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Review

Pediatric Solid Cancers: Dissecting the Tumor Microenvironment to Improve the Results of Clinical Immunotherapy

by
Cristina Belgiovine
1,2,*,
Kristiana Mebelli
2,
Alessandro Raffaele
2,
Marica De Cicco
3,
Jessica Rotella
4,
Paolo Pedrazzoli
5,6,
Marco Zecca
4,
Giovanna Riccipetitoni
1,2 and
Patrizia Comoli
3,*
1
Dipartimento di Scienze Clinico-Chirurgiche, Diagnostiche e Pediatriche, University of Pavia, 27100 Pavia, Italy
2
SC Chirurgia Pediatrica, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
3
SSD Cell Factory e Center for Advanced Therapies, Department of Woman and Child Health, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
4
SC Pediatric Hematology/Oncology, Department of Woman and Child Health, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
5
Medical Oncology, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
6
Department of Internal Medicine, University of Pavia, 27100 Pavia, Italy
*
Authors to whom correspondence should be addressed.
Int. J. Mol. Sci. 2024, 25(6), 3225; https://doi.org/10.3390/ijms25063225
Submission received: 13 December 2023 / Revised: 26 February 2024 / Accepted: 8 March 2024 / Published: 12 March 2024
(This article belongs to the Section Molecular Oncology)

Abstract

:
Despite advances in their diagnosis and treatment, pediatric cancers remain among the leading causes of death in childhood. The development of immunotherapies and other forms of targeted therapies has significantly changed the prognosis of some previously incurable cancers in the adult population. However, so far, the results in pediatric cohorts are disappointing, which is mainly due to differences in tumor biology, including extreme heterogeneity and a generally low tumor mutational burden. A central role in the limited efficacy of immunotherapeutic approaches is played by the peculiar characteristics of the tumor microenvironment (TME) in pediatric cancer, with the scarcity of tumor infiltration by T cells and the abundance of stromal cells endowed with lymphocyte suppressor and tumor-growth-promoting activity. Thus, progress in the treatment of pediatric solid tumors will likely be influenced by the ability to modify the TME while delivering novel, more effective therapeutic agents. In this review, we will describe the TME composition in pediatric solid tumors and illustrate recent advances in treatment for the modulation of immune cells belonging to the TME.

1. Introduction

The well-known role of T cells in the durable control of cancer has been impressively exploited in recent times through the therapeutic use of tumor-targeted advanced-therapy medicinal products (ATMPs), such as T cells that have been genetically modified to express chimeric antigen receptors (CARs) or natural T cell receptors (TCRs) bearing tumor-associated antigens [1]. Moreover, improved knowledge of cancer’s immune evasion mechanisms and host–tumor interactions [2] has led to the development of immune checkpoint inhibitors (ICIs), a class of agents that are able to counteract the suppressive effects of the tumor microenvironment (TME) on host immune cells. These compounds were able to achieve long-lasting remissions in previously unresponsive tumors and have rapidly become cornerstones of anticancer treatment [3].
The significant recent advances in the control of selected adult cancers [3] and adult and pediatric hematologic malignancies [4] have not been replicated so far in the setting of pediatric solid tumors. The causes consist, on the one hand, of the rarity of pediatric solid tumors, which, despite international efforts at cooperation, have resulted in major difficulties in developing novel therapies and conducting randomized clinical trials. In addition to this bottleneck, another major obstacle is represented by the peculiarities of pediatric tumors, which differ from adult cancer in terms of their mutational burden, underlying etiopathogenesis, and TME characteristics. Several studies have highlighted the critical role of the TME in response to therapy and the development of resistance in pediatric solid tumors [5]. Therefore, a better understanding of TME composition and function is crucial for the development of personalized and effective therapies in pediatric solid tumors. In this review, we will give an overview of the TME in the main pediatric solid cancers, highlighting how TME peculiarities may help personalize treatment for these tumors to optimize disease outcomes and illustrate the results of clinical trials that have attempted to modulate the TME using ICIs or ATMPs.

