P0010 Characterization of Proliferating Memory CD4⁺ T Cells Reveals a Distinct Immune Signature in Anti-Α4β7 Integrin Therapy Non-Responders Inflammatory Bowel Disease Patients
Journal of Crohn's and Colitis（2025）
Abstract
Abstract Background Failure to respond to the anti-α4β7 integrin therapy, vedolizumab, is observed in a subset of inflammatory bowel disease (IBD) patients, potentially linked to distinct T cell activation profiles. This study aims to characterize the transcriptional and phenotypic features of circulating memory CD4⁺ T cells in vedolizumab non-responders and their association with treatment resistance. Methods We performed multidimensional flow cytometry and single-cell RNA sequencing to analyze IBD patients' circulating memory CD4⁺ T cell compartment, comparing pre- and post-treatment peripheral blood samples from vedolizumab responders and non-responders. Proteogenomic analysis and TCR repertoire profiling of CD4⁺ T cells were conducted using matched peripheral blood samples. Flow cytometry characterized T cell subsets based on surface markers, migration receptors, transcription factors, and cytokine expression, focusing on differences in activation and migration profiles. Results Ki67⁺ cells were enriched in the memory CD4⁺ T cell population of vedolizumab non-responders in both UC and CD, confirmed by two independent cohorts. TCR repertoire analysis showed increased diversity in memory CD4⁺ T cells post-treatment. Single-cell sequencing and proteomics revealed these Ki67⁺ cells had a high activation and proliferation profile (HLA-DR, CD40LG, MKI67) with reduced IL7R and SELL expression. They displayed elevated integrins (α4, β1, β7) and gut-homing receptors (CXCR3, CCR6). Upregulated T-bet, EOMES, and RORγt and increased IL-17A, indicated a pro-inflammatory Th1/Th17 phenotype in non-responders. Conclusion Ki67⁺ memory CD4⁺ T cells are significantly enriched in the peripheral blood of vedolizumab non-responders, displaying a distinct transcriptional and phenotypic profile characterized by Th1/Th17 polarization, high integrin α4β1 expression, and enhanced gut-homing capacity. These findings indicate that proliferating effector memory CD4⁺ T cells could contribute to therapy resistance in IBD, emphasizing the need for alternative therapeutic strategies targeting these cells in anti-α4β7 integrin therapy non-responders.
MoreTranslated text
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined