T-cell Receptor Repertoire Sequencing Research Articles

Unraveling the chicken T cell repertoire with enhanced genome annotation.

T cell receptor (TCR) repertoire sequencing has emerged as a powerful tool for understanding the diversity and functionality of T cells within the host immune system. Yet, the chicken TCR repertoire remains poorly understood due to incomplete genome annotation of the TCR loci, despite the importance of chickens in agriculture and as an immunological model. Here, we addressed this critical issue by employing 5' rapid amplification of complementary DNA ends (5'RACE) TCR repertoire sequencing with molecular barcoding of complementary DNA (cDNA) molecules. Simultaneously, we enhanced the genome annotation of TCR Variable (V), Diversity (D, only present in β and δ loci) and Joining (J) genes in the chicken genome. To enhance the efficiency of TCR annotations, we developed VJ-gene-finder, an algorithm designed to extract VJ gene candidates from deoxyribonucleic acid (DNA) sequences. Using this tool, we achieved a comprehensive annotation of all known chicken TCR loci, including the α/δ locus on chromosome 27. Evolutionary analysis revealed that each locus evolved separately by duplication of long homology units. To define the baseline TCR diversity in healthy chickens and to demonstrate the feasibility of the approach, we characterized the splenic α/β/γ/δ TCR repertoire. Analysis of the repertoires revealed preferential usage of specific V and J combinations in all chains, while the overall features were characteristic of unbiased repertoires. We observed moderate levels of shared complementarity-determining region 3 (CDR3) clonotypes among individual birds within the α and γ chain repertoires, including the most frequently occurring clonotypes. However, the β and δ repertoires were predominantly unique to each bird. Taken together, our TCR repertoire analysis allowed us to decipher the composition, diversity, and functionality of T cells in chickens. This work not only represents a significant step towards understanding avian T cell biology, but will also shed light on host-pathogen interactions, vaccine development, and the evolutionary history of avian immunology.

Breakthrough infection evokes the nasopharyngeal innate immune responses established by SARS-CoV-2-inactivated vaccine.

Nasopharyngeal immune responses are vital for defense against SARS-CoV-2 infection. Although vaccination via muscle immunization has shown a high efficacy in reducing severity and death in COVID-19 infection, breakthrough infection frequently happens because of mutant variants and incompletely established mucosal immunity, especially in the upper respiratory tract. Here, we performed a single-cell RNA and T-cell receptor repertoire sequencing and delineated a high-resolution transcriptome landscape of nasopharyngeal mucosal immune and epithelial cells in vaccinated persons with breakthrough infection and non-vaccinated persons with natural infection as control. The epithelial cells showed anti-virus gene expression diversity and potentially recruited innate immune cells into the nasopharyngeal mucous of vaccinated patients. Upon infection, they released significant pro-inflammatory cytokines and chemokines by macrophages and monocytes and expressed antigen-presenting relevant genes by dendritic cells. Such immune responses of nasopharyngeal innate immune cells would facilitate the strengthened expression of cytotoxic genes in virus-specific T-cell or B-cell differentiation into antibody-secreting cells at the early stage of breakthrough infection through cell interaction between innate and adaptive immune cells. Notably, these alterations of nasopharyngeal immune cells in breakthrough infection depended on the activated Nuclear factor-κB (NF-κB) and NOD-, LRR- and pyrin domain-containing protein 3 (NLRP3) signaling rather than type I interferon responses due to the general reduction in interferon-stimulated gene expression. Our findings suggest that vaccination potentially strengthens innate immune barriers and virus-specific memory immune cell responses, which could be quickly activated to defend against variant breakthrough infection and maintain nasopharyngeal epithelial cell integrity. Thus, this study highlights the necessity of a boost via nasal mucous after intramuscular immunization.

