MiTCR: software for T-cell receptor sequencing data analysis

Multiple instance learning method based on convolutional neural network and self-attention for early cancer detection

Early cancer detection using T-cell receptor sequencing (TCR-seq) and multiple instances learning methods has shown significant effectiveness. We introduce a multiple instance learning method based on convolutional neural networks and self-attention (MICA). First, MICA preprocesses TCR-seq using word vectors and then extracts features using convolutional neural networks. Second, MICA uses an enhanced self-attention mechanism to extract relational features of instances. Finally, MICA can extract the crucial TCR-seq. After cross-validation, MICA achieves an area under the curve (AUC) of 0.911 and 0.946 on the lung and thyroid cancer datasets, which are 7.1% and 2.1% higher than other methods, respectively.

TCellR2Vec: efficient feature selection for TCR sequences for cancer classification

Cancer remains one of the leading causes of death globally. New immunotherapies that harness the patient's immune system to fight cancer show promise, but their development requires analyzing the diversity of immune cells called T-cells. T-cells have receptors that recognize and bind to cancer cells. Sequencing these T-cell receptors allows to provide insights into their immune response, but extracting useful information is challenging. In this study, we propose a new computational method, TCellR2Vec, to select key features from T-cell receptor sequences for classifying different cancer types. We extracted features like amino acid composition, charge, and diversity measures and combined them with other sequence embedding techniques. For our experiments, we used a dataset of over 50,000 T-cell receptor sequences from five cancer types, which showed that TCellR2Vec improved classification accuracy and efficiency over baseline methods. These results demonstrate TCellR2Vec's ability to capture informative aspects of complex T-cell receptor sequences. By improving computational analysis of the immune response, TCellR2Vec could aid the development of personalized immunotherapies tailored to each patient's T-cells. This has important implications for creating more effective cancer treatments based on the individual's immune system.

PseAAC2Vec protein encoding for TCR protein sequence classification

The classification and prediction of T-cell receptors (TCRs) protein sequences are of significant interest in understanding the immune system and developing personalized immunotherapies. In this study, we propose a novel approach using Pseudo Amino Acid Composition (PseAAC) protein encoding for accurate TCR protein sequence classification. The PseAAC2Vec encoding method captures the physicochemical properties of amino acids and their local sequence information, enabling the representation of protein sequences as fixed-length feature vectors. By incorporating physicochemical properties such as hydrophobicity, polarity, charge, molecular weight, and solvent accessibility, PseAAC2Vec provides a comprehensive and informative characterization of TCR protein sequences. To evaluate the effectiveness of the proposed PseAAC2Vec encoding approach, we assembled a large dataset of TCR protein sequences with annotated classes. We applied the PseAAC2Vec encoding scheme to each sequence and generated feature vectors based on a specified window size. Subsequently, we employed state-of-the-art machine learning algorithms, such as support vector machines (SVM) and random forests (RF), to classify the TCR protein sequences. Experimental results on the benchmark dataset demonstrated the superior performance of the PseAAC2Vec-based approach compared to existing methods. The PseAAC2Vec encoding effectively captures the discriminative patterns in TCR protein sequences, leading to improved classification accuracy and robustness. Furthermore, the encoding scheme showed promising results across different window sizes, indicating its adaptability to varying sequence contexts.

T-cell receptor repertoire analysis of CD4-positive T cells from blood and an affected organ in an autoimmune mouse model

One hallmark of some autoimmune diseases is the variability of symptoms among individuals. Organs affected by the disease differ between patients, posing a challenge in diagnosing the affected organs. Although numerous studies have investigated the correlation between T cell antigen receptor (TCR) repertoires and the development of infectious and immune diseases, the correlation between TCR repertoires and variations in disease symptoms among individuals remains unclear. This study aimed to investigate the correlation of TCRα and β repertoires in blood T cells with the extent of autoimmune signs that varies among individuals. We sequenced TCRα and β of CD4+ CD44high CD62Llow T cells in the blood and stomachs of mice deficient in autoimmune regulator (Aire) (AIRE KO), a mouse model of human autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy. Data analysis revealed that the degree of similarity in TCR sequences between the blood and stomach varied among individual AIRE KO mice and reflected the extent of T cell infiltration in the stomach. We identified a set of TCR sequences whose frequencies in blood might correlate with extent of the stomach manifestations. Our results propose a potential of using TCR repertoires not only for diagnosing disease development but also for diagnosing affected organs in autoimmune diseases.

Multi-omics indicators of long-term survival benefits after immune checkpoint inhibitor therapy

Molecular indicators of long-term survival (LTS) in response to immune-checkpoint inhibitor (ICI) treatment have the potential to provide both mechanistic and therapeutic insights. In this study, we construct predictive models of LTS following ICI therapy based on data from 158 clinical trials involving 21,023 patients of 25 cancer types with available 1-year overall survival (OS) rates. We present evidence for the use of 1-year OS rate as a surrogate for LTS. Based on these and corresponding TCGA multi-omics data, total neoantigen, metabolism score, CD8+ T cell, and MHC_score were identified as predictive biomarkers. These were integrated into a Gaussian process regression model that estimates "long-term survival predictive score of immunotherapy" (iLSPS). We found that iLSPS outperformed the predictive capabilities of individual biomarkers and successfully predicted LTS of patient groups with melanoma and lung cancer. Our study explores the feasibility of modeling LTS based on multi-omics indicators and machine-learning methods.

GENTLE: a novel bioinformatics tool for generating features and building classifiers from T cell repertoire cancer data

BACKGROUND

In the global effort to discover biomarkers for cancer prognosis, prediction tools have become essential resources. TCR (T cell receptor) repertoires contain important features that differentiate healthy controls from cancer patients or differentiate outcomes for patients being treated with different drugs. Considering, tools that can easily and quickly generate and identify important features out of TCR repertoire data and build accurate classifiers to predict future outcomes are essential.

RESULTS

This paper introduces GENTLE (GENerator of T cell receptor repertoire features for machine LEarning): an open-source, user-friendly web-application tool that allows TCR repertoire researchers to discover important features; to create classifier models and evaluate them with metrics; and to quickly generate visualizations for data interpretations. We performed a case study with repertoires of TRegs (regulatory T cells) and TConvs (conventional T cells) from healthy controls versus patients with breast cancer. We showed that diversity features were able to distinguish between the groups. Moreover, the classifiers built with these features could correctly classify samples ('Healthy' or 'Breast Cancer')from the TRegs repertoire when trained with the TConvs repertoire, and from the TConvs repertoire when trained with the TRegs repertoire.

CONCLUSION

The paper walks through installing and using GENTLE and presents a case study and results to demonstrate the application's utility. GENTLE is geared towards any researcher working with TCR repertoire data and aims to discover predictive features from these data and build accurate classifiers. GENTLE is available on https://github.com/dhiego22/gentle and https://share.streamlit.io/dhiego22/gentle/main/gentle.py .

