Abstract
Thyroid cancer is an excellent model for studying tumor immune microenvironment, as it often shows local signs of an immune response. The tumor immune microenvironment of thyroid cancer is the heterogeneous histological space in which tumor cells coexist with host cells. The final composition of this cellular aggregate is associated with the clinical aggressiveness characteristics of the neoplasm. High-performance multiplex technologies suggest that specific genetic signatures of the tumor immune microenvironment may provide data for the delineation of a robust prognostic model. Several proposals integrate clinic, pathologic and immunological information in an attempt to translate the knowledge gained from molecular science into a more personalized approach for the treatment strategy of patients with thyroid cancer. In addition, the tumor immune microenvironment displays multiple molecular connections between cells, revealing complex crosstalk. This interesting network generates several molecular nodes that can be used as targets for immunotherapy. In this scenario, immunotherapy emerges as a promising weapon, mainly for patients with advanced thyroid cancer, both medullary and follicular cell-derived. In fact, although most patients with thyroid cancer have an excellent prognosis with current therapies, around 30% of cases evolve in an unfavorable way, leading to the urgent need to improve immunotherapy for high-risk patients. Preclinical and early clinical investigations are providing optimistic prospects, but more studies are needed to make immunotherapy a more viable and efficient tool for years to come.
Introduction
Thyroid cancer is the most frequent endocrine malignancy, accounting for 44,280 estimated new cases in the United States in 2021 (Siegelet al. 2021). The incidence of differentiated thyroid cancer has more than doubled worldwide in the last three decades (Burgess & Tucker 2006, Davies & Welch 2006, Jemalet al. 2010), and although the implementation of a more conservative diagnostic approach in indolent thyroid lesions has led to a decrease in incidence among women in recent years, this does not occur among men (Morris et al. 2016, Siegelet al. 2021). In addition, even though most of the patients with thyroid cancer show excellent prognosis with current therapeutic tools, around 30% of them will evolve with relapse, will stop responding to current therapies, present metastatic spread and eventually contribute to the 2200 deaths that are estimated in 2021 in the United States (Siegelet al. 2021). In fact, after a slight increase in mortality from 2009 to 2018, recent data suggest stabilization (Siegelet al. 2021).
In an attempt to predict survival and relapse, the American Joint Committee on Cancer has changed the classification system routinely used in the staging of patients with thyroid cancer (Tuttle et al. 2017). Likewise, several other classification systems have emerged with the aim of improving the accuracy in predicting the prognosis of these patients (Byaret al. 1979, Cady & Rossi 1988, DeGrootet al. 1990, Hayet al. 1993, 2002, Mazzaferri & Jhiang 1994, Shaha et al. 1995, Shermanet al. 1998, American Thyroid Association Guidelines Taskforce 2009). These systems take into account prognostic factors identified in multivariate analyses of retrospective studies, especially the patient’s age at diagnosis, the presence of metastases at diagnosis and tumor extension. All systems allow for the accurate identification of the majority of patients at low risk of mortality, allowing these patients to undergo less aggressive therapy than patients identified as high risk, who benefit from a more vigorous therapeutic strategy. However, some uncertainties remain, such as the prediction of short-term prognosis and the probability of remaining free from the disease (American Thyroid Association Guidelines Taskforce 2009). Therefore, it is urgent to better understand the pathology of thyroid cancer, identify evolution markers and find new therapeutic targets in order to improve the management of these patients.
How does the immune response work in tumor microenvironment?
The relationship between tumor cells and immune cells has long been a focus of attention. Tumor transplant models provided experimental support for recognizing that tumor cells could be suppressed by the elements of the immune response, including antibodies and immune cells. These findings suggested that there would be tumor antigens that would form the basis of the so-called immunosurveillance theory, postulated by Burnet and Thomas (Burnet 1971, Thomas 1982). Although there is strong evidence that, in fact, immunosurveillance may restrict the growth of virus-initiated neoplasms, few evidence actually supports the idea that it is able to block chemical-induced tumor growth (Klein 1976, Kim et al. 2007), reinforcing the need for a more robust model to better explain the relationship between immune response and cancer.
In 2002, Dunn and Schrieber proposed the so-called immunoediting hypothesis. According to this theory, immunoediting phenomenon would be responsible both for eliminating tumors and for carving out immunogenic phenotypes that eventually form immunocompetent hosts (Dunnet al. 2002). This proposition, also known as the three ‘E’s theory, suggests that tumors and the immune system interact in three distinct steps. Tumor cells could be eliminated by the immune system even before they become clinically detectable, which would be equivalent to the immunosurveillance phase described above. Elimination would be followed by the equilibrium phase, in which the elimination process of less immunogenic variants may take over until the establishment of the evasion (or escape) phase of immunosurveillance (Dunnet al. 2002). This equilibrium phase could explain the small tumors often found at autopsies and the excellent reports of patients with differentiated thyroid cancer (DTC) undergoing active surveillance. In addition, some small PTCs that do not progress can also be the consequence of specific genetic lesions, such as RET/PTC or BRAFV600E. These lesions are known to induce hyperactivation of the RAS/ERK signaling cascade, DNA replication stress and oncogene-induced senescence too (Vizioli 2011). However, many tumors are clinically diagnosed when they are clearly evading and may even use immune mechanisms to promote their own growth and progression (French 2013). This molecular scenario is the main obstacle to the success of immunotherapy today, as we will further discuss.
