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Updated: Aug 28, 2025
![Dynamic Imaging of Chimeric Antigen Receptor T Cells with [18F]Tetrafluoroborate Positron Emission Tomography/Computed Tomography](/_next/image?url=https%3A%2F%2Fcloudfront.jove.com%2FCDNSource%2Fteasers%2F62334.jpg&w=3840&q=50)
Dynamic Imaging of Chimeric Antigen Receptor T Cells with [18F]Tetrafluoroborate Positron Emission Tomography/Computed Tomography
Published on: February 17, 2022
Investigation of CRS-associated cytokines in CAR-T therapy with meta-GNN and pathway crosstalk
Zhenyu Wei1, Qi Cheng1, Nan Xu2,3
1College of Intelligent Systems Science and Engineering, Institute of Intelligent System and Bioinformatics, Harbin Engineering University, Harbin, 150001, China.
Background:
Chimeric antigen receptor T-cell (CAR-T) therapy is a new and efficient cellular immunotherapy. The therapy shows significant efficacy, but also has serious side effects, collectively known as cytokine release syndrome (CRS). At present, some CRS-related cytokines and their roles in CAR-T therapy have been confirmed by experimental studies. However, the mechanism of CRS remains to be fully understood.
Methods:
Based on big data for human protein interactions and meta-learning graph neural network, we employed known CRS-related cytokines to comprehensively investigate the CRS associated cytokines in CAR-T therapy through protein interactions. Subsequently, the clinical data for 119 patients who received CAR-T therapy were examined to validate our prediction results. Finally, we systematically explored the roles of the predicted cytokines in CRS occurrence by protein interaction network analysis, functional enrichment analysis, and pathway crosstalk analysis.
Results:
We identified some novel cytokines that would play important roles in biological process of CRS, and investigated the biological mechanism of CRS from the perspective of functional analysis.
Conclusions:
128 cytokines and related molecules had been found to be closely related to CRS in CAR-T therapy, where several important ones such as IL6, IFN-γ, TNF-α, ICAM-1, VCAM-1 and VEGFA were highlighted, which can be the key factors to predict CRS.
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