IL-2 and IL-15 drive intrathymic development of distinct periphery-seeding CD4+Foxp3+ regulatory T lymphocytes

Development of Foxp3-expressing regulatory T-lymphocytes (Treg) in the thymus is controlled by signals delivered in T-cell precursors via the TCR, co-stimulatory receptors, and cytokine receptors. In absence of IL-2, IL-15 or their receptors, fewer Treg apparently develop in the thymus. However, it was recently shown that a substantial part of thymic Treg are cells that had recirculated from the periphery back to the thymus, troubling interpretation of these results. We therefore reassessed the involvement of IL-2 and IL-15 in the development of Treg, taking into account Treg-recirculation. At the age of three weeks, when in wt and IL-15-deficient (but not in IL-2-deficient) mice substantial amounts of recirculating Treg are present in the thymus, we found similarly reduced proportions of newly developed Treg in absence of IL-2 or IL-15, and in absence of both cytokines even less Treg developed. In neonates, when practically no recirculating Treg were found in the thymus, the absence of IL-2 led to substantially more reduced Treg-development than deficiency in IL-15. IL-2 but not IL-15 modulated the CD25, GITR, OX40, and CD73-phenotypes of the thymus-egress-competent and periphery-seeding Treg-population. Interestingly, IL-2 and IL-15 also modulated the TCR-repertoire expressed by developing Treg. Upon transfer into Treg-less Foxp3^sf mice, newly developed Treg from IL-2- (and to a much lesser extent IL-15-) deficient mice suppressed immunopathology less efficiently than wt Treg. Taken together, our results firmly establish important non-redundant quantitative and qualitative roles for IL-2 and, to a lesser extent, IL-15 in intrathymic Treg-development.

The splenic T cell receptor repertoire during an immune response against a complex antigen: Expanding private clones accumulate in the high and low copy number region

Large cellular antigens comprise a variety of different epitopes leading to a T cell response of extreme diversity. Therefore, tracking such a response by next generation sequencing of the T cell receptor (TCR) in order to identify common TCR properties among the expanding T cells represents an enormous challenge. In the present study we adapted a set of established indices to elucidate alterations in the TCR repertoire regarding sequence similarities between TCRs including VJ segment usage and diversity of nucleotide coding of a single TCR. We combined the usage of these indices with a new systematic splitting strategy regarding the copy number of the extracted clones to divide the repertoire into multiple fractions for separate analysis. We implemented this new analytic approach using the splenic TCR repertoire following immunization with sheep red blood cells (SRBC) in mice. As expected, early after immunization presumably antigen-specific clones accumulated in high copy number fractions, but at later time points similar accumulation of specific clones occurred within the repertoire fractions of lowest copy number. For both repertoire regions immunized animals could reliably be distinguished from control in a classification approach, demonstrating the robustness of the two effects at the individual level. The direction in which the indices shifted after immunization revealed that for both the early and the late effect alterations in repertoire parameters were caused by antigen-specific private clones displacing non-specific public clones. Taken together, tracking antigen-specific clones by their displacement of average TCR repertoire characteristics in standardized repertoire fractions ensures that our analytical approach is fairly independent from the antigen in question and thus allows the in-depth characterization of a variety of immune responses.

Immune Subtypes in LUAD Identify Novel Tumor Microenvironment Profiles With Prognostic and Therapeutic Implications

The six transcriptomic immune subtypes (ISs) (C1 - C6) were reported to have complex and different interplay between TME and cancer cells in TCGA (The Cancer Genome Atlas) pan-cancer cohort. Our study specifically explored how the consequence of interplay determines the prognosis and the response to therapy in LUAD cohorts. Clinical and molecular information of LUAD patients were from TCGA and Gene Expression Omnibus (GEO). The immune cell populations and gene/pathway enrichment analysis were performed to explore the molecular differences among the C3 IS and other ISs in the LUAD population. The proportion of C3 inflammatory IS was identified as the most common IS in both TCGA (N = 457) and GEO (N = 901) cohorts. The C3 IS was also found to be the most accurate prognostic subtype, which was associated with significantly longer OS (p <0.001) and DFS (p <0.001). The C3 IS presented higher levels of CD8 T, M1 macrophage, and myeloid dendritic cells, while lower levels of M2 macrophages and cancer-associated fibroblast cells. Moreover, the C3 subtype was enriched in the antigen process and presenting, interferon-gamma response, T cell receptor signaling, and natural killer cell-mediated cytotoxicity pathways than C1/C2. In contrast, the C1/C2 presented greater activation of pathways related to the cell cycles, DNA repair, and p53 signaling pathways. The immune-related C3 IS had a great ability to stratify the prognosis of LUAD, providing clues for further pathogenic research. This classification might help direct precision medicine screenings of LUAD patients, thus possibly improving their prognoses.

Purpose-Built Immunoinformatics for BcR IG/TR Repertoire Data Analysis

The study of antigen receptor gene repertoires using next-generation sequencing (NGS) technologies has disclosed an unprecedented depth of complexity, requiring novel computational and analytical solutions. Several bioinformatics workflows have been developed to this end, including the T-cell receptor/immunoglobulin profiler (TRIP), a web application implemented in R shiny, specifically designed for the purposes of comprehensive repertoire analysis, which is the focus of this chapter. TRIP has the potential to perform robust immunoprofiling analysis through the extraction and processing of the IMGT/HighV-Quest output, via a series of functions, ensuring the analysis of high-quality, biologically relevant data through a multilevel process of data filtering. Subsequently, it provides in-depth analysis of antigen receptor gene rearrangements, including (a) clonality assessment; (b) extraction of variable (V), diversity (D), and joining (J) gene repertoires; (c) CDR3 characterization at both the nucleotide and amino acid level; and (d) somatic hypermutation analysis, in the case of immunoglobulin gene rearrangements. Relevant to mention, TRIP enables a high level of customization through the integration of various options in key aspects of the analysis, such as clonotype definition and computation, hence allowing for flexibility without compromising on accuracy.

Influenza vaccination induces autoimmunity against orexinergic neurons in a mouse model for narcolepsy

Narcolepsy with cataplexy or narcolepsy type 1 is a disabling chronic sleep disorder resulting from the destruction of orexinergic neurons in the hypothalamus. The tight association of narcolepsy with HLA-DQB1*06:02 strongly suggest an autoimmune origin to this disease. Furthermore, converging epidemiological studies have identified an increased incidence for narcolepsy in Europe following Pandemrix® vaccination against the 2009-2010 pandemic 'influenza' virus strain. The potential immunological link between the Pandemrix® vaccination and narcolepsy remains, however, unknown. Deciphering these mechanisms may reveal pathways potentially at play in most cases of narcolepsy. Here, we developed a mouse model allowing to track and study the T-cell response against 'influenza' virus haemagglutinin, which was selectively expressed in the orexinergic neurons as a new self-antigen. Pandemrix® vaccination in this mouse model resulted in hypothalamic inflammation and selective destruction of orexin-producing neurons. Further investigations on the relative contribution of T-cell subsets in this process revealed that haemagglutinin-specific CD4 T cells were necessary for the development of hypothalamic inflammation, but insufficient for killing orexinergic neurons. Conversely, haemagglutinin-specific CD8 T cells could not initiate inflammation but were the effectors of the destruction of orexinergic neurons. Additional studies revealed pathways potentially involved in the disease process. Notably, the interferon-γ pathway was proven essential, as interferon-γ-deficient CD8 T cells were unable to elicit the loss of orexinergic neurons. Our work demonstrates that an immunopathological process mimicking narcolepsy can be elicited by immune cross-reactivity between a vaccine antigen and a neuronal self-antigen. This process relies on a synergy between autoreactive CD4 and CD8 T cells for disease development. This work furthers our understanding of the mechanisms and pathways potentially involved in the development of a neurological side effect due to a vaccine and, likely, to narcolepsy in general.

TCR-L: an analysis tool for evaluating the association between the T-cell receptor repertoire and clinical phenotypes

Background

T cell receptors (TCRs) play critical roles in adaptive immune responses, and recent advances in genome technology have made it possible to examine the T cell receptor (TCR) repertoire at the individual sequence level. The analysis of the TCR repertoire with respect to clinical phenotypes can yield novel insights into the etiology and progression of immune-mediated diseases. However, methods for association analysis of the TCR repertoire have not been well developed.

