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T cells are a critical part of the adaptive immune system that are able to distinguish between healthy and unhealthy cells. Upon recognition of protein fragments (peptides), activated T cells will contribute to the immune response and help clear infection. The major histocompatibility complex (MHC) molecules, or human leukocyte antigens (HLA) in humans, bind these peptides to present them to T cells that recognise them with their surface T cell receptors (TCR). This recognition event is the first step that leads to T cell activation, and in turn can dictate disease outcomes. The visualisation of TCR interaction with pMHC using structural biology has been crucial in understanding this key event, unravelling the parameters that drive this interaction and their impact on the immune response. The last five years has been the most productive within the field, wherein half of current unique TCR–pMHC-I structures to date were determined within this time. Here, we review the new insights learned from these recent TCR–pMHC-I structures and their impact on T cell activation.

To redirect T cells against tumor cells, T cells can be engineered ex vivo to express cancer-antigen specific T cell receptors (TCRs), generating products known as TCR-engineered T cells (TCR T). Unlike chimeric antigen receptors (CARs), TCRs recognize HLA-presented peptides derived from proteins of all cellular compartments. The use of TCR T cells for adoptive cellular therapies (ACT) has gained increased attention, especially as efforts to treat solid cancers with ACTs have intensified. In this review, we describe the differing mechanisms of T cell antigen recognition and signal transduction mediated through CARs and TCRs. We describe the classes of cancer antigens recognized by current TCR T therapies and discuss both classical and emerging pre-clinical strategies for antigen-specific TCR discovery, enhancement, and validation. Finally, we review the current landscape of clinical trials for TCR T therapy and discuss what these current results indicate for the development of future engineered TCR approaches.

The diversity of antigen receptors and the specificity it underlies are the hallmarks of the cellular arm of the adaptive immune system. T and B lymphocytes are indeed truly unique in their ability to generate receptors capable of recognizing virtually any pathogen. It has been known for several decades that T lymphocytes recognize short peptides derived from degraded proteins presented by major histocompatibility complex （MHC） molecules at the cell surface. Interaction between peptide-MHC （pMHC） and the T cell receptor （TCR） is central to both thymic selection and peripheral antigen recognition. It is widely assumed that TCR diversity is required, or at least highly desirable, to provide sufficient immune coverage. However, a number of immune responses are associated with the selection of predictable, narrow, or skewed repertoires and public TCR chains. Here, we summarize the current knowledge on the formation of the TCR repertoire and its maintenance in health and disease. We also outline the various molecular mechanisms that govern the composition of the pre-selection, naive and antigen-specific TCR repertoires. Finally, we suggest that with the development of high-throughput sequencing, common TCR ＇signatures＇ raised against specific antigens could provide important diagnostic biomarkers and surrogate predictors of disease onset, progression and outcome.

Recombinant antibodies and, more recently, T cell receptor (TCR)-engineered T cell therapies represent two immunological strategies that have come to the forefront of clinical interest for targeting intracellular neoantigens in benign and malignant diseases. T cell-based therapies targeting neoantigens use T cells expressing a recombinant complete TCR (TCR-T cell), a chimeric antigen receptor (CAR) with the variable domains of a neoepitope-reactive TCR as a binding domain (TCR-CAR-T cell) or a TCR-like antibody as a binding domain (TCR-like CAR-T cell). Furthermore, the synthetic T cell receptor and antigen receptor (STAR) and heterodimeric TCR-like CAR (T-CAR) are designed as a double-chain TCRαβ-based receptor with variable regions of immunoglobulin heavy and light chains (VH and VL) fused to TCR-Cα and TCR-Cβ, respectively, resulting in TCR signaling. In contrast to the use of recombinant T cells, anti-neopeptide MHC (pMHC) antibodies and intrabodies neutralizing intracellular neoantigens can be more easily applied to cancer patients. However, different limitations should be considered, such as the loss of neoantigens, the modification of antigen peptide presentation, tumor heterogenicity, and the immunosuppressive activity of the tumor environment. The simultaneous application of immune checkpoint blocking antibodies and of CRISPR/Cas9-based genome editing tools to engineer different recombinant T cells with enhanced therapeutic functions could make T cell therapies more efficient and could pave the way for its routine clinical application.

