Information-Theoretic Analysis of a Model of CAR-4-1BB-Mediated NFκB Activation

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 NFκB signaling initiated by the CAR following antigen encounter. First, we estimated channel capacity for CAR-4-1BB-mediated NFκB 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 NFκB 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 NFκB carries a higher channel capacity for the pathway than NFκB'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 IKKβ 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.

Computational analysis of 4-1BB-induced NFκB signaling suggests improvements to CAR cell design

Background

Chimeric antigen receptor (CAR)-expressing cells are a powerful modality of adoptive cell therapy against cancer. The potency of signaling events initiated upon antigen binding depends on the costimulatory domain within the structure of the CAR. One such costimulatory domain is 4-1BB, which affects cellular response via the NFκB pathway. However, the quantitative aspects of 4-1BB-induced NFκB signaling are not fully understood.

Methods

We developed an ordinary differential equation-based mathematical model representing canonical NFκB signaling activated by CD19scFv-4-1BB. After a global sensitivity analysis on model parameters, we ran Monte Carlo simulations of cell population-wide variability in NFκB signaling and quantified the mutual information between the extracellular signal and different levels of the NFκB signal transduction pathway.

Results

In response to a wide range of antigen concentrations, the magnitude of the transient peak in NFκB nuclear concentration varies significantly, while the timing of this peak is relatively consistent. Global sensitivity analysis showed that the model is robust to variations in parameters, and thus, its quantitative predictions would remain applicable to a broad range of parameter values. The model predicts that overexpressing NEMO and disabling IKKβ deactivation can increase the mutual information between antigen levels and NFκB activation.

Conclusions

Our modeling predictions provide actionable insights to guide CAR development. Particularly, we propose specific manipulations to the NFκB signal transduction pathway that can fine-tune the response of CD19scFv-4-1BB cells to the antigen concentrations they are likely to encounter.