Bruno Larrivee
Associate Professor · Developmental and Pathological Angiogenesis
University of MontrealAbout
Bruno Larrivee is an Associate Professor in the Department of Ophthalmology at the University of Montreal and leads the Developmental and Pathological Angiogenesis Research Unit. His work focuses on identifying novel signaling pathways, particularly in the BMP and Notch families, that regulate blood vessel formation and integrity in ocular diseases and cancer.
- Affiliation: Faculty of Medicine, University of Montreal
- Research Units: CRHMR (Maisonneuve-Rosemont Hospital Research Center), Montreal Diabetes Research Center
- Projects: Targeting VEGF-independent pathways for ocular therapeutics, Vascular normalization in tumors, Mechanisms of ALK1/Notch crosstalk
Research Focus: Dr. Larrivee investigates angiogenesis in diabetic retinopathy and AMD, aiming to develop safer inhibitors than VEGF-targeting therapies. His lab also explores tumor vascular normalization to enhance chemotherapy and immunotherapy efficacy, with key work on BMP9/ALK1 pathway regulation of endothelial quiescence.
Publication Trends: Recent studies emphasize TGF-β and BMP signaling in ocular pathologies, tumor vascular normalization, and mechanotransduction in hereditary vascular diseases. Collaborative projects span diabetes, cancer, and retinal degeneration, highlighting interdisciplinary approaches.
Scientific Awards:
- Louise Rousselle Trottier Award (2016)
- New Investigator Award, Heart and Stroke Foundation (2014)
- Scientist Development Award, American Heart Association (2013)
Grants: Funded by CIHR, NSERC, and foundations like Mitacs and the Foundation Fighting Blindness, with projects on AMD, diabetic retinopathy, and tumor angiogenesis. Collaborations include teams at Yale, the College of France, and INSERM.
Labs & Teams: Affiliated with CRHMR and the Montreal Diabetes Research Center, working alongside students and researchers like Naoufal Akla, Natalija Popovic, and Cindy Lora Gil. His lab integrates computational methods (e.g., machine learning) for vascular analysis.
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