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Impact of PD‑L1 upregulation on immune checkpoint inhibitor efficacy in triple‑negative breast cancer using a 4T1 murine model

  • Authors:
    • A. Young Park
    • Ju Hee Kim
    • Sangeun Lee
    • Hoe Suk Kim
    • Hong Kyu Kim
    • Han-Byoel Lee
    • Wonshik Han
  • View Affiliations / Copyright

    Affiliations: Cancer Research Institute, Seoul National University, Seoul 03080, Republic of Korea
    Copyright: © Park et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 54
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    Published online on: June 11, 2025
       https://doi.org/10.3892/ijo.2025.5760
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Abstract

Triple‑negative breast cancer (TNBC) is a lethal subtype of breast cancer with a poor prognosis and limited existing treatment options. The immune checkpoint inhibitor, anti‑programmed death ligand 1 (PD‑L1), has recently emerged as a promising alternative in treating TNBC. PD‑L1 is critical in tumor immune evasion and is therefore a key target for cancer immunotherapy. Although anti‑PD‑L1 therapy is effective in breast cancer based on clinical trials, the relationship between PD‑L1 expression levels and treatment response remains unclear. To investigate this, a 4T1 breast cancer cell line that stably overexpressed PD‑L1 was established and was used to create a tumor model in mice. Mice were treated with anti‑PD‑L1 antibodies, and tumor growth was compared between the control and treated groups. PD‑L1 overexpressing tumors did not exhibit an antitumor response to anti‑PD‑L1 therapy compared with the control tumors. Additionally, immune cell infiltration and activation were significantly altered, as shown by immunohistochemical staining and bulk RNA sequencing. In PD‑L1‑overexpressing tumors that did not respond to treatment, immune cell markers and antitumor immune pathways were downregulated. These results demonstrated that excessive PD‑L1 expression creates an immunosuppressive tumor microenvironment, which impairs the efficacy of anti‑PD‑L1 therapy. The present study suggests that excessive PD‑L1 expression reduces the effectiveness of antitumor immunotherapy, and that PD‑L 1 expression levels are essential in predicting the response to antitumor immunotherapy.
View Figures

Figure 1

PD-L1 expression and survival
analysis in the TCGA and METABRIC datasets. (A) Expression levels
of PD-L1 in breast cancer subtypes (TCGA, n=1,084; METABRIC,
n=1,905). (B) Kaplan-Meier curves according to PD-L1 expression in
TNBC (TCGA, n=163; METABRIC, n=233; two-sided log-rank test).
*P<0.05, ***P<0.001,
****P<0.0001 by one-way ANOVA with Tukey's post hoc
test. PD-L1, programmed death-ligand 1; TCGA, The Cancer Genome
Atlas; METABRIC, Molecular Taxonomy of Breast Cancer International
Consortium; TNBC, triple-negative breast cancer; LumA/B, Luminal A
and Luminal B subtypes.

Figure 2

Effect of PD-L1 overexpression on
phenotypic changes and the impact of αPD-L1 treatment on
proliferation. (A) Relationship between the proliferation rate and
overexpression of PD-L1 in the 4T1 cell line (n=3, mean ± SEM;
****P<0.0001 by two-way ANOVA with Tukey's post hoc
test). (B) Images and quantification data examined in the migration
and invasion of PD-L1-overexpressed 4T1 cells (n=3, mean ± SEM;
**P<0.01 and ****P<0.0001 by
Mann-Whitney U test). (C) Images and quantification data examined
in the gap closure assay of PD-L1-overexpressed 4T1 cells (n=3,
mean ± SEM; ****P<0.0001 two-way ANOVA with Tukey's
post hoc test). (D) Proliferation rate in response to αPD-L1
treatment in 4T1 cells with PD-L1 overexpression (n=3, mean ± SEM;
*P<0.05, ***P<0.001,
****P<0.0001 by two-way ANOVA with Tukey's post hoc
test). αPD-L1, anti-PD-L1; PD-L1, programmed death-ligand 1; O/E,
overexpression; Ctl, control.

Figure 3

Differential effectiveness of αPD-L1
treatment on 4T1 breast tumors depending on the PD-L1 expression
levels. (A) Images of the tumor tissues (scale bar, 1 cm) and the
(B) volume and (C) weight of tumors treated with IgG or αPD-L1 with
or without high levels of PD-L1 overexpression (n=6, mean ± SEM;
**P<0.01, ***P<0.001,
****P<0.0001 by two-way ANOVA with Tukey's post hoc
test). (D) Flow cytometric sorting of 4T1 cells based on GFP
expression and PD-L1 levels and (E) immunoblot validation of PD-L1
expression in the sorted cell lines. (F) Images of tumor tissues
(scale bar, 1 cm) and the tumor (G) volume and (H) weight of mice
treated with IgG or αPD-L1 with or without medium or high levels of
PD-L1 overexpression (n=5, mean ± SEM; *P<0.05,
****P<0.0001 by multiple t-two-way ANOVA with Tukey's
post hoc test). αPD-L1, anti-PD-L1. αPD-L1, anti-PD-L1 antibody;
PD-L1, programmed death-ligand 1; IgG, immunoglobulin G; GFP, green
fluorescent protein; Ctl, control; O/E, overexpression.