An important tumor escape mechanism is T-cell dysfunction. T cells are a frequent finding among tumor-infiltrating lymphocytes (Leeet al. 1999). Most of them are naive lymphocytes, functionally unable to recognize neoplastic cells (Zhou et al. 2006). A small portion, although showing signs of activation, are anergic or tumor-tolerant lymphocytes (Zhou et al. 2006). Cancer-induced T-lymphocyte tolerance can be directed to self or non-self antigens (Bogen 1996, Staveley-O’Carrollet al. 1998, Willimsky & Blankenstein 2005). Lee and colleagues investigated circulating cytotoxic T cells in melanoma patients (Leeet al. 1999). They observed that some of these cells had both effector and naive cell markers (Leeet al. 1999). However, all these cells were functionally unresponsive, that is, unable to kill melanoma cells or produce cytokines in response to mitogens, suggesting that this cell population had become ‘anergic’ in vivo (Leeet al. 1999). These cytotoxic T cells did not express CD69, which is an early marker of lymphocyte activation, after being stimulated with tumor-associated antigens (Leeet al. 1999).
The tumor microenvironment is nothing more than the histological space in which tumor cells coexist with host cells (stromal and epithelial) so that the final composition of this cell aggregate determines clinical characteristics of aggressiveness of the neoplasm (Zhanget al. 2019). Indeed, the degree of T cell infiltration in solid tumors has been considered both a prognostic factor and a predictor of response to immune checkpoint inhibitors (Noshoet al. 2010). Therefore, intratumoral infiltration of effector T cells and T cells previously exposed to tumor antigens have been associated with a better and more effective anti-tumor immune response (Noshoet al. 2010, Giannakiset al. 2016). Likewise, the infiltration of regulatory T lymphocytes and immature cells of a myeloid nature in solid tumors and the tumor expression of co-inhibitors of the immune response (immunological checkpoint) usually contribute to a more immunosuppressive microenvironment that favors characteristics of greater clinical aggressiveness (Masugiet al. 2017, Adamset al. 2018).
The immune microenvironment of differentiated thyroid cancer
Differentiated thyroid cancer is an excellent model for studying the tumor immune microenvironment, as it is often associated with local signs of immune response, such as the presence of concurrent chronic lymphocytic thyroiditis and rich aggregates of immune cells (Dailey et al. 1955). Furthermore, tumor-infiltrating lymphocytes and tumor-associated macrophages are also frequently found among differentiated thyroid cancer tumor cells, suggesting that the final composition of this microenvironment is relatively complex (Matsubayashiet al. 1995, Fiumaraet al. 1997, Dharet al. 1998, Guptaet al. 2001, Ryderet al. 2008). It is possible that these immune cells are not just histological findings, as formerly suggested, but do play a role in tumor growth promotion or elimination and contribute to the final prognosis of this patient (Table 1) (Kirkwoodet al. 2012). Studying 100 PTC cases, French and collaborators found that patients whose tumors had lymphocytes infiltrating tumor areas had a more advanced stage at diagnosis and a higher frequency of extrathyroid invasion and lymph node metastases, when compared to those whose tumors did not have lymphocytes (Frenchet al. 2010).
Description the different immune cells behavior and prognostic significance in DTC.
| Immune cell | Behavior in DTC |
|---|---|
| B lymphocytes |
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| Helper T lymphocytes |
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| Cytotoxic T lymphocytes |
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| NK lymphocytes |
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| Citotoxic NK lymphocytes |
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| Immunoregulatory NK lymphocytes |
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| Regulatory T lymphocytes |
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| Macrophages |
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| Myeloid-derived suppressor cells |
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Lymphocytes are a set of many cells that perform completely different functions depending on the phenotype of each cellular group. In fact, the literature has suggested that the role of the immune system in tumor progression is quite complex and would depend on a pleiotropic chain of pathophysiological events (Hanahan & Weinberg 2011). Thus, the extent to which an immune cell is determinant for a given clinical characteristic depends on several interactions with the microenvironment and with the host organism, which makes its pathophysiological interpretation difficult and research finding confusing.
Tumor cells can recruit monocytes from the circulation, making the microenvironment a cellular mixture of different immune cells. Within tumor tissue, monocytes can differentiate into macrophages. Macrophages are phenotypically recognized by the expression of CD68 and are functionally classified into two different lineages: M1 (promoter of phagocytosis) and M2 (promoter of immunosuppression) (Mantovaniet al. 2002, Caillouet al. 2011). Herrmann et al. observed that 75 thyroid carcinomas of follicular cell origin had high levels of macrophages associated with tumor dedifferentiation. The authors demonstrated a positive correlation between macrophage infiltration and infiltration of T lymphocytes and memory T lymphocytes, as well as a positive correlation between infiltration of these cells and intratumoral vascular density. This finding was expected since the interaction between macrophages and T lymphocytes leads to the production of angiogenic factors that promote tumor vascularization (Herrmannet al. 1994).
