Network modeling links breast cancer susceptibility and centrosome dysfunction (original) (raw)

References

1. Futreal, P.A. et al. A census of human cancer genes. Nat. Rev. Cancer 4, 177–183 (2004).
   Article CAS Google Scholar
2. Kitano, H. Cancer as a robust system: implications for anticancer therapy. Nat. Rev. Cancer 4, 227–235 (2004).
   Article CAS Google Scholar
3. Khalil, I.G. & Hill, C. Systems biology for cancer. Curr. Opin. Oncol. 17, 44–48 (2005).
   Article CAS Google Scholar
4. Thomas, R.K. et al. High-throughput oncogene mutation profiling in human cancer. Nat. Genet. 39, 347–351 (2007).
   Article CAS Google Scholar
5. Sjoblom, T. et al. The consensus coding sequences of human breast and colorectal cancers. Science 314, 268–274 (2006).
   Article Google Scholar
6. Greenman, C. et al. Patterns of somatic mutation in human cancer genomes. Nature 446, 153–158 (2007).
   Article CAS Google Scholar
7. Vidal, M. A biological atlas of functional maps. Cell 104, 333–339 (2001).
   Article CAS Google Scholar
8. Matthews, L.R. et al. Identification of potential interaction networks using sequence-based searches for conserved protein-protein interactions or 'interologs'. Genome Res. 11, 2120–2126 (2001).
   Article CAS Google Scholar
9. Futreal, P.A. et al. BRCA1 mutations in primary breast and ovarian carcinomas. Science 266, 120–122 (1994).
   Article CAS Google Scholar
10. Miki, Y. et al. A strong candidate for the breast and ovarian cancer susceptibility gene BRCA1. Science 266, 66–71 (1994).
    Article CAS Google Scholar
11. Wooster, R. et al. Identification of the breast cancer susceptibility gene BRCA2. Nature 378, 789–792 (1995).
    Article CAS Google Scholar
12. Renwick, A. et al. ATM mutations that cause ataxia-telangiectasia are breast cancer susceptibility alleles. Nat. Genet. 38, 873–875 (2006).
    Article CAS Google Scholar
13. Meijers-Heijboer, H. et al. Low-penetrance susceptibility to breast cancer due to CHEK2(*)1100delC in noncarriers of BRCA1 or BRCA2 mutations. Nat. Genet. 31, 55–59 (2002).
    Article CAS Google Scholar
14. Su, A.I. et al. Large-scale analysis of the human and mouse transcriptomes. Proc. Natl. Acad. Sci. USA 99, 4465–4470 (2002).
    Article CAS Google Scholar
15. Cunliffe, H.E. et al. The gene expression response of breast cancer to growth regulators: patterns and correlation with tumor expression profiles. Cancer Res. 63, 7158–7166 (2003).
    CAS PubMed Google Scholar
16. van't Veer, L.J. et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 415, 530–536 (2002).
    Article CAS Google Scholar
17. Gunsalus, K.C. et al. Predictive models of molecular machines involved in Caenorhabditis elegans early embryogenesis. Nature 436, 861–865 (2005).
    Article CAS Google Scholar
18. Maxwell, C.A. et al. RHAMM is a centrosomal protein that interacts with dynein and maintains spindle pole stability. Mol. Biol. Cell 14, 2262–2276 (2003).
    Article CAS Google Scholar
19. Entwistle, J., Hall, C.L. & Turley, E.A. HA receptors: regulators of signalling to the cytoskeleton. J. Cell. Biochem. 61, 569–577 (1996).
    Article CAS Google Scholar
20. Boulton, S.J. et al. BRCA1/BARD1 orthologs required for DNA repair in Caenorhabditis elegans. Curr. Biol. 14, 33–39 (2004).
    Article CAS Google Scholar
21. Li, S. et al. A map of the interactome network of the metazoan C. elegans. Science 303, 540–543 (2004).
    Article CAS Google Scholar
22. Bellanger, J.M. & Gonczy, P. TAC-1 and ZYG-9 form a complex that promotes microtubule assembly in C. elegans embryos. Curr. Biol. 13, 1488–1498 (2003).
    Article CAS Google Scholar
23. Le Bot, N., Tsai, M.C., Andrews, R.K. & Ahringer, J. TAC-1, a regulator of microtubule length in the C. elegans embryo. Curr. Biol. 13, 1499–1505 (2003).
    Article CAS Google Scholar
24. Srayko, M., Quintin, S., Schwager, A. & Hyman, A.A. Caenorhabditis elegans TAC-1 and ZYG-9 form a complex that is essential for long astral and spindle microtubules. Curr. Biol. 13, 1506–1511 (2003).
    Article CAS Google Scholar
25. Maxwell, C.A., Keats, J.J., Belch, A.R., Pilarski, L.M. & Reiman, T. Receptor for hyaluronan-mediated motility correlates with centrosome abnormalities in multiple myeloma and maintains mitotic integrity. Cancer Res. 65, 850–860 (2005).
    CAS PubMed Google Scholar