Methods

We introduce an analysis tool, TCR-L, for evaluating the association between the TCR repertoire and disease outcomes. Our approach is developed under a mixed effect modeling, where the fixed effect represents features that can be explicitly extracted from TCR sequences while the random effect represents features that are hidden in TCR sequences and are difficult to be extracted. Statistical tests are developed to examine the two types of effects independently, and then the p values are combined.

Results

Simulation studies demonstrate that (1) the proposed approach can control the type I error well; and (2) the power of the proposed approach is greater than approaches that consider fixed effect only or random effect only. The analysis of real data from a skin cutaneous melanoma study identifies an association between the TCR repertoire and the short/long-term survival of patients.

Conclusion

The TCR-L can accommodate features that can be extracted as well as features that are hidden in TCR sequences. TCR-L provides a powerful approach for identifying association between TCR repertoire and disease outcomes.

Protective HLA Alleles Recruit Biased and Largely Similar Antigen-Specific T Cell Repertoires across Different Outcomes in HIV Infection

CD8⁺ T cells play an important role in the control of untreated HIV infection. Several studies have suggested a decisive role of TCRs involved in anti-HIV immunity. HLA-B*27 and B*57 are often associated with a delayed HIV disease progression, but the exact correlates that provide superior immunity against HIV are not known. To investigate if the T cell repertoire underlies the protective effect in disease outcome in HLA-B*27 and B*57⁺ individuals, we analyzed Ag-specific TCR profiles from progressors (n = 13) and slow progressors (n = 11) expressing either B*27 or B*57. Our data showed no differences in TCR diversity between progressors and slow progressors. Both alleles recruit biased T cell repertoires (i.e., TCR populations skewed toward specific TRBV families or CDR3 regions). This bias was unrelated to disease progression and was remarkably profound for HLA-B*57, in which TRBV family usage and CDR3 sequences were shared to some extent even between epitopes. Conclusively, these data suggest that the T cell repertoires recruited by protective HLA alleles are highly similar between progressors and slow progressors in terms of TCR diversity, TCR usage, and cross-reactivity.

T-Cell Receptor Repertoire Analysis with Computational Tools-An Immunologist's Perspective

Over the last few years, there has been a rapid expansion in the application of information technology to biological data. Particularly the field of immunology has seen great strides in recent years. The development of next-generation sequencing (NGS) and single-cell technologies also brought forth a revolution in the characterization of immune repertoires. T-cell receptor (TCR) repertoires carry comprehensive information on the history of an individual’s antigen exposure. They serve as correlates of host protection and tolerance, as well as biomarkers of immunological perturbation by natural infections, vaccines or immunotherapies. Their interrogation yields large amounts of data. This requires a suite of highly sophisticated bioinformatics tools to leverage the meaning and complexity of the large datasets. Many different tools and methods, specifically designed for various aspects of immunological research, have recently emerged. Thus, researchers are now confronted with the issue of having to choose the right kind of approach to analyze, visualize and ultimately solve their task at hand. In order to help immunologists to choose from the vastness of available tools for their data analysis, this review addresses and compares commonly used bioinformatics tools for TCR repertoire analysis and illustrates the advantages and limitations of these tools from an immunologist’s perspective.

Cognate recognition of microbial antigens defines constricted CD4+ T cell receptor repertoires in the inflamed colon

Key aspects of intestinal T cells, including their antigen specificity and their selection by the microbiota and other intestinal antigens, as well as the contribution of individual T cell clones to regulatory and effector functions, remain unresolved. Here we tracked adoptively transferred T cell populations to specify the interrelation of T cell receptor repertoire and the gut antigenic environment. We show that dominant TCRα clonotypes were shared between interferon-γ- and interleukin-17-producing but not regulatory Foxp3⁺ T cells. Identical TCRα clonotypes accumulated in the colon of different individuals, whereas antibiotics or defined colonization correlated with the expansion of distinct expanded T cell clonotypes. Our results demonstrate key aspects of intestinal CD4⁺ T cell activation and suggest that few microbial species exert a dominant effect on the intestinal T cell repertoire during colitis. We speculate that dominant proinflammatory T cell clones might provide a therapeutic target in human inflammatory bowel disease.

Tools for fundamental analysis functions of TCR repertoires: a systematic comparison

The full set of T cell receptors (TCRs) in an individual is known as his or her TCR repertoire. Defining TCR repertoires under physiological conditions and in response to a disease or vaccine may lead to a better understanding of adaptive immunity and thus has great biological and clinical value. In the past decade, several high-throughput sequencing-based tools have been developed to assign TCRs to germline genes and to extract complementarity-determining region 3 (CDR3) sequences using different algorithms. Although these tools claim to be able to perform the full range of fundamental TCR repertoire analyses, there is no clear consensus of which tool is best suited to particular projects. Here, we present a systematic analysis of 12 available TCR repertoire analysis tools using simulated data, with an emphasis on fundamental analysis functions. Our results shed light on the detailed functions of TCR repertoire analysis tools and may therefore help researchers in the field to choose the right tools for their particular experimental design.

Evaluating the impact of age on immune checkpoint therapy biomarkers

Both tumors and aging alter the immune landscape of tissues. These interactions may play an important role in tumor progression among elderly patients and may suggest considerations for patient care. We leverage large-scale genomic and clinical databases to perform comprehensive comparative analysis of molecular and cellular markers of immune checkpoint blockade (ICB) response with patient age. These analyses demonstrate that aging is associated with increased tumor mutational burden, increased expression and decreased promoter methylation of immune checkpoint genes, and increased interferon gamma signaling in older patients in many cancer types studied, all of which are expected to promote ICB efficacy. Concurrently, we observe age-related alterations that might be expected to reduce ICB efficacy, such as decreases in T cell receptor diversity. Altogether, these changes suggest the capacity for robust ICB response in many older patients, which may warrant large-scale prospective study on ICB therapies among patients of advanced age.

Receptor repertoires of murine follicular T helper cells reveal a high clonal overlap in separate lymph nodes in autoimmunity

Follicular T helper cells (Tfh) are a specialized subset of CD4 effector T cells that are crucial for germinal center (GC) reactions and for selecting B cells to undergo affinity maturation. Despite this central role for humoral immunity, only few data exist about their clonal distribution when multiple lymphoid organs are exposed to the same antigen (Ag) as it is the case in autoimmunity. Here, we used an autoantibody-mediated disease model of the skin and injected one auto-Ag into the two footpads of the same mouse and analyzed the T cell receptor (TCR)β sequences of Tfh located in GCs of both contralateral draining lymph nodes. We found that over 90% of the dominant GC-Tfh clonotypes were shared in both lymph nodes but only transiently. The initially dominant Tfh clonotypes especially declined after establishment of chronic disease while GC reaction and autoimmune disease continued. Our data demonstrates a dynamic behavior of Tfh clonotypes under autoimmune conditions and emphasizes the importance of the time point for distinguishing auto-Ag-specific Tfh clonotypes from potential bystander activated ones.

High-throughput and single-cell T cell receptor sequencing technologies

T cells express T cell receptors (TCRs) composed of somatically recombined TCRα and TCRβ chains, which mediate recognition of major histocompatibility complex (MHC)-antigen complexes and drive the antigen-specific adaptive immune response to pathogens and cancer. The TCR repertoire in each individual is highly diverse, which allows for recognition of a wide array of foreign antigens, but also presents a challenge in analyzing this response using conventional methods. Recent studies have developed high-throughput sequencing technologies to identify TCR sequences, analyze their antigen specificities using experimental and computational tools, and pair TCRs with transcriptional and epigenetic cell state phenotypes in single cells. In this Review, we highlight these technological advances and describe how they have been applied to discover fundamental insights into T cell-mediated immunity.