Functionally, NK lymphocytes produce several cytokines such as tumor necrosis factor-alpha, interferon-γ and colony-stimulating factor (GM-CSF) (Vivieret al. 2011). NK lymphocytes are understood not only as cytolysis-promoting cells but also, on the contrary, as cells capable to influence the functioning of several other cells, such as dendritic cells, macrophages, neutrophils, as well as exerting a regulatory function in the mediated antigen presentation by T and B lymphocytes (Vivieret al. 2011). Gogali et al. investigated NK lymphocyte infiltration in 65 patients with PTCs and 25 patients with nodular goiters. They showed that NK lymphocytes were more frequently found in PTC tissues compared to nodular goiter tissues. In addition, advanced-stage malignant tumors had fewer NK lymphocytes than early stage diagnosed tumors (Gogaliet al. 2012).
NK lymphocytes can be subdivided into two lineages according to the expression of CD56. CD56 dim cells are cytotoxic, whereas CD56 bright cells execute a regulatory function (Liapiet al. 2013). These two strains have different potentials for cytokine production, cytokine response and cytotoxicity (Baumeet al. 1992, Cooperet al. 2001). Liapi and collaborators studied the presence of both strains in blood and tissue from patients with PTC and nodular goiter, compared to healthy donors. They did not observe differences between the amounts of the two subpopulations in the blood of the three studied groups. Cytotoxic NK lymphocytes were more commonly found in the microenvironment of nodular goiter than in PTC. On the contrary, immunoregulatory NK lymphocytes were more frequent in the microenvironment of PTCs than in nodular goiters, suggesting that the immunoregulatory pattern of NK lymphocytes is involved in thyroid carcinogenesis (Liapiet al. 2013). The authors also showed that the infiltration of cytotoxic NK lymphocytes was positively correlated with tumor staging, whereas immunoregulatory NK lymphocyte infiltration, on the contrary, was negatively correlated with tumor staging. They suggested that the tumor microenvironment would be the place where immature immunoregulatory cells would differentiate into mature cytotoxic cells. However, this differentiation program would not be functionally complete and the NK lymphocytes would be ‘reeducated’ by factors specific to the tumor microenvironment, explaining why NK lymphocyte infiltration could be associated with both favorable and unfavorable characteristics (Liapiet al. 2013).
The DTC microenvironment presents traces of the tumor evasion mechanism, as illustrated in Fig. 1. One of the evidences of the immune evasion skills of the rumor cell is the activation of the immune checkpoint (PD-1/PD-L1 axis, CTLA-4, TIGIT, TIM3) (Menicaliet al. 2020). The PD-1/PD-L1 axis activation appears to be one of the most important mechanisms of thyroid carcinogenesis (Cunhaet al. 2013b). Indeed, this cornerstone event intrinsically induces proliferation and migration of tumors cells, helping to explain the tight link between PD-1 and DTC aggressiveness (Liottiet al. 2021). We have previously demonstrated that PD-L1 is highly expressed by DTC cells when compared to benign lesions (Cunhaet al. 2013a). This expression is associated with aggressive features suggesting that elicitation of the PD-1/PD-L1 axis also influences tumor evasion process (Cunhaet al. 2013b). It is worth mentioning that the ideal cut-off point for choosing a PD-L1-positive tumor is not yet known. In fact, a systematic review with a meta-analysis conducted by Aghajani et al. demonstrated that positive PD-L1 expression is associated with poor survival among thyroid cancer patients (Aghajaniet al. 2018).
The tumor immune microenvironment presents several marks of the immune escape process. Tumor evasion is a decisive process for tumorigenesis. Molecular traces of these phenomena remain in the microenvironment and can be evidenced by techniques such as immunohistochemistry, immunofluorescence, flow cytometry and single-cell RNA seq. Tumor cells produce and secrete substances that lead to local immunosuppression. In addition, there are vessel growth and recruitment of cells as MDSCs that contribute to effector immune cell dysfunction, Treg proliferation and M2 macrophage differentiation. M2 macrophages inhibit T-cell response through several mechanisms, such as nutrient sequestration via arginase, generation of reactive oxygen species (ROS), nitric oxide (NO), as well as interfering with activator cell traffic within the tumor microenvironment. The production of immunosuppressive cytokines and the expression of molecules such as indolamine-2,3-dioxygenase (IDO) and arginase sequester essential nutrients for the expansion and differentiation of T cells. As a result, these cells enter an anergic state and lose their ability to eliminate tumor cells.