26. Hsu, L.C. & White, R.L. BRCA1 is associated with the centrosome during mitosis. Proc. Natl. Acad. Sci. USA 95, 12983–12988 (1998).
    Article CAS Google Scholar
27. Marmorstein, L.Y. et al. A human BRCA2 complex containing a structural DNA binding component influences cell cycle progression. Cell 104, 247–257 (2001).
    Article CAS Google Scholar
28. Bieche, I., Tozlu, S., Girault, I. & Lidereau, R. Identification of a three-gene expression signature of poor-prognosis breast carcinoma. Mol. Cancer 3, 37 (2004).
    Article Google Scholar
29. Freed, E. et al. Components of an SCF ubiquitin ligase localize to the centrosome and regulate the centrosome duplication cycle. Genes Dev. 13, 2242–2257 (1999).
    Article CAS Google Scholar
30. Hashizume, R. et al. The RING heterodimer BRCA1-BARD1 is a ubiquitin ligase inactivated by a breast cancer–derived mutation. J. Biol. Chem. 276, 14537–14540 (2001).
    Article CAS Google Scholar
31. Starita, L.M. et al. BRCA1-dependent ubiquitination of γ-tubulin regulates centrosome number. Mol. Cell. Biol. 24, 8457–8466 (2004).
    Article CAS Google Scholar
32. Ouchi, M. et al. BRCA1 phosphorylation by aurora-A in the regulation of G2 to M transition. J. Biol. Chem. 279, 19643–19648 (2004).
    Article CAS Google Scholar
33. Wang, X. et al. Overexpression of aurora kinase A in mouse mammary epithelium induces genetic instability preceding mammary tumor formation. Oncogene 25, 7148–7158 (2006).
    Article CAS Google Scholar
34. Claus, E.B., Risch, N.J. & Thompson, W.D. Using age of onset to distinguish between subforms of breast cancer. Ann. Hum. Genet. 54, 169–177 (1990).
    Article CAS Google Scholar
35. Mitchell, M.K., Gregersen, P.K., Johnson, S., Parsons, R. & Vlahov, D. The New York Cancer Project: rationale, organization, design, and baseline characteristics. J. Urban Health 81, 301–310 (2004).
    Article Google Scholar
36. Raff, J.W. Centrosomes and cancer: lessons from a TACC. Trends Cell Biol. 12, 222–225 (2002).
    Article CAS Google Scholar
37. Joukov, V. et al. The BRCA1/BARD1 heterodimer modulates ran-dependent mitotic spindle assembly. Cell 127, 539–552 (2006).
    Article CAS Google Scholar
38. Lingle, W.L. et al. Centrosome amplification drives chromosomal instability in breast tumor development. Proc. Natl. Acad. Sci. USA 99, 1978–1983 (2002).
    Article CAS Google Scholar
39. Pihan, G.A., Wallace, J., Zhou, Y. & Doxsey, S.J. Centrosome abnormalities and chromosome instability occur together in pre-invasive carcinomas. Cancer Res. 63, 1398–1404 (2003).
    CAS PubMed Google Scholar
40. Tutt, A. et al. Absence of Brca2 causes genome instability by chromosome breakage and loss associated with centrosome amplification. Curr. Biol. 9, 1107–1110 (1999).
    Article CAS Google Scholar
41. Xu, X. et al. Centrosome amplification and a defective G2-M cell cycle checkpoint induce genetic instability in BRCA1 exon 11 isoform–deficient cells. Mol. Cell 3, 389–395 (1999).
    Article CAS Google Scholar
42. Sotillo, R. et al. Mad2 overexpression promotes aneuploidy and tumorigenesis in mice. Cancer Cell 11, 9–23 (2007).
    Article CAS Google Scholar
43. Han, J.D. et al. Evidence for dynamically organized modularity in the yeast protein-protein interaction network. Nature 430, 88–93 (2004).
    Article CAS Google Scholar
44. Kim, S.K. et al. A gene expression map for Caenorhabditis elegans. Science 293, 2087–2092 (2001).
    Article CAS Google Scholar
45. Formstecher, E. et al. Protein interaction mapping: a Drosophila case study. Genome Res. 15, 376–384 (2005).
    Article CAS Google Scholar
46. Giot, L. et al. A protein interaction map of Drosophila melanogaster. Science 302, 1727–1736 (2003).
    Article CAS Google Scholar
47. Peri, S. et al. Human protein reference database as a discovery resource for proteomics. Nucleic Acids Res. 32, D497–D501 (2004).
    Article CAS Google Scholar
48. Walhout, A.J. & Vidal, M. High-throughput yeast two-hybrid assays for large-scale protein interaction mapping. Methods 24, 297–306 (2001).
    Article CAS Google Scholar
49. Barrett, J.C., Fry, B., Maller, J. & Daly, M.J. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21, 263–265 (2005).
    Article CAS Google Scholar
50. Solé, X., Guinó, E., Valls, J., Iniesta, R. & Moreno, V. SNPStats: a web tool for the analysis of association studies. Bioinformatics 22, 1928–1929 (2006).
    Article Google Scholar

