Transcriptional Networks Inferred from Molecular Signatures of Breast Cancer.
Am J Pathol. 2008 Feb;172(2):495-509. Epub 2008 Jan 10
Researchers from various departments at the National Cancer Institute, Bethesda, Maryland, in collaboration with several universities used Ingenuity Pathways Analysis to identify networks that appeared most associated with the regulatory signatures found in the promoters of five different molecular sub types of breast cancer. The regulatory signatures were defined as an assembly of transcription factor binding sites (TFBSs) found to be non-randomly shared by several genes associated with a molecular phenotype. One of the networks associated with a particular subtype (ERBB2) identified a novel role for NF-kB and ERBB2 in a self amplifying, auto regulatory module. The existence of this pathway was then empirically validated.
In this study the researchers have systematically analyzed the promoter regions for all the unique genes of the five different molecular sub types of breast cancer that correlated with specific clinical outcomes. The genes of each respective subtype were combined with the transcription factor genes cognate for the most significantly enriched TFBSs within each subtype. This created a composite list of the regulated and regulator for each genetic signature. These lists were then uploaded into IPA to build networks based on the curated molecular interactions between the genes in each of the lists. Using network analysis they were able to characterize the molecular signaling and cross talking interactions for each of the subtypes. In particular, the regulatory network for ERBB2 predicted a role for nuclear factor-_B in a novel feed-forward, self-amplifying, auto-regulatory module regulated by the ERBB family of growth factor receptors. The existence of this pathway was verified in vivo by chromatin immune-precipitation and shown to be deregulated in breast cancer cells over expressing ERBB2. This analysis indicates that approaches of this type can provide unique insights into the differential regulatory molecular programs associated with breast cancer and will aid in identifying specific transcriptional networks and pathways as potential targets for tumor subtype-specific therapeutic intervention.
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