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Network modeling links breast cancer susceptibility and centrosome dysfunction.

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

In: NAT GENET, Vol. 39, No. 11, 11, 2007, p. 1338-1349.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Pujana, MA, Han, J-DJ, Starita, LM, Stevens, KN, Tewari, M, Ahn, JS, Rennert, G, Moreno, V, Kirchhoff, T, Gold, B, Assmann, V, Elshamy, WM, Rual, J-F, Levine, D, Rozek, LS, Gelman, RS, Gunsalus, KC, Greenberg, RA, Sobhian, B, Bertin, N, Venkatesan, K, Ayivi-Guedehoussou, N, Solé, X, Hernández, P, Lázaro, C, Nathanson, KL, Weber, BL, Cusick, ME, Hill, DE, Offit, K, Livingston, DM, Gruber, SB, Parvin, JD & Vidal, M 2007, 'Network modeling links breast cancer susceptibility and centrosome dysfunction.', NAT GENET, vol. 39, no. 11, 11, pp. 1338-1349. <http://www.ncbi.nlm.nih.gov/pubmed/17922014?dopt=Citation>

APA

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., ... Vidal, M. (2007). Network modeling links breast cancer susceptibility and centrosome dysfunction. NAT GENET, 39(11), 1338-1349. [11]. http://www.ncbi.nlm.nih.gov/pubmed/17922014?dopt=Citation

Vancouver

Pujana MA, Han J-DJ, Starita LM, Stevens KN, Tewari M, Ahn JS et al. Network modeling links breast cancer susceptibility and centrosome dysfunction. NAT GENET. 2007;39(11):1338-1349. 11.

Bibtex

@article{407f55eed0c74c44a443c44c9a4e811b,
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.",
author = "Pujana, {Miguel Angel} and Han, {Jing-Dong J} and Starita, {Lea M} and Stevens, {Kristen N} and Muneesh Tewari and Ahn, {Jin Sook} and Gad Rennert and V{\'i}ctor Moreno and Tomas Kirchhoff and Bert Gold and Volker Assmann and Elshamy, {Wael M} and Jean-Fran{\c c}ois Rual and Douglas Levine and Rozek, {Laura S} and Gelman, {Rebecca S} and Gunsalus, {Kristin C} and Greenberg, {Roger A} and Bijan Sobhian and Nicolas Bertin and Kavitha Venkatesan and Nono Ayivi-Guedehoussou and Xavier Sol{\'e} and Pilar Hern{\'a}ndez and Conxi L{\'a}zaro and Nathanson, {Katherine L} and Weber, {Barbara L} and Cusick, {Michael E} and Hill, {David E} and Kenneth Offit and Livingston, {David M} and Gruber, {Stephen B} and Parvin, {Jeffrey D} and Marc Vidal",
year = "2007",
language = "Deutsch",
volume = "39",
pages = "1338--1349",
journal = "NAT GENET",
issn = "1061-4036",
publisher = "NATURE PUBLISHING GROUP",
number = "11",

}

RIS

TY - JOUR

T1 - Network modeling links breast cancer susceptibility and centrosome dysfunction.

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

Y1 - 2007

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.

AB - 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.

M3 - SCORING: Zeitschriftenaufsatz

VL - 39

SP - 1338

EP - 1349

JO - NAT GENET

JF - NAT GENET

SN - 1061-4036

IS - 11

M1 - 11

ER -