John C. Reed, M.D. , Ph.D

The Burnham Institute
10901 North Torrey Pines Road
La Jolla, CA
(858) 646-3132
http://www.burnham.org/

Cell death is a natural part of life. Every day in the human body, 50-70 billion cells die, making room for the equivalent number of new cells produced daily through cell division. So massive is the flux of cell birth and death in our bodies, that in the course of single year, each of us will produce and in parallel eradicate a mass of cells equal to our entire body weight.

Our cells are endowed with a suicide mechanism that instructs cells when it is time to die. Unfortunately, defects in the regulation of this cell suicide program can occur, leading to diseases characterized by either too much cell death [cell loss] (stroke; heart failure; Alzheimer’s; Parkinson’s; AIDS) or too little cell death [cell accumulation] (cancer; auto-immunity; coronary artery restenosis). In fact, it is estimated that over half of the major medical illnesses for which effective treatments or preventions are currently lacking can be attributed directly or indirectly to defective regulation of programmed cell death mechanisms.

Our laboratory studies fundamental mechanisms of cell life-span regulation, and analyzes how those mechanisms go awry in disease states. We use tools of genomics, proteomics, and bioinformatics to discover genes involved in the causation or suppression of cell death. Characterization of the molecular mechanisms by which the proteins encoded by those genes control cell life and death then provides insights that set the stage for drug discovery. Advances from our laboratory have thus far resulted in a new therapy for cancer, which is in final Phase III clinical trials, and numerous drug-discovery programs at earlier stages of development for cancer, stroke, inflammation, and auto-immunity. Discoveries from our laboratory have also revealed potential new diagnostic tests that can predict whether cancer patients will or will not relapse after receiving therapy, thus providing much need information in planning optimal medical management.