Citation: Endocrine-Related Cancer 29, 6; 10.1530/ERC-21-0414
It can be proposed that the activation of the PD-1/PD-L1 axis is just the tip of the iceberg, but the most important phenomenon is actually the entire process that occurs during immune evasion. Poschke et al. classified the tumor evasion process into two distinct mechanisms: camouflage and sabotage. Camouflage occurs at the level of the tumor microenvironment. It can be described as a set of abnormalities in the expression of class I antigens of the major histocompatibility complex that allow tumors to acquire a more inert phenotype to the immune system, so that tumor cells are not detected by immune system cells (Poschke et al. 2011). Sabotage, on the other hand, can be defined as the ability of some tumors to manipulate the host’s own immune system so that it starts to protect the tumor cells from immune attack. Tumors do this by recruiting or facilitating the differentiation of myeloid-derived suppressor cells and regulatory T lymphocytes (Treg). Under physiological conditions, these two cells contribute to the immune resolution that prevents an exacerbated inflammatory process (Poschke et al. 2011). The infiltration of these cells, together with the tumor production of inflammatory macromolecules, promotes a permissive microenvironment for tumor progression. It is possible that DTC cells increase the expression of immune evasive molecules such as indoleamine 2,3-dioxygenase 1 (IDO-1). IDO-1 stimulates local immune suppression. Moretti et al. demonstrated that the expression of IDO-1 is associated with the enrichment of Treg lymphocytes and with the aggressiveness of thyroid cancer (Morettiet al. 2014). Likewise, we demonstrated that elevated levels of PD-L1 protein were associated with the intratumoral infiltration of CD4+, CD8+, CD20+ cells, Treg lymphocytes, tumor-associated macrophage and myeloid-derived suppressor cells (Cunhaet al. 2013a). This aggregate of cells with an exhausted phenotype may fail to eliminate the tumor cells. On contrary, these cells may sustain a microenvironment embellished with molecules, such as IL-10, that favor the survival of the malignant cells. In fact, patients with intensely positive IL-10 tumors had shorter relapse-free survival than those with low IL-10 positivity (Cunhaet al. 2017a).
Although a detailed cell-by-cell investigation has its value in the description of the microenvironment, more and more high-performance and multiplex technologies have gained space in the literature. In 2018, Thorsson et al., using data compiled by the Cancer Genome Atlas (TCGA), performed extensive immunogenomic analysis and characterized the intratumoral immune status through the immune expression signature of more than 10,000 tumors comprising 33 different cancer histotypes (Thorssonet al. 2018). Authors identified six different immune phenotypes of the microenvironment that could be clustered as wound healing, IFN-gamma dominant, inflammatory, lymphocyte depleted, immunologically quiet and TGF-beta dominant. They proceeded to integrate both genomic, immunologic and clinical data using two complementary approaches, called Master Regulators and SIGNAL, to synthesize pan-cancer molecular big data. They identified the putative regulators of immune gene expression within immune subtypes. Interestingly, they observed that DTC predominantly presented the so-called C3 immune phenotype (inflammatory), characterized by elevated Th17 and Th1 genes (Thorssonet al. 2018).
The activation of the Th17 genes, such as IL-17 and IL-23, can be triggered by retinoic acid-related orphan receptor gamma (ROR-gamma T). Our group compared ROR-gamma T expression in DTC to other immune markers we had previously investigated, clinical and pathological data. We categorized the patients according to the clustering of immunological immune markers and could distinguish a subset (A) of patients who presented high expression of nuclear RORγt and tended to be scarce in proinflammatory immune markers. Another cluster (B) was characterized by tumors whose immune microenvironment accumulated proinflammatory markers and presented low expression of nuclear RORγt (Cunhaet al. 2020).
Single-cell RNA sequence allows the evaluation of gene expression of individualized cells. The identification of a specific genetic signature for each of the cells that compose a tissue allows assigning a barcode to these cells. This cell barcode can then be used to track millions of cells in parallel and becomes an efficient approach to investigate heterogeneous cell populations such as that of the tumor immune microenvironment. In recent years, cell barcoding has been used for cell differentiation mapping, lineage tracking and high-throughput screening and has led to important discoveries about the developmental biology and function of different genes. Driven by falling sequencing costs and the power of synthetic biology, cell barcoding is now expanding beyond traditional applications such as high-sensitivity neoplastic cell diagnosis (Kebschull & Zador 2018).
The tumor immune microenvironment may be the place where cells of different origins interact. In fact, venous, immature and arterial endothelial cells within the tumor stroma are closely connected to immune cells, collaborating in the establishment of a molecular milieu that may enable the immune editing process (Puet al. 2021). This phenomenon supports the idea that the presence of extensive vascular-immune crosstalk in the multicellular tumor microenvironment can be a target for multiple immunotherapy agents.
Pan et al. constructed the single-cell landscape of PTC investigating both carcinoma and non-carcinoma microenvironment cells of samples from eight PTC cases, including three patients with concurrent chronic lymphocytic thyroiditis. When a reclustering technique was applied, the authors observed that common tumor-infiltrating lymphocytes consisted of NK cells, Treg cells and follicular B cells, whereas most plasma cells and B cells came from PTC patients with concurrent thyroiditis tumor samples. It is possible that concurrent thyroiditis influences the homeostasis of PTC immune microenvironment. The autoimmune activity against the thyroid gland may exert a protective role in patients with DTC (Souza et al. 2003). The association between chronic thyroiditis and immune microenvironment in DTC patients is reported at a wide frequency, ranging from 0.5 to 38% but remains controversial. While some investigators found that the presence of concurrent thyroiditis was associated with a better prognosis and less aggressiveness of the disease at presentation (Schaffleret al. 1998, Lohet al. 1999, Guptaet al. 2001, Ramoset al. 2009, Abbasgholizadehet al. 2021), others have not found such an association, suggesting that autoimmune destruction of tumor cells is not able to effectively change the prognosis of these patients (Kebebewet al. 2001, Del Rioet al. 2008, Muzzaet al. 2010).
