Tcr Clonality
Tcr Clonality - Related Videos
19:05
Measuring TCR-pMHC Binding In Situ using a FRET-based Microscopy Assay
0 Views •
Cited by 9 •
2015
This manuscript describes how to conduct (single molecule) Förster Resonance Energy Transfer (FRET)- based assays to measure the binding dynamics between T-cell antigen receptor (TCR) and antigenic peptide-loaded MHC molecules as they occur within the immunological synapse of a T-cell in contact with a functionalized planar supported lipid bilayer.
11:21
Streamlined Single Cell TCR Isolation and Generation of Retroviral Vectors for In Vitro and In Vivo Expression of Human TCRs
0 Views •
Cited by 3 •
2017
The current protocol combines single cell paired human TCR alpha and beta chain sequencing with streamlined generation of retroviral vectors compatible with in vitro and in vivo TCR expression.
10:32
Enumeration of Neural Stem Cells Using Clonal Assays
0 Views •
Cited by 5 •
2016
Neural stem cells (NSCs) refer to cells which can self-renew and differentiate into the three neural lineages. Here, we describe a protocol to determine NSC frequency in a given cell population using neurosphere formation and differentiation under clonal conditions.
16:10
A TIRF Microscopy Technique for Real-time, Simultaneous Imaging of the TCR and its Associated Signaling Proteins
0 Views •
Cited by 13 •
2012
The compartmentalization of proteins either within the plasma membrane or into intracellular locations is one regulatory mechanism that can greatly influence signaling outcomes; hence, to understand signaling it is important to study the spatial and temporal behavior of the proteins involved. We describe here a TIRF microscopy based system to study signal transduction in T cells, but is broadly applicable.
06:42
Identifying Kinase Inhibitors that Modulate the Thymocyte Response to Strong TCR Signals
0 Views •
2025
In this video, we describe a method to identify the small-molecule kinase inhibitors that modulate the apoptosis of self-reactive CD4+CD8+ double-positive immature thymocytes. Apoptosis is induced in the double-positive thymocytes by activating them with anti-CD3- and anti-CD28-coated magnetic beads; this is followed by a small-molecule inhibitor treatment and flow cytometry analysis to detect if the inhibitors modulate the apoptotic marker expression.
FAQs
The complementarity-determining region 3, or CDR3, forms part of the antigen-binding region of the T-cell receptor and varies among rearranged receptors. Profiling this region allows researchers to distinguish clonotypes and measure how frequently each appears in a T-cell population. In tumor samples, these frequencies help identify immune-cell expansions that may reflect responses to tumor-associated antigens.
Clonality profiling compares the frequencies of individual TCR rearrangements within a repertoire. A population dominated by a small number of clonotypes indicates concentrated expansion, whereas a broader distribution reflects greater receptor diversity. This distinction helps cancer researchers determine whether tumor-infiltrating lymphocytes show selective enrichment or a more varied immune response within and across tumors.
Identical or closely related TCR rearrangements can indicate groups of T cells with related receptor patterns. Examining these relationships adds context beyond counting completely distinct sequences, particularly when assessing preferential expansion in tumors. Such patterns may help clarify whether antitumor immunity develops through selective enrichment of related T-cell populations during disease progression or treatment.
The analysis begins by amplifying or sequencing rearranged TCR genes, with particular attention to the CDR3 region. The resulting rearrangements are assigned to clonotypes, and the frequency of each clonotype is quantified. Researchers can then characterize the immune repertoire by examining dominant populations, overall diversity, and changes in these measurements between tumor samples or study time points.
Researchers compare the clonotype frequencies and repertoire patterns obtained from different tumors or from samples collected before and after treatment. Increases or decreases in dominant clonotypes can indicate changing immune-cell expansion, while shifts in diversity can reveal broader repertoire changes. These comparisons help track how tumor-associated immune responses develop, persist, or change during therapy and disease progression.
TCR clonality profiling can show whether particular T-cell populations expand, contract, or remain prominent during immunotherapy. Linking these repertoire changes with treatment time points may help evaluate immune responses and identify patterns associated with therapeutic effects. The approach also supports biomarker research and can contribute to studies investigating how antitumor immunity develops in individual tumors.