scholarly journals 69 Automated TRB locus haplotype analysis by long-amplicon TCRB chain sequencing for potential immune-related adverse events biomarker research

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A75-A75
Author(s):  
Jennifer Burke ◽  
Frances Chen ◽  
Jiajie Huang ◽  
Geoffrey Lowman ◽  
Timothy Looney ◽  
...  
Keyword(s):  
T Cell ◽  
Adverse Events ◽  
T Cell Receptor ◽  
Haplotype Analysis ◽  
Cell Receptor ◽  
Spearman Correlation ◽  
Sequencing Data ◽  
Haplotype Group ◽  
Group Assignment ◽  
Potential Biomarker

BackgroundIdentifying potential predictive biomarkers for immune related adverse events (irAEs) following checkpoint blockade inhibition (CPI) remains an outstanding goal of immune-oncology translational research. Polymorphism with the T cell receptor variable gene (TRBV) has been proposed as a potential risk factor for irAEs owing to a potential link between TRBV polymorphism and chronic autoimmune disease. Efforts to interrogate the potential biomarker utility of TRBV polymorphism have been hampered by the repetitive nature of the TRB locus. Our research has demonstrated a method for inferring TRB locus haplotypes from long-amplicon TCRB chain sequencing data, which we used to identify major haplotype groups in from nucleic acid. Here we present our research for a potential automated method for haplotype group assignment from TCRB chain sequencing data.MethodsRearranged TCRB chains from 10 blood samples were amplified and sequenced from 25ng peripheral blood total RNA via the Oncomine™ TCRB-LR assay using the Genexus™ Integrated Sequencer. 12 samples were run per chip with 4 samples run in each lane. TCRB clonotyping and repertoire feature analysis was performed using Genexus™ analysis software. Automated haplotype group assignment was performed by generation and comparison of TRBV allele profiles to those presented previously.1 For context, TCR evenness, convergence, and haplotype group assignment were compared to values obtained following analysis of the same samples via the GeneStudio™ S5 platform and Ion Reporter™ 5.12 software.ResultsTCR Evenness and convergence values were highly correlated across replicates run on the Genexus™ Integrated Sequencer (Spearman correlation >0.95 and >0.70, respectively). Evenness at equivalent clone count and convergence at equivalent sequencing depth were not significantly different across platforms (Spearman correlation >0.88). Haplotype group assignments demonstrated 100% agreement across replicates on both platforms.ConclusionsOur research has demonstrated a potential automated and reproducible method for TRB haplotype group assignment via the Oncomine™ TCR-Beta LR Assay, GX run on the Genexus™ Integrated Sequencer. Future studies will be needed to evaluate the potential biomarker utility of TRB haplotyping for the prediction of irAEs.For research use only not for diagnostic procedures.ReferenceLooney T, Duose D, Lowman G, Linch E, Hajjar J, Topacio-Hall D, Xu M, Zheng J, Alshawa A, Tapia C, Stephen B, Wang L, Meric-Bernstam F, Miller L, Glavin A, Lin L, Gong J, Conroy J, Morrison C, Hyland F, Naing A. Haplotype Analysis of the T-Cell Receptor Beta (TCRB) Locus by Long-amplicon TCRB Repertoire Sequencing. J Immunother Precis Oncol 2019;2:137–143.

scholarly journals Human T cell receptor occurrence patterns encode immune history, genetic background, and receptor specificity

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
William S DeWitt ◽  
Anajane Smith ◽  
Gary Schoch ◽  
John A Hansen ◽  
Frederick A Matsen ◽  
...  
Keyword(s):  
T Cell ◽  
T Cell Receptor ◽  
Genetic Background ◽  
Cell Receptor ◽  
Sequencing Data ◽  
Human T Cell ◽  
Disease Associations ◽  
Repertoire Sequencing ◽  
Mhc Polymorphism ◽  
Occurrence Patterns

The T cell receptor (TCR) repertoire encodes immune exposure history through the dynamic formation of immunological memory. Statistical analysis of repertoire sequencing data has the potential to decode disease associations from large cohorts with measured phenotypes. However, the repertoire perturbation induced by a given immunological challenge is conditioned on genetic background via major histocompatibility complex (MHC) polymorphism. We explore associations between MHC alleles, immune exposures, and shared TCRs in a large human cohort. Using a previously published repertoire sequencing dataset augmented with high-resolution MHC genotyping, our analysis reveals rich structure: striking imprints of common pathogens, clusters of co-occurring TCRs that may represent markers of shared immune exposures, and substantial variations in TCR-MHC association strength across MHC loci. Guided by atomic contacts in solved TCR:peptide-MHC structures, we identify sequence covariation between TCR and MHC. These insights and our analysis framework lay the groundwork for further explorations into TCR diversity.

