Network modeling links breast cancer susceptibility and centrosome dysfunction.
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.
Pujana
Miguel Angel
MA
Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute and Department of Genetics, Harvard Medical School, 44 Binney St., Boston, Massachusetts 02115, USA.
Han
Jing-Dong J
JD
Starita
Lea M
LM
Stevens
Kristen N
KN
Tewari
Muneesh
M
Ahn
Jin Sook
JS
Rennert
Gad
G
Moreno
Víctor
V
Kirchhoff
Tomas
T
Gold
Bert
B
Assmann
Volker
V
Elshamy
Wael M
WM
Rual
Jean-François
JF
Levine
Douglas
D
Rozek
Laura S
LS
Gelman
Rebecca S
RS
Gunsalus
Kristin C
KC
Greenberg
Roger A
RA
Sobhian
Bijan
B
Bertin
Nicolas
N
Venkatesan
Kavitha
K
Ayivi-Guedehoussou
Nono
N
Solé
Xavier
X
Hernández
Pilar
P
Lázaro
Conxi
C
Nathanson
Katherine L
KL
Weber
Barbara L
BL
Cusick
Michael E
ME
Hill
David E
DE
Offit
Kenneth
K
Livingston
David M
DM
Gruber
Stephen B
SB
Parvin
Jeffrey D
JD
Vidal
Marc
M
D064127:Aurora Kinases; D019313:BRCA1 Protein / Q000037:antagonists & inhibitors / Q000235:genetics / Q000378:metabolism; D024682:BRCA2 Protein / Q000037:antagonists & inhibitors / Q000235:genetics / Q000378:metabolism; D014408:Biomarkers, Tumor / Q000235:genetics / Q000378:metabolism; D001943:Breast Neoplasms / Q000235:genetics*; D016022:Case-Control Studies; D018385:Centrosome / Q000502:physiology*; D019295:Computational Biology; D016326:Extracellular Matrix Proteins / Q000037:antagonists & inhibitors / Q000235:genetics / Q000378:metabolism*; D005260:Female; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D020022:Genetic Predisposition to Disease; D006801:Humans; D018960:Hyaluronan Receptors / Q000235:genetics / Q000378:metabolism*; D016571:Neural Networks, Computer; D020411:Oligonucleotide Array Sequence Analysis; D016133:Polymerase Chain Reaction; D025941:Protein Interaction Mapping; D017346:Protein Serine-Threonine Kinases / Q000235:genetics / Q000378:metabolism; D034741:RNA, Small Interfering / Q000494:pharmacology; D025801:Ubiquitin / Q000378:metabolism
D019313:BRCA1 Protein; D024682:BRCA2 Protein; D014408:Biomarkers, Tumor; D016326:Extracellular Matrix Proteins; D018960:Hyaluronan Receptors; D034741:RNA, Small Interfering; D025801:Ubiquitin; C098946:hyaluronan-mediated motility receptor; D064127:Aurora Kinases; D017346:Protein Serine-Threonine Kinases