Exploration of biomarkers in potentially resectable stage IIIB NSCLC patients receiving neoadjuvant chemoimmunotherapy.

e20591 Background: Non–small cell lung cancer (NSCLC) is one of the main leading causes of cancer mortality in the world. NSCLC is incurable in most patients with potentially resectable locally advanced stage IIIB disease. Numerous studies suggest that advantageous chemoimmunotherapy is a promising treatment for resectable NSCLC. The determination of PD-L1, T-cell receptor (TCR) repertoire and tumor mutational burden (TMB) have been reported to predict the response to immunotherapy. However, the value of pathologic response determination in the context of neoadjuvant chemoimmunotherapy in resectable stage IIIB NSCLC is limited. Therefore, it is necessary to identify biomarkers for the prediction of the benefit from neoadjuvant chemoimmunotherapy in patients with potentially resectable stage IIIB NSCLC. Methods: A total of 15 patients with potentially resectable clinical stage IIIB NSCLC were enrolled into the study receiving neoadjuvant sintilimab (200mg IV Q3W) plus chemotherapy therapies for 4-6 weeks followed by surgery. All peripheral blood and tissue samples were collected and detected by using TCR repertoire sequencing before and after chemoimmunotherapy. The patients were divided into MPR group (n=5) and non-MPR group (n=10) according to MPR (<10% viable tumour at resection) as an index. Furthermore, TMB spectra of 1021-gene panels and PD-L1 immunohistochemical staining were performed in paraffin-embedded human NSCLC tissue before neoadjuvant chemoimmunotherapy. The Pearson correlation coefficient method was used to analyze correlation. The ROC analysis were performed using “pROC” R package. Results: In baseline tissue samples, the levels of TMB and NAD were higher in MPR compared with non-MPR groups (P=0.0328, P=0.015, respectively). The negative correlation was existed between pretreatment tissue TCR richness and TMB in non-MPR group (P=0.028, R=-0.66). In MPR group, TCR clones and evenness showed significant difference (P=0.00237, P=0.04658, respectively). In non-MPR group, the TCR repertoire of tissue in posttreatment showed significant difference compared with those of pretreatment, including clones (P=1.04x10-6), shannon’s diversity (P=0.00142), evenness (P=0.00433), richness (P=0.00591). The clinical data showed that MPR patients with DDR mutation had longer DFS after sintilimab plus chemotherapy therapies (18.4±5.41 months, X-squared=9.8, P=0.02034). DDR mutation, TMB and TCR richness revealed better sensitivity and specificity to classify patients achieving MPR after neoadjuvant chemoimmunotherapy (AUC=1.000, AUC=0.796, AUC=0.773, respectively). Conclusions: This study confirmed the superiority of neoadjuvant chemoimmunotherapy in patients with potentially resectable stage IIIB NSCLC in terms of MPR. TCR repertoire, TMB and DDR mutation were associated with pathologic response to neoadjuvant chemoimmunotherapy as biomarkers for effective anti-tumor immunity. Clinical trial information: ChiCTR2000040673 .

Abstract CT039: Immunomodulatory effects of ceralasertib in combination with durvalumab in patients with NSCLC and progression on anti-PD-(L)1 treatment (HUDSON, NCT03334617)

Abstract Background: Promising clinical activity has been described with the combination of ceralasertib (oral ATR inhibitor) and durvalumab (anti-PD-L1 mAb) in patients with NSCLC who have progressed on prior anti-PD-(L)1 immunotherapy (HUDSON, NCT03334617) (Besse et al., OA15.05, IASLC 2022 WCLC). Similarly promising clinical benefit has been seen with this combination in patients with immunotherapy-resistant melanoma, prompting ongoing Phase2/Phase3 trials in both melanoma (NCT05061134) and NSCLC (NCT05450692). Preliminary preclinical data showed that ceralasertib can modulate innate and adaptive immunity; here we extend these findings in the peripheral blood of HUDSON patients. Methods: Longitudinal blood samples were collected at baseline, on-therapy samples after 7 days of ceralasertib alone and after durvalumab treatment to evaluate gene expression analyzed using a linear mixed effects model, and T-cell receptor (TCR) repertoire sequencing were analyzed using paired Wilcoxon analyses. Results: Matched pre- and on-treatment blood samples were available for analysis from 48 patients for gene expression analysis and 62 patients for TCR repertoire sequencing. Gene expression analysis revealed dynamic, reversible changes upon ceralasertib treatment for 7 days (prior to durvalumab). Consistent with pre-clinical data, changes in innate and adaptive immunity-relevant signatures such as monocyte lineage (adjusted p-value [p.adj]=1.1e-23), cytotoxic (p.adj=7.4e-04), exhausted T-cell signatures (p.adj=1.5e-05) and increases in the IFNγ response (p.adj=2.0e-03), IFNα response (p.adj=3.7e-05), and TNFα signaling (p.adj=2.3e-13) signatures were seen, which reverted to baseline levels after ceralasertib followed by durvalumab treatment. Longitudinal TCR sequencing demonstrated similar cyclical changes, most notably reductions in clonality after ceralasertib treatment for 7 days (p=1.1e-06), with a return to baseline after ceralasertib followed by durvalumab treatment. An increase in peripheral TCR clonality was observed in most patients (n=48/58) after the addition of durvalumab, followed by an increase in expanded (p=3.29e-13) and newly detected expanded TCR clones (p=1e-15). The net result of TCR changes after ceralasertib followed by durvalumab treatment was an overall increase in clonality in most patients, without a significant difference in the composition of the most abundant T-cell clones, as measured by the Morisita index. Conclusions: We found that ceralasertib, combined with durvalumab treatment in relapsed/refractory NSCLC patients, decreased signatures associated with exhausted T-cells and, conversely, increased interferon pathway activation. Furthermore, we observed an expansion and maintenance of abundant T-cell clones indicative of an anti-tumor response. Citation Format: Sonia Iyer, James Conway, Deanna Russell, Avinash Reddy, Jan Cosaert, Simon Barry, Marlene Dressman, Ilhem Mensi, Boaz Aronson, Jane Peters, Helen Ambrose, Keunchil Park, Patrick Forde, Benjamin Besse, John V. Heymach, J. Carl Barrett. Immunomodulatory effects of ceralasertib in combination with durvalumab in patients with NSCLC and progression on anti-PD-(L)1 treatment (HUDSON, NCT03334617) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr CT039.