scholarly journals Checkpoint-blocker induced autoimmunity is associated with pretreatment T cell expression profiles and favourable outcome in melanoma

2020 ◽  
Author(s):  
W. Ye ◽  
A Olsson-Brown ◽  
R. A. Watson ◽  
V. T. F. Cheung ◽  
R. D. Morgan ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Clinical Outcome ◽  
Adverse Events ◽  
Metastatic Melanoma ◽  
T Cell Receptor ◽  
Immune Checkpoint ◽  
Single Agent ◽  
Cell Receptor ◽  
Pre Treatment

1Abstract1.1BackgroundImmune checkpoint blockers (ICBs) activate CD8+ T cells to elicit anti-cancer activity but frequently lead to immune-related adverse events (irAEs). The relationship of irAE with baseline parameters and clinical outcome is unclear. We investigated associations between irAE development, CD8+ T cell receptor diversity and expression and clinical outcome in a non-trial setting.1.2MethodsPatients ≥18 years old with metastatic melanoma (MM) receiving combination ICB (ipilimumab plus nivolumab – cICB, n=60) or single-agent ICB (nivolumab/pembrolizumab – sICB, n=78) were prospectively recruited. We retrospectively evaluated the impact of irAEs on survival. This analysis was repeated in an independent cohort of MM patients treated at a separate institution (n=210, cICB:74, sICB:136). We performed RNA sequencing of CD8+ T cells isolated from patients prior to treatment, analysing T cell receptor clonality differential transcript expression according to irAE development.1.3Results48.6% of patients experienced treatment-related irAEs within the first 5 cycles of treatment. Development of irAE prior to the 5th cycle of ICB was associated with longer progression-free and overall survival (PFS, OS) in the primary cohort (log-rank test, PFS: P=0.00034; OS: P<0.0001), replicated in the secondary cohort (OS: P=0.00064). Across cohorts median survival for those patients not experiencing irAE was 14.4 (95% CI:9.6-19.5) months vs not-reached (95% CI:28.9 - Inf), P=3.0×10−7. Pre-treatment performance status and neutrophil count, but not BMI, were additional predictors of clinical outcome. Analysis of CD8+ T cells from 128 patients demonstrated irAE development was associated with increased T cell receptor diversity post-treatment (P=4.3×10−5). Development of irAE in sICB recipients was additionally associated with baseline differential expression of 224 transcripts (FDR<0.1), enriched in pro-inflammatory pathway genes including CYP4F3 and PTGS2.1.4ConclusionsEarly irAE development post-ICB is strongly associated with favourable survival in MM and increased diversity of peripheral CD8+ T cell receptors after treatment. irAE post-sICB is associated with pre-treatment upregulation of inflammatory pathways, indicating irAE development may reflect baseline immune activation states.Key messageImmune-related adverse events (irAEs) commonly occur in patients with metastatic melanoma treated with immune checkpoint blockade (ICB) therapy. In real world setting we find development of early irAEs post-ICB treatment is associated with survival benefit, indicative of a shared mechanism with anti-tumour efficacy. CD8+ T cells from patients who develop irAE show increased receptor diversity, and pre-treatment samples from patients who develop irAE post single-agent anti-PD1 show over-expression of inflammatory pathways, indicating baseline immune state can determine irAE development.

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

2017 ◽  
Vol 20 (1) ◽  
pp. 222-234 ◽  
Author(s):  
Saira Afzal ◽  
Irene Gil-Farina ◽  
Richard Gabriel ◽  
Shahzad Ahmad ◽  
Christof von Kalle ◽  
...  
Keyword(s):  
Data Analysis ◽  
T Cell ◽  
Comparative Study ◽  
T Cell Receptor ◽  
Computational Methods ◽  
Cell Receptor ◽  
Sequencing Data ◽  
Sequencing Data Analysis

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

PLoS ONE ◽  
2020 ◽  
Vol 15 (3) ◽  
pp. e0229569 ◽  
Author(s):  
Jared Ostmeyer ◽  
Elena Lucas ◽  
Scott Christley ◽  
Jayanthi Lea ◽  
Nancy Monson ◽  
...  
Keyword(s):  
T Cell ◽  
Ovarian Carcinoma ◽  
T Cell Receptor ◽  
Cell Receptor ◽  
High Grade ◽  
Serous Ovarian Carcinoma ◽  
Potential Biomarker

Evaluating the link between T cell receptor beta variable gene polymorphism and immune mediated adverse events during checkpoint blockade immunotherapy.

