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TCR diversity

T cells recognize specific antigens by generating a diversity of transmembrane T Cell Receptors (TCRs). TCR diversity is generated by a heterodimer protein structure of interchangeable αβ or δΥ subunits and genomic rearrangement of the variable (V) domain of the TCR genes’ α, β, δ, and Υ subunits. Over 1 million distinct αβ TCR combinations are possible, with similar estimates for TCR δΥ. Each TCR obtains specificity from its unique variable domain, which provides a means for profiling TCR diversity in a given sample.

When measured by transcriptomic analysis, the natural diversity of T cells helps define precise biomarkers for any immune-infiltrated tissue. Immune system responses to disease or therapy can be assessed by monitoring changes in the diversity of a tissue’s TCR RNA population.1 For example, profiling TCR diversity in cancer patients treated with immunotherapies such as anti-PD-1/PDL-1 may improve predictions of patient response.2 To date, T cell infiltration of the tumor microenvironment (TME) has been analyzed by bulk tissue analysis of the gene expression signature Tumor Inflammation Signature (TIS) to predict patient response to anti-PD-1/PDL-1 treatment. However, a subset of patients carrying the appropriate TIS profile fails to respond to treatment. More precise immune cell analysis should identify specific TCRs in the TME that improve predictions of treatment response in these patients,3 further advancing precision medicine.

TCR Diversity Identified in Patient Studies

Recent studies support the development of TCR diversity-derived biomarkers. One study, using various approaches including a beta version of the nCounter® TCR Diversity Panel, compared TCR profiles of children diagnosed with post-COVID Multisystem Inflammatory Syndrome (MIS-C) with profiles of healthy donors. Results showed 75% of MIS-C patients displayed expansions of TCRβ variable genes 11-2 (TRBV11-2)/Vβ21.3+ while control groups did not.4 Additionally, polyclonal Vβ21.3+ T cells were the only cells expressing the interleukins associated with the characteristic MIS-C cytokine storm.4 Another study examined T cells collected from eosinophilic esophagitis patients and found activation of allergy-specific T cells caused upregulation of genes involved in lipid metabolism dysregulation, a mechanism seen in multiple allergic diseases. Subsequent TCR profiling indicated a clonal convergence of T cell lineages that may be allergen-specific.5 Another publication discusses targeting the limited TCR repertoire of pathogenic TH2 cells and their downstream activation pathways as a possible personalized allergy treatment.6 Together, these publications point toward TCR diversity as a relevant biomarker for
future studies and clinical interventions.

The nCounter TCR Diversity Panel and GeoMx DSP TCR Profiling Add-On

NanoString’s gene expression analysis tools are well-positioned to characterize TCR Diversity in various sample types. The TCR Diversity Panel can quickly detect shifts in TCR diversity with a simple expression assay requiring zero sequencing or enzymatic steps, with sample analysis (presented as a TCR Diversity Score) ready in minutes from the automated ROSALIND® platform.

Additionally, an add-on set of TCR diversity probes for spatial biology is being introduced for use on the GeoMx Digital Spatial Profiler (DSP). Covering 146 known α, β, δ, and γ chain genes, the TCR Profiling Add-On can be spiked into the Human GeoMx Whole Transcriptome Atlas or the Human GeoMx Cancer Transcriptome Atlas. This approach provides TCR variant analysis for quantification and localization of specific TCR genes in fresh-frozen or FFPE tissue sections.

Whether you want to distinguish between clonal and polyclonal T cell expansions, identify downstream pathways that explain disease mechanisms, or gain insight into how tissues mount an immune response to a disease, spatially uncovering the diversity of TCR species with the GeoMx TCR Profiling Add-On can move your research forward.


1. nanostring.com/blog/t-cell-receptor-diversitywhat-are-you-missing/
2. pubmed.ncbi.nlm.nih.gov/28650338/
3. pubmed.ncbi.nlm.nih.gov/36002182/
4. pubmed.ncbi.nlm.nih.gov/34035116/
5. pubmed.ncbi.nlm.nih.gov/34389613/
6. www.science.org/doi/10.1126/sciimmunol.abj1366


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