T cell receptor repertoire sequencing reveals chemotherapy-driven clonal expansion in colorectal liver metastases

Colorectal liver metastasis (CLM) is a leading cause of colorectal cancer mortality, and the response to immune checkpoint inhibition (ICI) in microsatellite-stable CRC has been disappointing. Administration of cytotoxic chemotherapy may cause increased density of tumor-infiltrating T cells, which has been associated with improved response to ICI. This study aimed to quantify and characterize T-cell infiltration in CLM using T-cell receptor (TCR) repertoire sequencing. Eighty-five resected CLMs from patients included in the Oslo CoMet study were subjected to TCR repertoire sequencing. Thirty-five and 15 patients had received neoadjuvant chemotherapy (NACT) within a short or long interval, respectively, prior to resection, while 35 patients had not been exposed to NACT. T-cell fractions were calculated, repertoire clonality was analyzed based on Hill evenness curves, and TCR sequence convergence was assessed using network analysis. Increased T-cell fractions (10.6%vs. 6.3%) were detected in CLMs exposed to NACT within a short interval prior to resection, while modestly increased clonality was observed in NACT-exposed tumors independently of the timing of NACT administration and surgery. While private clones made up >90% of detected clones, network connectivity analysis revealed that public clones contributed the majority of TCR sequence convergence. TCR repertoire sequencing can be used to quantify T-cell infiltration and clonality in clinical samples. This study provides evidence to support chemotherapy-driven T-cell clonal expansion in CLM in a clinical context.

T-Cell Receptor Repertoire Sequencing in the Era of Cancer Immunotherapy.

T cells are integral components of the adaptive immune system, and their responses are mediated by unique T-cell receptors (TCR) that recognize specific antigens from a variety of biological contexts. As a result, analyzing the T-cell repertoire offers a better understanding of immune responses and of diseases like cancer. Next-generation sequencing technologies have greatly enabled the high-throughput analysis of the TCR repertoire. On the basis of our extensive experience in the field from the past decade, we provide an overview of TCR sequencing, from the initial library preparation steps to sequencing and analysis methods and finally to functional validation techniques. With regards to data analysis, we detail important TCR repertoire metrics and present several computational tools for predicting antigen specificity. Finally, we highlight important applications of TCR sequencing and repertoire analysis to understanding tumor biology and developing cancer immunotherapies.

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.

T cell receptor repertoire analysis in HTLV-1-associated diseases.

