FOXP3+ regulatory T (Treg) cells are necessary to coordinate resolution of lung inflammation and a return to homeostasis after respiratory viral infections, but the specific molecular requirements for these functions and the cell types governed by Treg cells remain unclear. This question holds significance as clinical trials of Treg cell transfer therapy for respiratory viral infection are being planned and executed. Here, we report causal experiments in mice determining that Treg cells are necessary to control the numbers of activated CD8+ T cells during recovery from influenza infection. Using a genetic strategy paired with adoptive transfer techniques, we determined that Treg cells require the transcription factor TBET to regulate these potentially pro-inflammatory CD8+ T cells. Surprisingly, we found that Treg cells are dispensable for the generation of CD8+ lung tissue resident-memory T (Trm) cells yet similarly influence the transcriptional programming of CD8+ Trm and activated T cells. Our study highlights the role of Treg cells in regulating the CD8+ T cell response during recovery from influenza infection.
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http://dx.doi.org/10.1101/2024.05.30.596295 | DOI Listing |
Blood
January 2025
Stanford University Medical Center, Stanford, California, United States.
Allogeneic hematopoietic cell transplantation (HCT) is a curative therapy limited by graft-versus-host disease (GVHD). In preclinical studies and early-phase clinical studies enrichment of donor regulatory T cells (Tregs) appears to prevent GVHD and promote healthy immunity.We enrolled 44 patients on an open-label, single-center, phase 2 efficacy study investigating if a precision selected and highly purified Treg cell therapy manufactured from donor mobilized peripheral blood improves one-year GVHD-free relapse free survival (GRFS) after myeloablative conditioning (trial NCT01660607).
View Article and Find Full Text PDFSci Immunol
January 2025
Laboratory of Molecular Immunology and Immunology Center, National Heart, Lung, and Blood Institute, National Institutes of Health (NIH), Bethesda, MD 20892, USA.
Thymic stromal lymphopoietin (TSLP) is a type I cytokine that promotes allergic responses and mediates type 2 immunity. A balance between effector T cells (T), which drive the immune response, and regulatory T cells (T), which suppress the response, is required for proper immune homeostasis. Here, we report that TSLP differentially acts on T versus T to balance type 2 immunity.
View Article and Find Full Text PDFSci Immunol
January 2025
Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, GA, USA.
Regulatory T cells (T) accumulate in the visceral adipose tissue (VAT) to maintain systemic metabolic homeostasis but decline during obesity. Here, we explored the metabolic pathways controlling the homeostasis, composition, and function of VAT T under normal and high-fat diet feeding conditions. We found that cholesterol metabolism was specifically up-regulated in ST2 VAT T subsets.
View Article and Find Full Text PDFBrain Behav
January 2025
Department of Neurology, The First Affiliated Hospital, Jinan University, Guangzhou, Guangdong, China.
Background: The involvement of immune cells in the pathophysiology of intracerebral hemorrhage (ICH) is becoming increasingly recognized, yet their specific causal contributions remain uncertain. The objective of this research is to uncover the potential causal interactions between diverse immune cells and ICH using Mendelian randomization (MR) analysis.
Methods: Genetic variants associated with 731 immune cell traits were sourced from a comprehensive genome-wide association study (GWAS) involving 3757 participants.
Biol Direct
January 2025
School of Medicine, South China University of Technology, Guangzhou, 510006, China.
Background: Pancreatic cancer is characterized by a complex tumor microenvironment that hinders effective immunotherapy. Identifying key factors that regulate the immunosuppressive landscape is crucial for improving treatment strategies.
Methods: We constructed a prognostic and risk assessment model for pancreatic cancer using 101 machine learning algorithms, identifying OSBPL3 as a key gene associated with disease progression and prognosis.
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