TCRα reporter mice reveal contribution of dual TCRα expression to T cell repertoire and function

scRNA+ TCR-seq revealed dual TCR T cells antitumor response in the TME of NSCLC

The intricate origins, subsets, and characteristics of TCR (T Cell Receptor) s, along with the mechanisms underpinning the antitumor response of tumor-infiltrating T lymphocytes within the tumor microenvironment (TME) remain enigmatic. Recently, the advent of single-cell RNA+TCR-sequencing (scRNA+TCR seq) has revolutionized TME analysis, providing unprecedented insight into the origins, cell subsets, TCR CDR3 compositions, and the expression patterns of response/depletion factors within individual tumor-infiltrating T lymphocytes. Our analysis of the shared scRNA+TCR seq dataset revealed a substantial presence of dual TCR T cells, characterized by clonal hyperplasia and remarkable migratory prowess across various tissues, including blood, normal, peritumoral, and tumor tissues in non-small cell lung cancer patients. Notably, dual TCR CD8+T cells predominantly fell within the CXCL13+subset, displaying potent antitumor activity and a strong preference for tumor tissue residency. Conversely, dual TCR CD4+T cells were predominantly classified as CD5+ or LMNA+subsets, exhibiting a more even distribution across diverse tissue types. By harnessing scRNA+TCR seq and other cutting-edge technologies, we can delve deeper into the effects and mechanisms that regulate the antitumor response or tolerance of dual TCR T cells. This innovative approach holds immense promise in offering fresh perspectives and avenues for advancing research on TIL (Tumor infiltrating lymphocyte)s within the TME.

scRNA+TCR+BCR-seq revealed the proportions and gene expression patterns of dual receptor T and B lymphocytes in NPC and NLH

While the relationship between single receptor lymphocytes and cancer has been deeply researched, the origin and biological roles of dual receptor lymphocytes in tumor microenvironment (TME) remain largely unknown. And since nasopharyngeal carcinoma (NPC) is a type of cancer closely associated with immune infiltration, studying the TME of NPC holds particular significance. Utilizing single-cell RNA sequencing combined with T cell receptor (TCR) and B cell receptor (BCR) sequencing (scRNA + TCR + BCR-seq), we analyzed data from 7 patients with NPC and 3 patients with nasopharyngeal lymphatic hyperplasia (NLH). In our research, it was firstly found that the presence of dual receptor lymphocytes in both the TME of NPC and the inflammatory environment of NLH. We also confirmed their clonal expansion, suggesting their potential involvement in the immune response. Subsequently, we further discovered the lineage and the pairing characteristics. It was found that the dual receptor lymphocytes in NPC and NLH mainly originate from memory cells, and the predominant pairing type for dual TCR was β+α1+α2 and dual BCR was heavy+κ+λ. By further analyzing their gene expression, we compared the function of dual receptor cells with single receptor cells in the context of both NPC and NLH. This groundbreaking research has enhanced our comprehension of the features of dual-receptor cells and has contributed to a better understanding of the TME in NPC. By comparing with NLH, it illuminates part of the alterations in the process of malignant transformation in NPC. These findings present the potential to acquire improved diagnostic markers and treatment modalities.

Association of intestinal dysbiosis with susceptibility to multiple sclerosis: Evidence from different population studies (Review)

Understanding the relationship between microorganisms that live in our intestines and neuroinflammatory and neurodegenerative pathologies of the central nervous system (CNS) is essential, since they have been shown to have an immunomodulatory effect in neurological disorders, such as multiple sclerosis (MS). The gut microbiota can be affected by several environmental factors, including infections, physical and emotional stress and diet, the latter known as the main modulator of intestinal bacteria. An abrupt shift in the gut microbiota composition and function is known as dysbiosis, a state of local and systemic inflammation produced by pathogenic bacteria and its metabolites responsible for numerous neurological symptoms. It may also trigger neuronal damage in patients diagnosed with MS. Intestinal dysbiosis affects the permeability of the intestine, allowing chronic low-grade bacterial translocation from the intestine to the circulation, which may overstimulate immune cells and cells resident in the CNS, break immune tolerance and, in addition, alter the permeability of the blood-brain barrier (BBB). This way, toxins, inflammatory molecules and oxidative stress molecules can pass freely into the CNS and cause extensive damage to the brain. However, commensal bacteria, such as the Lactobacillus genus and Bacteroides fragilis, and their metabolites (with anti-inflammatory potential), produce neurotransmitters such as γ-aminobutyric acid, histamine, dopamine, norepinephrine, acetylcholine and serotonin, which are important for neurological regulation. In addition, reprogramming the gut microbiota of patients with MS with a healthy gut microbiota may help improve the integrity of the gut and BBB, by providing clinically protective anti-inflammatory effects and reducing the disease's degenerative progression. The present review provides valuable information about the relationship between gut microbiota and neuroinflammatory processes of the CNS. Most importantly, it highlights the importance of intestinal bacteria as an environmental factor that may mediate the clinical course of MS, or even predispose to the outbreak of this disease.