The immune microenvironment of anaplastic and poorly differentiated thyroid cancer
Anaplastic (ATC) and poorly differentiated thyroid carcinoma (PDTC) are aggressive neoplasms that account for 1–2% and 2–15% of all thyroid cancers, respectively (Jemalet al. 2011) and permit scarce therapeutic strategies. The current guideline of the American Thyroid Association recommends surgery in ATC cases stage IV-A and IV-B and a careful evaluation of surgical options in stage IV-C cases (Bibleet al. 2021). Conservative treatment may be an option for selected patients, as well as chemotherapy, radiotherapy or just supportive care (Bibleet al. 2021). The lack of a therapeutic strategy capable of changing the natural history of both ATC and PDTC reinforces the fact that the biology of dedifferentiation needs elucidation and understanding tumor immunological microenvironment emerges as a possible therapeutic perspective.
The immune profile of ATC and PDTC microenvironment seems to be peculiar and quite different from that of DTC. PD-L1 is more frequently found in ATC and PDTC (Ahnet al. 2017). Most ATC tumor cells are PD-L1-positive and its microenvironment is enriched with more PD-1/PD-L1-positive infiltrating lymphocytes (Ahnet al. 2021). PD-L1, but not PD-1, presents a positive staining pattern in most ATC cells (Chintakuntlawaret al. 2017).
Although both ATC and PDTC have an unfavorable prognosis, the immune microenvironment of these two entities may be distinct. Looking to draw a panorama that differentiates ATC from PDTC, Giannini and collaborators have investigated in depth their immune response profile using the Nanostring platform and its nCounter PanCancer Immune Profiling Panel (Gianniniet al. 2019). They observed that most ATC presented an immune microenvironment enriched by macrophages and T-cells with CD8+ effector phenotype, part of which functionally exhausted (Gianniniet al. 2019). Indeed, ATCs present a very dense network of interconnected ramified tumor-associated macrophages that are connected and interact with malignant cells (Caillouet al. 2011). It is even possible that more than half of the nucleated cells in ATC tumor microenvironment are actually macrophages, whose membrane prolongations facilitate the each-self connections, the distribution arising from perivascular clusters and the dissemination within the tumor stroma (Caillouet al. 2011). The macrophages appeared predominantly polarized to M2 phenotype, promoting an immune microenvironment that tends toward immune suppression (Ryderet al. 2008, Gianniniet al. 2019). ATC tumor cells are able to upregulate inhibitory immune checkpoint mediators (Gianniniet al. 2019). On the other hand, most PDTC displayed a poor or absent intratumoral infiltration by macrophages and T cells and were called ‘cold’ immune tumors (Gianniniet al. 2019). In fact, our previous data showing a higher expression of IL-10, an immunosuppressive cytokine, among PDTC sustain this hypothesis (Cunhaet al. 2017a), since the IL-10 produced and secreted by tumor cells would promote immunosuppressive milieu in PDTC microenvironment.
The immune microenvironment of medullary thyroid cancer
Medullary thyroid carcinoma (MTC) is a malignant neoplasm of C-cell origin capable to recapitulate the differentiation of the neuroendocrine lineage (Reynoldset al. 2001). MTC manifests as a sporadic tumor in 75% of the patients and as hereditary in about 25–40% of them (Daduet al. 2020). The hereditary presentation is often caused by germline mutations in the RET gene, configuring multiple endocrine neoplasia type 2 (MEN2) syndromes (Wellset al. 2015). The prognosis of MTC is favorable for most patients. However, distant metastases can be present in almost 20% of the cases at initial presentation or develop early in the course of the disease (Wellset al. 2015, Ceolinet al. 2019). The 5-year survival rate that ranges from 70 to 85% in patients with locoregional disease drops to 50–60% in patients with distant metastases (Wellset al. 2015). Even though the molecular biology of MTC has been deeply investigated in recent years, current therapies are not able to lead to complete remission in patients with aggressive disease (Michielset al. 1997, Castinettiet al. 2019).
Immune co-inhibitory molecules, mainly PD-1/PD-L1, are expressed in MTC tumor cells (Biet al. 2019). The co-expression of PD-1/PD-L1 is significantly correlated with aggressive features, such as distant metastases in TNM stage III/IV (Biet al. 2019). Other co-inhibitory molecules (e.g. TIM-3, CTLA-4, LAG-3 and TIGIT) can be detected in MTC and the evasive phenotype of the immune microenvironment is fairly associated with poor prognosis (Shiet al. 2021).
Although MTC cells can produce co-inhibitory molecules that potentiate tumor evasion, it is also possible that a subset of patients presents a tumor microenvironment composed of activated immune cells with effector mechanisms, prone to a favorable immune response. One explanation may lie on the RET gene (Rusminiet al. 2013, Castellone & Melillo 2018). A study with NIH-3T3 cells transfected with MEN2A-causing mutations (RET with gain of function C609Y and C634R) demonstrated that they were able to activate an anti-tumor immune response by stimulating pathways of proliferation, migration and cytotoxicity of NK lymphocytes. Likewise, RET gene mutations were shown to activate the production of stroma-modifying oncoproteins adjacent to tumor (Borrelloet al. 2005, Rusminiet al. 2013), suggesting that RET gene may influence the immune profile of the tumor microenvironment.
