Characterization of the T-cell receptor beta chain repertoire in tumor-infiltrating lymphocytes

The compositional behavior of the human T cell receptor repertoire in ovarian cancer compared to healthy donors

The distinctive characteristics of an individual's T cell receptor repertoire are crucial in recognizing and responding to a diverse array of antigens, contributing to immune specificity and adaptability. The repertoire, famously vast due to a series of cellular mechanisms, can be quantified using repertoire sequencing. In this study, we sampled the repertoire of 85 women: ovarian cancer patients (OC) and healthy donors (HD), generating a dataset of T cell clones and their abundance. For the alpha chain we obtained 6.4·106 reads, with an average of 75936 clones per sample, and an average of 30607 clonotypes per sample. For the beta chain we obtained 13.6·106 reads, with an average of 160400 clones per sample, and an average of 70071 clonotypes per sample. The changes in dynamics of the repertoire can be observed in response to disease, with specific clones undergoing clonal expansion and contraction. The data provided here offers a unique view of immune system behavior in health and disease and can be used to stratify OC and HD.

The Deep Learning Framework iCanTCR Enables Early Cancer Detection Using the T-cell Receptor Repertoire in Peripheral Blood

T cells recognize tumor antigens and initiate an anticancer immune response in the very early stages of tumor development, and the antigen specificity of T cells is determined by the T-cell receptor (TCR). Therefore, monitoring changes in the TCR repertoire in peripheral blood may offer a strategy to detect various cancers at a relatively early stage. Here, we developed the deep learning framework iCanTCR to identify patients with cancer based on the TCR repertoire. The iCanTCR framework uses TCRβ sequences from an individual as an input and outputs the predicted cancer probability. The model was trained on over 2,000 publicly available TCR repertoires from 11 types of cancer and healthy controls. Analysis of several additional publicly available datasets validated the ability of iCanTCR to distinguish patients with cancer from noncancer individuals and demonstrated the capability of iCanTCR for the accurate classification of multiple cancers. Importantly, iCanTCR precisely identified individuals with early-stage cancer with an AUC of 86%. Altogether, this work provides a liquid biopsy approach to capture immune signals from peripheral blood for noninvasive cancer diagnosis.

SIGNIFICANCE

Development of a deep learning-based method for multicancer detection using the TCR repertoire in the peripheral blood establishes the potential of evaluating circulating immune signals for noninvasive early cancer detection.

The combination of tumor mutational burden and T-cell receptor repertoire predicts the response to immunotherapy in patients with advanced non-small cell lung cancer

Tumor mutational burden (TMB) and T-cell receptor (TCR) might predict the response to immunotherapy in patients with non-small cell lung cancer (NSCLC). However, the predictive value of the combination of TMB and TCR was not clear. Targeted DNA and TCR sequencing were performed on tumor biopsy specimens. We combined TMB and TCR diversity into a TMB-and-TCR (TMR) score using logistic regression. In total, 38 patients with advanced NSCLC were divided into a discovery set (n = 17) and validation set (n = 21). A higher TMR score was associated with better response and longer progression-free survival to immunotherapy in both the discovery set and validation set. The performance of TMR score was confirmed in the two external validation cohorts of 225 NSCLC patients and 306 NSCLC patients. Tumors with higher TMR scores were more likely to combine with LRP1B gene mutation (p = 0.027) and top 1% CDR3 sequences (p = 0.001). Furthermore, LRP1B allele frequency was negatively correlated with the top 1% CDR3 sequences (r = -0.55, p = 0.033) and positively correlated with tumor shrinkage (r = 0.68, p = 0.007). The TMR score could serve as a potential predictive biomarker for the response to immunotherapy in advanced NSCLC.

