Back

Juxtacrine DLL4-NOTCH1 signaling between astrocytes drives neuroinflammation via the IL-6-STAT3 axis

Mora, P.; Laisne, M.; Bourguignon, C.; Rouault, P.; Renault, M. A.; Horng, S.; Couffinhal, T.; Chapouly, C.

2023-10-06 neuroscience
10.1101/2023.10.04.560826 bioRxiv
Show abstract

Under neuroinflammatory conditions, astrocytes acquire a reactive phenotype that drives acute inflammatory injury as well as chronic neurodegeneration. We hypothesized that astrocytic DLL4 may interact with its receptor NOTCH1 on neighboring astrocytes to regulate astrogliosis via downstream juxtacrine signaling pathways. Here we investigated the role of astrocytic DLL4 on neurovascular unit homeostasis under neuroinflammatory conditions. We probed for downstream effectors of the DLL4-NOTCH1 axis and targeted these for therapy in two models of CNS inflammatory disease. We first demonstrated that astrocytic DLL4 is upregulated during neuroinflammation, both in mice and humans, driving astrogliosis and subsequent blood brain barrier permeability and inflammatory infiltration. We then showed that the DLL4-mediated NOTCH1 signaling in astrocytes directly drives IL-6 levels, induces STAT3 phosphorylation promoting upregulation of astrocyte reactivity markers, pro-permeability factor secretion and consequent blood brain barrier destabilization. Finally we revealed that blocking DLL4 with antibodies improves experimental autoimmune encephalomyelitis symptoms in mice, identifying a potential novel therapeutic strategy for CNS autoimmune demyelinating disease. As a general conclusion, this study demonstrates that DLL4-NOTCH1 signaling is not only a key pathway in vascular development and angiogenesis, but also in the control of astrogliosis during neuroinflammation.

Matching journals

The top 10 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.