The purpose of this research is to use systems biology approaches to understand the specificity and temporal mechanisms that govern activation of transcription factor NF-kappaB, as well as how NF-kappaB evokes a transcriptional response, in order to better understand progression of certain types of cancer. Systems-based and computational approaches are particularly well-suited to address this issue. ? ? Using a combined computational modeling/experimental approach, we were able to characterize a previously-unknown part of the pathways which led from LPS stimulation to NF-kappaB activation. This approach also led to the explanation of a complex behavior: the observed stable activation of NF-kappaB under LPS stimulation. Moving forward, we propose to continue using an integrated approach to study the NF-kappaB network at several levels of abstraction.
Our Specific Aims are to: (1) reconstruct and analyze a network model of the entire known NF-kappaB signaling and transcriptional network; (2) derive a detailed description and model of the gene expression response to NF-kappaB activation; (3) build a quantitative description of B cell-related NF-kappaB activation dynamics into a detailed computational model; and (4) observe and model NF-kappaB-related activation and autocrine/paracrine signaling in single cells. ? ? PLAIN LANGUAGE SUMMARY: Advances in our ability to build computer models, and to use model predictions to guide experiments, have great potential in helping us to understand cancer progression. We propose to use computer modeling and experiments to help us understand the NF-kappaB signaling network and its role in cancer development, particularly with regard to diffuse large B cell lymphomas. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Career Transition Award (K99)
Project #
5K99CA125994-02
Application #
7470678
Study Section
Special Emphasis Panel (ZCA1-RTRB-A (M1))
Program Officer
Lohrey, Nancy
Project Start
2007-07-18
Project End
2009-06-30
Budget Start
2008-07-01
Budget End
2009-06-30
Support Year
2
Fiscal Year
2008
Total Cost
$137,457
Indirect Cost
Name
Stanford University
Department
Biomedical Engineering
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
Koechlein, Claire S; Harris, Jeffrey R; Lee, Timothy K et al. (2016) High-resolution imaging and computational analysis of haematopoietic cell dynamics in vivo. Nat Commun 7:12169
Karr, Jonathan R; Guturu, Harendra; Chen, Edward Y et al. (2015) NetworkPainter: dynamic intracellular pathway animation in Cytobank. BMC Bioinformatics 16:172
Gutschow, Miriam V; Hughey, Jacob J; Ruggero, Nicholas A et al. (2013) Single-cell and population NF-ýýB dynamic responses depend on lipopolysaccharide preparation. PLoS One 8:e53222
Hughey, Jacob J; Lee, Timothy K; Covert, Markus W (2010) Computational modeling of mammalian signaling networks. Wiley Interdiscip Rev Syst Biol Med 2:194-209
Tay, Savas; Hughey, Jacob J; Lee, Timothy K et al. (2010) Single-cell NF-kappaB dynamics reveal digital activation and analogue information processing. Nature 466:267-71
Seok, Junhee; Xiao, Wenzhong; Moldawer, Lyle L et al. (2009) A dynamic network of transcription in LPS-treated human subjects. BMC Syst Biol 3:78
Lee, Timothy K; Denny, Elissa M; Sanghvi, Jayodita C et al. (2009) A noisy paracrine signal determines the cellular NF-kappaB response to lipopolysaccharide. Sci Signal 2:ra65