Background The T-cell receptor (TCR), located on the surface of T cells, is responsible for the recognition of the antigen-major histocompatibility complex, leading to the initiation of an inflammatory response. Analysing the TCR repertoire may help to gain a better understanding of the immune system features and of the aetiology and progression of diseases, in particular those with unknown antigenic triggers. The extreme diversity of the TCR repertoire represents a major analytical challenge; this has led to the development of specialized methods which aim to characterize the TCR repertoire in-depth. Currently, next generation sequencing based technologies are most widely employed for the high-throughput analysis of the immune cell repertoire. Results Here, we report on the latest methodological advancements in the field by describing and comparing the available tools; from the choice of the starting material and library preparation method, to the sequencing technologies and data analysis. Finally, we provide a practical example and our own experience by reporting some exemplary results from a small internal benchmark study, where current approaches from the literature and the market are employed and compared. Conclusions Several valid methods for clonotype identification and TCR repertoire analysis exist, however, a gold standard method for the field has not yet been identified. Depending on the purpose of the scientific study, some approaches may be more suitable than others. Finally, due to possible method specific biases, scientists must be careful when comparing results obtained using different methods.

Background Deep immune receptor sequencing, RepSeq, provides unprecedented opportunities for identifying and studying condition-associated T-cell clonotypes, represented by T-cell receptor (TCR) CDR3 sequences. However, due to the immense diversity of the immune repertoire, identification of condition relevant TCR CDR3s from total repertoires has mostly been limited to either “public” CDR3 sequences or to comparisons of CDR3 frequencies observed in a single individual. A methodology for the identification of condition-associated TCR CDR3s by direct population level comparison of RepSeq samples is currently lacking. Results We present a method for direct population level comparison of RepSeq samples using immune repertoire sub-units (or sub-repertoires) that are shared across individuals. The method first performs unsupervised clustering of CDR3s within each sample. It then finds matching clusters across samples, called immune sub-repertoires, and performs statistical differential abundance testing at the level of the identified sub-repertoires. It finally ranks CDR3s in differentially abundant sub-repertoires for relevance to the condition. We applied the method on total TCR CDR3β RepSeq datasets of celiac disease patients, as well as on public datasets of yellow fever vaccination. The method successfully identified celiac disease associated CDR3β sequences, as evidenced by considerable agreement of TRBV-gene and positional amino acid usage patterns in the detected CDR3β sequences with previously known CDR3βs specific to gluten in celiac disease. It also successfully recovered significantly high numbers of previously known CDR3β sequences relevant to each condition than would be expected by chance. Conclusion We conclude that immune sub-repertoires of similar immuno-genomic features shared across unrelated individuals can serve as viable units of immune repertoire comparison, serving as proxy for identification of condition-associated CDR3s.

The complexity of intestinal homeostasis results from the ability of the intestinal epithelium to absorb nutrients, harbor multiple external and internal antigens, and accommodate diverse immune cells. Intestinal intraepithelial lymphocytes (IELs) are a unique cell population embedded within the intestinal epithelial layer, contributing to the formation of the mucosal epithelial barrier and serving as a first-line defense against microbial invasion. TCRαβ + CD4 - CD8αα + CD8αβ - and TCRγδ + CD4 - CD8αα + CD8αβ - IELs are the two predominant subsets of natural IELs. These cells play an essential role in various intestinal diseases, such as infections and inflammatory diseases, and act as immune regulators in the gut. However, their developmental and functional patterns are extremely distinct, and the mechanisms underlying their development and migration to the intestine are not fully understood. One example is that Bcl-2 promotes the survival of thymic precursors of IELs. Mature TCRαβ + CD4 - CD8αα + CD8αβ - IELs seem to be involved in immune regulation, while TCRγδ + CD4 - CD8αα + CD8αβ - IELs might be involved in immune surveillance by promoting homeostasis of host microbiota, protecting and restoring the integrity of mucosal epithelium, inhibiting microbiota invasion, and limiting excessive inflammation. In this review, we elucidated and organized effectively the functions and development of these cells to guide future studies in this field. We also discussed key scientific questions that need to be addressed in this area.

