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Review
. 2020 Mar 30;21(7):2378.
doi: 10.3390/ijms21072378.

Molecular T-Cell Repertoire Analysis as Source of Prognostic and Predictive Biomarkers for Checkpoint Blockade Immunotherapy

Affiliations
Review

Molecular T-Cell Repertoire Analysis as Source of Prognostic and Predictive Biomarkers for Checkpoint Blockade Immunotherapy

Ilenia Aversa et al. Int J Mol Sci. .

Abstract

The T cells are key players of the response to checkpoint blockade immunotherapy (CBI) and monitoring the strength and specificity of antitumor T-cell reactivity remains a crucial but elusive component of precision immunotherapy. The entire assembly of T-cell receptor (TCR) sequences accounts for antigen specificity and strength of the T-cell immune response. The TCR repertoire hence represents a "footprint" of the conditions faced by T cells that dynamically evolves according to the challenges that arise for the immune system, such as tumor neo-antigenic load. Hence, TCR repertoire analysis is becoming increasingly important to comprehensively understand the nature of a successful antitumor T-cell response, and to improve the success and safety of current CBI.

Keywords: T-cell repertoire; TCR clonotype; checkpoint blockade immunotherapy.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Interplay between co-stimulatory and inhibitory signals of a T-cell interacting with an antigen presenting cell (APC) or a cancer cell. See text for details.
Figure 2
Figure 2
(a,b) The diversity of T-cell receptor (TCR)αβ is a result of genetic recombination and diversification mechanisms occurring at the α and β TCR chain loci. Diversity is first created in the germline via recombination of variable V, diversity D (for β chain), and joining J segments. Further diversification occurs through imprecise junctions of these gene segments (addition of P- and N-nucleotides adjacent to the D segment), and the combination of α and β chains.
Figure 3
Figure 3
General workflow for TCR repertoire sequencing and analysis. From bulk samples (tissues or peripheral blood) or sorted cells, genomic DNA of mRNA templates are isolated and amplified by polymerase chain reaction (PCR) with specific primers to generate to generate the TCR library. High-throughput sequencing generate the TCR sequencing data that can be analyzed with bioinformatics tools based on different research objectives.

References

    1. Topalian S.L., Hodi F.S., Brahmer J.R., Gettinger S.N., Smith D.C., McDermott D.F., Powderly J.D., Sosman J.A., Atkins M.B., Leming P.D., et al. Five-year survival and correlates among patients with advanced melanoma, renal cell carcinoma, or non-small cell lung cancer treated with nivolumab. [(accessed on 25 July 2019)];Jama Oncol. 2019 Available online: https://jamanetwork.com/journals/jamaoncology/fullarticle/2738775. - PMC - PubMed
    1. Ribas A., Wolchok J.D. Cancer immunotherapy using checkpoint blockade. Science. 2018;359:1350–1355. doi: 10.1126/science.aar4060. - DOI - PMC - PubMed
    1. Topalian S.L., Taube J.M., Anders R.A., Pardoll D.M. Mechanism-driven biomarkers to guide immune checkpoint blockade in cancer therapy. Nat. Rev. Cancer. 2016;16:275–287. doi: 10.1038/nrc.2016.36. - DOI - PMC - PubMed
    1. Ribas A., Tumeh P.C. The future of cancer therapy: Selecting patients likely to respond to pd1/l1 blockade. Clin. Cancer Res.: Off. J. Am. Assoc. Cancer Res. 2014;20:4982–4984. doi: 10.1158/1078-0432.CCR-14-0933. - DOI - PMC - PubMed
    1. Masucci G.V., Cesano A., Hawtin R., Janetzki S., Zhang J., Kirsch I., Dobbin K.K., Alvarez J., Robbins P.B., Selvan S.R., et al. Validation of biomarkers to predict response to immunotherapy in cancer: Volume i-pre-analytical and analytical validation. J. Immunother. Cancer. 2016;4:76. doi: 10.1186/s40425-016-0178-1. - DOI - PMC - PubMed

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