2018 ◽  
Vol 36 (15_suppl) ◽  
pp. e15002-e15002 ◽  
Author(s):  
Timothy Looney ◽  
Elizabeth Linch ◽  
Geoffrey Lowman ◽  
Lauren Miller ◽  
Jianping Zheng ◽  
...  
Keyword(s):  
T Cell ◽  
Adverse Events ◽  
Gene Polymorphism ◽  
T Cell Receptor ◽  
Cell Receptor ◽  
Immune Mediated ◽  
T Cell Receptor Beta ◽  
Variable Gene ◽  
Beta Variable ◽  
Receptor Beta

IMMU-28. DECONVOLUTION OF SPATIALLY RESOLVED T CELL RECEPTOR PROFILING (SPTCR-seq) UNCOVERED REGIONAL ANTI-TUMOR IMMUNITY IN GLIOBLASTOMA

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi98-vi98
Author(s):  
Jasim Kada Benotmane ◽  
Jan Kückelhaus ◽  
Kevin Joseph ◽  
Jürgen Beck ◽  
Oliver Schnell ◽  
...  
Keyword(s):  
T Cell ◽  
T Cell Receptor ◽  
Tumor Immunity ◽  
Clonal Evolution ◽  
Cell Receptor ◽  
Sequencing Data ◽  
Spatially Resolved ◽  
Long Read ◽  
T Cell Clonality ◽  
Cell Clonality

Abstract The diversity to T cell responses and clonality in spatially heterogeneous glioblastoma is of paramount importance to explore underlying mechanisms of anti-tumor immunity. Spatial transcriptomics, a novel technology to map the transcriptional architecture, is technically limited to discover T cell receptor (TCR) sequences as the 3' approach lacks sufficient coverage. Here, we established SPTCR-seq, a method to capture TCR sequences followed by long-read sequencing to enable full-length TCR reconstruction. We performed 10X Visium spatial transcriptomics on 9 primary and recurrent glioblastoma with both 3’-sequencing and SPTCR-seq. For SPTCR-seq, we target enriched T cell receptor sequences by capturing by hybridization followed by Oxford-Nanopore long-read sequencing. The on-target rate was above 80% for captured TCR genes and spatial barcode was successfully aligned in more than 60%. IgBlast and MixCR were used to reconstruct the TCR and map T cell clonality. Within our recent developed spatial transcriptomic analysis framework (SPATA2), we build a novel toolbox, SPATA-Immunology, which enables integration of stRNA-sequencing data and spatially resolved TCR sequencing. Our data showed that clonal evolution of T cells is limited to regional areas underpinned by significant spatial autocorrelation coefficient (0.6-0.95, padj&lt; 0.001). In the surrounding tumor cell spots, the recently described transcriptional program “reactive immune” (RI), was significantly enriched. Using spotlight, a computational approach to project scRNA-sequencing into the spatial space, we found a local enrichment of CD163 positive macrophages exclusively in areas of large T cell clonality. Imaging mass cytometry of a consecutive section confirmed the spatial confluence of T-cell infiltration and CD163-positive macrophages. Through DeepTCR we uncovered potential epitopes which correlate with T cell clonality and might help to discover novel targets for CART therapy. Spatial profiling of TCR sequences through SPTCR-seq is a powerful tool to investigate anti-tumor immunity in glioblastoma and allows to discover general and personalized targets for immunotherapy.

scholarly journals T-cell Receptor Diversity Estimates for Repertoires (TCRDivER) uses sequence similarity to find signatures of immune response

2021 ◽  
Author(s):  
Milena Vujović ◽  
Paolo Marcatili ◽  
Benny Chain ◽  
Joseph Kaplinsky ◽  
Thomas Lars Andresen
Keyword(s):  
T Cell ◽  
T Cell Receptor ◽  
Sequence Similarity ◽  
Cell Receptor ◽  
Sequence Motifs ◽  
Sequencing Data ◽  
Cell Repertoire ◽  
Specific Sequence ◽  
Clone Size ◽  
Diversity Estimates

AbstractWe propose TCRDivER, a global approach to T-cell repertoire comparison using diversity profiles sensitive to both clone size and sequence similarity. As immunotherapies improve, the long standing biological interest in connecting outcome with T cell receptor (TCR) repertoire status has become more urgent. Here we show that new insights can be extracted from high throughput repertoire sequencing data. Most current efforts focus on identification of immunisation-specific sequence motifs or on monitoring changes in frequency of individual clones. Applying TCRDivER to murine spleen samples shows it characterises an additional dimension of repertoire variation, beyond conventional diversity estimates, allowing distinction between immunised and non-immunised samples. We further apply TCRDivER to repertoires from human blood. In both cases we show characteristic relationships between repertoire features. These reveal biologically interpretable relationships between sequence similarity and clonal expansions. We thereby demonstrate a new tool for investigation in clinical and research applications.