Ovarian cancer is detectable from peripheral blood using machine learning over T-cell receptor repertoires

The extraordinary diversity of T cells and B cells is critical for body maintenance. This diversity has an important role in protecting against tumor formation. In humans, the T-cell receptor (TCR) repertoire is generated through a striking stochastic process called V(D)J recombination, in which different gene segments are assembled and modified, leading to extensive variety. In ovarian cancer (OC), an unfortunate 80% of cases are detected late, leading to poor survival outcomes. However, when detected early, approximately 94% of patients live longer than 5 years after diagnosis. Thus, early detection is critical for patient survival. To determine whether the TCR repertoire obtained from peripheral blood is associated with tumor status, we collected blood samples from 85 women with or without OC and obtained TCR information. We then used machine learning to learn the characteristics of samples and to finally predict, over a set of unseen samples, whether the person is with or without OC. We successfully stratified the two groups, thereby associating the peripheral blood TCR repertoire with the formation of OC tumors. A careful study of the origin of the set of T cells most informative for the signature indicated the involvement of a specific invariant natural killer T (iNKT) clone and a specific mucosal-associated invariant T (MAIT) clone. Our findings here support the proposition that tumor-relevant signal is maintained by the immune system and is coded in the T-cell repertoire available in peripheral blood. It is also possible that the immune system detects tumors early enough for repertoire technologies to inform us near the beginning of tumor formation. Although such detection is made by the immune system, we might be able to identify it, using repertoire data from peripheral blood, to offer a pragmatic way to search for early signs of cancer with minimal patient burden, possibly with enhanced sensitivity.

Tumor-Infiltrating Lymphocytes and Adoptive Cell Therapy: State of the Art in Colorectal, Breast and Lung Cancer

Our knowledge of tumor-infiltrating lymphocytes (TILs) is dramatically expanding. These cells have proven prognostic and therapeutic value for many cancer outcomes and potential to treat also disseminated breast, colorectal, or lung cancer. However, the therapeutical outcome of TILs is negatively affected by tumor mutational burden and neoantigens. On the other hand, it can be improved in combination with checkpoint blockade therapy. This knowledge and rapid detection techniques alongside gene editing allow us to classify and modify T cells in many ways. Hence, to tailor them precisely to the patient´s needs as to program T cell receptors to recognize specific tumor-associated neoantigens and to insert them into lymphocytes or to select tumor neoantigen-specific T cells, for the development of vaccines that recognize tumor-specific antigens in tumors or metastases. Further studies and clinical trials in the field are needed for an even better-detailed understanding of TILs interactions and aiming in the fight against multiple cancers.

Strategies for improving detection of circulating tumor DNA using next generation sequencing

Cancer has become a global health issue and liquid biopsy has emerged as a non-invasive tool for various applications. In cancer, circulating tumor DNA (ctDNA) can be detected from cell-free DNA (cfDNA) obtained from plasma and has potential for early diagnosis, treatment, resistance, minimal residual disease detection, and tumoral heterogeneity identification. However, the low frequency of ctDNA requires techniques for accurate analysis. Multitarget assay such as Next Generation Sequencing (NGS) need improvement to achieve limits of detection that can identify the low frequency variants present in the cfDNA. In this review, we provide a general overview of the use of cfDNA and ctDNA in cancer, and discuss techniques developed to optimize NGS as a tool for ctDNA detection. We also summarize the results obtained using NGS strategies in both investigational and clinical contexts.

Tumor-infiltrating lymphocyte: features and prognosis of lymphocytes infiltration on colorectal cancer

Tumor-infiltrating lymphocytes (TILs) are vital elements of the tumor microenvironment (TME), and the anti-tumor activity of TILs on colorectal cancer (CRC) has been a topic of concern. However, the characteristics and prognosis of the various types of lymphocyte infiltration in CRC have not been fully explained. Our study aimed to identify distinct features and prognosis of TILs. We integrated multiple-cohort databases to illustrate the features, proportions, and prognosis of TILs on CRC. We found that macrophages were significantly enriched in CRC. When we used the scRNA-seq database to further evaluate the proportion of TILs, we noticed markedly higher numbers of CD4 + T cell, B cell, and CD8 + T cell in four Gene Expression Omnibus Series (GSE) CRC cohorts. Interestingly, we found that the infiltrating level of TIL subgroups from highest to lowest is always dendritic cells, CD8 + T cells, CD4 + T cells, neutrophils, B cells, and macrophages; the proportion of infiltration is largely constant regardless of mutations in specific genes or somatic copy number variation (sCNV). In addition, the data corroborated that CD4+ TILs and CD8+ TILs have certain application values in the prognosis of CRCs, and age negatively related to CD8+ TILs and B plasma infiltration. Finally, patients with CRC who are older than 70 years have a better response to immune-checkpoint blockade.

