ArticleBiophysical journal2018
Computational Model of Chimeric Antigen Receptors Explains Site-Specific Phosphorylation Kinetics.
Article in Biophysical journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
30 citing papers in PubMed, 1 synthesis or guideline pooled it, 46 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
- Review
- Parallel reactions on a single T cell receptor offer a robust kinetic proofreading mechanism.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- A Proteomics Outlook on the Molecular Effectors of CAR-T Cell Therapy in Cancer Management.Journal of proteome research · 2025Review
- A stochastic framework for evaluating CAR T cell therapy efficacy and variability.Mathematical biosciences · 2024Article
- Current advances in experimental and computational approaches to enhance CAR T cell manufacturing protocols and improve clinical efficacy.Frontiers in molecular medicine · 2024Review
- Harnessing CD3 diversity to optimize CAR T cells.Nature immunology · 2023Article
- Deconvolution of clinical variance in CAR-T cell pharmacology and response.Nature biotechnology · 2023Article
- PASCAR: a multiscale framework to explore the design space of constitutive and inducible CAR T cells.Life science alliance · 2023Article
- A systems and computational biology perspective on advancing CAR therapy.Seminars in cancer biology · 2023Review
- CD28-CAR-T cell activation through FYN kinase signaling rather than LCK enhances therapeutic performance.Cell reports. Medicine · 2023Article
- Toward high-throughput engineering techniques for improving CAR intracellular signaling domains.Frontiers in bioengineering and biotechnology · 2023Article
- Recent advances and clinical pharmacology aspects of Chimeric Antigen Receptor (CAR) T-cellular therapy development.Clinical and translational science · 2022Review
- Modelling predicts differences in chimeric antigen receptor T-cell signalling due to biological variability.Royal Society open science · 2022Article
- Spatially resolved in silico modeling of NKG2D signaling kinetics suggests a key role of NKG2D and Vav1 Co-clustering in generating natural killer cell activation.PLoS computational biology · 2022Article
- Data-driven learning how oncogenic gene expression locally alters heterocellular networks.Nature communications · 2022Article
- Mapping CAR T-Cell Design Space Using Agent-Based Models.Frontiers in molecular biosciences · 2022Article
- Dawn of a New Era for Membrane Protein Design.Biodesign research · 2022Review
- Design and development of engineered receptors for cell and tissue engineering.Current opinion in systems biology · 2021Article
- Comparative analysis of TCR and CAR signaling informs CAR designs with superior antigen sensitivity and in vivo function.Science signaling · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Chimeric antigen receptors (CARs) have recently been approved for the treatment of hematological malignancies, but our lack of understanding of the basic mechanisms that activate these proteins has made it difficult to optimize and control CAR-based therapies. In this study, we use phosphoproteomic mass spectrometry and mechanistic computational modeling to quantify the in vitro kinetics of individual tyrosine phosphorylation on a variety of CARs. We show that each of the 10 tyrosine sites on the CD28-CD3ζ CAR is phosphorylated by lymphocyte-specific protein-tyrosine kinase (LCK) with distinct kinetics. The addition of CD28 at the N-terminal of CD3ζ increases the overall rate of CD3ζ phosphorylation. Our computational model identifies that LCK phosphorylates CD3ζ through a mechanism of competitive inhibition. This model agrees with previously published data in the literature and predicts that phosphatases in this system interact with CD3ζ through a similar mechanism of competitive inhibition. This quantitative modeling framework can be used to better understand CAR signaling and T cell activation.
Indexed as
Identifiers
What OpenQuestion holds
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.