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.
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