A comparison of immune receptor recombination databases sourced from tumour exome or RNAseq files: Verifications of immunological distinctions between primary and metastatic melanoma

It became apparent several years ago that RNAseq and exome files prepared from tissue could be mined for adaptive immune receptor (IR) recombinations, which has given extra value to datasets originally intended for gene expression or mutation studies. For example, recovery of IR recombination reads from tumour specimen genomics files can correlate with survival rates. In particular, many benchmarking processes have been applied to the two sets of the IR recombination reads obtained from the cancer genome atlas files, but these two sets have never been directly compared. Here we show that both sets largely agree regarding several parameters. For example, recovery of TRB recombination reads from both WXS and RNAseq files representing metastatic melanoma was associated with a better outcome (p < .0004 in both cases); and T-cell receptor recombination read recovery, for both genomics file types, associated very strongly with T-cell gene expression markers. However, the use of CDR3 chemical features for survival distinctions was not consistent. This topic, and the surprising result that both datasets indicated that primary melanoma with recovery of IR recombination reads, in stark contrast to metastatic melanoma, represents a worse outcome, are discussed.

A comparative study of multiple instance learning methods for cancer detection using T-cell receptor sequences

As a branch of machine learning, multiple instance learning (MIL) learns from a collection of labeled bags, each containing a set of instances. The learning process is weakly supervised due to ambiguous instance labels. Since its emergence, MIL has been applied to solve various problems including content-based image retrieval, object tracking/detection, and computer-aided diagnosis. In biomedical research, the use of MIL has been focused on medical image analysis and molecule activity prediction. We review and apply 16 methods to investigate the applicability of MIL to a novel biomedical application, cancer detection using T-cell receptor (TCR) sequences. This important application can be a viable approach for large-scale cancer screening, as TCRs can be easily profiled from a subject's peripheral blood. We consider two feasible data-generating mechanisms, and for the purpose of performance evaluation, we simulate data under each mechanism, where we vary potentially important factors to mimic realistic situations. We also apply the methods to sequencing data of ten cancer types from The Cancer Genome Atlas, as an early proof of concept for distinguishing tumor patients from healthy individuals via TCR sequencing of peripheral blood. We find that given an appropriate MIL method is used, satisfactory performance with Area Under the Receiver Operating Characteristic Curve above 80% can be achieved for five in the ten cancers. Based on our numerical results, we make suggestions about selection of a proper method and avoidance of any method with poor performance. We further point out directions of future research as well as identify a pressing need of new MIL methodologies for improved performance (for some cancer types) and more explainable outcomes.

Neoantigen landscape in metastatic nasopharyngeal carcinoma

Background: Reportedly, nasopharyngeal carcinoma (NPC) patients with MHC I Class aberration are prone to poor survival outcomes, which indicates that the deficiency of tumor neoantigens might represent a mechanism of immune surveillance escape in NPC.

Methods: To clearly delineate the landscape of neoantigens in NPC, we performed DNA and RNA sequencing on paired primary tumor, regional lymph node metastasis and distant metastasis samples from 26 patients. Neoantigens were predicted using pVACseq pipeline. Subtype prediction model was built using random forest algorithm.

Results: Portraying the landscape of neoantigens in NPC for the first time, we found that the neoantigen load of NPC was above average compared to that of other cancers in The Cancer Genome Atlas program. While the quantity and quality of neoantigens were similar among primary tumor, regional lymph node metastasis and distant metastasis samples, neoantigen depletion was more severe in metastatic sites than in primary tumors. Upon tracking the clonality change of neoantigens, we found that neoantigen reduction occurred during metastasis. Building a subtype prediction model based on reported data, we observed that subtype I lacked T cells and suffered from severe neoantigen depletion, subtype II highly expressed immune checkpoint molecules and suffered from the least neoantigen depletion, and subtype III was heterogenous.

Conclusions: These results indicate that neoantigens are conducive to the guidance of clinical treatment, and personalized therapeutic vaccines for NPC deserve deeper basic and clinical investigations to make them feasible in the future.

Common clonal origin of conventional T cells and induced regulatory T cells in breast cancer patients

Regulatory CD4+ T cells (Treg) prevent tumor clearance by conventional T cells (Tconv) comprising a major obstacle of cancer immune-surveillance. Hitherto, the mechanisms of Treg repertoire formation in human cancers remain largely unclear. Here, we analyze Treg clonal origin in breast cancer patients using T-Cell Receptor and single-cell transcriptome sequencing. While Treg in peripheral blood and breast tumors are clonally distinct, Tconv clones, including tumor-antigen reactive effectors (Teff), are detected in both compartments. Tumor-infiltrating CD4+ cells accumulate into distinct transcriptome clusters, including early activated Tconv, uncommitted Teff, Th1 Teff, suppressive Treg and pro-tumorigenic Treg. Trajectory analysis suggests early activated Tconv differentiation either into Th1 Teff or into suppressive and pro-tumorigenic Treg. Importantly, Tconv, activated Tconv and Treg share highly-expanded clones contributing up to 65% of intratumoral Treg. Here we show that Treg in human breast cancer may considerably stem from antigen-experienced Tconv converting into secondary induced Treg through intratumoral activation.

Surface NKG2C Identifies Differentiated αβT-Cell Clones Expanded in Peripheral Blood

T cells that express CD56 in peripheral blood of healthy humans represent a heterogeneous and poorly studied subset. In this work, we analyzed this subset for NKG2C expression. In both CD56+ and CD56- subsets most of the NKG2C+ T cells had a phenotype of highly differentiated CD8+ TEMRA cells. The CD56+NKG2C+ T cells also expressed a number of NK cell receptors, such as NKG2D, CD16, KIR2DL2/DL3, and maturation marker CD57 more often than the CD56-NKG2C+CD3+ cells. TCR β-chain repertoire of the CD3+CD56+NKG2C+ cell fraction was limited by the prevalence of one or several clonotypes which can be found within the most abundant clonotypes in total or CD8+ T cell fraction TCRβ repertoire. Thus, NKG2C expression in highly differentiated CD56+ T cells was associated with the most expanded αβ T cell clones. NKG2C+ T cells produced almost no IFN-γ in response to stimulation with HCMV pp65-derived peptides. This may be partially due to the high content of CD45RA+CD57+ cells in the fraction. CD3+NKG2C+ cells showed signs of activation, and the frequency of this T-cell subset in HCMV-positive individuals was positively correlated with the frequency of NKG2C+ NK cells that may imply a coordinated in a certain extent development of the NKG2C+ T and NK cell subsets under HCMV infection.

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

It is known that a subpopulation of T cells expresses two T cell receptor (TCR) clonotypes, though the extent and functional significance of this is not established. To definitively evaluate dual TCRα cells, we generated mice with green fluorescent protein and red fluorescent protein reporters linked to TCRα, revealing that ∼16% of T cells express dual TCRs, notably higher than prior estimates. Importantly, dual TCR expression has functional consequences, as dual TCR cells predominated response to lymphocytic choriomeningitis virus infection, comprising up to 60% of virus-specific CD4⁺ and CD8⁺ T cells during acute responses. Dual receptor expression selectively influenced immune memory, as postinfection memory CD4⁺ populations contained significantly increased frequencies of dual TCR cells. These data reveal a previously unappreciated contribution of dual TCR cells to the immune repertoire and highlight their potential effects on immune responses.

