Quantitative analysis of adenoviral vector modification of a cytokine-mediated cell death decision

Abstract

Intracellular networks arise from complex interactions between proteins that relay signals and control cellular responses. Viruses, with limited genetic material, can modify network signals and change cell behavior. Replication-deficient viruses are used extensively as delivery vectors in clinical gene therapy and in molecular biology, but little is known about how the viral carrier itself contributes to cellular responses. In this thesis, we explored the link between viral vector modifications of signaling networks to changes in cellular phenotype. We approached this problem by studying a therapeutically relevant model in which an adenoviral vector (Adv) sensitizes human tumor epithelial cells to tumor necrosis factor (TNF)-induced apoptosis. We first measured TNF-stimulated signaling profiles over a range of Adv infection levels for a distribution of kinases centrally involved in the TNF signaling network. We then applied quantitative analytical techniques to determine the most important signals contributing to Adv-induced changes in TNF-mediated apoptosis. We experimentally derived a mathematical equation describing the saturation of anti-apoptotic Akt effector signaling in the presence of high levels of Adv infection, which could predict TNF-induced apoptosis in HT-29 cells.

(cont.) However, the same equation did not apply in HeLa cells, suggesting that one-signal models are insufficient to account for complex network interactions. Therefore, we applied a systems-modeling approach to our Adv-TNF system and mathematically identified a multivariate signal-processing function sufficient to predict Adv-TNF induced apoptosis in both HT-29 cells and HeLa cells. The common-processing model identified critical Adv-induced cell-specific signaling modifications, and accurately predicted apoptosis following perturbation with pharmacological inhibitors of Akt and IKK. Thus, by combining experimental and computational approaches, this thesis has identified an important biological principle, common signal processing, for studying cell-specific responses to viral infections and rational drug therapies.