Single-cell characterisation of tissue homing CD4 + and CD8 + T cell clones in immune-mediated refractory arthritis

BACKGROUND

Immune-mediated arthritis is a group of autoinflammatory diseases, where the patient's own immune system attacks and destroys synovial joints. Sustained remission is not always achieved with available immunosuppressive treatments, warranting more detailed studies of T cell responses that perpetuate synovial inflammation in treatment-refractory patients.

METHODS

In this study, we investigated CD4 + and CD8 + T lymphocytes from the synovial tissue and peripheral blood of patients with treatment-resistant immune-mediated arthritis using paired single-cell RNA and TCR-sequencing. To gain insights into the trafficking of clonal families, we compared the phenotypes of clones with the exact same TCRß amino acid sequence between the two tissues.

RESULTS

Our results show that both CD4 + and CD8 + T cells display a more activated and inflamed phenotype in the synovial tissue compared to peripheral blood both at the population level and within individual T cell families. Furthermore, we found that both cell subtypes exhibited clonal expansion in the synovial tissue.

CONCLUSIONS

Our findings suggest that the local environment in the synovium drives the proliferation of activated cytotoxic T cells, and both CD4 + and CD8 + T cells may contribute to tissue destruction and disease pathogenesis.

Single-Cell Landscape Highlights Heterogenous Microenvironment, Novel Immune Reaction Patterns, Potential Biomarkers and Unique Therapeutic Strategies of Cervical Squamous Carcinoma, Human Papillomavirus-Associated (HPVA) and Non-HPVA Adenocarcinoma

Cervical adenocarcinomas (ADCs), including human papillomavirus (HPV)-associated (HPVA) and non-HPVA (NHPVA), though exhibiting a more malignant phenotype and poorer prognosis, are treated identically to squamous cell carcinoma (SCC). This clinical dilemma requires a deeper investigation into their differences. Herein a transcriptomic atlas of SCC, HPVA, and NHPVA-ADC using single-cell RNA (scRNA) and T-cell receptor sequencing (TCR-seq) is presented. Regarding structural cells, the malignancy origin of epithelial cells, angiogenic tip cells and two subtypes of fibroblasts is revealed. The promalignant properties of the structural cells using organoids are further confirmed. Regarding immune cells, myeloid cells with multiple functions other than antigen presentation and exhausted T lymphocytes contribute to immunosuppression. From the perspective of HPV infection, not only is HPV-dependent and independent cervical cancer oncogenesis proposed but also three immune reaction patterns mediated by T cells (coordinated/inactive/imbalanced) are identified. Strikingly, diagnostic biomarkers to distinguish ADC from SCC are discovered and prognostic biomarkers with marker genes for malignant epithelial cells, tip cells, and SPP1/C1QC macrophages are generated. Importantly, the efficacy of anti-CD96 and anti-TIGIT, not inferior to anti-PD1, in animal experiments is confirmed and targeted therapies specifically for HPV-positive SCC, HPVA and NHPVA-ADC, providing essential clues for further clinical trials, are proposed.

Integrated single-cell multiomics reveals novel immune candidate markers for post-traumatic coagulopathy

Introduction

Post-traumatic coagulopathy (PTC) is a critical pathology in traumatic brain injury (TBI), however, its potential mechanism is not clear. To explore this in peripheral samples, we integrated single cell RNA-sequencing and T cell repertoire (TCR)-sequencing across a cohort of patients with TBI.

Methods

Clinical samples from patients with more brain severity demonstrated overexpression of T cell receptor-encoding genes and less TCR diversity.

Results

By mapping TCR clonality, we found patients with PTC have less TCR clones, and the TCR clones are mainly distributed in cytotoxic effector CD8+T cell. In addition, the counts of CD8+ T cell and natural killer (NK) cells are associated with the coagulation parameter by WGCNA, and the granzyme and lectin-like receptor profiles are also decreased in the peripheral blood from TBI patients, suggesting that reduced peripheral CD8+ clonality and cytotoxic profiles may be involved in PTC after TBI.

Conclusion

Our work systematically revealed the critical immune status in PTC patients at the single-cell level.

T-cell repertoire diversity: friend or foe for protective antitumor response?

Profiling the T-Cell Receptor (TCR) repertoire is establishing as a potent approach to investigate autologous and treatment-induced antitumor immune response. Technical and computational breakthroughs, including high throughput next-generation sequencing (NGS) approaches and spatial transcriptomics, are providing unprecedented insight into the mechanisms underlying antitumor immunity. A precise spatiotemporal variation of T-cell repertoire, which dynamically mirrors the functional state of the evolving host-cancer interaction, allows the tracking of the T-cell populations at play, and may identify the key cells responsible for tumor eradication, the evaluation of minimal residual disease and the identification of biomarkers of response to immunotherapy. In this review we will discuss the relationship between global metrics characterizing the TCR repertoire such as T-cell clonality and diversity and the resultant functional responses. In particular, we will explore how specific TCR repertoires in cancer patients can be predictive of prognosis or response to therapy and in particular how a given TCR re-arrangement, following immunotherapy, can predict a specific clinical outcome. Finally, we will examine current improvements in terms of T-cell sequencing, discussing advantages and challenges of current methodologies.

pyTCR: A comprehensive and scalable solution for TCR-Seq data analysis to facilitate reproducibility and rigor of immunogenomics research

