Dissecting efficiency of a 5' rapid amplification of cDNA ends (5'-RACE) approach for profiling T-cell receptor beta repertoire

T-cell Receptor Repertoire Analysis in the Context of Transarterial Chemoembolization Synergy with Systemic Therapy for Hepatocellular Carcinoma

T-cell receptor (TCR) sequencing provides a novel platform for insight into and characterization of intricate T-cell profiles, advancing the understanding of tumor immune heterogeneity. Recently, transarterial chemoembolization (TACE) combined with systemic therapy has become the recommended regimen for advanced hepatocellular carcinoma. The regulation of the immune microenvironment after TACE and its impact on tumor progression and recurrence has been a focus of research. By examining and tracking fluctuations in the TCR repertoire following combination treatment, novel perspectives on the modulation of the tumor microenvironment post-TACE and the underlying mechanisms governing tumor progression and recurrence can be gained. Clarifying the distinctive metrics and dynamic alterations of the TCR repertoire within the context of combination therapy is imperative for understanding the mechanisms of anti-tumor immunity, assessing efficacy, exploiting novel treatments, and further advancing precision oncology in the treatment of hepatocellular carcinoma. In this review, we initially summarized the fundamental characteristics of TCR repertoire and depicted immune microenvironment remodeling after TACE. Ultimately, we illustrated the prospective applications of TCR repertoires in TACE combined with systemic therapy.

Benchmarking and integrating human B-cell receptor genomic and antibody proteomic profiling

Immunoglobulins (Ig), which exist either as B-cell receptors (BCR) on the surface of B cells or as antibodies when secreted, play a key role in the recognition and response to antigenic threats. The capability to jointly characterize the BCR and antibody repertoire is crucial for understanding human adaptive immunity. From peripheral blood, bulk BCR sequencing (bulkBCR-seq) currently provides the highest sampling depth, single-cell BCR sequencing (scBCR-seq) allows for paired chain characterization, and antibody peptide sequencing by tandem mass spectrometry (Ab-seq) provides information on the composition of secreted antibodies in the serum. Yet, it has not been benchmarked to what extent the datasets generated by these three technologies overlap and complement each other. To address this question, we isolated peripheral blood B cells from healthy human donors and sequenced BCRs at bulk and single-cell levels, in addition to utilizing publicly available sequencing data. Integrated analysis was performed on these datasets, resolved by replicates and across individuals. Simultaneously, serum antibodies were isolated, digested with multiple proteases, and analyzed with Ab-seq. Systems immunology analysis showed high concordance in repertoire features between bulk and scBCR-seq within individuals, especially when replicates were utilized. In addition, Ab-seq identified clonotype-specific peptides using both bulk and scBCR-seq library references, demonstrating the feasibility of combining scBCR-seq and Ab-seq for reconstructing paired-chain Ig sequences from the serum antibody repertoire. Collectively, our work serves as a proof-of-principle for combining bulk sequencing, single-cell sequencing, and mass spectrometry as complementary methods towards capturing humoral immunity in its entirety.

A current and future perspective on T cell receptor repertoire profiling

T cell receptors (TCR) play a vital role in the immune system's ability to recognize and respond to foreign antigens, relying on the highly polymorphic rearrangement of TCR genes. The recognition of autologous peptides by adaptive immunity may lead to the development and progression of autoimmune diseases. Understanding the specific TCR involved in this process can provide insights into the autoimmune process. RNA-seq (RNA sequencing) is a valuable tool for studying TCR repertoires by providing a comprehensive and quantitative analysis of the RNA transcripts. With the development of RNA technology, transcriptomic data must provide valuable information to model and predict TCR and antigen interaction and, more importantly, identify or predict neoantigens. This review provides an overview of the application and development of bulk RNA-seq and single-cell (SC) RNA-seq to examine the TCR repertoires. Furthermore, discussed here are bioinformatic tools that can be applied to study the structural biology of peptide/TCR/MHC (major histocompatibility complex) and predict antigenic epitopes using advanced artificial intelligence tools.