Preselection TCR repertoire predicts CD4+ and CD8+ T-cell differentiation state

T cells must display diversity regarding both the cell state and T-cell receptor (TCR) repertoire to provide effective immunity against pathogens; however, the generation and evolution of cellular T-cell heterogeneity in the adaptive immune system remains unclear. In the present study, a combination of multiplex PCR and immune repertoire sequencing (IR-seq) was used for a standardized analysis of the TCR β-chain repertoire of CD4⁺ naive, CD4⁺ memory, CD8⁺ naive and CD8⁺ memory T cells. We showed that the T-cell subsets could be distinguished from each another with regard to the TCR β-chain (TCR-β) diversity, CDR3 length distribution and TRBV usage, which could be observed both in the preselection and in the post-selection repertoire. Moreover, the Dβ-Jβ and Vβ-Dβ combination patterns at the initial recombination step, template-independent insertion of nucleotides and inter-subset overlap were consistent between the pre- and post-selection repertoires, with a remarkably positive correlation. Taken together, these results support differentiation of the CD4⁺ and CD8⁺ T-cell subsets prior to thymic selection, and these differences survived both positive and negative selection. In conclusion, these findings provide deeper insight into the generation and evolution of TCR repertoire generation.

TRIP - T cell receptor/immunoglobulin profiler

Background

Antigen receptors are characterized by an extreme diversity of specificities, which poses major computational and analytical challenges, particularly in the era of high-throughput immunoprofiling by next generation sequencing (NGS). The T cell Receptor/Immunoglobulin Profiler (TRIP) tool offers the opportunity for an in-depth analysis based on the processing of the output files of the IMGT/HighV-Quest tool, a standard in NGS immunoprofiling, through a number of interoperable modules. These provide detailed information about antigen receptor gene rearrangements, including variable (V), diversity (D) and joining (J) gene usage, CDR3 amino acid and nucleotide composition and clonality of both T cell receptors (TR) and B cell receptor immunoglobulins (BcR IG), and characteristics of the somatic hypermutation within the BcR IG genes. TRIP is a web application implemented in R shiny.

Results

Two sets of experiments have been performed in order to evaluate the efficiency and performance of the TRIP tool. The first used a number of synthetic datasets, ranging from 250k to 1M sequences, and established the linear response time of the tool (about 6 h for 1M sequences processed through the entire BcR IG data pipeline). The reproducibility of the tool was tested comparing the results produced by the main TRIP workflow with the results from a previous pipeline used on the Galaxy platform. As expected, no significant differences were noted between the two tools; although the preselection process seems to be stricter within the TRIP pipeline, about 0.1% more rearrangements were filtered out, with no impact on the final results.

Conclusions

TRIP is a software framework that provides analytical services on antigen receptor gene sequence data. It is accurate and contains functions for data wrangling, cleaning, analysis and visualization, enabling the user to build a pipeline tailored to their needs. TRIP is publicly available at https://bio.tools/TRIP_-_T-cell_Receptor_Immunoglobulin_Profiler.

PIRD: Pan Immune Repertoire Database

MOTIVATION

T and B cell receptors (TCRs and BCRs) play a pivotal role in the adaptive immune system by recognizing an enormous variety of external and internal antigens. Understanding these receptors is critical for exploring the process of immunoreaction and exploiting potential applications in immunotherapy and antibody drug design. Although a large number of samples have had their TCR and BCR repertoires sequenced using high-throughput sequencing in recent years, very few databases have been constructed to store these kinds of data. To resolve this issue, we developed a database.

RESULTS

We developed a database, the Pan Immune Repertoire Database (PIRD), located in China National GeneBank (CNGBdb), to collect and store annotated TCR and BCR sequencing data, including from Homo sapiens and other species. In addition to data storage, PIRD also provides functions of data visualization and interactive online analysis. Additionally, a manually curated database of TCRs and BCRs targeting known antigens (TBAdb) was also deposited in PIRD.

AVAILABILITY AND IMPLEMENTATION

PIRD can be freely accessed at https://db.cngb.org/pird.

γ9δ2T cell diversity and the receptor interface with tumor cells

γ9δ2T cells play a major role in cancer immune surveillance, yet the clinical translation of their in vitro promise remains challenging. To address limitations of previous clinical attempts using expanded γ9δ2T cells, we explored the clonal diversity of γ9δ2T cell repertoires and characterized their target. We demonstrated that only a fraction of expanded γ9δ2T cells was active against cancer cells and that activity of the parental clone, or functional avidity of selected γ9δ2 T cell receptors (γ9δ2TCRs), was not associated with clonal frequency. Furthermore, we analyzed the target-receptor interface and provided a 2-receptor, 3-ligand model. We found that activation was initiated by binding of the γ9δ2TCR to BTN2A1 through the regions between CDR2 and CDR3 of the TCR γ chain and modulated by the affinity of the CDR3 region of the TCRδ chain, which was phosphoantigen independent (pAg independent) and did not depend on CD277. CD277 was secondary, serving as a mandatory coactivating ligand. We found that binding of CD277 to its putative ligand did not depend on the presence of γ9δ2TCR, did depend on usage of the intracellular CD277, created pAg-dependent proximity to BTN2A1, enhanced cell-cell conjugate formation, and stabilized the immunological synapse (IS). This process critically depended on the affinity of the γ9δ2TCR and required membrane flexibility of the γ9δ2TCR and CD277, facilitating their polarization and high-density recruitment during IS formation.

VisTCR: An Interactive Software for T Cell Repertoire Sequencing Data Analysis

Recent progress in high throughput sequencing technologies has provided an opportunity to probe T cell receptor (TCR) repertoire, bringing about an explosion of TCR sequencing data and analysis tools. For easier and more heuristic analysis TCR sequencing data, we developed a client-based HTML program (VisTCR). It has a data storage module and a data analysis module that integrate multiple cutting-edge analysis algorithms in a hierarchical fashion. Researchers can group and re-group samples for different analysis purposes by customized "Experiment Design File." Moreover, the VisTCR provides a user-friendly interactive interface, by all the TCR analysis methods and visualization results can be accessed and saved as tables or graphs in the process of analysis. The source code is freely available at https://github.com/qingshanni/VisTCR.

The Identity Card of T Cells-Clinical Utility of T-cell Receptor Repertoire Analysis in Transplantation

There is a clear medical need to change the current strategy of "one-size-fits-all" immunosuppression for controlling transplant rejection to precision medicine and targeted immune intervention. As T cells play a key role in both undesired graft rejection and protection, a better understanding of the fate and function of both alloreactive graft-deteriorating T cells and those protecting to infections is required. The T-cell receptor (TCR) is the individual identity card of each T cell clone and can help to follow single specificities. In this context, tracking of lymphocytes with certain specificity in blood and tissue in clinical follow up is of especial importance. After overcoming technical limitations of the past, novel molecular technologies opened new avenues of diagnostics. Using advantages of next generation sequencing, a method was established for T-cell tracing by detection of variable TCR region as identifiers of individual lymphocyte clones. The current review describes principles of laboratory and computational methods of TCR repertoire analysis, and gives an overview on applications for the basic understanding of transplant biology and immune monitoring. The review also delineates methodological pitfalls and challenges. With the outlook on prediction of antigens in immune-mediated processes including those of unknown causative pathogens, monitoring the fate and function of individual T cell clones, and the adoptive transfer of protective effector or regulatory T cells, this review highlights the current and future capability of TCR repertoire analysis.

T cell receptor repertoire as a prognosis marker for heat shock protein peptide complex-96 vaccine trial against newly diagnosed glioblastoma

Glioblastoma multiforme (GBM) is the most common primary malignant brain tumor in adults with a dismal prognosis. We previously reported that vaccination with heat shock protein peptide complex-96 (HSPPC-96) improves survival in patients with newly diagnosed GBM (NCT02122822). Especially for patients with a strong antitumor immune response after vaccination, a durable survival benefit can be achieved. Here, we conducted T cell receptor (TCR) sequencing to retrospectively examine the TCR repertoires of tumor-infiltrating lymphocytes in long-term survivors (LTS) and short-term survivors (STS). We found that LTS exhibit lower TCR repertoire diversity compared with STS, indicating the prevalence of dominant TCR clones in LTS tumors. Accordingly, the LTS group showed increased inter-patient similarity, especially among high-frequency TCR clones, implying some of these dominant clones are shared among LTS. Indeed, we discovered four TCR clones significantly enriched in the LTS group: the presence of these clones has predictive value for stratifying patients prior to vaccination. Together, these findings uncover a group of preexisting TCR clones shared in LTS that can be utilized as candidate biomarkers to select GBM patients most likely to durably respond to HSPPC-96 treatment.

