TCR signal strength as an immune biomarker to predict the effectiveness of anti-CD3 therapy for T1D

Prevention of type 1 diabetes (T1D) in susceptible individuals has been aimed at either boosting immunosuppressive T regulatory (Treg) or reducing autoreactive T effector (Teff) cell number and function. Low dose anti-CD3 antibody therapy has been widely used both in preclinical models of T1D and in several phase 2/3 clinical trials. While this approach has proved successful in mouse models of T1D the results of the clinical trials have been disappointing overall. The mechanism of action of anti-CD3 therapy is not fully understood and many trials have not adequately investigated the immune consequences of this therapy. We have made the novel observation that T cell receptor (TCR) signals of varying strength lead to distinct patterns of activation in signaling pathways important for determining Th cell fate. In particular, we have uncovered a novel feedback loop between phosphatase and tensin homolog (PTEN), the transcription factor FoxO1 and the serine/threonine kinase Akt. We have also shown that TCR signals of high and low strength change the phosphorylation state of Akt, which results in the phosphorylation of non-overlapping sets of Akt substrates, that include RNA processing proteins. These RNA processing factors influence Treg differentiation and have resulted in the induction of alternatively spliced molecules important in TCR signaling, including CD3 ζ (CD247) and Tec kinase. We have assessed whether alternatively spliced variants of CD247 and Tec kinase may be used as immune biomarkers to monitor the effectiveness of low-dose anti-CD3 therapy in T1D.