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Single-cell RNA sequencing reveals distinct T cell populations in immune-related adverse events of checkpoint inhibitors

PD-1 is an inhibitory receptor in T cells, and antibodies that block its interaction with ligands augment anti-tumor immune responses. The clinical potential of these agents is limited by the fact that half of all patients develop immune-related adverse events (irAEs). To generate insights into the...

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Detalles Bibliográficos
Autores principales: Bukhari, Shoiab, Henick, Brian S., Winchester, Robert J., Lerrer, Shalom, Adam, Kieran, Gartshteyn, Yevgeniya, Maniar, Rohan, Lin, Ziyan, Khodadadi-Jamayran, Alireza, Tsirigos, Aristotelis, Salvatore, Mary M., Lagos, Galina G., Reiner, Steven L., Dallos, Matthew C., Mathew, Matthen, Rizvi, Naiyer A., Mor, Adam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9873824/
https://www.ncbi.nlm.nih.gov/pubmed/36513074
http://dx.doi.org/10.1016/j.xcrm.2022.100868
Descripción
Sumario:PD-1 is an inhibitory receptor in T cells, and antibodies that block its interaction with ligands augment anti-tumor immune responses. The clinical potential of these agents is limited by the fact that half of all patients develop immune-related adverse events (irAEs). To generate insights into the cellular changes that occur during anti-PD-1 treatment, we performed single-cell RNA sequencing of circulating T cells collected from patients with cancer. Using the K-nearest-neighbor-based network graph-drawing layout, we show the involvement of distinctive genes and subpopulations of T cells. We identify that at baseline, patients with arthritis have fewer CD8 T(CM) cells, patients with pneumonitis have more CD4 T(H2) cells, and patients with thyroiditis have more CD4 T(H17) cells when compared with patients who do not develop irAEs. These data support the hypothesis that different populations of T cells are associated with different irAEs and that characterization of these cells’ pre-treatment has the potential to serve as a toxicity-specific predictive biomarker.