Human T lymphotropic virus 1 (HTLV-1) is a human retrovirus identified as the causative agent in adult T-cell leukemia/lymphoma (ATL) and chronic-progressive neuroinflammatory disorder HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). HTLV-1 is estimated to infect between 5-20 million people worldwide, although most infected individuals remain asymptomatic. HTLV-1 infected persons carry an estimated lifetime risk of approximately 5% of developing ATL, and between 0.25% and 1.8% of developing HAM/TSP. Most HTLV-1 infection is detected in CD4+ T cells in vivo which causes the aggressive malignancy in ATL. In HAM/TSP, the increase of HTLV-1 provirus induces immune dysregulation to alter inflammatory milieu, such as expansion of HTLV-1-specific CD8+ T cells, in the central nervous system of the infected subjects, which have been suggested to underlie the pathogenesis of HAM/TSP. Factors contributing to the conversion from asymptomatic carrier to disease state remain poorly understood. As such, the identification and tracking of HTLV-1-specific T cell biomarkers that may be used to monitor the progression from primary infection to immune dysfunction and disease are of great interest. T cell receptor (TCR) repertoires have been extensively investigated as a mechanism of monitoring adaptive T cell immune response to viruses and tumors. Breakthrough technologies such as single-cell RNA sequencing have increased the specificity with which T cell clones may be characterized and continue to improve our understanding of TCR signatures in viral infection, cancer, and associated treatments. In HTLV-1-associated disease, sequencing of TCR repertoires has been used to reveal repertoire patterns, diversity, and clonal expansions of HTLV-1-specific T cells capable of immune evasion and dysregulation in ATL as well as in HAM/TSP. Conserved sequence analysis has further been used to identify CDR3 motif sequences and exploit disease- or patient-specificity and commonality in HTLV-1-associated disease. In this article we review current research on TCR repertoires and HTLV-1-specific clonotypes in HTLV-1-associated diseases ATL and HAM/TSP and discuss the implications of TCR clonal expansions on HTLV-1-associated disease course and treatments.

T-Cell Receptor Repertoire Sequencing and Its Applications: Focus on Infectious Diseases and Cancer.

The immune system is a dynamic feature of each individual and a footprint of our unique internal and external exposures. Indeed, the type and level of exposure to physical and biological agents shape the development and behavior of this complex and diffuse system. Many pathological conditions depend on how our immune system responds or does not respond to a pathogen or a disease or on how the regulation of immunity is altered by the disease itself. T-cells are important players in adaptive immunity and, together with B-cells, define specificity and monitor the internal and external signals that our organism perceives through its specific receptors, TCRs and BCRs, respectively. Today, high-throughput sequencing (HTS) applied to the TCR repertoire has opened a window of opportunity to disclose T-cell repertoire development and behavior down to the clonal level. Although TCR repertoire sequencing is easily accessible today, it is important to deeply understand the available technologies for choosing the best fit for the specific experimental needs and questions. Here, we provide an updated overview of TCR repertoire sequencing strategies, providers and applications to infectious diseases and cancer to guide researchers’ choice through the multitude of available options. The possibility of extending the TCR repertoire to HLA characterization will be of pivotal importance in the near future to understand how specific HLA genes shape T-cell responses in different pathological contexts and will add a level of comprehension that was unthinkable just a few years ago.

Utility of Bulk T-Cell Receptor Repertoire Sequencing Analysis in Understanding Immune Responses to COVID-19.

Measuring immunity to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 19 (COVID-19), can rely on antibodies, reactive T cells and other factors, with T-cell-mediated responses appearing to have greater sensitivity and longevity. Because each T cell carries an essentially unique nucleic acid sequence for its T-cell receptor (TCR), we can interrogate sequence data derived from DNA or RNA to assess aspects of the immune response. This review deals with the utility of bulk, rather than single-cell, sequencing of TCR repertoires, considering the importance of study design, in terms of cohort selection, laboratory methods and analysis. The advances in understanding SARS-CoV-2 immunity that have resulted from bulk TCR repertoire sequencing are also be discussed. The complexity of sequencing data obtained by bulk repertoire sequencing makes analysis challenging, but simple descriptive analyses, clonal analysis, searches for specific sequences associated with immune responses to SARS-CoV-2, motif-based analyses, and machine learning approaches have all been applied. TCR repertoire sequencing has demonstrated early expansion followed by contraction of SARS-CoV-2-specific clonotypes, during active infection. Maintenance of TCR repertoire diversity, including the maintenance of diversity of anti-SARS-CoV-2 response, predicts a favourable outcome. TCR repertoire narrowing in severe COVID-19 is most likely a consequence of COVID-19-associated lymphopenia. It has been possible to follow clonotypic sequences longitudinally, which has been particularly valuable for clonotypes known to be associated with SARS-CoV-2 peptide/MHC tetramer binding or with SARS-CoV-2 peptide-induced cytokine responses. Closely related clonotypes to these previously identified sequences have been shown to respond with similar kinetics during infection. A possible superantigen-like effect of the SARS-CoV-2 spike protein has been identified, by means of observing V-segment skewing in patients with severe COVID-19, together with structural modelling. Such a superantigen-like activity, which is apparently absent from other coronaviruses, may be the basis of multisystem inflammatory syndrome and cytokine storms in COVID-19. Bulk TCR repertoire sequencing has proven to be a useful and cost-effective approach to understanding interactions between SARS-CoV-2 and the human host, with the potential to inform the design of therapeutics and vaccines, as well as to provide invaluable pathogenetic and epidemiological insights.

