Robert Kurt, PhD: No financial relationships to disclose
Introduction/Rationale: Several interconnected Toll-like receptor (TLR) signaling cascades in total were studied to determine if there was any significant difference from studying them individually. The large space of possible behaviors required that we develop a computational model to effectively search the space and design the experiments. Computational models can be difficult to develop especially with large, interacting cascades. Our approach was to (1) develop a tool to construct agent based models of single (simpler) TLR signaling cascades, and then (2) enhance it with the ability to combine multiple individual models into a single, more complex model.
Methods: The merged model that we created incorporated all parts of the component cascades, and was used to investigate single, dual, and triple TLR signaling cascades. To validate the model single, dual, and triple TLR agonist treated bone marrow-derived macrophages (BMDM) were assessed for gene expression, phagocytic activity, production of nitrite and reactive oxygen species, IL-12 secretion, and anti-tumor activity against three different murine mammary carcinoma models; 4T1, EMT6, and 168.
Results: The data indicate that the different TLR signaling cascades interact with each other in multiple ways, and that these interactions affect the cell response to both increased dosages and combinations of agonists. The behaviors of the cascades in total were significantly different from those of the individual cascades, even when there was only one agonist.
Conclusion: The data and interactions highlight the necessity of studying the TLR cascades in total rather than individually as has been done previously. They also underscore the utility of having a computational model to study multiple signaling cascades in toto rather than in isolation in order to more closely recapitulate anti-tumor activity and understand the behavior of interconnected signaling cascades.