T cell repertoire in peripheral blood as a potential biomarker for predicting response to concurrent cetuximab and nivolumab in head and neck squamous cell carcinoma

BACKGROUND

T cell receptor (TCR) signaling profile is a fundamental property that underpins both adaptive and innate immunity in the host. Despite its potential clinical relevance, the TCR repertoire in peripheral blood has not been thoroughly explored for its value as an immunotherapy efficacy biomarker in head and neck squamous cell carcinoma (HNSCC). The purpose of the present study is to characterize and compare the TCR repertoire in peripheral blood mononuclear cells (PBMC) from patients with HNSCC treated with the combination of cetuximab and nivolumab.

METHODS

We used the immunoSEQ assay to sequence the TCR beta (TCR-B) chain repertoire from serially obtained PBMC at baseline and during the treatments from a total of 41 patients who received the combination (NCT03370276). Key TCR repertoire metrics, including diversity and clonality, were calculated and compared between patients with different therapy responses and clinical characteristics (eg, human papillomavirus (HPV) status and smoking history). Patient survival outcomes were compared according to patient groups stratified by the TCR-B clonotyping. To confirm the observed patterns in TCR spectrum, samples from patients who achieved complete response (CR) and partial response (PR) were further profiled with the immunoSEQ deep resolution assay.

RESULTS

Our data indicated that the patients who achieved CR and PR had an increased TCR sequence diversity in their baseline samples, this tendency being more pronounced in HPV-negative patients or those with a smoking history. Notably, the CR/PR group had the lowest proportion of patients with oligoclonal TCR clones (2 out of 8 patients), followed by the stable disease group (9 out of 20 patients) and lastly the progressive disease group (7 out of 10 patients). An overall trend toward favorable patient survival was also observed in the polyclonal group. Finally, we reported the shared TCR clones across patients within the same response group, as well as the shared clones by aligning immunoSEQ reads with TCR data retrieved from The Cancer Genome Atlas- head and neck squamous cell carcinoma (TCGA-HNSC) cohort.

CONCLUSIONS

Our data suggest that, despite the great clinical heterogeneity of HNSCC and the limited responders in the present cohort, the peripheral TCR repertoires from pretreatment PBMC may be developed as biomarkers for the benefit of immunotherapy in HNSCC.

TCR-sequencing in cancer and autoimmunity: barcodes and beyond

The T cell receptor (TCR) endows T cells with antigen specificity and is central to nearly all aspects of T cell function. Each naïve T cell has a unique TCR sequence that is stably maintained during cell division. In this way, the TCR serves as a molecular barcode that tracks processes such as migration, differentiation, and proliferation of T cells. Recent technological advances have enabled sequencing of the TCR from single cells alongside deep molecular phenotypes on an unprecedented scale. In this review, we discuss strengths and limitations of TCR sequences as molecular barcodes and their application to study immune responses following Programmed Death-1 (PD-1) blockade in cancer. Additionally, we consider applications of TCR data beyond use as a barcode.

