CAR-4-1BB 介导的 NFκB 激活模型的信息论分析

Systems biology utilizes computational approaches to examine an array of biological processes, such as cell signaling, metabolomics and pharmacology. This includes mathematical modeling of CAR T cells, a modality of cancer therapy by which genetically engineered immune cells recognize and combat a cancerous target. While successful against hematologic malignancies, CAR T cells have shown limited success against other cancer types.

Thus, more research is needed to understand their mechanisms of action and leverage their full potential. In our work, we set out to apply information theory on a mathematical model of NF B signaling initiated by the CAR following antigen encounter. First, we estimated channel capacity for CAR-4-1BB-mediated NF B signal transduction. Next, we evaluated the pathway's ability to distinguish contrasting "low" and "high" antigen concentration levels, depending on the amount of variability in protein concentrations.

Finally, we assessed the fidelity by which NF B activation reflects the encountered antigen concentration, depending on the prevalence of antigen-positive targets in tumor population.

We found that in most scenarios, fold change in the nuclear concentration of NF B carries a higher channel capacity for the pathway than NF B's absolute response.

Additionally, we found that most errors in transducing the antigen signal through the pathway skew towards underestimating the concentration of encountered antigen.

Finally, we found that disabling IKK deactivation could increase signaling fidelity against targets with antigen-negative cells.

Our information-theoretic analysis of signal transduction can provide novel perspectives on biological signaling, as well as enable a more informed path to cell engineering. Kindly check and confirm whether the corresponding affiliation is correctly identified. this is correct.