Figure 4

Influence of PD-L1 overexpression on
immune cell infiltration and T cell activation in response to
αPD-L1 therapy. Representative (A) PD-L1 and (B) CD45
immunohistochemistry images (scale bar, 100 μm) and the
corresponding quantification data of the tumor tissues (n=3, mean ±
SEM; *P<0.05, **P<0.01,
***P<0.001, ****P<0.0001 by two-way
ANOVA with Tukey's post hoc test). (C) Representative tissue images
of stained CD4 and CD8 (scale bar, 100 μm) and the
corresponding quantification data of the images (n=5, mean ± SEM;
*P<0.05, **P<0.01,
****P<0.0001 by two-way ANOVA with Tukey's post hoc
test). (D) Percentage of CD4 and CD8+ T cells in the
total immune cells analyzed through flow cytometry (n=5, mean ±
SEM; *P<0.05 by two-way ANOVA with Tukey's post hoc
test). Tumor groups are distinguished by color and fill across the
graph panels in A-D: Black (hollow): 4T1-Ctl + IgG, blue (hollow):
4T1-Ctl + αPD-L1, green (solid): 4T1-PD-L1 O/E + IgG, red (solid):
4T1-PD-L1 O/E + αPD-L1. (E) KEGG pathway analysis of DEGs
upregulated in control tumors treated with αPD-L1 compared with
IgG-treated controls. (F) KEGG pathway analysis of DEGs
downregulated in PD-L1 overexpressing tumors treated with αPD-L1
compared with control tumors treated with αPD-L1. PD-L1, programmed
death-ligand 1; αPD-L1, anti-PD-L1 antibody; CD45, cluster of
differentiation 45; CD4, cluster of differentiation 4; CD8, cluster
of differentiation 8; KEGG, Kyoto Encyclopedia of Genes and
Genomes; DEGs, differentially expressed genes; IgG, immunoglobulin
G; O/E, overexpression.
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Copy and paste a formatted citation
Spandidos Publications style
Park AY, Kim JH, Lee S, Kim HS, Kim HK, Lee H and Han W: Impact of PD‑L1 upregulation on immune checkpoint inhibitor efficacy in triple‑negative breast cancer using a 4T1 murine model. Int J Oncol 67: 54, 2025.
APA
Park, A.Y., Kim, J.H., Lee, S., Kim, H.S., Kim, H.K., Lee, H., & Han, W. (2025). Impact of PD‑L1 upregulation on immune checkpoint inhibitor efficacy in triple‑negative breast cancer using a 4T1 murine model. International Journal of Oncology, 67, 54. https://doi.org/10.3892/ijo.2025.5760
MLA
Park, A. Y., Kim, J. H., Lee, S., Kim, H. S., Kim, H. K., Lee, H., Han, W."Impact of PD‑L1 upregulation on immune checkpoint inhibitor efficacy in triple‑negative breast cancer using a 4T1 murine model". International Journal of Oncology 67.1 (2025): 54.
Chicago
Park, A. Y., Kim, J. H., Lee, S., Kim, H. S., Kim, H. K., Lee, H., Han, W."Impact of PD‑L1 upregulation on immune checkpoint inhibitor efficacy in triple‑negative breast cancer using a 4T1 murine model". International Journal of Oncology 67, no. 1 (2025): 54. https://doi.org/10.3892/ijo.2025.5760
Copy and paste a formatted citation
x
Spandidos Publications style
Park AY, Kim JH, Lee S, Kim HS, Kim HK, Lee H and Han W: Impact of PD‑L1 upregulation on immune checkpoint inhibitor efficacy in triple‑negative breast cancer using a 4T1 murine model. Int J Oncol 67: 54, 2025.
APA
Park, A.Y., Kim, J.H., Lee, S., Kim, H.S., Kim, H.K., Lee, H., & Han, W. (2025). Impact of PD‑L1 upregulation on immune checkpoint inhibitor efficacy in triple‑negative breast cancer using a 4T1 murine model. International Journal of Oncology, 67, 54. https://doi.org/10.3892/ijo.2025.5760
MLA
Park, A. Y., Kim, J. H., Lee, S., Kim, H. S., Kim, H. K., Lee, H., Han, W."Impact of PD‑L1 upregulation on immune checkpoint inhibitor efficacy in triple‑negative breast cancer using a 4T1 murine model". International Journal of Oncology 67.1 (2025): 54.
Chicago
Park, A. Y., Kim, J. H., Lee, S., Kim, H. S., Kim, H. K., Lee, H., Han, W."Impact of PD‑L1 upregulation on immune checkpoint inhibitor efficacy in triple‑negative breast cancer using a 4T1 murine model". International Journal of Oncology 67, no. 1 (2025): 54. https://doi.org/10.3892/ijo.2025.5760
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