Revealing the Immune Heterogeneity between Systemic Lupus Erythematosus and Rheumatoid Arthritis Based on Multi-Omics Data Analysis.

The pathogenesis of systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) are greatly influenced by different immune cells. Nowadays both T-cell receptor (TCR) and B-cell receptor (BCR) sequencing technology have emerged with the maturity of NGS technology. However, both SLE and RA peripheral blood TCR or BCR repertoire sequencing remains lacking because repertoire sequencing is an expensive assay and consumes valuable tissue samples. This study used computational methods TRUST4 to construct TCR repertoire and BCR repertoire from bulk RNA-seq data of both SLE and RA patients’ peripheral blood and analyzed the clonality and diversity of the immune repertoire between the two diseases. Although the functions of immune cells have been studied, the mechanism is still complicated. Differentially expressed genes in each immune cell type and cell–cell interactions between immune cell clusters have not been covered. In this work, we clustered eight immune cell subsets from original scRNA-seq data and disentangled the characteristic alterations of cell subset proportion under both SLE and RA conditions. The cell–cell communication analysis tool CellChat was also utilized to analyze the influence of MIF family and GALECTIN family cytokines, which were reported to regulate SLE and RA, respectively. Our findings correspond to previous findings that MIF increases in the serum of SLE patients. This work proved that the presence of LGALS9, PTPRC and CD44 in platelets could serve as a clinical indicator of rheumatoid arthritis. Our findings comprehensively illustrate dynamic alterations in immune cells during pathogenesis of SLE and RA. This work identified specific V genes and J genes in TCR and BCR that could be used to expand our understanding of SLE and RA. These findings provide a new insight inti the diagnosis and treatment of the two autoimmune diseases.

Prediction of immunodominant CD4+ SARS-CoV-2 epitopes with TCR repertoire sequencing data

Abstract The T cell receptor (TCR) is a hypervariable molecule defining the specificity of T cells for peptide-MHC complex. Defining exact epitopes is crucial to profile T cell responses in COVID-19 and yet very few MHC-II restricted SARS-CoV-2 epitopes are currently known. Here, we propose a reverse epitope discovery technique, which, instead of using large pools of peptides to identify reactive T cells, utilizes TCR repertoire sequencing data as the means to predict immunodominant epitopes. The core idea of the approach is to combine information from large, publicly available TCR repertoire datasets: TCRbeta repertoires from cohorts of COVID-19 patients and controls, and paired TCR repertoires of single T cells activated by SARS-CoV-2 peptides. Our pipeline allows us to predict the HLA-restriction of public SARS-CoV-2 specific TCR clonotypes, which in turn allows us to predict binding to a specific peptide. We applied this approach to single cell TCR repertoires of CD4+ T cells from COVID-19 patients, and predicted six MHC-II restricted immunodominant epitopes and alpha-beta TCR motifs recognising them and tested our predictions experimentally. We further applied this technique to bulk TCRalpha repertoires from T follicular helper cells from draining lymph nodes of healthy donors after BNT162b2 mRNA vaccination. We found that the DPB1*04 restricted S167–180 epitope is responsible for the largest public CD4+ response, and recognition of this epitope is driven by a semi-invariant TCR alpha chain. This finding led to generation of the DPB1*04 S167–180 tetramer, allowing to track SARS-CoV-2 specific CD4 cells in peripheral blood and lymph node samples with flow cytometry. This work was partially supported by R01AI136514 grant. This work was partially supported by R01AI136514 grant. 