T-regulatory cells (Tregs) represent a unique subpopulation of helper T-cells by maintaining immune equilibrium using various mechanisms. The role of T-cell receptors (TCR) in providing homeostasis and activation of conventional T-cells is well-known; however, for Tregs, this area is understudied. In the last two decades, evidence has accumulated to confirm the importance of the TCR in Treg homeostasis and antigen-specific immune response regulation. In this review, we describe the current view of Treg subset heterogeneity, homeostasis and function in the context of TCR involvement. Recent studies of the TCR repertoire of Tregs, combined with single-cell gene expression analysis, revealed the importance of TCR specificity in shaping Treg phenotype diversity, their functions and homeostatic maintenance in various tissues. We propose that Tregs, like conventional T-helper cells, act to a great extent in an antigen-specific manner, which is provided by a specific distribution of Tregs in niches.

[This corrects the article DOI: 10.3389/fimmu.2022.960920.].[This corrects the article DOI: 10.3389/fimmu.2022.960920.].

Background Deep ‘bulk’ T-cell receptor (TCR) sequencing is a comprehensive approach to gauge the TCR repertoire in clinical specimens to address spatio-temporal differences in TCR compositions. Clonal T-cell expansion in the course of anti-cancer directed cellular immune responses can be antigen-driven, either by commonly shared or mutant tumor-associated antigens (TAAs), by viral targets, or reflect ‘bystander activation’ of T-cell clones. Different analytic tools and platforms are available to describe the molecular texture of the TCR composition. We report here on an open-access platform ‘TCRcloud’ that enables to address the unmet need to visualize TCR diversity in cellular immune response, e.g. to checkpoint blockade therapies, termed ‘clonal replacement’. We took advantage of a publicly available dataset that linked TCR composition analysis with clinically relevant responses to immune checkpoint inhibitor (ICI) treatment and visualized the TCR changes using the TCRcloud platform described in this report. In order to test ‘real world data’, we visualized TCRs and B-cell receptors (BCRs) in blood and matching tumor tissue from 3 patients with pancreatic cancer. Results TCRcloud, is a computational tool to screen the ‘TCR data warehouse’ for biologically and clinically relevant patterns, i.e. the CDR3 length, number of unique CDR3 transcripts, TCR convergence, different indices gauging the TCR composition in biological samples, i.e. the D50 Index, Gini Coefficient, Shannon Index, Gini-Simpson Index, Chao1 index, as well as the changes in amino acid usage at each position of the TCR and BCR CDR3. TCRcloud is a free open-source software distributed under the MIT license and available from https://github.com/eriicdesousa/TCRcloud or via the Python Package Index (PyPI). TCRcloud is compatible with both TCR and BCR molecular datasets if these fulfill Adaptive Immune Receptor Repertoire (AIRR) community standards. The analysis of a public TCR database allowed us to select a subject to demonstrate detailed molecular changes in the CDR3 TCR datasets which have been associated with relevant clinical responses in patients with basal cell cancer or squamous cell carcinoma receiving checkpoint inhibitor treatment (Yost et al. 10.1038/s41591-019–0522-3). Analysis of real world immune receptor sequencing data obtained from tissue from patients with cancer allowed us to demonstrate the different dynamics in the TCR and BCR in blood and corresponding tumor from of 3 patients with pancreatic cancer. Conclusion TCRcloud enables to i) intuitively visualize molecular TCR compositions, ii) combine different TCR repertoire measurements within a single radar plot to capture biologically relevant TCR indices in a single image iii) visualize the usage of the V-genes and iv) visualize the frequency of amino acids in the CDR3. This easy to use tool enables to intuitively visualize changes in bulk TCR and BCR compositions in association with immunotherapies in a spatio-temporal fashion.