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Quantitative NetworkSignal CombinationsDownstream of TCRActivation CanPredict IL-2Production Response Melissa L. KempLucia WilleChristina L. Lewis2007 год

Quantitative Network Signal Combinations Downstream of TCR Activation Can Predict IL-2 Production Response
статья из журнала

Полный текстСтраница публикацииПубликация в OpenAlex
Аннотация: Abstract Proximal signaling events activated by TCR-peptide/MHC (TCR-pMHC) binding have been the focus of intense ongoing study, but understanding how the consequent downstream signaling networks integrate to govern ultimate avidity-appropriate TCR-pMHC T cell responses remains a crucial next challenge. We hypothesized that a quantitative combination of key downstream network signals across multiple pathways must encode the information generated by TCR activation, providing the basis for a quantitative model capable of interpreting and predicting T cell functional responses. To this end, we measured 11 protein nodes across six downstream pathways, along five time points from 10 min to 4 h, in a 1B6 T cell hybridoma stimulated by a set of three myelin proteolipid protein 139–151 altered peptide ligands. A multivariate regression model generated from this data compendium successfully comprehends the various IL-2 production responses and moreover successfully predicts a priori the response to an additional peptide treatment, demonstrating that TCR binding information is quantitatively encoded in the downstream network. Individual node and/or time point measurements less effectively accounted for the IL-2 responses, indicating that signals must be integrated dynamically across multiple pathways to adequately represent the encoded TCR signaling information. Of further importance, the model also successfully predicted a priori direct experimental tests of the effects of individual and combined inhibitors of the MEK/ERK and PI3K/Akt pathways on this T cell response. Together, our findings show how multipathway network signals downstream of TCR activation quantitatively integrate to translate pMHC stimuli into functional cell responses.
Год издания: 2007
Авторы: Melissa L. Kemp, Lucia Wille, Christina L. Lewis, Lindsay B. Nicholson, Douglas A. Lauffenburger
Издательство: American Association of Immunologists
Источник: The Journal of Immunology
Ключевые слова: Computational Drug Discovery Methods, Viral Infectious Diseases and Gene Expression in Insects, Microbial Natural Products and Biosynthesis
Другие ссылки: The Journal of Immunology (PDF)
The Journal of Immunology (HTML)
PubMed (HTML)