Molecular T-Cell Repertoire Analysis as Source of Prognostic and Predictive Biomarkers for Checkpoint Blockade Immunotherapy

The T cells are key players of the response to checkpoint blockade immunotherapy (CBI) and monitoring the strength and specificity of antitumor T-cell reactivity remains a crucial but elusive component of precision immunotherapy. The entire assembly of T-cell receptor (TCR) sequences accounts for antigen specificity and strength of the T-cell immune response. The TCR repertoire hence represents a “footprint” of the conditions faced by T cells that dynamically evolves according to the challenges that arise for the immune system, such as tumor neo-antigenic load. Hence, TCR repertoire analysis is becoming increasingly important to comprehensively understand the nature of a successful antitumor T-cell response, and to improve the success and safety of current CBI.

Using RNA Sequencing to Characterize the Tumor Microenvironment

RNA sequencing (RNA-seq) is an integral tool in immunogenomics, allowing for interrogation of the transcriptome of a tumor and its microenvironment. Analytical methods to deconstruct the genomics data can then be applied to infer gene expression patterns associated with the presence of various immunocyte populations. High quality RNA-seq is possible from formalin-fixed, paraffin-embedded (FFPE), fresh-frozen, and fresh tissue, with a wide variety of sequencing library preparation methods, sequencing platforms, and downstream bioinformatics analyses currently available. Selection of an appropriate library preparation method is largely determined by tissue type, quality of RNA, and quantity of RNA. Downstream of sequencing, many analyses can be applied to the data, including differential gene expression analysis, immune gene signature analysis, gene pathway analysis, T/B-cell receptor inference, HLA inference, and viral transcript quantification. In this chapter, we will describe our workflow for RNA-seq from bulk tissue to evaluable data, including extraction of RNA, library preparation methods, sequencing of libraries, alignment and quality assurance of data, and initial downstream analyses of RNA-seq data to extract relevant immunogenomics features. Systems biology methods that draw additional insights by integrating these features are covered further in Chapters 28 - 30 .

Tissue-specific shaping of the TCR repertoire and antigen specificity of iNKT cells

Tissue homeostasis is critically dependent on the function of tissue-resident lymphocytes, including lipid-reactive invariant natural killer T (iNKT) cells. Yet, if and how the tissue environment shapes the antigen specificity of iNKT cells remains unknown. By analysing iNKT cells from lymphoid tissues of mice and humans we demonstrate that their T cell receptor (TCR) repertoire is highly diverse and is distinct for cells from various tissues resulting in differential lipid-antigen recognition. Within peripheral tissues iNKT cell recent thymic emigrants exhibit a different TCR repertoire than mature cells, suggesting that the iNKT population is shaped after arrival to the periphery. Consistent with this, iNKT cells from different organs show distinct basal activation, proliferation and clonal expansion. Moreover, the iNKT cell TCR repertoire changes following immunisation and is shaped by age and environmental changes. Thus, post-thymic modification of the TCR-repertoire underpins the distinct antigen specificity for iNKT cells in peripheral tissues

No difference in TCRβ repertoire of CD4+ naive T cell between patients with primary biliary cholangitis and healthy control subjects

Primary biliary cholangitis (PBC) is considered as a model of organ-specific autoimmune disease based on the serological findings of anti-mitochondrial antibodies (AMA), infiltrates of T cells, and selective destruction of epithelial cells in the liver. T-cell-mediated autoimmune mechanisms are considered to be involved in the pathogenesis of primary biliary cholangitis (PBC). In this context, we used a combination of multiplex-PCR, Illumina sequencing and IMGT/HighV-QUEST for a standardized analysis of the T cell receptor β-chain (TCRβ) repertoire of CD4^＋naive T cells in PBC patients compared with healthy volunteers. Nonfunctional TCRs were used to study the pre-selection TCR repertoire, as they are not subject to functional selection (positive and negative selection). Functional TCRs were used to study the post-selection TCR repertoire. The results showed that there was not significant difference between PBC patients and healthy volunteers in TCRβ diversity, CDR3 length distributions, degree of sequence sharing, and usage frequency of TRBV and TRBJ segments, no matter in Pre-selection or Post-selection repertoires. In conclusion, early events in thymic T cell development and repertoire generation are not abnormality in PBC patients. The breakdown of self-tolerance to autoantigen may be derived from other immunological dysregulation or environmental agents.

Identification of a CD8+ T-cell response to a predicted neoantigen in malignant mesothelioma

Neoantigens present unique and specific targets for personalized cancer immunotherapy strategies. Given the low mutational burden yet immunotherapy responsiveness of malignant mesothelioma (MM) when compared to other carcinogen-induced malignancies, identifying candidate neoantigens and T cells that recognize them has been a challenge. We used pleural effusions to gain access to MM tumor cells as well as immune cells in order to characterize the tumor-immune interface in MM. We characterized the landscape of potential neoantigens from SNVs identified in 27 MM patients and performed whole transcriptome sequencing of cell populations from 18 patient-matched pleural effusions. IFNγ ELISpot was performed to detect a CD8+ T cell responses to predicted neoantigens in one patient. We detected a median of 68 (range 7–258) predicted neoantigens across the samples. Wild-type non-binding to mutant binding predicted neoantigens increased risk of death in a model adjusting for age, sex, smoking status, histology and treatment (HR: 33.22, CI: 2.55–433.02, p = .007). Gene expression analysis indicated a dynamic immune environment within the pleural effusions. TCR clonotypes increased with predicted neoantigen burden. A strong activated CD8+ T-cell response was identified for a predicted neoantigen produced by a spontaneous mutation in the ROBO3 gene. Despite the challenges associated with the identification of bonafide neoantigens, there is growing evidence that these molecular changes can provide an actionable target for personalized therapeutics in difficult to treat cancers. Our findings support the existence of candidate neoantigens in MM despite the low mutation burden of the tumor, and may present improved treatment opportunities for patients.

HPV-positive status associated with inflamed immune microenvironment and improved response to anti-PD-1 therapy in head and neck squamous cell carcinoma

Chemotherapy and radiotherapy predominantly improve the clinical outcomes of patients with human papillomavirus (HPV)-related head and neck squamous cell carcinoma (HNSCC). Whether this superiority goes on when treated with immune checkpoint inhibitors is still unclear. This study sought to determine the predictive value and potential mechanisms of HPV status for the treatment of programmed cell death 1 (PD-1)/ligand 1(PD-L1) inhibitors. We conducted an integrated analysis of the relationships between HPV status and PD-L1, tumor mutation burden (TMB) and inflammation-related immune cells and molecules, based on the analysis of repository databases and resected HNSCC specimens. The pooled analysis of overall survival (OS) and objective response rate (ORR) suggested that HPV-positive patients benefited more from PD-1/PD-L1 inhibitors than HPV-negative patients (OS: hazard ratio (HR) = 0.71, p = 0.02; ORR: 21.9% vs 14.1%, odds ratio (OR) = 1.79, p = 0.01). Analysis of public databases and resected HNSCC specimens revealed that HPV status was independent of PD-L1 expression and TMB in HNSCC. However, HPV infection significantly increased T-cell infiltration, immune effector cell activation and the diversity of T-cell receptors. Notably, HPV-positivity correlated with increased immune cytolytic activity and a T-cell-inflamed gene expression profile. This work provides evidence that HPV status can be used to predict the effectiveness of PD-1 inhibitors in HNSCC, independently of PD-L1 expression and TMB, and probably results from an inflamed immune microenvironment induced by HPV infection.

