Network modeling links breast cancer susceptibility and centrosome dysfunction Journal Article


Authors: Pujana, M. A.; Han, J. D. J.; Starita, L. M.; Stevens, K. N.; Tewari, M.; Ahn, J. S.; Rennert, G.; Moreno, V.; Kirchhoff, T.; Gold, B.; Assmann, V.; Elshamy, W. M.; Rual, J. F.; Levine, D.; Rozek, L. S.; Gelman, R. S.; Gunsalus, K. C.; Greenberg, R. A.; Sobhian, B.; Bertin, N.; Venkatesan, K.; Ayivi-Guedehoussou, N.; Solé, X.; Hernández, P.; Lazaro, C.; Nathanson, K. L.; Weber, B. L.; Cusick, M. E.; Hill, D. E.; Offit, K.; Livingston, D. M.; Gruber, S. B.; Parvin, J. D.; Vidal, M.
Article Title: Network modeling links breast cancer susceptibility and centrosome dysfunction
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. © 2007 Nature Publishing Group.
Keywords: controlled study; human cell; case-control studies; cancer risk; ubiquitin; polymerase chain reaction; gene; cancer susceptibility; genetic predisposition to disease; breast cancer; gene expression profiling; computational biology; tumor markers, biological; rna, small interfering; gene locus; breast neoplasms; brca1 protein; brca2 protein; proteomics; oncogene; oligonucleotide array sequence analysis; protein-serine-threonine kinases; cell damage; genomics; protein interaction mapping; neural networks (computer); centrosome; gene regulatory networks; antigens, cd44; extracellular matrix proteins
Journal Title: Nature Genetics
Volume: 39
Issue: 11
ISSN: 1061-4036
Publisher: Nature Publishing Group  
Date Published: 2007-11-01
Start Page: 1338
End Page: 1349
Language: English
DOI: 10.1038/ng.2007.2
PUBMED: 17922014
PROVIDER: scopus
DOI/URL:
Notes: --- - "Cited By (since 1996): 139" - "Export Date: 17 November 2011" - "CODEN: NGENE" - "Source: Scopus"
Altmetric
Citation Impact
BMJ Impact Analytics
MSK Authors
  1. Kenneth Offit
    789 Offit
  2. Douglas A Levine
    380 Levine