Viral infection reveals hidden sharing of TCR CDR3 sequences between individuals

The T cell receptor is generated by a process of random and imprecise somatic recombination. The number of possible T cell receptors which this process can produce is enormous, greatly exceeding the number of T cells in an individual. Thus, the likelihood of identical TCRs being observed in multiple individuals (public TCRs) might be expected to be very low. Nevertheless such public TCRs have often been reported. In this study we explore the extent of TCR publicity in the context of acute resolving Lymphocytic choriomeningitis virus (LCMV) infection in mice. We show that the repertoire of effector T cells following LCMV infection contains a population of highly shared TCR sequences. This subset of TCRs has a distribution of naive precursor frequencies, generation probabilities, and physico-chemical CDR3 properties which lie between those of classic public TCRs, which are observed in uninfected repertoires, and the dominant private TCR repertoire. We have named this set of sequences "hidden public" TCRs, since they are only revealed following infection. A similar repertoire of hidden public TCRs can be observed in humans after a first exposure to SARS-COV-2. The presence of hidden public TCRs which rapidly expand following viral infection may therefore be a general feature of adaptive immunity, identifying an additional level of inter-individual sharing in the TCR repertoire which may form an important component of the effector and memory response.

Individual Epitope-Specific CD8+ T Cell Immune Responses Are Shaped Differently during Chronic Viral Infection

A hallmark in chronic viral infections are exhausted antigen-specific CD8⁺ T cell responses and the inability of the immune system to eliminate the virus. Currently, there is limited information on the variability of epitope-specific T cell exhaustion within one immune response and the relevance to the T cell receptor (TCR) repertoire. The aim of this study was a comprehensive analysis and comparison of three lymphocytic choriomeningitis virus (LCMV) epitope-specific CD8⁺ T cell responses (NP396, GP33 and NP205) in a chronic setting with immune intervention, e.g., immune checkpoint inhibitor (ICI) therapy, in regard to the TCR repertoire. These responses, though measured within the same mice, were individual and independent from each other. The massively exhausted NP396-specific CD8⁺ T cells revealed a significantly reduced TCR repertoire diversity, whereas less-exhausted GP33-specific CD8⁺ T cell responses were rather unaffected by chronicity in regard to their TCR repertoire diversity. NP205-specific CD8⁺ T cell responses showed a very special TCR repertoire with a prominent public motif of TCR clonotypes that was present in all NP205-specific responses, which separated this from NP396- and GP33-specific responses. Additionally, we showed that TCR repertoire shifts induced by ICI therapy are heterogeneous on the epitope level, by revealing profound effects in NP396-, less severe and opposed effects in NP205-, and minor effects in GP33-specific responses. Overall, our data revealed individual epitope-specific responses within one viral response that are differently affected by exhaustion and ICI therapy. These individual shapings of epitope-specific T cell responses and their TCR repertoires in an LCMV mouse model indicates important implications for focusing on epitope-specific responses in future evaluations for therapeutic approaches, e.g., for chronic hepatitis virus infections in humans.

Dual receptor T cells mediate effective antitumor immune responses via increased recognition of tumor antigens

BACKGROUND

Discovery that ~16% of T cells naturally co-express two T-cell receptor (TCR) clonotypes prompts examining the role of dual TCR cells in immune functions.

METHODS

Using TCRα-reporter transgenic mice, enabling unambiguous identification of single-TCR and dual-TCR cells, we tested the role of dual TCR cells in antitumor immune responses against immune-responsive syngeneic 6727 sarcoma and immune-resistant B16F10 melanoma.

RESULTS

Dual TCR cells were specifically increased among tumor-infiltrating lymphocytes (TILs) in both models, indicating selective advantage in antitumor responses. Phenotype and single-cell gene expression analyses identified dual TCR are predominant during the effective antitumor response, demonstrating selectively increased activation in the TIL compartment and skewing toward an effector memory phenotype. Absence of dual TCR cells impaired immune response to B16F10 but not 6727, suggesting that dual TCR cells may be more influential in responses against poorly immunogenic tumors. Dual TCR cells demonstrated an advantage in recognition of B16F10-derived neoantigens in vitro, providing a mechanistic basis for their antitumor reactivity.

CONCLUSIONS

These results discover an unrecognized role for dual TCR cells in protective immune function and identify these cells and their TCRs as a potential resource for antitumor immunotherapy.

Dual TCR-Expressing T Cells in Cancer: How Single-Cell Technologies Enable New Investigation

TCR diversity measures are often used to understand the immune response in cancer. Traditional measures of diversity rely on bulk RNA sequencing (RNAseq) of the β-chain variable regions. However, the full αβ TCR repertoire is a combination of both the α- and β-chains, which are encoded by separate genes. In contrast with bulk RNAseq, single-cell RNAseq (scRNAseq) allows paired chain analyses, yielding a more accurate measure of the repertoire. Interestingly, ∼30% of mature peripheral T cells express multiple TCR alleles (e.g., two α-chains) and may exhibit dual Ag specificity. scRNAseq has become increasingly common, and data from both human and animal studies are publicly available. However, routine workflows discard secondary TCR alleles and focus on a single TCR clone per cell. This perspectives piece emphasizes why this may not be good practice and highlights unanswered questions in the field of T cell dual specificity.

Machine Learning Approaches to TCR Repertoire Analysis

Sparked by the development of genome sequencing technology, the quantity and quality of data handled in immunological research have been changing dramatically. Various data and database platforms are now driving the rapid progress of machine learning for immunological data analysis. Of various topics in immunology, T cell receptor repertoire analysis is one of the most important targets of machine learning for assessing the state and abnormalities of immune systems. In this paper, we review recent repertoire analysis methods based on machine learning and deep learning and discuss their prospects.