Analysis of TCR β CDR3 sequencing data for tracking anti-tumor immunity

Anti-tumor T cells are the soldiers in the body's war against cancer. Effector T cells can detect and eliminate cells expressing their cognate antigen via activation through engagement of the T cell receptor (TCR) with its cognate peptide:MHC complex. Owing to the recent success of immunotherapy in the treatment of many different cancer types, research efforts have shifted toward identifying and tracking anti-tumor T cell responses upon treatment in cancer patients. While traditional methods, such as ELISpot and flow cytometric intracellular staining have had limited success, likely owing to the inability to get viable biospecimens or the lower magnitude of tumor-specific T cell responses relative to virus-specific responses, new techniques that utilize next generation sequencing enable T cell response tracking independent of cytokine production or cell viability. The TCR, which confers T cell antigen-specificity, can be used as a molecular barcode to track T cell clonotypic dynamics across biological compartments and over time in cancer patients undergoing treatment. Because this method does not require viable cells, these T cell clonotypes can also be tracked in archival tumor tissue and flash frozen cell pellets. While exciting, quantitative TCR sequencing (TCRseq) technologies have been met with the conundrum of how to properly analyze and interpret the data. Here we provide a comprehensive guide on how to acquire, analyze, and interpret TCRseq data, as well as special considerations that should be taken prior to experimental setup.

Characterization of Distinct T Cell Receptor Repertoires in Tumor and Distant Non-tumor Tissues from Lung Cancer Patients

T cells and T cell receptors (TCRs) play pivotal roles in adaptive immune responses against tumors. The development of next-generation sequencing technologies has enabled the analysis of the TCRβ repertoire usage. Given the scarce investigations on the TCR repertoire in lung cancer tissues, in this study, we analyzed TCRβ repertoires in lung cancer tissues and the matched distant non-tumor lung tissues (normal lung tissues) from 15 lung cancer patients. Based on our results, the general distribution of T cell clones was similar between cancer tissues and normal lung tissues; however, the proportion of highly expanded clones was significantly higher in normal lung tissues than in cancer tissues (0.021% ± 0.002% vs. 0.016% ± 0.001%, P = 0.0054, Wilcoxon signed rank test). In addition, a significantly higher TCR diversity was observed in cancer tissues than in normal lung tissues (431.37 ± 305.96 vs. 166.20 ± 101.58, P = 0.0075, Mann-Whitney U test). Moreover, younger patients had a significantly higher TCR diversity than older patients (640.7 ± 295.3 vs. 291.8 ± 233.6, P = 0.036, Mann-Whitney U test), and the higher TCR diversity in tumors was significantly associated with worse cancer outcomes. Thus, we provided a comprehensive comparison of the TCR repertoires between cancer tissues and matched normal lung tissues and demonstrated the presence of distinct T cell immune microenvironments in lung cancer patients.

TCR repertoire and CDR3 motif analyses depict the role of αβ T cells in Ankylosing spondylitis

Background

Ankylosing spondylitis (AS) is a chronic inflammatory disease with worldwide high prevalence. Although AS is strongly associated with HLA-B27 MHC-I antigen presentation, the role played by αβ T cells in AS remains elusive.

Methods

Utilizing TCRβ repertoire sequencing and bioinformatics tools developed in house, we analyzed overall TCR repertoire structures and antigen-recognizing CDR3 motifs in AS patients with different disease activities.

Findings

We found that disease progression is associated with both CD4+ and CD8+ T cell oligo-clonal expansion, which suggests that αβ T cell activation may mediate AS disease progression. By developing a bioinformatics platform to dissect antigen-specific responses, we discovered a cell population consisting of both CD4+ and CD8+ T cells expressing identical TCRs, herein termed CD4/8 T cells. CD4/8 clonotypes were highly enriched in the spondyloarthritic joint fluid of patients, and their expansion correlated with the activity of disease.

Interpretation

These results provide evidence on the T cell clone side to reveal the potential role of CD4/8 T cells in the etiology of AS development.

Systematic comparative study of computational methods for T-cell receptor sequencing data analysis

High-throughput sequencing technologies have exposed the possibilities for the in-depth evaluation of T-cell receptor (TCR) repertoires. These studies are highly relevant to gain insights into human adaptive immunity and to decipher the composition and diversity of antigen receptors in physiological and disease conditions. The major objective of TCR sequencing data analysis is the identification of V, D and J gene segments, complementarity-determining region 3 (CDR3) sequence extraction and clonality analysis. With the advancement in sequencing technologies, new TCR analysis approaches and programs have been developed. However, there is still a deficit of systematic comparative studies to assist in the selection of an optimal analysis approach. Here, we present a detailed comparison of 10 state-of-the-art TCR analysis tools on samples with different complexities by taking into account many aspects such as clonotype detection [unique V(D)J combination], CDR3 identification or accuracy in error correction. We used our in silico and experimental data sets with known clonalities enabling the identification of potential tool biases. We also established a new strategy, named clonal plane, which allows quantifying and comparing the clonality of multiple samples. Our results provide new insights into the effect of method selection on analysis results, and it will assist users in the selection of an appropriate analysis method.

Shorter TCR β-Chains Are Highly Enriched During Thymic Selection and Antigen-Driven Selection

The adaptive immune system uses several strategies to generate a repertoire of T cell receptors (TCR) with sufficient diversity to recognize the universe of potential pathogens. However, it remains unclear how differences in the T cell receptor (TCR) contribute to heterogeneity in T cell state. In this study, we used polychromatic flow cytometry to isolate highly pure CD4⁺/CD8⁺ naive and memory T cells, and applied deep sequencing to characterize corresponding TCR β-chain (TCRβ) complementary-determining region 3 (CDR3) repertoires. We find that shorter TCRβ CDR3s with fewer insertions were highly enriched during thymic selection. Antigen-experienced T cells (memory T cells) harbor shorter CDR3s vs. naive T cells. Moreover, the public TCRβ CDR3 clonotypes within cell subsets or interindividual tend to have shorter CDR3 length and a significantly larger size compared with “private” clonotypes. Taken together, shorter CDR3s highly enriched during thymic selection and antigen-driven selection, and further enriched in public T-cell responses. These results indicated that it may be evolutionary pressures drive short CDR3s to recognize most of antigen in nature.

Immune rebound associates with a favorable clinical response to autologous HSCT in systemic sclerosis patients

To evaluate the immunological mechanisms associated with clinical outcomes after autologous hematopoietic stem cell transplantation (AHSCT), focusing on regulatory T- (Treg) and B- (Breg) cell immune reconstitution, 31 systemic sclerosis (SSc) patients underwent simultaneous clinical and immunological evaluations over 36-month posttransplantation follow-up. Patients were retrospectively grouped into responders (n = 25) and nonresponders (n = 6), according to clinical response after AHSCT. Thymic function and B-cell neogenesis were respectively assessed by quantification of DNA excision circles generated during T- and B-cell receptor rearrangements. At the 1-year post-AHSCT evaluation of the total set of transplanted SSc patients, thymic rebound led to renewal of the immune system, with higher T-cell receptor (TCR) diversity, positive correlation between recent thymic emigrant and Treg counts, and higher expression of CTLA-4 and GITR on Tregs, when compared with pretransplant levels. In parallel, increased bone marrow output of newly generated naive B-cells, starting at 6 months after AHSCT, renovated the B-cell populations in peripheral blood. At 6 and 12 months after AHSCT, Bregs increased and produced higher interleukin-10 levels than before transplant. When the nonresponder patients were evaluated separately, Treg and Breg counts did not increase after AHSCT, and high TCR repertoire overlap between pre- and posttransplant periods indicated maintenance of underlying disease mechanisms. These data suggest that clinical improvement of SSc patients is related to increased counts of newly generated Tregs and Bregs after AHSCT as a result of coordinated thymic and bone marrow rebound.

