components of the network is HMMR, encoding a centrosome subunit, for which we demonstrate previously unknown functional associations with the breast cancer-associated gene BRCA1. Two case-control studies of incident breast cancer indicate that the HMMR locus is associated with higher risk of breast cancer in humans. Our network modeling strategy should be useful for the discovery of additional cancer-associated genes. JF - Nat Genet SN - 1061-4036 AD - [1] Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute and Department of Genetics, Harvard Medical School, 44 Binney St., Boston, Massachusetts 02115, USA. [2] Department of Cancer Biology, Dana-Farber Cancer Institute and Department of Genetics, Harvard Medical School, 44 Binney St., Boston, Massachusetts 02115, USA. [3] Present addresses: Bioinformatics and Biostatistics Unit, Translational Research Laboratory, Catalan Institute of Oncology, IDIBELL, Gran Vía km 2.7, L'Hospitalet, Barcelona 08907, Spain (M.A.P.); Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Datun Rd., Beijing 100101, China (J.-D.J.H.); Department of Genome Sciences, University of Washington, 1705 NE Pacific St., Seattle, Washington 98195, USA (L.M.S.); Human Biology Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. North, Seattle, Washington 98109, USA (M.T.); Harvard School of Public Health, Boston, Massachusetts 02115, USA (N.A.-G.); Department of Biomedical Informatics, Ohio State University Medical Center, 460 West 12th Ave., Columbus, Ohio 43210, USA (J.D.P.). [4] These authors contributed equally to this work. TI - Network modeling links breast cancer susceptibility and centrosome dysfunction. KW - brca KW - breast_cancer KW - network AU - Pujana, Miguel Angel AU - Han, Jing-Dong J AU - Starita, Lea M AU - Stevens, Kristen N AU - Tewari, Muneesh AU - Ahn, Jin Sook AU - Rennert, Gad AU - Moreno, Víctor AU - Kirchhoff, Tomas AU - Gold, Bert AU - Assmann, Volker AU - Elshamy, Wael M AU - Rual, Jean-François AU - Levine, Douglas AU - Rozek, Laura S AU - Gelman, Rebecca S AU - Gunsalus, Kristin C AU - Greenberg, Roger A AU - Sobhian, Bijan AU - Bertin, Nicolas AU - Venkatesan, Kavitha AU - Ayivi-Guedehoussou, Nono AU - Solé, Xavier AU - Hernández, Pilar AU - Lázaro, Conxi AU - Nathanson, Katherine L AU - Weber, Barbara L AU - Cusick, Michael E AU - Hill, David E AU - Offit, Kenneth AU - Livingston, David M AU - Gruber, Stephen B AU - Parvin, Jeffrey D AU - Vidal, Marc PY - 2007/10/07/ UR - http://dx.doi.org/10.1038/ng.2007.2 ER -