Individualized expansion of T cells from CLL patients for immunotherapy

Abstract

Abstract T cell therapy has shown significant promise in treating blood cancers, yet high proportions of T cells from patients are either unresponsive to stimulation methods or show wide variability in regards to which activation conditions induce optimal expansion. In this work, we explore how expansion of T cells from CLL patients using scaffolds with tunable physical parameters (rigidity, fiber dimensions, pore size) is correlated to patient biomarker data, as well as exhaustion and functional profiles of patient T cells, to gain insight on personalizing T cell production for immunotherapy. Polymer fiber scaffolds are fabricated via electrospinning with PDMS/PCL polymer blend and coated with activating antibodies to CD3 and CD28 to stimulate T cells isolated from CLL patients with pre-annotated mutation burdens and disease progression. Exhaustion surface markers, memory/effector phenotyping, and cytokine secretion are measured via immunostaining before and after expansion. Preliminary data has shown that decreasing fiber diameters (from 6 to 1 μm) enhanced T cell expansion and increased the ratio of effector memory to central memory phenotypes. We observe that higher CLL Rai stage leads to decrease in proliferative potential. Interestingly, cells from each CLL patient in our initial study showed different patterns of expansion for the same set of scaffold compositions. Machine learning methods can identify clinical markers that predict exhaustion and functional profiles from starting cell populations as well as expansion with different biomaterial parameters. Collectively, insight into predicting how patient T cells can be robustly expanded in a personalized approach is powerful for translating T cell therapies to more patients.