The PD-1 expression balance between effector and regulatory T cells predicts the clinical efficacy of PD-1 blockade therapies
Immune checkpoint blockade has provided a paradigm shift in cancer therapy, but the success of this approach is very variable; therefore, biomarkers predictive of clinical efficacy are urgently required. Here, we show that the frequency of PD-1 + CD8 + T cells relative to that of PD-1 + regulatory T...
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Published in | Nature immunology Vol. 21; no. 11; pp. 1346 - 1358 |
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Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
New York
Nature Publishing Group US
01.11.2020
Nature Publishing Group |
Subjects | |
Online Access | Get full text |
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Summary: | Immune checkpoint blockade has provided a paradigm shift in cancer therapy, but the success of this approach is very variable; therefore, biomarkers predictive of clinical efficacy are urgently required. Here, we show that the frequency of PD-1
+
CD8
+
T cells relative to that of PD-1
+
regulatory T (T
reg
) cells in the tumor microenvironment can predict the clinical efficacy of programmed cell death protein 1 (PD-1) blockade therapies and is superior to other predictors, including PD ligand 1 (PD-L1) expression or tumor mutational burden. PD-1 expression by CD8
+
T cells and T
reg
cells negatively impacts effector and immunosuppressive functions, respectively. PD-1 blockade induces both recovery of dysfunctional PD-1
+
CD8
+
T cells and enhanced PD-1
+
T
reg
cell–mediated immunosuppression. A profound reactivation of effector PD-1
+
CD8
+
T cells rather than PD-1
+
T
reg
cells by PD-1 blockade is necessary for tumor regression. These findings provide a promising predictive biomarker for PD-1 blockade therapies.
Checkpoint blockade is effective in only a subset of patients; therefore, biomarkers that can predict efficacy would be clinically highly valuable. Nishkawa and colleagues develop a biomarker based on PD-1 positivity of effector and regulatory T cells in the tumor microenvironment that accurately predicts the effectiveness of checkpoint blockade in patients. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 1529-2908 1529-2916 1529-2916 |
DOI: | 10.1038/s41590-020-0769-3 |