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Institute of Experimental Immunology Neuroimmunology

Neuroimmunology

Neuroimmunology

Overview
The dynamic interaction of the central nervous system (CNS) and the immune system is a critical feature of tissue integrity and homeostatic immune surveillance. Simultaneously, highly efficient tolerance mechanisms have to ensure that patrolling T cells do not gain access to the immune-privileged brain parenchyma and contribute to the resolution of ongoing inflammation to protect the vulnerable cells of the CNS from irreversible damage and contribute to the resolution of ongoing inflammation to protect the vulnerable cells of the CNS from irreversible damage. Neuroimmune interactions, including tolerance mechanisms, are still poorly understood. However, many brain diseases such as multiple sclerosis (MS) (autoimmunity) and glioma (cancer) are strongly influenced by CNS-specific protective mechanisms. Understanding the underlying neuroimmune crosstalk is required to develop effective and safe therapies for this extremely vulnerable site of the body.
While tolerance mechanisms have evolved to protect against autoimmunity, they also present a major hurdle for cancer immunotherapy, where tolerance has to be bypassed in order to promote anti-tumor immunity. The use of monoclonal antibodies against immune checkpoint molecules has revolutionized the field of oncology in recent years with proven efficacy in a significant fraction of cancer patients. However, so-called immune related adverse events (irAEs), including autoimmune attacks of the CNS, have emerged as a frequent complication, highlighting the physiological role of these pathways in maintaining peripheral tolerance.

Specific questions
•Which mechanims contribute to tolerance during homostasis and neuroinflammation?
•Is tolerance failure the reason of disease progression in MS?
•Which cell types are involved in tolerance maintenance and disease progression?

Methodology
We  mainly use a combination of conditional gene targeting in mice (CreLoxP), highly multiplexed flow cytometry and computational data mining (R)