T cell receptor (TCR) studies have grown substantially with the advancement in the sequencing techniques of T cell receptor repertoire sequencing (TCR-Seq). The analysis of the TCR-Seq data requires computational skills to run the computational analysis of TCR repertoire tools. However biomedical researchers with limited computational backgrounds face numerous obstacles to properly and efficiently utilizing bioinformatics tools for analyzing TCR-Seq data. Here we report pyTCR, a computational notebook-based solution for comprehensive and scalable TCR-Seq data analysis. Computational notebooks, which combine code, calculations, and visualization, are able to provide users with a high level of flexibility and transparency for the analysis. Additionally, computational notebooks are demonstrated to be user-friendly and suitable for researchers with limited computational skills. Our tool has a rich set of functionalities including various TCR metrics, statistical analysis, and customizable visualizations. The application of pyTCR on large and diverse TCR-Seq datasets will enable the effective analysis of large-scale TCR-Seq data with flexibility, and eventually facilitate new discoveries.

TCR-Seq Identifies Distinct Repertoires of Distant-Metastatic and Nondistant-Metastatic Thyroid Tumors

CONTEXT

Malignant thyroid tumor with distant metastasis is associated with poor outcome. Early detection of distant metastasis is of great clinical importance.

OBJECTIVE

Thyroid tumor infiltrated with T cells can serve as a biomarker for monitoring metastasis.

DESIGN

A retrospective analysis was performed of patient clinical samples collected between 2012 to 2018, using T-cell receptor sequencing (TCR-seq) for clinical exploration.

SETTING

This study took place at Zhejiang Cancer Hospital.

PATIENTS

Sixty-eight patients with papillary thyroid cancer (PTC) (distinct metastatic status) and 21 patients with benign nodules were enrolled. All patients had not received any treatment before surgery.

MAIN OUTCOME MEASURE

The characteristics of TCRβ complementary-determining region 3 (CDR3) for each patient were determined by high-throughput sequencing.

RESULTS

The TCRβ diversity of malignant tumors is significantly higher than benign nodules both in blood and tumor samples (Shannon index, blood, P < .01; tumor, P < .001). The malignant tumors with distant metastasis or invasiveness showed lower TCRβ diversity than nonmetastasis (Shannon index, P < .01) or noninvasive (Shannon index, P < .01) malignant tumors. Analysis of the Morisita-Horn similarity index indicated significant TCRβ repertoire similarity between tumor and blood in distant-metastatic patients (comparison with nonmetastasis, P < .05). According to the discrepancy of the CDR3 among patients with different clinicopathological status, the classifier was constructed to discriminate distant-metastatic individuals. A promising area under the curve value of 83.8% was obtained with the number of overlapping CDR3 clonotypes.

CONCLUSION

The availability and reliability of TCR-seq render it prospective to translate these intrinsic attributes into clinical practice for monitoring distant metastasis in PTC patients.

Deciphering the TCR Repertoire to Solve the COVID-19 Mystery

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected several millions and killed more than quarter of a million worldwide to date. Important questions have remained unanswered: why some patients develop severe disease, while others do not; and what roles do genetic variabilities play in the individual immune response to this viral infection. Here, we discuss the critical role T cells play in the orchestration of the antiviral response underlying the pathogenesis of the disease, COVID-19. We highlight the scientific rationale for comprehensive and longitudinal TCR analyses in COVID-19 and reason that analyzing TCR repertoire in COVID-19 patients would reveal important findings that may explain the outcome disparity observed in these patients. Finally, we provide a framework describing the different strategies, the advantages, and the challenges involved in obtaining useful TCR repertoire data to advance our fight against COVID-19.

CD4(+) T Cell-Receptor Repertoire Diversity is Compromised in the Spleen but Not in the Bone Marrow of Aged Mice Due to Private and Sporadic Clonal Expansions

Reduction in T cell receptor (TCR) diversity in old age is considered as a major cause for immune complications in the elderly population. Here, we explored the consequences of aging on the TCR repertoire in mice using high-throughput sequencing (TCR-seq). We mapped the TCRβ repertoire of CD4+ T cells isolated from bone marrow (BM) and spleen of young and old mice. We found that TCRβ diversity is reduced in spleens of aged mice but not in their BM. Splenic CD4+ T cells were also skewed toward an effector memory phenotype in old mice, while BM cells preserved their memory phenotype with age. Analysis of Vβ and Jβ gene usage across samples, as well as comparison of CDR3 length distributions, showed no significant age dependent changes. However, comparison of the frequencies of amino-acid (AA) TCRβ sequences between samples revealed repertoire changes that occurred at a more refined scale. The BM-derived TCRβ repertoire was found to be similar among individual mice regardless of their age. In contrast, the splenic repertoire of old mice was not similar to those of young mice, but showed an increased similarity with the BM repertoire. Each old-mouse had a private set of expanded TCRβ sequences. Interestingly, a fraction of these sequences was found also in the BM of the same individual, sharing the same nucleotide sequence. Together, these findings show that the composition and phenotype of the CD4+ T cell BM repertoire are relatively stable with age, while diversity of the splenic repertoire is severely reduced. This reduction is caused by idiosyncratic expansions of tens to hundreds of T cell clonotypes, which dominate the repertoire of each individual. We suggest that these private and abundant clonotypes are generated by sporadic clonal expansions, some of which correspond to pre-existing BM clonotypes. These organ- and age-specific changes of the TCRβ repertoire have implications for understanding and manipulating age-associated immune decline.