Cancer is a multifaceted disease. Can we find patterns in presentation that improve research and treatment?
Quite often, T cells from cancer patients are difficult to activate and grow, complicating the use of cellular immunotherapy. This phenomenon resembles T cell exhaustion in response to chronic stimulation, but the underlying mechanisms are not well understood. Our group applied a multi-factor data analysis approach to produce an algorithm that can predict the long-term growth of cells from a set of biomarkers and short-term measure of live cell function. The vision is for these analyses to allow tailoring of cell growth conditions to an individual, optimizing production of sufficient numbers of high quality cells.