ArticleJournal of theoretical biology2020
Data-driven analysis of a mechanistic model of CAR T cell signaling predicts effects of cell-to-cell heterogeneity.
Article in Journal of theoretical biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it, 43 citations in OpenAlex.
- A Systematic Review of the Efforts and Hindrances of Modeling and Simulation of CAR T-cell Therapy.The AAPS journal · 2021Pooled it
- Artificial intelligence-enabled multi-scale virtual cell: perspective, challenges, and opportunities.Briefings in bioinformatics · 2026Review
- ASAS-NANP SYMPOSIUM: Mathematical modeling in animal nutrition-modeling in the agriculture 4.0 era and beyond: merging mechanistic knowledge and artificial intelligence with hybrid modeling.Journal of animal science · 2026Article
- Mathematical modeling of combinatorial antigen targeting with multiple CAR T-cell products for glioblastoma treatment.NPJ systems biology and applications · 2026Article
- Navigating the landscape of personalized oncology: overcoming challenges and expanding horizons with computational modeling.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Systems modeling and uncertainty quantification of AMP-activated protein kinase signaling.NPJ systems biology and applications · 2025Article
- LAG3+ CD8+ T cell subset drives HR+/HER2- breast cancer reduction in bispecific antibody armed activated T cell therapy.Journal of immunology (Baltimore, Md. : 1950) · 2025Article
- Prolonged Hyperactivity Elicits Massive and Persistent Chloride Ion Redistribution in Subsets of Cultured Hippocampal Dentate Granule Cells.bioRxiv : the preprint server for biology · 2025Article
- Design specifications for biomedical virtual twins in engineered adoptive cellular immunotherapies.NPJ digital medicine · 2025Review
- A stochastic framework for evaluating CAR T cell therapy efficacy and variability.Mathematical biosciences · 2024Article
- Synthetic living materials in cancer biology.Nature reviews bioengineering · 2023Article
- Information-Theoretic Analysis of a Model of CAR-4-1BB-Mediated NFκB Activation.Bulletin of mathematical biology · 2023Article
- A systems and computational biology perspective on advancing CAR therapy.Seminars in cancer biology · 2023Review
- Proof-of-concept for incorporating mechanistic insights from multi-omics analyses of polymyxin B in combination with chloramphenicol against Klebsiella pneumoniae.CPT: pharmacometrics & systems pharmacology · 2023Article
- Computational model of CAR T-cell immunotherapy dissects and predicts leukemia patient responses at remission, resistance, and relapse.Journal for immunotherapy of cancer · 2022Article
- A computational modeling approach for predicting multicell spheroid patterns based on signaling-induced differential adhesion.PLoS computational biology · 2022Article
- Recent advances and clinical pharmacology aspects of Chimeric Antigen Receptor (CAR) T-cellular therapy development.Clinical and translational science · 2022Review
- Computational analysis of 4-1BB-induced NFκB signaling suggests improvements to CAR cell design.Cell communication and signaling : CCS · 2022Article
- Modelling predicts differences in chimeric antigen receptor T-cell signalling due to biological variability.Royal Society open science · 2022Article
- Mapping CAR T-Cell Design Space Using Agent-Based Models.Frontiers in molecular biosciences · 2022Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Due to the variability of protein expression, cells of the same population can exhibit different responses to stimuli. It is important to understand this heterogeneity at the individual level, as population averages mask these underlying differences. Using computational modeling, we can interrogate a system much more precisely than by using experiments alone, in order to learn how the expression of each protein affects a biological system. Here, we examine a mechanistic model of CAR T cell signaling, which connects receptor-antigen binding to MAPK activation, to determine intracellular modulations that can increase cellular response. CAR T cell cancer therapy involves removing a patient's T cells, modifying them to express engineered receptors that can bind to tumor-associated antigens to promote tumor cell killing, and then injecting the cells back into the patient. This population of cells, like all cell populations, would have heterogeneous protein expression, which could affect the efficacy of treatment. Thus, it is important to examine the effects of cell-to-cell heterogeneity. We first generated a dataset of simulated cell responses via Monte Carlo simulations of the mechanistic model, where the initial protein concentrations were randomly sampled. We analyzed the dataset using partial least-squares modeling to determine the relationships between protein expression and ERK phosphorylation, the output of the mechanistic model. Using this data-driven analysis, we found that only the expressions of proteins relating directly to the receptor and the MAPK cascade, the beginning and end of the network, respectively, are relevant to the cells' response. We also found, surprisingly, that increasing the amount of receptor present can actually inhibit the cell's ability to respond due to increasing the strength of negative feedback from phosphatases. Overall, we have combined data-driven and mechanistic modeling to generate detailed insight into CAR T cell signaling.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.