| dc.description.abstract | Many diseases, including cancer, autoimmunity, infections, and allergies, are associated with dysregulation of immune responses. Therapeutic strategies targeting the immune system have succeeded in treating a wide range of diseases. However, we lack the detailed understanding of the immune system needed to design more effective and targeted therapies for many immune-mediated diseases that yet have no cure.
To address this knowledge gap, this thesis presents a dictionary of immune responses. We leveraged recent advancements in high-throughput genomic technologies to comprehensively interrogate how major cell types involved in the immune system respond to immune stimuli. We created a dictionary of single-cell transcriptomic profiles of individual responses to 86 cytokines and 5 vaccine adjuvants in over 20 cell populations, representing one of the most comprehensive analyses of cellular responses to immune stimuli to date. Based on the dictionary, we created companion software for assessing cytokine activities, constructing cell-cell communication network models, and analyzing time-series data. Our dictionary reveals principles of immune responses, expands our knowledge of activation states in each immune cell type, and provides a framework to assess the roles that cytokines and cell-cell communication networks play in any immune response.
Based on a detailed understanding of immune responses provided by these systems approaches, we created vaccination strategies that significantly enhanced CD8+ T-cell responses in animal studies. Overall, this thesis combines high-throughput computational and experimental approaches to systematically characterize immune responses, enabling the design of more targeted and effective vaccines and immune-based therapies for thus far incurable diseases. | |