Biophysicochemical motifs in T cell receptor sequences as a potential biomarker for high-grade serous ovarian carcinoma

We previously showed, in a pilot study with publicly available data, that T cell receptor (TCR) repertoires from tumor infiltrating lymphocytes (TILs) could be distinguished from adjacent healthy tissue repertoires by the presence of TCRs bearing specific, biophysicochemical motifs in their antigen binding regions. We hypothesized that such motifs might allow development of a novel approach to cancer detection. The motifs were cancer specific and achieved high classification accuracy: we found distinct motifs for breast versus colorectal cancer-associated repertoires, and the colorectal cancer motif achieved 93% accuracy, while the breast cancer motif achieved 94% accuracy. In the current study, we sought to determine whether such motifs exist for ovarian cancer, a cancer type for which detection methods are urgently needed. We made two significant advances over the prior work. First, the prior study used patient-matched TILs and healthy repertoires, collecting healthy tissue adjacent to the tumors. The current study collected TILs from patients with high-grade serous ovarian carcinoma (HGSOC) and healthy ovary repertoires from cancer-free women undergoing hysterectomy/salpingo-oophorectomy for benign disease. Thus, the classification task is distinguishing women with cancer from women without cancer. Second, in the prior study, classification accuracy was measured by patient-hold-out cross-validation on the training data. In the current study, classification accuracy was additionally assessed on an independent cohort not used during model development to establish the generalizability of the motif to unseen data. Classification accuracy was 95% by patient-hold-out cross-validation on the training set and 80% when the model was applied to the blinded test set. The results on the blinded test set demonstrate a biophysicochemical TCR motif found overwhelmingly in women with HGSOC but rarely in women with healthy ovaries, strengthening the proposal that cancer detection approaches might benefit from incorporation of TCR motif-based biomarkers. Furthermore, these results call for studies on large cohorts to establish higher classification accuracies, as well as for studies in other cancer types.

The Diagnostic, Prognostic, and Therapeutic Potential of Adaptive Immune Receptor Repertoire Profiling in Cancer

Lymphocytes play a critical role in antitumor immune responses. They are directly targeted by some therapies, and the composition and spatial organization of intratumor T-cell populations is prognostic in some cancer types. A better understanding of lymphocyte population dynamics over the course of disease and in response to therapy is urgently needed to guide therapy decisions and to develop new therapy targets. Deep sequencing of the repertoire of antigen receptor-encoding genes expressed in a lymphocyte population has become a widely used approach for profiling the population's immune status. Lymphocyte antigen receptor repertoire deep sequencing data can be used to assess the clonal richness and diversity of lymphocyte populations; to track clone members over time, between tissues, and across lymphocyte subsets; to detect clonal expansion; and to detect the recruitment of new clones into a tissue. Repertoire sequencing is thus a critical complement to other methods of lymphocyte and immune profiling in cancer. This review describes the current state of knowledge based on repertoire sequencing studies conducted on human cancer patients, with a focus on studies of the T-cell receptor beta chain locus. The review then outlines important questions left unanswered and suggests future directions for the field.

Determination of the complexity and diversity of the TCR β-chain CDR3 repertoire in bladder cancer using high-throughput sequencing

The present study aimed to investigate the complexity and diversity of the T lymphocyte immune repertoire in patients with bladder cancer. To do so, the immune state of patients was assessed. The study also aimed to elucidate the aetiology and pathogenesis of bladder cancer to provide a novel theoretical basis for disease prevention, diagnosis, treatment and prognosis monitoring. Cancerous and paracancerous (control) tissue samples were collected from five patients diagnosed with muscle-invasive bladder cancer. Multiplex polymerase chain reaction and Illumina high-throughput sequencing were used to determine the characteristics and clonal diversity of the T-cell receptor (TCR) β-chain complementarity-determining region 3 (CDR3) gene in the cancerous and paracancerous tissues of patients with bladder cancer. The degree of clonal expansion in malignant samples was significantly higher than in adjacent samples. Furthermore, ΤCRβ variable (TRBV), ΤCRβ diversity (TRBD) and ΤCRβ joining (TRBJ) repertoires were significantly different in cancerous samples compared with adjacent samples. In addition, 13 identified V-J pairs were highly expressed in cancerous samples whereas they had low expression in control samples. In conclusion, the degree of T-cell clonal expansion in bladder cancerous tissue was higher than in paracancerous tissue, whereas the immune diversity of the tissues of patients with bladder cancer was significantly lower. The DNA sequence and amino acid sequences, and V-J combination level may be used to comprehensively understand the diversity and characteristics of TCR CDR3 in bladder cancer and paracancerous tissues, and to evaluate the immune status of bladder cancer to develop therapeutic targets and biomarkers for prognosis monitoring.