scholarly journals Tracking SARS-CoV-2 T cells with epitope-T-cell receptor recognition models

2020 ◽  
Author(s):  
Pieter Meysman ◽  
Anna Postovskaya ◽  
Nicolas De Neuter ◽  
Benson Ogunjimi ◽  
Kris Laukens
Keyword(s):  
T Cells ◽  
T Cell ◽  
T Cell Receptor ◽  
Adaptive Immune Response ◽  
Adaptive Immune System ◽  
Cell Receptor ◽  
Sequencing Data ◽  
Adaptive Immune ◽  
Cell Diversity ◽  
Longitudinal Profiles

Much is still not understood about the human adaptive immune response to SARS-CoV-2, the causative agent of COVID-19. In this paper, we demonstrate the use of machine learning to classify SARS-CoV-2 epitope specific T-cell clonotypes in T-cell receptor (TCR) sequencing data. We apply these models to public TCR data and show how they can be used to study T-cell longitudinal profiles in COVID-19 patients to characterize how the adaptive immune system reacts to the SARS-CoV-2 virus. Our findings confirm prior knowledge that SARS-CoV-2 reactive T-cell diversity increases over the course of disease progression. However our results show a difference between those T cells that react to epitope unique to SARS-CoV-2, which show a more prominent increase, and those T cells that react to epitopes common to other coronaviruses, which begin at a higher baseline.

scholarly journals Haplotype Analysis of the T-Cell Receptor Beta (TCRB) Locus by Long-amplicon TCRB Repertoire Sequencing

2019 ◽  
Vol 0 (0) ◽  
pp. 0 ◽  
Author(s):  
TimothyJ Looney ◽  
DzifaY Duose ◽  
Geoffrey Lowman ◽  
Elizabeth Linch ◽  
Joud Hajjar ◽  
...  
Keyword(s):  
T Cell ◽  
T Cell Receptor ◽  
Haplotype Analysis ◽  
Cell Receptor ◽  
Repertoire Sequencing ◽  
T Cell Receptor Beta ◽  
Tcrb Locus ◽  
Receptor Beta

scholarly journals Profiling the T Cell Receptor Alpha/Delta Locus in Salmonids

2021 ◽  
Vol 12 ◽  
Author(s):  
Eva-Stina Edholm ◽  
Christopher Graham Fenton ◽  
Stanislas Mondot ◽  
Ruth H. Paulssen ◽  
Marie-Paule Lefranc ◽  
...  
Keyword(s):  
Rainbow Trout ◽  
T Cell ◽  
Atlantic Salmon ◽  
T Cell Receptor ◽  
High Throughput ◽  
Vaccine Development ◽  
Cell Receptor ◽  
T Cell Subsets ◽  
Sequencing Data ◽  
Repertoire Sequencing

In jawed vertebrates, two major T cell populations have been characterized. They are defined as α/β or γ/δ T cells, based on the expressed T cell receptor. Salmonids (family Salmonidae) include two key teleost species for aquaculture, rainbow trout (Oncorhynchus mykiss) and Atlantic salmon (Salmo salar) which constitute important models for fish immunology and important targets for vaccine development. The growing interest to decipher the dynamics of adaptive immune responses against pathogens or vaccines has resulted in recent efforts to sequence the immunoglobulin (IG) or antibodies and T cell receptor (TR) repertoire in these species. In this context, establishing a comprehensive and coherent locus annotation is the fundamental basis for the analysis of high-throughput repertoire sequencing data. We therefore decided to revisit the description and annotation of TRA/TRD locus in Atlantic salmon and two strains of rainbow trout (Swanson and Arlee) using the now available high-quality genome assemblies. Phylogenetic analysis of functional TRA/TRD V genes from these three genomes led to the definition of 25 subgroups shared by both species, some with particular feature. A total of 128 TRAJ genes were identified in Salmo, the majority with a close counterpart in Oncorhynchus. Analysis of expressed TRA repertoire indicates that most TRAV gene subgroups are expressed at mucosal and systemic level. The present work on TRA/TRD locus annotation along with the analysis of TRA repertoire sequencing data show the feasibility and advantages of a common salmonid TRA/TRD nomenclature that allows an accurate annotation and analysis of high-throughput sequencing results, across salmonid T cell subsets.

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