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. 2017 Dec;30(4):341-352.
doi: 10.1177/0394632017734459. Epub 2017 Oct 9.

Immunological effects of everolimus in patients with metastatic renal cell cancer

Affiliations

Immunological effects of everolimus in patients with metastatic renal cell cancer

Charlotte M Huijts et al. Int J Immunopathol Pharmacol. 2017 Dec.

Abstract

The mammalian target of rapamycin (mTOR) is a crucial kinase present in all cells. Besides its role in the regulation of cell-growth, proliferation, angiogenesis, and survival of malignant tumors, mTOR additionally plays an important role in immune regulation by controlling the balance between effector T cells and regulatory T cells (Tregs). This critically affects the suppressive state of the immune system. Here, the systemic immunological effects of everolimus treatment were comprehensively investigated in five patients with metastatic renal cell cancer. In this hypothesis generating study, the immunological alterations in circulating immune subsets induced by everolimus included a (non-significant) increase in the frequency of Tregs, a significant increase in monocytic myeloid-derived suppressor cells, a significant decrease in the frequency of immunoregulatory natural killer cells, classical CD141+ (cDC1) and CD1c+ (cDC2) dendritic cell subsets, as well as a decrease in the activation status of plasmacytoid dendritic cells and cDC1. These date indicate that the immunological effects of everolimus affect multiple immune cell subsets and altogether tip the balance in favor of immunosuppression, which can be considered a detrimental effect in the treatment of cancer, and may require combination treatment with agents able to negate immune suppression and boost T cell immunity.

Keywords: Treg; everolimus; immune monitoring; mTOR; suppression.

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Conflict of interest statement

Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
Effect of everolimus treatment on the frequency of Tregs and their suppressive function. (a) Representative dot plots illustrating the gating strategy applied to analyze Tregs, defined as CD3+CD4+CD25hiFoxP3+, within the total isolated PBMC population. (b) Percentages of Tregs within CD4+ T cells (left graph) and CD4+ T cells within CD3+ T cells (right graph), determined in freshly isolated PBMC from five patients treated with everolimus at baseline and subsequently 2, 4, and 8 weeks after start of treatment. Mean ± SEM are shown. (c) For two patients, sufficient PBMC were available to perform CD4+CD25+ T cell isolation at two time-points. Their capacity to suppress T cell proliferation was tested by measuring CFSE dilution of CD8+ responder T cells stimulated with anti-CD3 mAb, anti-CD28 mAb, and IL-2. Representative histograms showing CFSE dilution of CD8+ responder T cells in the various conditions, upper panels for patient 01 and lower panels for patient 04. Unstimulated CD8+ responder T cells without the addition of anti-CD3 mAb, anti-CD28 mAb, and IL-2 and CD8+ responder T cells stimulated with anti-CD3 mAb, anti-CD28 mAb, and IL-2, both without the addition of isolated CD4+CD25+ T cells (two panels on the left) were used as control conditions. Two panels on the right show the CFSE dilution of responder T cells cultured with CD4+CD25+ T cells isolated from PBMC drawn at time-point 0 and 4 weeks.
Figure 2.
Figure 2.
Overall T cell cytokine production is not altered by everolimus treatment. (a) Bar graph showing the percentage of IL-17, IFN-γ, IL-4, TNF-α, IL-5, and IL-2 positive cells in unstimulated PBMC from patients with mRCC. Upper panel shows cytokine production in CD4+ T cells, and lower panel shows cytokine production in CD8+ T cells, n = 3–4. (b) Bar graph showing the percentage of IL-17, IFN-γ, IL-4, TNF-α, IL-5, and IL-2 positive cells in patient PBMC stimulated with PMA and ionomycin for 4 h. Upper panel shows cytokine production in CD4+ T cells, and lower panel shows cytokine production in CD8+ T cells, n = 3–4. (c) Graphs showing relative quantification (RQ) values for IL-10 (left graph) and TGFβ (right graph) mRNA expression measured in whole blood in five patients. Each value is derived from three technical replicates. Mean ± SEM are shown.
Figure 3.
Figure 3.
Everolimus treatment results in a decrease in the frequency of immunoregulatory NK cells. NK cell percentages present in patient PBMC. Upper panel shows CD56brightCD16dim/− immunoregulatory NK cells, and lower panel CD56dimCD16+ cytotoxic NK cells. Due to missing values, as a result of disease progression, statistics were performed on data from four patients, comparing week 0 to weeks 2 and 4, respectively. Mean ± SEM are shown; P-values are indicated with asterisk; *P ⩽ 0.05; n = 4 on weeks 0–4; two-way repeated measures ANOVA with Dunnett’s post-test.
Figure 4.
Figure 4.
Increase in MDSC frequencies in response to everolimus correlates with increased arginase expression. (a) Percentages of mMDSC (upper graph) and gMDSC (lower graph) in patient PBMC as assessed by flow cytometry. Mean ± SEM are shown; P-value is indicated with asterisk; *P ⩽ 0.05; n = 5 at weeks 0–4; two-way repeated measures ANOVA with Dunnett’s post-test. (b) Correlation between the frequency of gMDSC and the RQ of arginase mRNA expression. Each point represents an individual data point. P < 0.05, R = 0.53.
Figure 5.
Figure 5.
Frequency and activation of monocytes and three different circulating blood DC subsets. Percentages of monocytes (CD14+CD11c+), cDC1 (BDCA3+CD14CD11c+), cDC2 (BDCA1+CD19CD14CD11c+), and pDC (BDCA2+CD123+) were assessed by flow cytometry, and the median fluorescent intensity (MFI) of CD40 and CD86 was determined. Mean ± SEM are shown; P-values are indicated with asterisks; *P ⩽ 0.05, **P < 0.01, ***P < 0.001; one-way repeated measures ANOVA with Dunnett’s post-test.

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