PD-L1 expression and its correlation with tumor biomarkers in Chinese urothelial bladder cancer
Data on prevalence of programmed death ligand-1 (PD-L1) expression and its correlation with tumor biomarkers in Chinese patients with muscle-invasive urothelial bladder cancer (MIUBC) are scarce. We investigated the prevalence of PD-L1 expression, PD-L1 expression in tumor cells (TC) and immune cell...
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Published in | Scientific reports Vol. 14; no. 1; pp. 16753 - 11 |
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Main Authors | , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
20.07.2024
Nature Publishing Group Nature Portfolio |
Subjects | |
Online Access | Get full text |
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Summary: | Data on prevalence of programmed death ligand-1 (PD-L1) expression and its correlation with tumor biomarkers in Chinese patients with muscle-invasive urothelial bladder cancer (MIUBC) are scarce. We investigated the prevalence of PD-L1 expression, PD-L1 expression in tumor cells (TC) and immune cells (IC), and its correlation with tumor biomarkers (CD8+ T cells and tumor mutation burden [TMB]) in Chinese patients with newly diagnosed MIUBC (NCT03433924). Of 248 patients enrolled, 229 with PD-L1 data available were analysed. High PD-L1 expression (≥ 25% of TC or IC with PD-L1 expression) was observed in 120 (52.4%) patients. 59 cases showed positive staining in ≥ 25% of TC, and 82 cases had positive staining in ≥ 25% of IC. High expression of CD8+ T cell and TMB (> 10 mutations/megabase) was observed in 44.5% and 54.1% patients, respectively. A positive correlation was observed between percentage of TC with membrane PD-L1 positivity and CD8+ T cells (0.34;
P
< 0.001) and between IC with membrane PD-L1 positivity and CD8+ T cells (0.44;
P
< 0.001). There is high prevalence of PD-L1 expression in Chinese patients with MIUBC, suggesting that a sizable subset of patients could benefit from immunotherapy. The correlation of PD-L1 expression with tumor biomarkers provide clues for mechanisms underlying the effects of biomarkers for predicting efficacy. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Undefined-3 |
ISSN: | 2045-2322 2045-2322 |
DOI: | 10.1038/s41598-024-67508-6 |