Application of T cell receptor (TCR) repertoire analysis for the advancement of cancer immunotherapy

2022 ◽  
Vol 74 ◽  
pp. 1-8
Author(s):  
Kroopa Joshi ◽  
Martina Milighetti ◽  
Benjamin M Chain
2021 ◽  
Vol 12 ◽  
Author(s):  
Valentina Ceglia ◽  
Erin J. Kelley ◽  
Annalee S. Boyle ◽  
Sandra Zurawski ◽  
Heather L. Mead ◽  
...  

Common approaches for monitoring T cell responses are limited in their multiplexity and sensitivity. In contrast, deep sequencing of the T Cell Receptor (TCR) repertoire provides a global view that is limited only in terms of theoretical sensitivity due to the depth of available sampling; however, the assignment of antigen specificities within TCR repertoires has become a bottleneck. This study combines antigen-driven expansion, deep TCR sequencing, and a novel analysis framework to show that homologous ‘Clusters of Expanded TCRs (CETs)’ can be confidently identified without cell isolation, and assigned to antigen against a background of non-specific clones. We show that clonotypes within each CET respond to the same epitope, and that protein antigens stimulate multiple CETs reactive to constituent peptides. Finally, we demonstrate the personalized assignment of antigen-specificity to rare clones within fully-diverse uncultured repertoires. The method presented here may be used to monitor T cell responses to vaccination and immunotherapy with high fidelity.


2021 ◽  
Vol 9 (11) ◽  
pp. 1252-1261
Author(s):  
Uri Greenbaum ◽  
Ecaterina I. Dumbrava ◽  
Amadeo B. Biter ◽  
Cara L. Haymaker ◽  
David S. Hong

Pathogens ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 121
Author(s):  
Yu-Wen Liao ◽  
Bing-Ching Ho ◽  
Min-Hsuan Chen ◽  
Sung-Liang Yu

Enterovirus 71 (EV71) has become an important public health problem in the Asia-Pacific region in the past decades. EV71 infection might cause neurological and psychiatric complications and even death. Although an EV71 vaccine has been currently approved, there is no effective therapy for treating EV71-infected patients. Virus infections have been reported to shape host T cell receptor (TCR) repertoire. Therefore, understanding of host TCR repertoire in EV71 infection could better the knowledge in viral pathogenesis and further benefit the anti-viral therapy development. In this study, we used a mouse-adapted EV71 (mEV71) model to observe changes of host TCR repertoire in an EV71-infected central nervous system. Neonate mice were infected with mEV71 and mouse brainstem TCRβ repertoires were explored. Here, we reported that mEV71 infection impacted host brainstem TCRβ repertoire, where mEV71 infection skewed TCRβ diversity, changed VJ combination usages, and further expanded specific TCRβ CDR3 clones. Using bioinformatics analysis and ligand-binding prediction, we speculated the expanded TCRβ CDR3 clone harboring CASSLGANSDYTF sequence was capable of binding cleaved EV71 VP1 peptides in concert with major histocompatibility complex (MHC) molecules. We observed that mEV71 infection shaped host TCRβ repertoire and presumably expanded VP1-specific TCRβ CDR3 in mEV71-infected mouse brainstem that integrated EV71 pathogenesis in central nervous system.


Cancers ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2974
Author(s):  
Andrea Sesma ◽  
Julián Pardo ◽  
Mara Cruellas ◽  
Eva M. Gálvez ◽  
Marta Gascón ◽  
...  

