Completed Cancer Infection & Immunity

The molecular basis of gamma delta T cell recognition in health and disease.

In plain English

AI plain-English summary

A type of white blood cell called gamma/delta T cells can detect infections and tumours, but no one knows exactly how they do it at a molecular level. This matters because the immune system has two parallel detection systems. One—alpha/beta T cells and B cells—is well understood and forms the basis of vaccines and immunotherapies. The other—gamma/delta T cells—was discovered at the same time, in the 1980s, but remains a black box. Researchers know these cells respond to stress signals from infected or cancerous cells, but they do not know what molecules trigger that response, how those molecules appear on a cell’s surface, or how the T cell receptor physically binds to them. Without that knowledge, the entire gamma/delta system is unusable for medicine. This project aims to crack that problem by identifying the specific molecules that human gamma/delta T cells recognise, characterising how those molecules change during disease, and mapping the T cell populations that respond. The lab has already found two novel targets for these cells. If successful, this fundamental science could open a new branch of immunotherapy—one that targets stress signals common across many cancers and infections, rather than the single proteins targeted by current treatments. That is a long-term goal, but understanding the basic recognition mechanism is the necessary first step.

View original technical description
Gamma/delta T-cells have co-evolved alongside alpha/beta T-cells and B cells, and are increasingly recognized as mediating important non-redundant roles in lymphoid stress surveillance, during both pathogen infection and anti-tumour immunity. However, whereas alpha/beta T-cells and B cells are relatively well characterised, we lack the most basic knowledge of gamma/delta T-cell recognition. Indeed, despite gamma, delta, alpha and beta TCR genes being discovered contemporaneously in the 1980s, th e central issue of the role of the gamma/delta TCR in antigen recognition, remains unresolved at a molecular level. The nature of the antigens recognized by gamma/delta T-cells, and how their expression on target cells communicates signals of infection or non-microbial stress to T-cells that respond to them, remain some of the most fundamental unanswered questions in vertebrate immunology. This proposal outlines a comprehensive attempt to address these questions by defining the molecular ba sis of gamma/delta T-cell antigen recognition. Focusing predominantly on human Vdelta2-negative gamma/delta T-cells, it employs diverse molecular techniques focused on five key goals: (i)identification of gamma/delta TCR ligands (ii)characterizing their regulation/dysregulation in disease (iii)understanding how in molecular terms they are recognized and in what cellular context (iv)defining key gamma/delta T-cell populations that respond to them (v)investigating therapeutic exploitation of gamma /delta T-cell recognition. It capitalizes on studies in my laboratory that have identified two novel non-MHC ligands for human gamma/delta TCRs, facilitated by an outstanding group of UK/international collaborators. These studies should provide a major step forward in our understanding of, and ultimately in our therapeutic exploitation of, gamma/delta T-cell recognition.

View the original record at the funder ↗

Researchers

Benjamin Willcox (EPMC Awardee)

Related Research

Grants with similar aims, by meaning.

Molecular mechanisms of phosphoantigen sensing by human gamma delta T cells
Exploring innate-like and adaptive gamma delta T cell paradigms in health and disease
Understanding thymic acquisition of gamma/delta T cell effector function
Defining signals of cellular stress recognized by tumour-reactive gamma delta T cells
Understanding T cell receptor (TCR) signalling requirements for thymic gamma/delta cell development; are gamma/delta cells selected through their TCR?.

Original classification

Investigator Award in Science

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.