Final Report Summary - IT-DC (Large-scale integrative biology of human dendritic cells)
Dendritic cells (DC) are considered as the gatekeepers or sentinels of the immune system. They constantly receive and integrate signals associated to a danger for our organism. Some may come directly from a microbe, and some may derive from the response of host tissues following damage. Most studies have addressed the response of DC to individual stimuli. Hence, the integration process and the possibility of interactions were not taken into account. In fact, multiple signal integration is an extremely complex phenomenon, lacking systematic formalization and specific analysis in immune and other cell types. This complexity lies at two levels: 1) when a cell receives two signals, each signal can affect the response to the other in a mode that most of the time cannot be predicted (so-called “nonlinear”); 2) the cellular response to individual and multiple signals is achieved through modulation of hundreds of genes, controlling 10s of biological pathways. In our ERC project, we undertook the challenge to deceive for the complexity of multiple signal integration, considering at the same time the modulation of hundreds of genes in the way DC respond to microbial and host derived signals. This required putting together an interdisciplinary team and collaborators in the fields of immunology, molecular biology, mathematical modeling, bioinformatics and computational biology. We uncovered that interaction modes between two stimuli are way more complex and numerous than the previously described “synergy”and “antagonism”. This was established in studying human DC as a model, but can be now extended and applied to any cell type integrating any pairs of stimuli. In addition, we found that these complex interaction modes do not affect all cellular outputs in the same manner. In other words, two stimuli can be synergistic for some of the cellular responses, and antagonistic for the others, a concept that we called “multimodality”. We now propose the concepts of context dependency and multimodality as generally affecting most of the stimuli received by immune cells in complex inflammatory environments. We have studied some of these combinations in specific disease context, such as human psoriasis. We also have deciphered the impact of multiple signal integration on immune cell connectivity, i.e the ability of an immune cell type to communicate with other cells.
The impact of our work is very broad in immunology, cell biology, and also pharmacology. We have started a project applying our innovative methodologies to the field of drug combinations. We aim at establishing proof of concept that the powerful computational methods can help improve drug combination strategies, and select the most promising combination of drugs to develop in the clinics. Our project also paved the way to even more complex questions related to how cells integrate a multiplicity of stimuli relevant to an immune response or other biological processes.
The impact of our work is very broad in immunology, cell biology, and also pharmacology. We have started a project applying our innovative methodologies to the field of drug combinations. We aim at establishing proof of concept that the powerful computational methods can help improve drug combination strategies, and select the most promising combination of drugs to develop in the clinics. Our project also paved the way to even more complex questions related to how cells integrate a multiplicity of stimuli relevant to an immune response or other biological processes.