![]() Single-cell sequencing is a breakthrough technology that can link phenotype with specificity, identifying T cell clones that are crucial for successful ICT. Discovery of predictive biomarkers could lie in novel analysis approaches, such as network analysis of amino acids similarities between TCR sequences. We discuss the advantages and limitations of current metrics used to characterize and represent TCR repertoire diversity. We will also explore how changes to the repertoire in different anatomical locations can better correlate and perhaps predict treatment outcome. Here, we review how the repertoire influences response to ICT and conversely how ICT affects repertoire diversity. T cell receptor (TCR) sequencing allows for sensitive tracking of dynamic changes in antigen-specific T cells at the clonal level, giving unprecedented insight into the mechanisms by which ICT alters T cell responses. T cell repertoires can be comprehensively profiled by high-throughput sequencing at the bulk and single-cell level. The specificity of adaptive immune cells, such as T and B cells, is determined by antigen-specific receptors. ICT primarily acts at the level of adaptive immunity. Understanding immune mechanisms that underlie responsiveness to ICT will help identify predictive biomarkers of response and develop treatments to convert non-responding patients to responding ones. However, the majority of treated patients do not respond. In particular, immune checkpoint therapy (ICT) leads to durable responses in some patients with some cancers. Immunotherapies have revolutionized cancer treatment.
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