T cells orchestrate the adaptive immune response, making them targets for immunotherapy.Although immunosuppressive therapies prevent disease progression, they also leave patients susceptible to opportunistic infections.To identify novel drug targets, we established a Video transmitter logical model describing T-cell receptor (TCR) signaling.
However, to have a model that is able to predict new therapeutic approaches, the current drug targets must be included.Therefore, as a next step we generated the interleukin-2 receptor (IL-2R) signaling network and developed a tool to merge logical models.For IL-2R signaling, we show that STAT activation is independent of both Src- and PI3-kinases, while ERK activation depends upon both kinases and additionally requires novel PKCs.
In addition, our merged model correctly predicted TCR-induced STAT activation.The combined network also allows information transfer from one receptor to add detail to another, thereby predicting that LAT mediates Wood Markers JNK activation in IL-2R signaling.In summary, the merged model not only enables us to unravel potential cross-talk, but it also suggests new experimental designs and provides a critical step towards designing strategies to reprogram T cells.