CDR3 repertoire diversity of CD8+ T lymphocytes in patients with HCV

T cell receptors (TCR) diversity is known to serve as a defining hallmark of the antigen-reactive T cell repertoire. Complementarity determining region 3 (CDR3) was the most important region for the recognition of peptide-major histocompatibility complex (MHC) complexes and represented the diversity of TCR repertoire. In this study, we detected the CDR3 spectratypes by complexity scoring system to assess TCR repertoire diversity and further analyzed the correlation of CDR3 score with CD8+ T cell function and with the prognosis of chronic hepatitis C virus (HCV)-infected patients. The results demonstrated that CDR3 score was related to CD8+ T cell function and prognosis by analyzing the clinical indicators such as viral load (VL), rapid virologic response (RVR), early virologic response (EVR) and sustained virologic response (SVR). Importantly, we found that Vβ27, a member of CDR3 subfamily, might play an important role in the clearance of HCV. These findings indicate that TCR diversity maybe serve as a biomarker to predict the clinical parameters of HCV-infected patients.

A comprehensive study of immunology repertoires in both preoperative stage and postoperative stage in patients with colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is the 3rd most common cancer type in the world. The correlation between immune repertoire and prognosis of CRC has been well studied in the last decades. The diversity and stability of the immune cells can be measured by hypervariable complementarity-determining region 3 (CDR3) segments of the T-cell receptor (TCR).

METHODS

In this study, we collected five healthy controls and 19 CRC patients' peripheral blood mononuclear cells (PBMCs) in three stages, namely 1 day preoperative, 3 days' postoperative, and 7 days' postoperative, respectively. Simultaneously, we have also done the comparative analysis of these two different anesthesia methods, namely TIVA and CEGA. Sequencing of the TCR segments has been performed by multiplex PCR and high-throughput next-generation sequencing. We also analyzed the distribution of CDR3 length, highly expansion clones (HECs), TRBV, and TRBJ gene usage.

RESULTS

Our result showed a significant difference between TCR CDR3 length distribution and HEC distribution between CRC patients and healthy controls. We also found that TRBV11-2, TRBV12-1, TRBV16, TRBV3-2, TRBV4-2, TRBV4-3, TRBV5-4, TRBV6-8, TRBV7-8, TRBV7-9 and RBV11-2, TRBV12-1, TRBV16, TRBV3-2, TRBV4-2, TRBV4-3, TRBV5-4, TRBV6-8, TRBV7-8, and TRBV7-9 usages are different between CRC patients and healthy controls.

CONCLUSION

In conclusion, CRC patients were presented with different immune repertoire in comparison with healthy controls. In this study, significant difference in TRBV and TRBJ gene usage in between case and control group could provide some potential biomarker for the diagnosis and the treatment of the patients with CRC.

Biophysicochemical Motifs in T-cell Receptor Sequences Distinguish Repertoires from Tumor-Infiltrating Lymphocyte and Adjacent Healthy Tissue