Despite therapeutic advances, lung cancer (LC) is one of the leading causes of cancer morbidity and mortality worldwide. Recently, the treatment of advanced LC has experienced important changes in survival benefit due to immune checkpoint inhibitors (ICIs). However, overall response rates (ORR) remain low in unselected patients and a large proportion of patients undergo disease progression in the first weeks of treatment. Therefore, there is a need of biomarkers to identify patients who will benefit from ICIs. The programmed cell death ligand 1 (PD-L1) expression has been the first biomarker developed. However, its use as a robust predictive biomarker has been limited due to the variability of techniques used, with different antibodies and thresholds. In this context, tumor mutational burden (TMB) has emerged as an additional powerful biomarker based on the observation of successful response to ICIs in solid tumors with high TMB. TMB can be defined as the total number of nonsynonymous mutations per DNA megabases being a mechanism generating neoantigens conditioning the tumor immunogenicity and response to ICIs. However, the latest data provide conflicting results regarding its role as a biomarker. Moreover, considering the results of the recent data, the use of peripheral blood T cell receptor (TCR) repertoire could be a new predictive biomarker. This review summarises recent findings describing the clinical utility of TMB and TCRβ (TCRB) and concludes that immune, neontigen, and checkpoint targeted variables are required in combination for accurately identifying patients who most likely will benefit of ICIs.


2017 ◽  
Vol 77 (10) ◽  
pp. 2699-2711 ◽  
Author(s):  
Demin Li ◽  
Carol Bentley ◽  
Amanda Anderson ◽  
Sarah Wiblin ◽  
Kirstie L.S. Cleary ◽  
...  

2020 ◽  
Vol 59 (7) ◽  
pp. 862-870 ◽  
Author(s):  
Michele M. Hoffmann ◽  
Jill E. Slansky

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 1451-1451
Author(s):  
Chao Wang ◽  
Qiang Gong ◽  
Weiwei Zhang ◽  
Javeed Iqbal ◽  
Yang Hu ◽  
...  

Abstract Introduction: Diversity of the T-cell receptor (TCR) repertoire reflects the initial V(D)J recombination events as shaped by selection by self and foreign antigens. Next generation sequencing is a powerful method for profiling the TCR repertoire, including sequences encoding complementarity-determining region 3 (CDR3). Peripheral T-cell lymphoma (PTCL) is a group of malignancies that originate from mature T-cells. T-cell clonality of PTCL is routinely evaluated with a PCR-based method to detect TCR gamma and less frequently beta chain rearrangements using genomic DNA. However, there are limitations with this approach, chief among which is the lack of sequence information. To date, the TCR repertoire of different subtypes of PTCL remains poorly defined. Objective: The purpose of this study was to determine the utility of RNA-seq for assessing T-cell clonality and analyzing the TCR usage in PTCL samples. Methods: We analyzed RNA-seq data from 30 angioimmunoblastic T-cell lymphoma (AITL), 23 Anaplastic large cell lymphoma (ALCL), 10 PTCL-NOS, and 17 NKCL. Data from naïve T cells, TFH cells, and T-effector cells (CD4+ CD45RA− TCRβ+ PD-1lo CXCR5lo PSGL-1hi) were obtained from publicly available resources. Referenced TCR and immunoglobulin transcripts according to the International ImMunoGeneTics Information System (IMGT) database were quantified by Kallisto software. We divided the pattern of Vβ (T-cell receptor beta variable region) into three categories: monoclonal (mono- or bi-allelic), oligoclonal (3-4 dominant clones), and polyclonal. CDR3 sequences were extracted by MiXCR program. PCR of the gamma chain using genomic DNA was utilized to validate the clonality of selected cases. Single nucleotide variants (SNVs) were called from aligned RNA-seq data using Samtools and VarScan 2 programs. Results: Analysis of RNA-seq data identified preferential usage of TCR-Vβ, Dβ (diversity region), and Jβ (joining region), length diversity of CDR3, and usage of nontemplated bases. Dominant clones could be identified by transcriptome sequencing in most cases of AITL (21/30), ALCL (14/23), and PTCL-NOS (7/10). Median CDR3 length is 42 nucleotides (nt) in normal T cells, 41 nt in ALCL, 48 nt in PTCL-NOS, and 44 nt in AITL. In 30 AITL samples, 20 showed monoclonal Vβ with a single peak, and 9 showed polyclonal Vβ. One case had two dominant clones with different CDR3, only one of which was in frame, implying biallelic rearrangements. As many as 3511 clones supported by at least four reads could be detected in polyclonal cases. In monoclonal cases, the dominant clone varied between 11.8% and 92.8% of TCR with Vβ rearrangements. TRBV 20-1, which is the most commonly used segment in normal T cells, is also frequently used in the dominant clones in AITL. The monoclonal AITL cases showed mutation of TET2, RHOA, DNMT3A or IDH2 whereas most of the polyclonal cases were negative or had low VAF mutation suggesting low or absent of tumor infiltrate in the specimen sequenced. There is no obvious correlation of any of the mutations with Vβ usage. Clonal B cell expansion was noted in some AITL samples. The occurrence of a preferential TRBV9 expansion in PTCL-NOS was striking. More than half of ALCL samples (14/23) showed expression of clonal Vβ, but 3/14 dominant clones were out-of-frame. γ chain expression was very low in cells expressing TCRαβ, but both expression levels and clonality were higher in TCRγδ expressing tumors. NKCL did not express significant levels of TCR Vβ or Vγ genes. Discussion/Interpretation: Transcriptome sequencing is a useful tool for understanding the TCR repertoire in T cell lymphoma and for detecting clonality for diagnosis. Clonal, often out-of-frame, Vβ transcripts are detectable in most ALCL cases and preferential TRBV9 usage is found in PTCL-NOS. Disclosures No relevant conflicts of interest to declare.