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Acknowledgements

We thank members of our laboratories for discussion and comments on the manuscript; A. Merdes (Wellcome Trust Centre for Cell Biology) for anti-PCM1; B. Koch (Research Institute of Molecular Pathology) for anti-CSPG6 and anti-SMC1L1; K.-T. Jeang (National Institute of Allergy and Infectious Disease) for anti-MAD1L1 (Dap23); D.-Y. Jin (University Hong Kong) for anti-MAD1L1 (81d); E.A. Nigg (Max Planck Institute of Biochemistry) for anti-CEP2; D.R. Scoles (University California Los Angeles) for providing constructs; V. Joulov for sharing results before publication; C. McCowan, T. Clingingsmith and C. You for administrative assistance; and K. Salehi-Ashtiani, D. Szeto, R. Murray and C. Lin for characterizing the genomic structure of HMMR. L.M.S. was supported by a Department of Defense Breast Cancer Research Program fellowship and a grant from the National Cancer Institute (CA90281to J.D.P.). M.T. was supported by an award from the National Institutes of Health (NIH; K08-AG21613). K.C.G. received support from the US Army Medical Research Acquisition Activity (W23RYX-3275-N605) and NYSTAR (C040066). This work was supported by an NIH/National Cancer Institute (NCI) R33 grant (to M.V.), an NIH/NCI U01 grant (to S. Korsmeyer, S. Orkin, G. Gilliland and M.V.), an NIH/NCI ICBP grant (to J. Nevins and M.V.), an 'interactome mapping' grant from the NIH/National Human Genome Research Institute and the NIH/National Institute of General Medical Sciences (to F. Roth and M.V.), an NIH/NCI P30 grant (CA046592 to the University of Michigan), a Spanish Ministry of Education and Science grant (PR2006-0474 to V.M.) and awards from the Breast Cancer Research Foundation (BCRF13740) and the Niehaus, Southworth, Weissenbach Foundation (to K.O.) and the Koodish Foundation (to T.K.). We also acknowledge the role of the New York Cancer Project, supported by the Academic Medicine Development Company of New York.

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Author notes

1. Miguel Angel Pujana, Jing-Dong J Han, Lea M Starita, Muneesh Tewari, Nono Ayivi-Guedehoussou & Jeffrey D Parvin
   Present address: 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.).,
2. Miguel Angel Pujana, Jing-Dong J Han, Lea M Starita and Kristen N Stevens: These authors contributed equally to this work.