Immune repertoire deep sequencing allows comprehensive characterization of antigen receptor-encoding genes in a lymphocyte population. We hypothesized that this method could enable a novel approach to diagnose disease by identifying antigen receptor sequence patterns associated with clinical phenotypes. In this study, we developed statistical classifiers of T-cell receptor (TCR) repertoires that distinguish tumor tissue from patient-matched healthy tissue of the same organ. The basis of both classifiers was a biophysicochemical motif in the complementarity determining region 3 (CDR3) of TCRβ chains. To develop each classifier, we extracted 4-mers from every TCRβ CDR3 and represented each 4-mer using biophysicochemical features of its amino acid sequence combined with quantification of 4-mer (or receptor) abundance. This representation was scored using a logistic regression model. Unlike typical logistic regression, the classifier is fitted and validated under the requirement that at least 1 positively labeled 4-mer appears in every tumor repertoire and no positively labeled 4-mers appear in healthy tissue repertoires. We applied our method to publicly available data in which tumor and adjacent healthy tissue were collected from each patient. Using a patient-holdout cross-validation, our method achieved classification accuracy of 93% and 94% for colorectal and breast cancer, respectively. The parameter values for each classifier revealed distinct biophysicochemical properties for tumor-associated 4-mers within each cancer type. We propose that such motifs might be used to develop novel immune-based cancer screening assays. SIGNIFICANCE: This study presents a novel computational approach to identify T-cell repertoire differences between normal and tumor tissue.See related commentary by Zoete and Coukos, p. 1299.

Informatics for cancer immunotherapy

The rapid development of immunomodulatory cancer therapies has led to a concurrent increase in the application of informatics techniques to the analysis of tumors, the tumor microenvironment, and measures of systemic immunity. In this review, the use of tumors to gather genetic and expression data will first be explored. Next, techniques to assess tumor immunity are reviewed, including HLA status, predicted neoantigens, immune microenvironment deconvolution, and T-cell receptor sequencing. Attempts to integrate these data are in early stages of development and are discussed in this review. Finally, we review the application of these informatics strategies to therapy development, with a focus on vaccines, adoptive cell transfer, and checkpoint blockade therapies.

T Cell Receptor Profiling in Type 1 Diabetes

PURPOSE OF REVIEW

The genetic susceptibility and dominant protection for type 1 diabetes (T1D) associated with human leukocyte antigen (HLA) haplotypes, along with minor risk variants, have long been thought to shape the T cell receptor (TCR) repertoire and eventual phenotype of autoreactive T cells that mediate β-cell destruction. While autoantibodies provide robust markers of disease progression, early studies tracking autoreactive T cells largely failed to achieve clinical utility.

RECENT FINDINGS

Advances in acquisition of pancreata and islets from T1D organ donors have facilitated studies of T cells isolated from the target tissues. Immunosequencing of TCR α/β-chain complementarity determining regions, along with transcriptional profiling, offers the potential to transform biomarker discovery. Herein, we review recent studies characterizing the autoreactive TCR signature in T1D, emerging technologies, and the challenges and opportunities associated with tracking TCR molecular profiles during the natural history of T1D.

Characterization of the T-cell receptor beta chain repertoire in tumor-infiltrating lymphocytes

Tumor‐infiltrating lymphocytes (TILs) are direct effectors of tumor immunity, and their characterization is important for further development of immunotherapy. Recent advances in high‐throughput sequencing technologies have enabled a comprehensive analysis of T‐cell receptor (TCR) complementarity‐determining region 3 (CDR3) sequences, which may provide information of therapeutic importance. We developed a high‐fidelity target sequencing method with the ability for absolute quantitation, and performed large‐scale sequencing of TCR beta chain (TCRB) CDR3 regions in TILs and peripheral blood lymphocytes (PBLs). The estimated TCRB repertoire sizes of PBLs from four healthy individuals and TILs from four colorectal cancer tissue samples were 608,664–1,003,098 and 90,228–223,757, respectively. The usage of J‐ and V‐regions was similar in PBLs and TILs. Proportions of CDR3 amino acid (aa) sequences occupying more than 0.01% of the total molecular population were 0.33–0.43% in PBLs and 1.3–3.6% in TILs. Additional low coverage sequencing of 15 samples identified five CDR3 aa sequences that were shared by nine patients, one sequence shared by 10 patients, and one sequence shared by 12 patients. The estimated size of the TCRB repertoire in TILs was significantly smaller than that in PBLs. The proportion of abundant species (>0.01%) in TILs was larger than that in PBLs. Shared CDR3 aa sequences represent a response to common antigens, and the identification of such CDR3 sequences may be beneficial in developing clinical biomarkers.