2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 1075-1075
Author(s):  
Ju Won Kim ◽  
Yun Suk Yu ◽  
Jung Yoon Choi ◽  
Soohyeon Lee ◽  
Won Jin Chang ◽  
...  

1075 Background: Triple negative breast cancer (TNBC) is defined by the lack of two hormone receptors (HR) and human epidermal growth factor receptor 2 (HER2), and well known to have poor prognosis. In this study, we conducted a RNA sequencing including T-cell receptor (TCR) repertoire analysis to develop prognostic biomarker in patients with TNBC. In addition, genes and signaling pathways that correlated with selected biomarker were also investigated. Methods: Total of 78 tumor tissues from TNBC patients were participated for RNA-seq (Illumina Hiseq) analysis. Groups of significant genes were selected by differentially expressed genes (DEGs) analysis, whose expression levels differed more than 1.5 times between patients and normal, or early stage and advanced stage TNBC. Transcript expression levels for prognostic biomarker were analyzed based on R v3.4.3. Using CBS ProbePINGS, a genomic big data analytics platform, we evaluated druggable pathways and protein-protein interaction (PPI). The Interaction Frequency Ratio Score (IFRS) was calculated by investigating highly interactive pathways, and the drugs were matched to patients. TCR repertoire analysis was performed by MiXCR. Results: Ten candidate gene signatures were selected based on RNA sequencing data of each sample. Cross-validation through machine learning showed that the accuracy of the first-ranked signature was 92.3%, the second was 92.0%, and the third was 90.3%. The accuracy of 4th to 6th was 88.7%, and the accuracy of 7th to 10th was over 88.0%. Cross-validated gene signature, age, and TNM staging showed significant discriminant power under univariate Cox regression analysis (p < 0.05). In the CBS ProbePINGS, human papillomavirus infection, MAPK pathway, and tumorigenesis pathway were correlated with cell signaling. CDK2, FN1, and JUN genes were highly interactive each other. In addition, the drug matching result according to IFRS value suggested imatinib and regorafenib could be possible candidates. TCR repertoire analysis presented that number of clonecount was lower in recurrent or metastatic TNBC than early stage cancer. Conclusions: This study revealed a specific gene signatures that can accurately determine recurrence and metastasis in patients with TNBC based on RNA sequencing analysis. TCR repertoire analysis and CBS ProbePINGS could be valuable method in treatment selection


Sign in / Sign up

Export Citation Format

Share Document