Pozdeyev et al. have shown that tissues from MTC have an inflammatory infiltrate permeated by CD8+ T cells and scarce myeloid cells with features of exhaustion, a process characterized by the progressive loss of function of some cells of the immune system (Pozdeyevet al. 2020). In this study, the PD-L1 expression in tumor-infiltrating lymphocytes was rare, whereas adhesion molecules such as CD155 and CD47 were abundantly expressed on lymphocytes, suggesting that MTC had an immunogenic phenotype.
The immune response as a prognostic marker of patients with thyroid cancer
Models capable of predicting the prognosis of patients with thyroid cancer have been explored for a long time, seeking to better individualize the treatment and follow-up of these patients. Although the criteria mentioned above can add value in the follow-up of patients with thyroid cancer, there are still some imperfections that suggest that these proposals need improvement.
We previously provided a comprehensive analysis of the prognosis of patients with DTC considering their clinical, demographic, pathologic and immunologic characteristics (Cunhaet al. 2015). Different models evidenced COX2 expression and infiltration of CD8 cells by immunohistochemistry as independent prognostic markers of relapse-free time (Cunhaet al. 2015). The inclusion of immunological parameters (COX2/CD8) in the score system significantly improved the prognosticator capacity of pTNM system, suggesting that a relatively simple pathology tool may help clinicians select cases that may benefit from a more aggressive approach, sparing most patients from unnecessary procedures (Cunhaet al. 2015).
The immune phenotype described by Thorsson seems to be relevant for prognostic prediction in patients with thyroid cancer. Thorsson et al. immune subtypes were associated with overall survival and progression-free interval (Thorssonet al. 2018). Authors observed that thyroid cancer restores the inflammatory subtype (defined by elevated Th17 and Th1 genes with low to moderate tumor cell proliferation) that had the best prognosis. On the contrary, tumors with IFN-gamma subtype (defined by highest M1/M2 macrophage polarization) and wound healing (defined by elevated expression of angiogenic genes, a high proliferation rate, and a Th2 cell bias to the adaptive immune infiltrate) had less favorable outcomes despite having a substantial immune component (Thorssonet al. 2018). It is possible that the higher M1/M2 ratio reiterates the local proinflammatory state in these patients that would benefit tumor cell survival and dissemination (Thorssonet al. 2018). Wu et al. built a bioinformatics tool with the objective of establishing a molecular model capable of predicting the survival of patients with thyroid cancer (Wu et al. 2021). Authors analyzed the correlation between an immune-related genes prognostic signature and tumor-infiltrating immune cells, tumor mutation burden and immune checkpoint protein expression in patients with thyroid cancer (Wu et al. 2021). The final model, which compiles the expression of eight genes, presented area under the curve of the risk score for overall survival of 0.998 at 1 year, 0.930 at 3 years and 0.937 at 5 years (Wu et al. 2021). In addition, this risk signature was correlated with the composition of tumor immune microenvironment and the low-risk group was enriched with dendritic cells, CD8+ T cells, macrophages, neutrophils, natural killer cells, type 1 T helper cells, type 2 T helper cells, TILs and regulatory T cells (Wu et al. 2021).
One of the advantages of molecular pathology is the estimation of the ImmunoScore (Fig. 2), a quantification index of the in situ immune infiltrate (Galonet al. 2014). Immunoscore takes into account the type of the immune cell, the density, the location of the immune cell within the tumor and the phenotypic orientation of the immune cells (Galonet al. 2014). This score demonstrated a prognostic significance superior to that of the AJCC/UICC TNM classification system for some cancers (Galonet al. 2014). ImmuneScore has significant negative correlation with the differentiation status of thyroid cancer and was higher among tumor positive for BRAFV600E mutation (Na & Choi 2018). High ImmuneScore patients presented worse recurrence-free survival (Na & Choi 2018). ImmuneScore and/or other immune markers may be incorporated into the routine of thyroid cancer pathology providing valuable tools for planning personalized patient management.
ImmunoScore was initially developed in patients with colon cancer. The objective of this method is to estimate the capacity of the immune response to eradicate tumor cells. For this, the ImmunoScore assesses the phenotype of the immune cell (mainly CD3 and CD8), the density of these cells and the location of these cells in the tumor microenvironment. The higher the ImmunoScore of the tumor microenvironment, the more effective the anti-tumor effector immune response should be and, therefore, the more favorable the patient’s prognosis.
Citation: Endocrine-Related Cancer 29, 6; 10.1530/ERC-21-0414
Interestingly, the presence of lymph node metastasis at diagnosis is not the best independent marker of prognosis. This could be explained by an increase in effector mechanisms of the immune response, with important infiltration of activated lymphocytes in the lymph node metastasis microenvironment (Cunhaet al. 2017b ). Additionally, lymph node metastasis may undergo a reduction in tumor evasion mechanisms. In fact, we found an important decrease in the expression of PD-L1, which is a co-inhibitory molecule involved in tumor evasion, in metastatic lymph nodes (Cunhaet al. 2013a).