Controlling for Confounding Factors when Diagnosing Cancer from T Cell Receptor Repertoires

Abstract Our publications have shown that T cell receptor (TCR) repertoires sequenced from tissue biopsies can be used to distinguish tumor from control tissue with > 90% classification accuracies, suggesting that TCR repertoires can be used to diagnose cancer. TCR repertoires sequenced from blood samples of cancer patients are now publicly available, and it is tempting to use these existing samples to develop blood-based assays for diagnosing cancer. Already, research groups including us obtained promising results. However, these results are obtained by combining cancer and control samples from mismatching studies. Without controlling for age, sex, race, and even the reduced amount of blood volume collected from cancer patients relative to controls, these exciting results could merely be an artifact of confounding factors. In this study, we control for possible confounding factors and observe that our ability to diagnose cancer from TCR repertoires sequenced from blood does not vanish. On patient-holdout cross-validations, we achieve diagnostic accuracies of 90% for colorectal cancer (controlling for depth coverage), 84% for breast cancer (controlling for depth coverage and age), and 83% for lung cancer (controlling for age, sex, race, and depth coverage). While it is impossible to control for all potential confounding factors like variations in geographic locations, these results are encouraging. We propose future studies that (i) collect matching controls and cases and (ii) confirm TCR repertoire sequencing provides a distinct signal for diagnosing cancer independent of other blood-based assays and therefore can improve the diagnostic performance of these other blood-based assays.

Human γδ TCR Repertoires in Health and Disease.

The T cell receptor (TCR) repertoires of γδ T cells are very different to those of αβ T cells. While the theoretical TCR repertoire diversity of γδ T cells is estimated to exceed the diversity of αβ T cells by far, γδ T cells are still understood as more invariant T cells that only use a limited set of γδ TCRs. Most of our current knowledge of human γδ T cell receptor diversity builds on specific monoclonal antibodies that discriminate between the two major subsets, namely Vδ2+ and Vδ1+ T cells. Of those two subsets, Vδ2+ T cells seem to better fit into a role of innate T cells with semi-invariant TCR usage, as compared to an adaptive-like biology of some Vδ1+ subsets. Yet, this distinction into innate-like Vδ2+ and adaptive-like Vδ1+ γδ T cells does not quite recapitulate the full diversity of γδ T cell subsets, ligands and interaction modes. Here, we review how the recent introduction of high-throughput TCR repertoire sequencing has boosted our knowledge of γδ T cell repertoire diversity beyond Vδ2+ and Vδ1+ T cells. We discuss the current understanding of clonal composition and the dynamics of human γδ TCR repertoires in health and disease.

Investigation of Antigen-Specific T-Cell Receptor Clusters in Human Cancers.

Cancer antigen-specific T cells are key components in antitumor immune response, yet their identification in the tumor microenvironment remains challenging, as most cancer antigens are unknown. Recent advance in immunology suggests that similar T-cell receptor (TCR) sequences can be clustered to infer shared antigen specificity. This study aims to identify antigen-specific TCRs from the tumor genomics sequencing data. We used the TRUST (Tcr Repertoire Utilities for Solid Tissue) algorithm to assemble the TCR hypervariable CDR3 regions from 9,700 bulk tumor RNA-sequencing (RNA-seq) samples, and developed a computational method, iSMART, to group similar TCRs into antigen-specific clusters. Integrative analysis on the TCR clusters with multi-omics datasets was performed to profile cancer-associated T cells and to uncover novel cancer antigens. Clustered TCRs are associated with signatures of T-cell activation after antigen encounter. We further elucidated the phenotypes of clustered T cells using single-cell RNA-seq data, which revealed a novel subset of tissue-resident memory T-cell population with elevated metabolic status. An exciting application of the TCR clusters is to identify novel cancer antigens, exemplified by our identification of a candidate cancer/testis gene, HSFX1, through integrated analysis of HLA alleles and genomics data. The target was further validated using vaccination of humanized HLA-A*02:01 mice and ELISpot assay. Finally, we showed that clustered tumor-infiltrating TCRs can differentiate patients with early-stage cancer from healthy donors, using blood TCR repertoire sequencing data, suggesting potential applications in noninvasive cancer detection. Our analysis on the antigen-specific TCR clusters provides a unique resource for alternative antigen discovery and biomarker identification for cancer immunotherapies.

A T-cell reporter platform for high-throughput and reliable investigation of TCR function and biology.