TCR sequencing and cloning methods for repertoire analysis and isolation of tumor-reactive TCRs

T cell receptor (TCR) technologies, including repertoire analyses and T cell engineering, are increasingly important in the clinical management of cellular immunity in cancer, transplantation, and other immune diseases. However, sensitive and reliable methods for repertoire analyses and TCR cloning are still lacking. Here, we report on SEQTR, a high-throughput approach to analyze human and mouse repertoires that is more sensitive, reproducible, and accurate as compared with commonly used assays, and thus more reliably captures the complexity of blood and tumor TCR repertoires. We also present a TCR cloning strategy to specifically amplify TCRs from T cell populations. Positioned downstream of single-cell or bulk TCR sequencing, it allows time- and cost-effective discovery, cloning, screening, and engineering of tumor-specific TCRs. Together, these methods will accelerate TCR repertoire analyses in discovery, translational, and clinical settings and permit fast TCR engineering for cellular therapies.

satmut_utils: a simulation and variant calling package for multiplexed assays of variant effect

The impact of millions of individual genetic variants on molecular phenotypes in coding sequences remains unknown. Multiplexed assays of variant effect (MAVEs) are scalable methods to annotate relevant variants, but existing software lacks standardization, requires cumbersome configuration, and does not scale to large targets. We present satmut_utils as a flexible solution for simulation and variant quantification. We then benchmark MAVE software using simulated and real MAVE data. We finally determine mRNA abundance for thousands of cystathionine beta-synthase variants using two experimental methods. The satmut_utils package enables high-performance analysis of MAVEs and reveals the capability of variants to alter mRNA abundance.

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

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

Enhancing diagnosis of T-cell lymphoma using non-recombined T-cell receptor sequences

Clonality assessment, which can detect neoplastic T cells by identifying the uniquely recombined T-cell receptor (TCR) genes, provides important support in the diagnosis of T-cell lymphoma (TCL). BIOMED-2 is the gold standard clonality assay and has proven to be effective in European TCL patients. However, we failed to prove its sensitivity in Taiwanese TCL patients, especially based on the TCRβ gene. To explore potential impact of genetic background in the BIOMED-2 test, we analyzed TCRβ sequences of 21 healthy individuals and two TCL patients. This analysis suggests that genetic variations in the BIOMED-2 primer sites could not explain the difference in sensitivity. The BIOMED-2 test results of the two TCL patients were positive and negative, respectively. Interestingly, a higher percentage (>81%) of non-recombined TCRβ sequences was observed in the test-negative patient than those of the test-positive patient and all healthy individuals (13~66%). The result suggests a new TCR target for enhancing TCL diagnosis. To further explore the hypothesis, we proposed a cost-effective digital PCR assay that quantifies the relative abundance of non-recombined TCRβ sequences containing a J2-2P~J2-3 segment. With the digital PCR assay, bone marrow specimens from TCL patients (n=9) showed a positive outcome (i.e., the relative abundance of the J2-2P~J2-3 sequences ≧5%), whereas non-TCL patients (n=6) gave a negative result. As five of nine TCL patients had a negative BIOMED-2 test result, the J2-2P~J2-3 sequences may improve TCL detection. This is the first report showing the capability of characterizing non-recombined TCR sequences as a supplementary strategy for the BIOMED-2 clonality test.

Analysis of TCR Repertoire by High-Throughput Sequencing Indicates the Feature of T Cell Immune Response after SARS-CoV-2 Infection

Coronavirus disease 2019 (COVID-19) is a global infectious disease caused by the SARS-CoV-2 coronavirus. T cells play an essential role in the body’s fighting against the virus invasion, and the T cell receptor (TCR) is crucial in T cell-mediated virus recognition and clearance. However, little has been known about the features of T cell response in convalescent COVID-19 patients. In this study, using 5′RACE technology and PacBio sequencing, we analyzed the TCR repertoire of COVID-19 patients after recovery for 2 weeks and 6 months compared with the healthy donors. The TCR clustering and CDR3 annotation were exploited to discover groups of patient-specific TCR clonotypes with potential SARS-CoV-2 antigen specificities. We first identified CD4⁺ and CD8⁺ T cell clones with certain clonal expansion after infection, and then observed the preferential recombination usage of V(D) J gene segments in CD4⁺ and CD8⁺ T cells of COVID-19 patients with different convalescent stages. More important, the TRBV6-5-TRBD2-TRBJ2-7 combination with high frequency was shared between CD4⁺ T and CD8⁺ T cells of different COVID-19 patients. Finally, we found the dominant characteristic motifs of the CDR3 sequence between recovered COVID-19 and healthy control. Our study provides novel insights on TCR in COVID-19 with different convalescent phases, contributing to our understanding of the immune response induced by SARS-CoV-2.