Modelling predicts differences in chimeric antigen receptor T-cell signalling due to biological variability

Tserunyan, Vardges; Finley, Stacey D.

doi:10.1098/rsos.220137

Cited by 4 publications

(2 citation statements)

References 34 publications

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“…However, as we see here, much goes into the mechanical crosstalk to help set the stage for potential cell breakout that must be understood. We need such starting points that contain information beyond automaton models [41][42][43] that include mechanics and chemical signaling [44] to begin to make quantitative predictions for cell breakout. While cell breakout is the obvious next step, we must also consider the multiscale aspect of cells [45] as well as the adaptability of cells and their ability to "train" the fiber network to be able to escape within a physical learning framework [46,47] just as neural networks are trained to perform a specific function.…”

Section: Discussionmentioning

confidence: 99%

Enhanced extracellular matrix remodeling due to embedded spheroid fluidization

Zhang,

Ameen,

Ghosh

et al. 2024

Preprint

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Tumor spheroids arein vitrothree-dimensional, cellular collectives consisting of cancerous cells. Embedding these spheroids in anin vitrofibrous environment, such as a collagen network, to mimic the extracellular matrix (ECM) provides an essential platform to quantitatively investigate the biophysical mechanisms leading to tumor invasion of the ECM. To understand the mechanical interplay between tumor spheroids and the ECM, we computationally construct and study a three-dimensional vertex model for a tumor spheroid that is mechanically coupled to a cross-linked network of fibers. In such a vertex model, cells are represented as deformable polyhedrons that share faces. Some fraction of the boundary faces of the tumor spheroid contain linker springs connecting the center of the boundary face to the nearest node in the fiber network. As these linker springs actively contract, the fiber network remodels. By toggling between fluid-like and solid-like spheroids via changing the dimensionless cell shape index, we find that the spheroid rheology affects the remodeling of the fiber network. More precisely, fluid-like spheroids displace the fiber network more on average near the vicinity of the spheroid than solid-like spheroids. We also find more densification of the fiber network near the spheroid for the fluid-like spheroids. These spheroid rheology-dependent effects are the result of cellular motility due to active cellular rearrangements that emerge over time in the fluid-like spheroids to generate spheroid shape fluctuations. These shape fluctuations lead to emergent feedback between the spheroid and the fiber network to further remodel the fiber network with, for example, lower radial alignment of the higher-tensioned fibers given the breaking of spheroidal radial symmetry, which can then further remodel the spheroid. Our results uncover intricate morphological-mechanical interplay between an embedded spheroid and its surrounding fiber network with both spheroid contractile strengthandspheroid shape fluctuations playing important roles in the pre-invasion stages of tumor invasion.

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Section: Discussionmentioning

confidence: 99%

Enhanced extracellular matrix remodeling due to embedded spheroid fluidization

Zhang,

Ameen,

Ghosh

et al. 2024

Preprint

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“…By considering the impact of added CD28 signaling, this study underscored the advantages of second-generation CARs over the first-generation design. The same model was later used to compare the impact of population-wide cell heterogeneity on the activation of CAR T cells (Cess and Finley 2020 ; Tserunyan and Finley 2022b ). By applying insights from information theory on CAR-4-1BB constructs, our research group was able to assess the fidelity of CAR-4-1BB-mediated activation of the NFκB pathway by a candidate distribution of the targeted CD19 antigen (Tserunyan and Finley 2022a ).…”

Section: Introductionmentioning

confidence: 99%

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

Tserunyan,

Finley

2023

Bull Math Biol

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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

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Modelling predicts differences in chimeric antigen receptor T-cell signalling due to biological variability

Tserunyan

Finley

2022

R. Soc. open sci.

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In recent decades, chimeric antigen receptors (CARs) have been successfully used to generate engineered T cells capable of recognizing and eliminating cancer cells. The structure of CARs typically includes costimulatory domains, which enhance the T-cell response upon antigen encounter. However, it is not fully known how those co-stimulatory domains influence cell activation in the presence of biological variability. In this work, we used mathematical modelling to elucidate how the inclusion of one such costimulatory molecule, CD28, impacts the response of a population of CAR T cells under different sources of variability. Particularly, we demonstrate that CD28-bearing CARs mediate a faster and more consistent population response under both target antigen variability and kinetic rate variability. Next, we identify kinetic parameters that have the most impact on cell response time. Finally, based on our findings, we propose that enhancing the catalytic activity of lymphocyte-specific protein tyrosine kinase can result in drastically reduced and more consistent response times among heterogeneous CAR T-cell populations.

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Modelling predicts differences in chimeric antigen receptor T-cell signalling due to biological variability

Cited by 4 publications

References 34 publications

Enhanced extracellular matrix remodeling due to embedded spheroid fluidization

Enhanced extracellular matrix remodeling due to embedded spheroid fluidization

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

Modelling predicts differences in chimeric antigen receptor T-cell signalling due to biological variability

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