CapTCR-seq: hybrid capture for T-cell receptor repertoire profiling

Mature T-cell lymphomas consisting of an expanded clonal population of T cells that possess common rearrangements of the T-cell receptor (TCR) encoding genes can be identified and monitored using molecular methods of T-cell repertoire analysis. We have developed a hybrid-capture method that enriches DNA sequencing libraries for fragments encoding rearranged TCR genes from all 4 loci in a single reaction. We use this method to describe the TCR repertoires of 63 putative lymphoma clinical isolates, 7 peripheral blood mononuclear cell (PBMC) populations, and a collection of tumor infiltrating lymphocytes. Dominant Variable (V) and Joining (J) gene pair rearrangements in cancer cells were confirmed by polymerase chain reaction (PCR) amplification and Sanger sequencing; clonality assessment of clinical isolates using BIOMED-2 methods showed agreement for 73% and 77% of samples at the β and γ loci, respectively, whereas β locus V and J allele prevalence in PBMCs were well correlated with results from commercial PCR-based DNA sequencing assays (r 2 = 0.94 with Adaptive ImmunoSEQ, 0.77-0.83 with Invivoscribe LymphoTrack TRB Assay). CapTCR-seq allows for rapid, high-throughput and flexible characterization of dominant clones within TCR repertoire that will facilitate quantitative analysis of patient samples and enhance sensitivity of tumor surveillance over time.

Low and variable tumor reactivity of the intratumoral TCR repertoire in human cancers

Infiltration of human cancers by T cells is generally interpreted as a sign of immune recognition, and there is a growing effort to reactivate dysfunctional T cells at such tumor sites¹. However, these efforts only have value if the intratumoral T cell receptor (TCR) repertoire of such cells is intrinsically tumor reactive, and this has not been established in an unbiased manner for most human cancers. To address this issue, we analyzed the intrinsic tumor reactivity of the intratumoral TCR repertoire of CD8⁺ T cells in ovarian and colorectal cancer-two tumor types for which T cell infiltrates form a positive prognostic marker^2,3. Data obtained demonstrate that a capacity to recognize autologous tumor is limited to approximately 10% of intratumoral CD8⁺ T cells. Furthermore, in two of four patient samples tested, no tumor-reactive TCRs were identified, despite infiltration of their tumors by T cells. These data indicate that the intrinsic capacity of intratumoral T cells to recognize adjacent tumor tissue can be rare and variable, and suggest that clinical efforts to reactivate intratumoral T cells will benefit from approaches that simultaneously increase the quality of the intratumoral TCR repertoire.

Evaluation of the capacities of mouse TCR profiling from short read RNA-seq data

Profiling T cell receptor (TCR) repertoire via short read transcriptome sequencing (RNA-Seq) has a unique advantage of probing simultaneously TCRs and the genome-wide RNA expression of other genes. However, compared to targeted amplicon approaches, the shorter read length is more prone to mapping error. In addition, only a small percentage of the genome-wide reads may cover the TCR loci and thus the repertoire could be significantly under-sampled. Although this approach has been applied in a few studies, the utility of transcriptome sequencing in probing TCR repertoires has not been evaluated extensively. Here we present a systematic assessment of RNA-Seq in TCR profiling. We evaluate the power of both Fluidigm C1 full-length single cell RNA-Seq and bulk RNA-Seq in characterizing the repertoires of different diversities under either naïve conditions or after immunogenic challenges. Standard read length and sequencing coverage were employed so that the evaluation was conducted in accord with the current RNA-Seq practices. Despite high sequencing depth in bulk RNA-Seq, we encountered difficulty quantifying TCRs with low transcript abundance (<1%). Nevertheless, top enriched TCRs with an abundance of 1–3% or higher can be faithfully detected and quantified. When top TCR sequences are of interest and transcriptome sequencing is available, it is worthwhile to conduct a TCR profiling using the RNA-Seq data.

Characteristic analysis of TCR β-chain CDR3 repertoire for pre- and post-liver transplantation

Liver cirrhosis of hepatitis B is an immune-related disease in which liver cells die during the body’s immune system activation to clear the virus, and the progress is closely related to T lymphocytes. T lymphocyte cells recognise antigens, specifically by major histocompatibility complex (MHC), through a membrane protein T cell receptor (TCR). Here, we used high throughput immune repertoire sequencing technique to study the characteristics and diversity of the TCR repertoire between patients who underwent liver transplantation and healthy controls (NC). We sequenced the TCR β-chain complementary-determining region 3 (CDR3) repertoire in peripheral blood mononuclear cells (PBMCs) from 6 liver transplantation patients before transplantation (Pre) and on the first (Post1) and seventh days (Post7) after transplantation along with 6 NC. We observed that the distributions of CDR3, VD indel, and DJ indel lengths were similar among the Pre, Post1, Post7 and NC groups. We found that the TCR repertoire diversity of transplantation groups was relatively lower compared to NC group. The Pre-group had more highly expanded T cell clones compared to Post1, Post7 and NC groups, and the diversity of the T cell repertoire of the Post7 group was significantly decreased compared to the Pre, Post1 and NC groups. In addition, we found our results also show that various TRBV expression increased and some public sequences at different time points after liver transplantation, and the expression levels of 3 TRBV segments and 2 TRBJ segments were also significantly different in Pre, Post1, Post7 and NC groups. Moreover, 1 aa sequence shared by all liver transplantation patients and 2 aa sequences shared by at least two groups, which may serve as biomarkers to monitor the immune status of liver transplant patients.

T-cell receptor-α repertoire of CD8+ T cells following allogeneic stem cell transplantation using next-generation sequencing

Alloreactivity or opportunistic infections following allogeneic stem cell transplantation are difficult to predict and contribute to post-transplantation mortality. How these immune reactions result in changes to the T-cell receptor repertoire remains largely unknown. Using next-generation sequencing, the T-cell receptor alpha (TRα) repertoire of naïve and memory CD8⁺ T cells from 25 patients who had received different forms of allogeneic transplantation was analyzed. In parallel, reconstitution of the CD8⁺/CD4⁺ T-cell subsets was mapped using flow cytometry. When comparing the influence of anti-T-cell therapy, a delay in the reconstitution of the naïve CD8⁺ T-cell repertoire was observed in patients who received in vivo T-cell depletion using antithymocyte globulin or post-transplantation cyclophosphamide in case of haploidentical transplantation. Sequencing of the TRα identified a repertoire consisting of more dominant clonotypes (>1% of reads) in these patients at 6 and 18 months post transplantation. When comparing donor and recipient, approximately 50% and approximately 80% of the donors’ memory repertoire were later retrieved in the naïve and memory CD8⁺ T-cell receptor repertoire of the recipients, respectively. Although there was a remarkable expansion of single clones observed in the recipients’ memory CD8⁺ TRα repertoire, no clear association between graft-versus-host disease or cytomegalovirus infection and T-cell receptor diversity was identified. A lower TRα diversity was observed in recipients of a cytomegalovirus-seropositive donor (P=0.014). These findings suggest that CD8⁺ T-cell reconstitution in transplanted patients is influenced by the use of T-cell depletion or immunosuppression and the donor repertoire.