A genomic strategy to elucidate modules of oncogenic pathway signaling networks.
Recent studies have emphasized the importance of pathway-specific interpretations for understanding the functional relevance of gene alterations in human cancers. Although signaling activities are often conceptualized as linear events, in reality, they reflect the activity of complex functional networks assembled from modules that each respond to input signals. To acquire a deeper understanding of this network structure, we developed an approach to deconstruct pathways into modules represented by gene expression signatures. Our studies confirm that they represent units of underlying biological activity linked to known biochemical pathway structures. Importantly, we show that these signaling modules provide tools to dissect the complexity of oncogenic states that define disease outcomes as well as response to pathway-specific therapeutics. We propose that this model of pathway structure constitutes a framework to study the processes by which information propogates through cellular networks and to elucidate the relationships of fundamental modules to cellular and clinical phenotypes.
Institute for Genome Sciences and Policy, Duke University Medical Center, Duke University, Durham, NC 27708, USA.
Jeffrey T
JT
Chang
Carlos
C
Carvalho
Seiichi
S
Mori
Andrea H
AH
Bild
Michael L
ML
Gatza
Quanli
Q
Wang
Joseph E
JE
Lucas
Anil
A
Potti
Phillip G
PG
Febbo
Mike
M
West
Joseph R
JR
Nevins
D045744:Cell Line, Tumor; D016000:Cluster Analysis; D050684:E2F Transcription Factors / Q000235:genetics / Q000378:metabolism; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D023281:Genomics / Q000379:methods*; D006801:Humans; D008957:Models, Genetic; D009369:Neoplasms / Q000235:genetics* / Q000378:metabolism; D015398:Signal Transduction / Q000235:genetics*; D018631:ras Proteins / Q000235:genetics / Q000378:metabolism
D050684:E2F Transcription Factors; D018631:ras Proteins