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. 2015 Sep;3(9):1017-29.
doi: 10.1158/2326-6066.CIR-14-0244. Epub 2015 May 26.

Resistance to Antiangiogenic Therapy Is Associated With an Immunosuppressive Tumor Microenvironment in Metastatic Renal Cell Carcinoma

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Free PMC article

Resistance to Antiangiogenic Therapy Is Associated With an Immunosuppressive Tumor Microenvironment in Metastatic Renal Cell Carcinoma

Xian-De Liu et al. Cancer Immunol Res. .
Free PMC article

Abstract

Renal cell carcinoma (RCC) is an immunogenic and proangiogenic cancer, and antiangiogenic therapy is the current mainstay of treatment. Patients with RCC develop innate or adaptive resistance to antiangiogenic therapy. There is a need to identify biomarkers that predict therapeutic resistance and guide combination therapy. We assessed the interaction between antiangiogenic therapy and the tumor immune microenvironment and determined their impact on clinical outcome. We found that antiangiogenic therapy-treated RCC primary tumors showed increased infiltration of CD4(+) and CD8(+) T lymphocytes, which was inversely related to patient overall survival and progression-free survival. Furthermore, specimens from patients treated with antiangiogenic therapy showed higher infiltration of CD4(+)FOXP3(+) regulatory T cells and enhanced expression of checkpoint ligand programed death-ligand 1 (PD-L1). Both immunosuppressive features were correlated with T-lymphocyte infiltration and were negatively related to patient survival. Treatment of RCC cell lines and RCC xenografts in immunodeficient mice with sunitinib also increased tumor PD-L1 expression. Results from this study indicate that antiangiogenic treatment may both positively and negatively regulate the tumor immune microenvironment. These findings generate hypotheses on resistance mechanisms to antiangiogenic therapy and will guide the development of combination therapy with PD-1/PD-L1-blocking agents.

Conflict of interest statement

Conflict of Interest Disclosure: The authors disclose no potential conflicts of interest