French et al. demonstrated that metastatic lymph nodes from patients with PTC have a high density of IFNγ+CD8+ T lymphocytes (Frenchet al. 2012). They suggested that the presence of metastasis does not arrest and may even promote an immune response supported by the production of IFN-γ. Supporting this hypothesis, the authors found that lymph nodes committed to metastasis present lymphocytes in proliferative activity. This data, together with ours, as reported above, could explain at least in part why the presence of lymph node metastasis at diagnosis is not a strong predictor of survival or progression in DTC patients (Frenchet al. 2012).
The immune response as therapeutic target in patients with thyroid cancer
The historical perspective
As early as 1891, William Coley demonstrated that bacterial products were able to control the immune system, helping patients with inoperable solid tumors (Dobosz & Dzieciątkowski 2019). The clinical benefits of Bacillus Calmette-Guerin and other immunostimulatory substances led to the approval of the use of these compounds in patients with solid tumors such as bladder cancer (Dobosz & Dzieciątkowski 2019). The 20th century was decisive for the enormous development of cellular and molecular immunology techniques, which enabled high accuracy in the development of personalized precision therapies, as exemplified in Table 2. In 2018, James P Allison and Tasuku Honjo shared the Nobel Prize in Physiology or Medicine for their discovery of immunotherapy based on inhibitors of the immune checkpoints inhibitors (ICI). Allison contributed identifying the CTLA-4 molecule, whose blockage by the antibody ipilimumab is capable of increasing the immune system’s capacity to destroy tumor cells. Tasuku Honjo contributed to the discovery of the PD-1 molecule, originally found on autoreactive T cells in the thymus that were sent to programmed cell death PD-1 blockade, like CTLA-4 blockade, removing the natural brake on the immune response and enhancing the immune attack against tumor cells. New molecules have been discovered since then and more studies have been reinforcing the tremendous impact that ICIs have on cancer treatment, as represented in Fig. 3.
The immune checkpoints inhibitors and their targets. The immune checkpoints inhibitors are monoclonal antibodies designed as humanized antibodies with high affinity to molecules that brake the immune response. By inhibiting this brake, the immune response upstage its activation and the anti-tumor effector mechanisms take place.
Citation: Endocrine-Related Cancer 29, 6; 10.1530/ERC-21-0414
Most important modalities of immunotherapy currently available to treat cancer patients.
| Immunotherapy modality | Principles of the immune response | Examples of the modality | Possible applications for thyroid cancers | Main limitations |
|---|---|---|---|---|
| Antibody-based therapy |
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| CAR T cell therapy |
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| Cancer vaccines |
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| Cytokines and interleukins |
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| Oncolytic viruses |
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The adverse effects of ICIs may be classified as immune and non-immune. Most are manageable (grade I or II) and rarely require drug discontinuation. These adverse effects were thoroughly detailed by Karhapää et al. in a recent publication (Karhapää et al. 2022).
Preclinical experiences
The preclinical results of immunotherapies for PDTC and ATC are highly optimistic. Vanden Borre et al. investigated the response of genetically defined murine PTC and ATC cell lines to BRAFV600E inhibitors in vitro (Vanden Borre et al. 2014). In addition to inhibiting proliferation and migration, BRAFV600E inhibitors lead to infiltration of immune cells and reduce tumor volume, suggesting that blocking BRAF could burst the immunogenicity of these thyroid cancers (Vanden Borre et al. 2014). The same group further investigated anti-PD-L1 antibody alone and combined with a BRAFV600E inhibitor in mice implanted with BRAFV600E/WT P53−/− murine tumor cells (Brauner et al. 2016). Mice treated with the combination of these drugs presented a shrinkage of the tumor volume associated with an enrichment of cytotoxic CD8 cells (Brauner et al. 2016).
Gunda et al. investigated one immunocompetent murine model of orthotopic ATC (Gunda et al. 2019). Mice treated with lenvatinib (a multi-targeted tyrosine kinase inhibitor) and anti-PD-1 antibody presented an intense intratumoral inflammation characterized by an increase of CD8+ cells and decrease of polymorphonuclear myeloid-derived suppressor cells (Gunda et al. 2019). Interestingly, when myeloid-derived suppressor cells (MDSCs) were targeted by an anti-Gr-1 antibody, the response to lenvatinib was potentiated, suggesting that MDSCs may be useful as immunotherapy adjuvants (Gunda et al. 2019).
The chimeric antigen receptor (CAR) T-cell technology
CAR T-cell therapy represents a cornerstone in personalized cancer treatment (Feins et al. 2019). In this therapy, patient’s own T cells are genetically engineered to express a synthetic receptor with affinity to a specific tumor antigen (Feins et al. 2019). CAR T cells are then expanded ex vivo and infused back into the patient (Feins et al. 2019). CARs are synthetic receptors composed of: (i) extracellular domain, (ii) a transmembrane domain and (iii) an intracellular domain and one or two co-stimulatory domains (Safarzadeh Kozani et al. 2021), as illustrated in Fig. 4. The co-stimulatory domains are fundamental for the activation of the signal triggered by the recognition of the antigen (Safarzadeh Kozani et al. 2021). Li et al. developed a CAR T cell with two co-stimulatory domains and thyroid-stimulating hormone receptor (TSHR) as the target tumor-associated antigen (Li et al. 2021). An in vivo test using a xenograft mouse model of DTC demonstrated that these CART T cells diminished tumor volume efficaciously (Li et al. 2021).
