T cell surfaces are covered with microvilli, actin-rich and flexible protrusions. We use super-resolution microscopy to show that ≥90% of T cell receptor (TCR) complex molecules TCRαβ and TCRζ, as well as the co-receptor CD4 (cluster of differentiation 4) and the co-stimulatory molecule CD2, reside on microvilli of resting human T cells. Furthermore, TCR proximal signaling molecules involved in the initial stages of the immune response, including the protein tyrosine kinase Lck (lymphocyte-specific protein tyrosine kinase) and the key adaptor LAT (linker for activation of T cells), are also enriched on microvilli. Notably, phosphorylated proteins of the ERM (ezrin, radixin, and moesin) family colocalize with TCRαβ as well as with actin filaments, implying a role for one or more ERMs in linking the TCR complex to the actin cytoskeleton within microvilli. Our results establish microvilli as key signaling hubs, in which the TCR complex and its proximal signaling molecules and adaptors are preassembled prior to activation in an ERM-dependent manner, facilitating initial antigen sensing.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.celrep.2020.02.069 | DOI Listing |
J Immunother Cancer
December 2024
Swiss Institute of Bioinformatics, Lausanne, Switzerland
Background: The adoptive cell transfer (ACT) of T cell receptor (TCR)-engineered T cells targeting the HLA-A2-restricted epitope NY-ESO-1 (A2/NY) has yielded important clinical responses against several cancers. A variety of approaches are being taken to augment tumor control by ACT including TCR affinity-optimization and T-cell coengineering strategies to address the suppressive tumor microenvironment (TME). Most TCRs of clinical interest are evaluated in immunocompromised mice to enable human T-cell engraftment and do not recapitulate the dynamic interplay that occurs with endogenous immunity in a treated patient.
View Article and Find Full Text PDFMol Cells
January 2025
Laboratory of Host Defenses, Department of Biological Sciences, KAIST, Daejeon 34141, Republic of Korea; KAIST Institute of Health Science and Technology, KAIST, Daejeon 34141, Republic of Korea. Electronic address:
The role of γδ T cells in antitumor responses has gained significant attention due to their unique major histocompatibility complex (MHC)-independent killing mechanisms, which distinguish them from conventional αβ T cells. Notably, γδ tumor-infiltrating lymphocytes (TILs) have been identified as favorable prognostic markers in various cancers. However, γδ TIL subsets, including Vδ1, Vδ2, and Vδ3, exhibit distinct prognostic implications and phenotypes from one another within the tumor microenvironment (TME).
View Article and Find Full Text PDFFront Immunol
January 2025
Key Laboratory of Laboratory Medicine, Ministry of Education, School of Laboratory Medicine and Life Science, Wenzhou Medical University, Wenzhou, China.
Introduction: Challenges remain in reducing antigen escape and tumor recurrence while CAR-T cell therapy has substantially improved outcomes in the treatment of multiple myeloma. T cell receptor fusion construct (TRuC)-T cells, which utilize intact T cell receptor (TCR)-CD3 complex to eliminate tumor cells in a non-major histocompatibility complex (MHC)-restricted manner, represent a promising strategy. Moreover, interleukin-7 (IL-7) is known to enhance the proliferation and survival of T cells.
View Article and Find Full Text PDFFront Immunol
January 2025
Institute for Immunodeficiency, Center for Chronic Immunodeficiency, University Medical Center Freiburg, Freiburg, Germany.
Background: Hypomorphic mutations in the () gene cause a glycosylation disorder that leads to immunodeficiency. It is often associated with recurrent infections and atopy. The exact etiology of this condition remains unclear.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
School of Computer Science, The University of Birmingham, Edgbaston, Birmingham B15 2TT, U.K.
Predicting protein-protein interaction (PPI) binding affinities in unseen protein complex clusters is essential for elucidating complex protein interactions and for the targeted screening of peptide- or protein-based drugs. We introduce MCGLPPI++, a meta-learning framework designed to improve the adaptability of pretrained geometric models in such scenarios. To effectively boost the meta-learning optimization by injecting prior intersample distribution knowledge, three specially designed training sample cluster splitting patterns based on protein interaction interfaces are introduced.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!