ObjectiveTransgenic re‐expression enables unbiased investigation of T‐cell receptor (TCR)‐intrinsic characteristics detached from its original cellular context. Recent advancements in TCR repertoire sequencing and development of protocols for direct cloning of full TCRαβ constructs now facilitate large‐scale transgenic TCR re‐expression. Together, this offers unprecedented opportunities for the screening of TCRs for basic research as well as clinical use. However, the functional characterisation of re‐expressed TCRs is still a complicated and laborious matter. Here, we propose a Jurkat‐based triple parameter TCR signalling reporter endogenous TCR knockout cellular platform (TPRKO) that offers an unbiased, easy read‐out of TCR functionality and facilitates high‐throughput screening approaches.MethodsAs a proof‐of‐concept, we transgenically re‐expressed 59 human cytomegalovirus‐specific TCRs and systematically investigated and compared TCR function in TPRKO cells versus primary human T cells.ResultsWe demonstrate that the TPRKO cell line facilitates antigen‐HLA specificity screening via sensitive peptide‐MHC‐multimer staining, which was highly comparable to primary T cells. Also, TCR functional avidity in TPRKO cells was strongly correlating to primary T cells, especially in the absence of CD8αβ co‐receptor.ConclusionOverall, our data show that the TPRKO cell lines can serve as a surrogate of primary human T cells for standardised and high‐throughput investigation of TCR biology.

VDJdb in 2019: database extension, new analysis infrastructure and a T-cell receptor motif compendium.

Here, we report an update of the VDJdb database with a substantial increase in the number of T-cell receptor (TCR) sequences and their cognate antigens. The update further provides a new database infrastructure featuring two additional analysis modes that facilitate database querying and real-world data analysis. The increased yield of TCR specificity identification methods and the overall increase in the number of studies in the field has allowed us to expand the database more than 5-fold. Furthermore, several new analysis methods are included. For example, batch annotation of TCR repertoire sequencing samples allows for annotating large datasets on-line. Using recently developed bioinformatic methods for TCR motif mining, we have built a reduced set of high-quality TCR motifs that can be used for both training TCR specificity predictors and matching against TCRs of interest. These additions enhance the versatility of the VDJdb in the task of exploring T-cell antigen specificities. The database is available at https://vdjdb.cdr3.net.

Immune Correlates of Abscopal Response in a Lead-in Phase II Trial of Neoadjuvant Stereotactic Ablative Radiotherapy (SABR) for Renal Cell Carcinoma Inferior Vena Cava Tumor Thrombus

We report on outcome, abscopal responses and immunologic correlates of the lead-in phase of a phase II trial of neoadjuvant (NA) stereotactic ablative radiotherapy (SABR) to inferior vena cava tumor thrombus (IVC-TT) followed by radical nephrectomy and thrombectomy (RN-T) for 6 patients with renal cell carcinoma (RCC). Serum was collected before, during and after SABR and surgery along with radiated IVC-TT, primary tumor, normal kidney and lung metastasis. Serum was analyzed for cytokines/chemokines, and IgG autoantibodies by microarrays and ELISA. Peripheral blood mononuclear cells (PBMC) were analyzed using mass cytometry (CyTOF) and T-cell receptor repertoire sequencing (TCRrs). Tumor and normal tissue were analyzed using immunohistochemistry and TCRrs. We enrolled 6 RCC patients and treated with NA- SABR (40Gy/5fx) followed by RN-T within a week. The regimen was tolerated well and at a median follow-up of 24 months, all patients are alive. Of the 3 non-metastatic patients, 2 are disease-free (DF) and 1 developed lung metastasis. Of the 3 patients with metastasis at diagnosis, 2 demonstrated abscopal response (1 complete and 1 partial) and 1 had progressive disease (PD). Overall autoantibody titers enhanced post-treatment in the DF patients but did not change in the patients with PD. ELISA of CA IX IgG titers showed the same trend. Pro-inflammatory cytokines/chemokines were increased only in the DF group. We explored the immune mechanisms that possibly caused the complete abscopal response in the patient that had a growing 2.3 cm lingular lung metastasis and smaller lung nodules at baseline. Post-treatment, the lingular lesion showed surrounding ground-glass densities suggesting local inflammation and resolved over the next 6 months. CT-guided biopsy of the lesion showed inflammatory and fibrohistiocytic reparative changes, abundant CD68+ macrophages and CD4+ and CD8+ T cells. Patient remains metastasis-free at 30 months. FoxP3+ cells were identified in both IVC-TT and regressing lung metastasis suggesting that these cells may attenuate cytotoxic T cells and persist to surveil upon tumor elimination. CyTOF showed significant increment of central and effector memory CD4 and CD8 cells overexpressing PD-1 only in the abscopal response patient. TCRrs of PBMC, primary tumor, regressing metastatic site and non-tumor adjacent tissues showed proliferation of multiple new, systemic and persistent tumor associated T cells induced by SABR that reached lung metastasis and their titers correlated with radiographic regression of the metastasis. Neo-Adjuvant SABR for IVC -TT is feasible, safe and in conjunction with surgery led to abscopal responses. SABR and surgery induced immunogenic systemic effects that correlated with improved patient outcome. SABR induced tumor neo-antigen presentation leading to proliferation of new and existing tumor associated T cells that traveled to the metastatic site to induce abscopal response.