Figures

Figure 1
Figure 1
RCC is associated with immune-cell infiltration. (A) Quantification of immune-cell infiltration. CD8+ cells were labeled in blue, and CD8 cells were labeled in red. Representative original images, corresponding quantification images and the percentage of CD8+ cells were shown. (B) CD3+ T-cell infiltration. (C) CD45RO+ T-cell infiltration. (D) CD4+ T-cell infiltration. (E) CD8+ T-cell infiltration. (F) CD68+ cell infiltration. Tissue microarrays (TMA) from normal kidney or RCC were immunohistochemically stained with anti-CD3 antibody, anti-CD45RO antibody, anti-CD4 antibody, anti-CD8 antibody or anti-CD68 antibody. Immunoreactivity was visualized with DAB (brown), and nuclear counterstain was shown by hematoxylin (blue). Representative images and the percentages of CD3+, CD45RO+, CD4+, CD8+ or CD68+ cells in each group were shown. Statistical analysis was performed with unpaired Student’s t-test.
Figure 2
Figure 2
Anti-angiogenic therapy increases immune-cell infiltration. TMAs from untreated RCC controls or RCCs treated with sunitinib or bevacizumab were immunohistochemically stained with anti-CD3 antibody (A), anti-CD45RO antibody (B), anti-CD4 antibody (C), anti-CD8 antibody or anti-CD68 antibody (E). Immunoreactivity was visualized with DAB (brown), and nuclear counterstain was shown by hematoxylin (blue). Representative images and the percentages of CD3+, CD45RO+, CD4+, CD8+ or CD68+ cells in each group were shown. Statistical analysis was performed with unpaired Student’s t-test.
Figure 3
Figure 3
CD4+ and CD8+ T-lymphocyte infiltration inversely correlate with patient survival. Based on the distribution of tumor-infiltrating T lymphocytes and patient overall survival (OS) or progression-free survival (FPS), we divided each cohort of patients into 2 subgroups. The percentages of CD4+ (A), CD8+ (B) or CD68+ (C) cells in each subgroup were shown. Statistical analysis was performed with unpaired Student’s t-test.
Figure 4
Figure 4
Anti-angiogenic therapy increases regulatory T-cell infiltration. TMAs from untreated RCC controls or RCCs treated with sunitinib or bevacizumab were immunohistochemically stained with anti-CD4 antibody and anti-FOXP3 antibody at the same time. FOXP3 immunoreactivity was visualized with DAB (brown), CD4 immunoreactivity was visualized with warp red chromogen (red), and nuclear counterstain was shown by hematoxylin (blue). (A) Representative original images and corresponding quantification images. CD4+ cells were labeled in red, FOXP3+ cells were labeled in green, CD4+FOXP3+ Tregs were labeled in yellow. Negative cells were labeled in blue. (B) Percentages of CD4+FOXP3+ Tregs in each group were shown. The ratio of CD4+FOXP3+ Tregs to (C) CD4+ single positive cells or (D) CD8+ positive cells. (E) Correlation between Treg infiltration and patient survival. Based on the distribution of tumor-infiltrating T lymphocytes and patient OS or FPS, we divided each group of patients into 2 subgroups. The percentages of CD4+FOXP3+ Tregs in each subgroup were shown. Statistical analysis was performed with unpaired Student’s t-test. (F) Correlation between CD8+ T-lymphocyte infiltration and Tregs infiltration.
Figure 5
Figure 5
Anti-angiogenic therapy increases PD-L1 expression in human RCC. Human placenta tissues and TMAs from untreated RCC controls or RCCs treated with sunitinib or bevacizumab were immunohistochemically stained with anti-PD-L1 antibody. Immunoreactivity was visualized with DAB (brown), and nuclear counterstain was shown by hematoxylin (blue). (A) Human placenta tissues were immunohistochemically stained with anti-PD-L1 antibody (left), and non-primary antibody control (right) was included. (B) Representative images and the percentage of PD-L1 positive cells in whole RCC tissue were shown. (C) Correlation between PD-L1 expression and patient survival. Based on the distribution of tumor-infiltrating T lymphocytes and patient OS or FPS, we divided each group of patients into 2 subgroups. The percentages of PD-L1 positive cells in each subgroup were shown. Statistical analysis was performed with unpaired Student’s t-test. (D) Correlation between CD8+ T lymphocyte infiltration and PD-L1 expression.
Figure 6
Figure 6
(A) PD-L1 antibody validation. 786-O cells stably expressing PD-L1 shRNA were treated IFNγ (10ng/ml) for 1 or 3 hrs. Cell lysates were analyzed by immunoblot using anti-PD-L1 antibody, anti-P-STAT1 (Y701) antibody or anti-β-actin antibody. (B) Sunitinib treatment increases PD-L1 protein levels in 786-O cells-induced xenograft. After the tumors are palpable (i.e., tumor volume reached 100 mm3), mice were treated with sunitinib (50mg/kg) by oral gavage 3 times/week for 3 weeks. Each lane is a separate xenograft experiment. PD-L1 band intensity was analyzed using ImageJ software. The average level of PD-L1 in PBS-treated xenografts was normalized to 1. Statistical analysis was performed with unpaired Student’s t-test. (C) Sunitinib treatment increases PD-L1 protein level but not mRNA level in 786-O cell line. 786-O cells were incubated in the presence of sunitinib for 16 hrs at the concentration of 0.5, 1, 2, 5 or 10 μM. Cell lysates were analyzed by immunoblot using an anti-PD-L1 antibody, anti-HIF2α antibody or anti-β-actin antibody. PD-L1 band intensity with or without sunitinib (5μM) treatment was analyzed using ImageJ software. The average level of PD-L1 in control cells was normalized to 1. Statistical analysis was performed with unpaired Student’s t-test, n=4. Total RNA were analyzed by real-time PCR using primers specific for PD-L1 (CD274). mRNA level in control cells was normalized to 1. GAPDH were used as endogenous control. (D) Bevacizumab treatment increases PD-L1. 786-O cells were treated with bevacizumab (10μg/ml or 25μg/ml) for 16 hr. Cell lysates were analyzed by immunoblot using anti-PD-L1 antibody or anti-β-actin antibody. (E) Sunitinib treatment increases PD-L1 protein levels in different RCC cell lines. RCC cell lines (A-498, RCC4, 786-O, CaKi-1, TK-10 and SN12C) were treated with sunitinib (5μM) for 16 hr. Cell lysates were analyzed by immunoblot using anti-PD-L1 antibody or anti-GAPDH antibody. (F) Working model. Anti-angiogenic therapy generates an immunosuppressive tumor microenvironment. On the one hand, anti-angiogenic therapy increased T-lymphocyte infiltration to eliminate cancer cells. Anti-angiogenic therapy might induce the expression of adhesion molecules and chemokines or the activation of autophagy, which subsequently attract and promote T-lymphocyte infiltration. On the other hand, anti-angiogenic therapy promotes tumorigenesis by generating an immunosuppressive tumor microenvironment associated with PD-L1 upregulation. Anti-angiogenic therapy can upregulate PD-L1 directly at post-transcriptional level or indirectly mediated by CD8+ T-lymphocyte infiltration and IFNγ secretion. The increased expression of PD-L1 act as a negative feedback mechanism to inactivate tumor-infiltrating T lymphocytes or subvert T lymphocytes to play a tumor-promoting role, which leads to immune escape. Combination with anti-PD-L1 therapy will re-activate tumor-infiltrating T cells to exert anticancer cytotoxicity.

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