Director, Pain Medicine Fellowship, Massachusetts General Hospital
Associate Professor, Harvard Medical School
Gary J. Brenner currently sees patients at the Massachusetts General Hospital Pain Management Center where he is the Director of the Mass General Pain Medicine Fellowship. He is an Associate Professor in Anesthesia at Harvard Medical School. Dr. Brenner runs an NIH-funded lab focused on developing gene therapy for the often painful peripheral nervous system tumors associated with neurofibromatosis. He also conducts neuroscience research on the mechanism of action of opioids in the brain, and has authored more than 45 articles, reviews, chapters, and abstracts on gene therapy strategies for NF tumors, the pathophysiology of pain, basic pain mechanisms and immune function, and clinical approaches to chronic pain. Dr. Brenner currently has several national leadership positions related to pain medicine education/training. He completed his MD and PhD degrees at the University of Rochester School of Medicine and Dentistry, and completed an anesthesiology residency and a pain medicine fellowship at the Massachusetts General Hospital.
Clinical Interests:
Treats:
Mass General Anesthesia and Pain Medicine
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My laboratory currently focuses efforts on two projects. The first involves the development of novel therapeutic strategies for the treatment of Schwann-cell derived nerve sheath tumors. In particular, we are utilizing adenovirus associated vectors to deliver caspase-1 to tumor cells. Delivery of this apoptosis-generating transgene both directly kills tumor cells in which it is expressed and activates anti-tumor host responses. We are investigating the mechanisms through which our vector kills tumor and are developing the therapeutic strategy for translation into phase 0/1 clinical trials.
The second project utilizes optogenetic modulation of brain circuits to investigate nociceptive processing that occurs in the context of nociceptive sensitization associated with peripheral nerve injury. This approach may improve the positive predictive value for preclinical modeling of clinical pain.
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