Principal Investigator

Vincent Quoc-Huy Trinh

Digital Histology and Advanced Pathology

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Until very recently, Dr. Q. Trinh held the position of Surgery Research Instructor in the Department of Surgery of the Vanderbilt University Medical Center, in Nashville, Tennessee. He received his medical degree from the UdeM in 2014, then completed a Master’s in Biomedical Sciences (CRCHUM) and his residency in Anatomic Pathology at the UdeM in 2019. Subsequently, as a Fellow of the McLaughlin Foundation, he completed a clinical specialization in gastrointestinal and liver pathology at Vanderbilt (2019-2020), before being named as a Research Instructor at that same institution.

Dr. Q. Trinh’s main research interest involves the role played by fibroblasts and stellate cells in the tumor microenvironment of pancreatic cancer precursor cells. The study of progenitor cell populations during oncogenesis in other types of cancers will also be at the heart of his research program. By combining cutting-edge approaches in digital morphometrics, multiplex immunohistochemistry/immunofluorescence and single cell sequencing techniques, he will aim to redefine the diagnostic approach in pathology to help prevent tumor progression by specifically targeting those well-defined cell populations.

Principal Investigator, Digital Histology and Advanced Pathology Research Unit, IRIC

Clinical Associate Professor, Department of Pathology and Cellular Biology, Faculty of Medicine, Université de Montréal

Pathologist, Department of Pathology, Centre hospitalier de l’Université de Montréal (CHUM)

Digital Histology and Advanced Pathology Research Unit

Marcelle-Coutu Pavilion, 3440-1

Phone (office)
(514) 343-7894
(514) 343-7780

Digital Histology and Advanced Pathology

Dr. Vincent Quoc-Huy Trinh and his team utilize imaging and characterization techniques of cancerous tissue to develop new diagnostic and therapeutic tools. These techniques are centered around his training as a medical pathologist and medical knowledge associated with various visual manifestations identified in the tumors of both patients and animals. His team employs, among other methods, multiplex imaging, secretome analysis, artificial intelligence applied to images, transgenic murine models, and spatial transcriptomics.

Research topics