Authors and Affiliations

1. Dana-Farber Cancer Institute and Department of Genetics, Center for Cancer Systems Biology (CCSB), Harvard Medical School, 44 Binney St., Boston, 02115, Massachusetts, USA
   Miguel Angel Pujana, Jing-Dong J Han, Muneesh Tewari, Jin Sook Ahn, Jean-François Rual, Nicolas Bertin, Kavitha Venkatesan, Nono Ayivi-Guedehoussou, Michael E Cusick, David E Hill & Marc Vidal
2. Department of Cancer Biology, Dana-Farber Cancer Institute and Department of Genetics, Harvard Medical School, 44 Binney St., Boston, 02115, Massachusetts, USA
   Miguel Angel Pujana, Jing-Dong J Han, Muneesh Tewari, Jin Sook Ahn, Wael M ElShamy, Jean-François Rual, Roger A Greenberg, Bijan Sobhian, Nicolas Bertin, Kavitha Venkatesan, Nono Ayivi-Guedehoussou, Michael E Cusick, David E Hill, David M Livingston & Marc Vidal
3. Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, 77 Louis Pasteur Ave., Boston, 02115, Massachusetts, USA
   Lea M Starita & Jeffrey D Parvin
4. Department of Epidemiology, University of Michigan, 109 Zina Pitcher Pl., Ann Arbor, 48109, Michigan, USA
   Kristen N Stevens & Stephen B Gruber
5. Department of Community Medicine and Epidemiology, CHS National Cancer Control Center, Carmel Medical Center and Bruce Rappaport Faculty of Medicine, Technion, 34362, Haifa, Israel
   Gad Rennert
6. Department of Internal Medicine, University of Michigan, 109 Zina Pitcher Pl., Ann Arbor, 48109, Michigan, USA
   Víctor Moreno, Laura S Rozek & Stephen B Gruber
7. Department of Epidemiology and Cancer Registry, and Translational Research Laboratory, Catalan Institute of Oncology, IDIBELL, Gran Vía km 2.7, L'Hospitalet, Barcelona, 08907, Spain
   Víctor Moreno & Xavier Solé
8. Department of Medicine, Clinical Genetics Service, Memorial Sloan-Kettering Cancer Center, 1275 York Ave., New York, 10021, New York, USA
   Tomas Kirchhoff, Douglas Levine & Kenneth Offit
9. National Cancer Institute, Human Genetics Section, Laboratory of Genomic Diversity, Frederick, 21702, Maryland, USA
   Bert Gold
10. Center for Experimental Medicine, Institute of Tumor Biology, University Hospital Hamburg–Eppendorf, Martinistrasse 52, Hamburg, 20246, Germany
    Volker Assmann
11. Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Department of Biostatistics, Harvard School of Public Health, 44 Binney St., Boston, 02115, Massachusetts, USA
    Rebecca S Gelman
12. Department of Biology, Center for Comparative Functional Genomics, New York University, 100 Washington Square East, New York, New York, 10003, USA
    Kristin C Gunsalus
13. Translational Research Laboratory, Catalan Institute of Oncology, IDIBELL, Gran Vía km 2.7, L'Hospitalet, Barcelona, 08907, Spain
    Pilar Hernández & Conxi Lázaro
14. Abramson Family Cancer Research Institute, University of Pennsylvania School of Medicine, 421 Curie Blvd., Philadelphia, 19104, Pennsylvania, USA
    Katherine L Nathanson & Barbara L Weber
15. Department of Human Genetics, University of Michigan, 109 Zina Pitcher Pl., Ann Arbor, 48109, Michigan, USA
    Stephen B Gruber

Authors

1. Miguel Angel Pujana
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2. Jing-Dong J Han
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3. Lea M Starita
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4. Kristen N Stevens
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5. Muneesh Tewari
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6. Jin Sook Ahn
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7. Gad Rennert
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8. Víctor Moreno
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9. Tomas Kirchhoff
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10. Bert Gold
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11. Volker Assmann
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12. Wael M ElShamy
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13. Jean-François Rual
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14. Douglas Levine
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15. Laura S Rozek
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16. Rebecca S Gelman
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17. Kristin C Gunsalus
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18. Roger A Greenberg
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19. Bijan Sobhian
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20. Nicolas Bertin
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21. Kavitha Venkatesan
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22. Nono Ayivi-Guedehoussou
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23. Xavier Solé
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24. Pilar Hernández
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25. Conxi Lázaro
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26. Katherine L Nathanson
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27. Barbara L Weber
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28. Michael E Cusick
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29. David E Hill
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30. Kenneth Offit
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31. David M Livingston
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32. Stephen B Gruber
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33. Jeffrey D Parvin
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34. Marc Vidal
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Contributions

Experiments and data analyses were coordinated by M.A.P., J.-D.J.H., L.M.S and K.N.S. Computational analyses were performed by J.-D.J.H., K.C.G., N.B. and K.V. Yeast two-hybrid analysis screens were performed by M.A.P., J.S.A., J.-F.R and N.A.-G. Biochemical experiments were performed by M.A.P., L.M.S., W.M.E., R.A.G. and B.S. Cell culture and immunofluorescence experiments were performed by M.A.P. and L.M.S. The case-control study in Israel was conceived and executed by G.R. Genotyping and statistical analyses of the case-control studies were performed by K.N.S., L.S.R., G.R., V.M., T.K., B.G., D.L., K.O. and S.B.G. M.A.P., X.S. and P.H. performed the HapMap genotype-haplotype and gene expression association analysis. V.A. provided biochemical analysis support, R.S.G. provided statistical support and M.T., C.L., K.L.N., B.L.W., M.E.C., D.E.H. and D.M.L. helped with overall interpretation of the data. The manuscript was written by M.A.P., J.-D.J.H., L.M.S., D.E.H., M.E.C., S.B.G., J.D.P. and M.V. The project was conceived by M.V. and codirected by S.B.G., J.D.P. and M.V.

Corresponding authors

Correspondence toStephen B Gruber, Jeffrey D Parvin or Marc Vidal.

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Competing interests

D.M.L. is a research grantee of and a consultant to the Novartis Institute for Biomedical Research.

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Pujana, M., Han, JD., Starita, L. et al. Network modeling links breast cancer susceptibility and centrosome dysfunction.Nat Genet 39, 1338–1349 (2007). https://doi.org/10.1038/ng.2007.2

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• Received: 31 March 2007
• Accepted: 02 August 2007
• Published: 07 October 2007
• Issue Date: November 2007
• DOI: https://doi.org/10.1038/ng.2007.2