Chimeric antigen receptor T cells (CART) are T lymphocytes genetically engineered to produce an artificial T cell receptor for tumor antigen recognition and adoptive cell immunotherapy. The chimeric receptor construct presents an external protein region capable to recognize tumor antigens such as the TSH and GNFRa receptor expressed on DTC and MTC tumor cells, respectively, with high specificity. Third-generation CARs, like those tested in preclinical studies against thyroid cancer, have two costimulatory intracellular domains and a CD3 zeta segment, which ensure the firing of the intracellular signal that culminates in the activation of the T cells against tumor.
Citation: Endocrine-Related Cancer 29, 6; 10.1530/ERC-21-0414
MTC derives from the neural crest and secretes calcitonin and carcinoembryonic antigen. Previous genomic investigation identified the RET-associated receptor of the glial-derived neurotrophic factor (GDNF) receptor (GFR) family, GFRα4, as an MTC-associated antigen with highly restricted expression in humans (Lindahl et al. 2001). Bhoj et al. developed CAR T cells harboring the CD3ζ and the CD137 costimulatory domains (Bhoj et al. 2021). They further demonstrated that these GFRα4-specific CAR T cells eliminated tumors of an MTC xenograft mouse model (Bhoj et al. 2021). Antitumor activity was accompanied by T-cell expansion, suggesting these cells are a promising modality of immunotherapy for MTC (Bhoj et al. 2021).
Clinical experiences
Traditional therapies, including surgery, radioactive iodine and TSH suppression are effective for most DTC, but patients with advanced DTC, PDTC and ATC frequently present unfavorable prognosis and need new strategies. We still lack data from large, randomized clinical trials but do have results from compilation series. Iyer et al. retrospectively investigated 12 patients with ATC who received pembrolizumab in combination with kinase inhibitors by the time of progression (Iyer et al. 2018). They observed a partial response in five patients (42%); four patients (33%) presented stable disease and three patients (25%) presented progressive disease (Iyer et al. 2018). Chintakuntlawar et al. performed a phase 2 trial evaluating three patients with pembrolizumab combined with chemoradiotherapy (Chintakuntlawar et al. 2019). Despite an initial response, all three patients died before 6 months of starting therapy (Chintakuntlawar et al. 2019). Dierks et al. reported six patients with metastatic ATC and two patients with PDTC who were submitted to a combination therapy with lenvatinib and pembrolizumab (Dierks et al. 2021). Four out of the ATC patients (66%) presented a complete remission, one patient (16%) had stable disease and one patient (16%) presented a progressive disease after a maximum treatment duration of 40 months (Dierks et al. 2021). The two patients with PDTC had partial remission (Dierks et al. 2021). Grade III/IV toxicity was observed in half of the patients (4 cases) (Dierks et al. 2021). Interestingly, the best responses were obtained in patients with the highest tumor mutational burden or PD-L1 expression level (Dierks et al. 2021).
In a phase 1b proof-of-concept non-randomized study, Mehnert et al. investigated 22 patients with advanced DTC, no response to standard therapy and PD-L1 positive at immunohistochemistry (Mehnert et al. 2019). They were submitted to anti-PD-1 (pembrolizumab) treatment with excellent tolerance and no death during follow-up. Only one patient presented a grade III colitis (Mehnert et al. 2019). After a median follow-up of 31 months, two patients (9%) presented partial response, thirteen patients (59%) presented stable disease and seven patients (32%) presented progressive disease (Mehnert et al. 2019). The rate of clinical benefit with confirmed partial response or stable disease for 6 months was 50% (Mehnert et al. 2019). Clinical trials are ongoing and more data are eagerly awaited to clarify the impact of ICIs in patients with DTC, PDTC and ATC. These patients would benefit from pembrolizumab, recently approved by the FDA for the treatment of adult and pediatric patients with unresectable or metastatic tumor mutational burden-high (TMB-H; ≥10 mutations/megabase (mut/Mb)) solid tumors that have progressed following prior treatment and have no satisfactory alternative treatment options (Marcus et al. 2021).
Closing remarks
In summary, the immune tumor microenvironment is a heterogeneous composition of cells from different origins that can be assessed by thyroid pathologists. The complexity of the tumor microenvironment has been recently unveiled by high throughput and multiplex technologies, such as the single-cell RNA sequence. The in-depth investigation of the molecular connections between immune and non-immune cells enriched in the tumor microenvironment will allow the construction of new clinical tools capable of better prognosing patients with thyroid cancer. Indeed, immunohistochemistry is an example of a practical and cost-effective technique that may be translated from routine pathology laboratories to clinical practice, helping bedside endocrinologists to predict relapse in thyroid cancer patients. In addition, the crosstalk between tumor and stromal cells gives rise to a complex molecular network that may be targeted by new therapeutic agents. These agents are the focus of new immunotherapy modalities that could change thyroid cancer treatment paradigm in the coming years.
Declaration of interest
The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of this review.
Funding
This work did not receive any specific grant from any funding agency in the public, commercial, or not-for-profit sector.
Acknowledgement
The authors thank the FAPESP for grants and funding for research.
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