Journal Article

Network modeling links breast cancer susceptibility and centrosome dysfunction

Ayivi-Guedehoussou, Nono, Lázaro, Conxi, Weber, Barbara L, Kirchhoff, Tomas, Offit, Kenneth, Livingston, David M, Starita, Lea M, Assmann, Volker, Bertin, Nicolas, Stevens, Kristen N, ElShamy, Wael M, Levine, Douglas, Parvin, Jeffrey D, Moreno, Víctor, Greenberg, Roger A, Nathanson, Katherine L, Rennert, Gad, Cusick, Michael E, Ahn, Jin Sook, Pujana, Miguel Angel, Han, Jing-Dong J, Gold, Bert, Hernández, Pilar, Vidal, Marc, Solé, Xavier, Tewari, Muneesh, Rual, Jean-François, Hill, David E, Gruber, Stephen B, Rozek, Laura S, Sobhian, Bijan, Venkatesan, Kavitha, Gelman, Rebecca S, Gunsalus, Kristin C

2007

Overview

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.

• Publisher: Nature Publishing Group US,Nature Publishing Group
• Subject: Agriculture / Animal Genetics and Genomics / Aurora Kinases / Biological and medical sciences / Biomarkers, Tumor - genetics / Biomarkers, Tumor - metabolism / Biomedical and Life Sciences / Biomedicine / BRCA1 Protein - antagonists & inhibitors / BRCA1 Protein - genetics / BRCA1 Protein - metabolism / BRCA2 Protein - antagonists & inhibitors / BRCA2 Protein - genetics / BRCA2 Protein - metabolism / Breast cancer / Breast Neoplasms - genetics / Cancer Research / Case studies / Case-Control Studies / Cellular biology / Centrosome - physiology / Complications and side effects / Computational Biology / Extracellular Matrix Proteins - antagonists & inhibitors / Extracellular Matrix Proteins - genetics / Extracellular Matrix Proteins - metabolism / Female / Fundamental and applied biological sciences. Psychology / Gene expression / Gene Expression Profiling / Gene Function / Gene mutations / Gene Regulatory Networks / Genes / Genetic aspects / Genetic Predisposition to Disease / Genetic research / Genetics of eukaryotes. Biological and molecular evolution / Genomics / Gynecology. Andrology. Obstetrics / Human Genetics / Humans / Hyaluronan Receptors - genetics / Hyaluronan Receptors - metabolism / Identification and classification / Mammary gland diseases / Medical sciences / Mutation / Neural Networks, Computer / Oligonucleotide Array Sequence Analysis / Polymerase Chain Reaction / Protein Interaction Mapping / Protein Serine-Threonine Kinases - genetics / Protein Serine-Threonine Kinases - metabolism / Risk factors / RNA, Small Interfering - pharmacology / Tumors / Ubiquitin - metabolism