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.
Chang
Jeffrey T
JT
Institute for Genome Sciences and Policy, Duke University Medical Center, Duke University, Durham, NC 27708, USA.
Carvalho
Carlos
C
Mori
Seiichi
S
Bild
Andrea H
AH
Gatza
Michael L
ML
Wang
Quanli
Q
Lucas
Joseph E
JE
Potti
Anil
A
Febbo
Phillip G
PG
West
Mike
M
Nevins
Joseph R
JR
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