Immune Repertoire Sequencing Using Molecular Identifiers Enables Accurate Clonality Discovery and Clone Size Quantification.

Unique molecular identifiers (MIDs) have been demonstrated to effectively improve immune repertoire sequencing (IR-seq) accuracy, especially to identify somatic hypermutations in antibody repertoire sequencing. However, evaluating the sensitivity to detect rare T cells and the degree of clonal expansion in IR-seq has been difficult due to the lack of knowledge of T cell receptor (TCR) RNA molecule copy number and a generalized approach to estimate T cell clone size from TCR RNA molecule quantification. This limited the application of TCR repertoire sequencing (TCR-seq) in clinical settings, such as detecting minimal residual disease in lymphoid malignancies after treatment, evaluating effectiveness of vaccination and assessing degree of infection. Here, we describe using an MID Clustering-based IR-Seq (MIDCIRS) method to quantitatively study TCR RNA molecule copy number and clonality in T cells. First, we demonstrated the necessity of performing MID sub-clustering to eliminate erroneous sequences. Further, we showed that MIDCIRS enables a sensitive detection of a single cell in as many as one million naïve T cells and an accurate estimation of the degree of T cell clonal expression. The demonstrated accuracy, sensitivity, and wide dynamic range of MIDCIRS TCR-seq provide foundations for future applications in both basic research and clinical settings.

TCR repertoire sequencing of 254 resected non-small cell lung cancers to reveal TCR clonality in normal tissues compared to tumor tissues.

11500 Background: The mechanisms underlying resistance to immune checkpoint blockade are poorly understood. Major efforts have been made to understand how mutations, through generation of neoantigens, may alter tumor immunogenicity and anti-tumor responses, particularly through T cell responses. However, the T cell repertoire and its interaction with cancers bearing specific molecular alterations have not been systemically studied. Methods: We delineated the landscapes in the T cell receptor (TCR) repertoire, immune infiltration (immunohistochemistry using multiple immune markers), genome (exome sequencing), epigenome (methylation array) and transcriptome (mRNA gene expression array) of 254 resected non-small cell lung cancers (NSCLC), matched normal lung tissues and peripheral blood mononuclear cells (PBMC). We report herein the preliminary analyses of TCR sequencing of NSCLC tumors and matched normal lung tissues. Results: We observed that: 1) Smaller tumors (smaller than median) had a higher T cell infiltrate (p = 0.0016) and higher entropy than larger tumors (p = 0.0098); 2) Tumors from ever/current smokers had higher T cell clonality than former/never-smokers (p = 0.005); 3) TCR clonality was positively correlated with mutational burden (p = 0.0026); 4) Compared to tumors, normal lung tissues demonstrated significantly less T cell infiltration (p = 2.1x10^-11), but a significantly higher clonality (p = 3.9x10^-7). Finally, many T cell clones, including major clones were shared between normal lung tissues and matched NSCLC tumors. Conclusions: Our preliminary data demonstrate the distinct immune microenvironment in different NSCLC tumors may be associated with particular clinicopathological features. The higher TCR clonality in normal lung tissues and overlap of T cell clones between normal lung and NSCLC tumors implies a significant proportion of tumor infiltrating T cells may be a function of constant exposure to mutagens rather than an anti-tumor response. Analysis of the peripheral TCR repertoire, the molecular landscape of these tumors and the association with immune profiling is underway.