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Review
. 2019 Aug 13;20(16):3934.
doi: 10.3390/ijms20163934.

The Immune Landscape of Thyroid Cancer in the Context of Immune Checkpoint Inhibition

Affiliations
Review

The Immune Landscape of Thyroid Cancer in the Context of Immune Checkpoint Inhibition

Gilda Varricchi et al. Int J Mol Sci. .

Abstract

Immune cells play critical roles in tumor prevention as well as initiation and progression. However, immune-resistant cancer cells can evade the immune system and proceed to form tumors. The normal microenvironment (immune cells, fibroblasts, blood and lymphatic vessels, and interstitial extracellular matrix (ECM)) maintains tissue homeostasis and prevents tumor initiation. Inflammatory mediators, reactive oxygen species, cytokines, and chemokines from an altered microenvironment promote tumor growth. During the last decade, thyroid cancer, the most frequent cancer of the endocrine system, has emerged as the fifth most incident cancer in the United States (USA), and its incidence is steadily growing. Inflammation has long been associated with thyroid cancer, raising critical questions about the role of immune cells in its pathogenesis. A plethora of immune cells and their mediators are present in the thyroid cancer ecosystem. Monoclonal antibodies (mAbs) targeting immune checkpoints, such as mAbs anti-cytotoxic T lymphocyte antigen 4 (anti-CTLA-4) and anti-programmed cell death protein-1/programmed cell death ligand-1 (anti-PD-1/PD-L1), have revolutionized the treatment of many malignancies, but they induce thyroid dysfunction in up to 10% of patients, presumably by enhancing autoimmunity. Combination strategies involving immune checkpoint inhibitors (ICIs) with tyrosine kinase (TK) or serine/threonine protein kinase B-raf (BRAF) inhibitors are showing considerable promise in the treatment of advanced thyroid cancer. This review illustrates how different immune cells contribute to thyroid cancer development and the rationale for the antitumor effects of ICIs in combination with BRAF/TK inhibitors.

Keywords: CXCL8; T reg cells; angiogenesis; chemokines; dendritic cells; lymphangiogenesis; macrophages; mast cells; neutrophils; thyroid cancer.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Hypothetical scheme of immune contexture of thyroid cancer (TC). The immune network in thyroid cancer is a complex and dynamic system characterized by multiple interactions between tumor cells and nearly all immune cells. Tumor-associated macrophages (TAM), M2 macrophages, tumor-associated mast cells, monocytes, polymorphonuclear-myeloid-derived suppressor cells (PMN-MDSCs), monocyte-derived suppressor cells (M-MDSCs), T regulatory cells (Treg) and T helper 2 (Th2) cells, tumor-associated neutrophils (TAN), and immature DCs (iDCs) and their mediators play protumorigenic roles in thyroid cancer. M1 macrophages, cytotoxic CD8+ T cells, natural killer (NK) cells, Th1 cells, mature DCs (mDCs), and their mediators play an antitumorigenic role. There is increasing evidence that eosinophils play an antitumorigenic role in different cancers [102,108,109]. VEGF-A and CXCL8 produced by thyroid cancer cells activate tumor angiogenesis. Mast cells and macrophages are major producers of lymphangiogenic factors (VEGF-C and VEGF-D). The antitumorigenic role of γδ T cells, Th9 cells, and type I natural killer T (NKT) cells (grey and dashed lines) have been demonstrated in several other human cancers. The protumorigenic role of Tfh cells and of type II NKT cells has been shown in several other human tumors (grey and dashed lines). Protumor or antitumor activities of Th17 and Tc17 cells are context-dependent (grey and dashed line). Modified with permission from Galdiero et al. [110].
Figure 2
Figure 2
Schematic representation of the rationale developing combinatorial therapies of advanced thyroid cancer involving immune checkpoint inhibitors (monoclonal antibodies (mAbs) anti-cytotoxic T lymphocyte antigen 4 (anti-CTLA-4), anti-programmed cell death protein-1 (anti-PD-1), or anti-programmed cell death ligand-1 (anti-PD-L1)), BRAF inhibitors (BRAFi), multi-targeted tyrosine kinase inhibitors (TKIs) (e.g., lenvatinib), chemotherapies, or radiotherapies. (A) Cancer cells release neoantigens (dots of different colors) that are captured by antigen-presenting cells (APCs). These cells present peptides in the context of MHC I molecule/T cell receptor (TCR) on the surface of CD8+ cytotoxic T cells. APCs can also present peptides bound to MHC II molecules on CD4+ T helper cells. T-cell activation requires costimulatory signals transmitted via CD28, which is activated by binding to CD80 and/or CD86 on APCs. Tumor cells up-regulate CTLA-4 on T cells, which competes with CD28 for binding to CD80/CD86 on APCs. The interaction of CTLA-4 with CD80/CD86 results in inhibitory signaling in T cells, which favors thyroid cancer cell proliferation. The immunosuppressive activity of CTLA-4 is mediated by the down-regulation of Th cells and the enhancement of Treg cells. Moreover, tumor cells express high levels of PD-L1 and/or PD-L2, which binds to PD-1 on T cells, resulting in inhibitory signals that decrease cytotoxicity and lead to T-cell exhaustion. (B) mAbs blocking CTLA-4 (e.g., ipilimumab, tremelimumab), PD-1 (nivolumab, pembrolizumab, spartalizumab), or PD-L1 (avelumab, atezolizumab, durvalumab) inhibit the interactions of CTLA-4/CD80/86 and PD-1/PD-L1, respectively, and activate T-cell cytotoxicity. BRAF inhibitors (BRAFi), TKIs (e.g., lenvatinib), chemotherapies, and radiotherapies can induce thyroid cancer cell death, increasing the release of tumor neoantigens in the tumor microenvironment. Combining an anti-PD-L1 antibody with BRAFi [228,229] or with lenvatinib [229] improved survival and tumor immunity in a immunocompetent murine model of ATC. Several combination strategies involving immune checkpoint inhibitors (ICIs) are under evaluation in patients with advanced TC (see Table 1 and Table 2).

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