2. Overview of Solid Cancers in Childhood

The incidence of pediatric solid tumors in Europe varies depending on the type of cancer, patient age, and country [6]. Tumors of the brain and central nervous system are the most common pediatric solid tumors, followed by neuroblastoma, soft-tissue sarcoma, Wilms tumor, and bone tumors. Thanks to advances in diagnosis and treatment, survival rates have significantly improved in recent years. According to the National Cancer Institute, the overall 5-year survival rate for children with all types of pediatric solid tumors is about 75%. However, very rare childhood solid tumors are lacking in treatment options, with many of these diseases continuing to have a dismal prognosis.
The cellular origin of childhood solid tumors is diverse, as they can arise from different cell types, including embryonic or fetal cells [7], and their mutational burden is low [8], likely as a consequence of their manifesting in precursor cells of non-self-renewing tissues that have accumulated a lower number of mutations than that of cells of origin in adult tumors [9]. Thus, the genomic-based alterations and mechanisms in pediatric cancer are different from those observed in adult tumors, often being driven by the epigenetic deregulation of gene transcription, rather than the accumulation of somatic gene mutations [10], and showing unique genetic mutations that distinguish them from adult solid tumors [11]. Indeed, a significant proportion of pediatric brain tumors are driven by mutations in genes such as TP53, BRAF, and IDH1/2, which are less common in adult brain tumors. Similarly, structural changes, such as gene fusions and specific rearrangements, have been found to play a role in childhood cancer pathogenesis: EWSR1 in Ewing’s sarcoma, PAX3/7-FOXO in rhabdomyosarcoma, and MYCN or ALK in neuroblastoma [10]. Some of these genomic alterations have been associated with prognosis, allowing risk stratification and translation into therapeutic reduction or intensification, leading to a direct impact of genomic studies in pediatric cancer.
As knowledge on the molecular basis of tumorigenesis is being built, thanks to the efforts of international consortia, progress in drug development and early-phase clinical trials for targeted therapies in pediatric oncology is advancing. While some targeted therapeutic approaches specific to molecular alterations in pediatric cancer are being tested, other strategies for implementing treatment may rely on the modulation of the TME and the enhancement of protective cellular immunity. The success of ICIs largely depends on the presence of tumor-infiltrating lymphocytes that are specific to tumor-associated antigens and are able to mediate cancer cell lysis. As pediatric cancers have been described to have a low mutational burden, they generally have only a limited set of neoantigens that may be recognized and targeted by T cells, and the TME shows paucity in infiltrating T cells. Consequently, the activity of ICIs against any of the common solid cancers occurring in children and adolescents is suboptimal, and it is difficult to find suitable targets for the development of ATMPs. A way to overcome this situation could be to combine different strategies, such as ATMPs and ICIs, and/or act on other components of the TME to reduce its immune-suppressive and tumor-promoting effects.

3. The TME in Solid Tumors

The tumor microenvironment is a complex ecosystem of cellular and non-cellular components that surround and interact with cancer cells. The composition of the TME is a critical determinant of tumor progression, metastasis, and response to therapy, and its study is central to amelioration of results in cancer (Figure 1). The immune TME is composed of different cell types that play a role in tumor proliferation and progression depending on their inherent functions and the cytokines or inhibitory ligands that they express. In pediatric solid tumors, the TME is highly heterogeneous, dynamic, and distinct from that of adult tumors.

3.1. The Non-Immune Component: Extracellular Matrix and Fibroblasts

The stromal part of the TME is composed of stromal cells, cancer-associated fibroblasts (CAFs), and an extracellular matrix (ECM). While angiogenesis and the proteins involved have been studied in many tumors, other factors that affect immune cells present within the tumor, such as the composition of the cellular matrix, the presence of CAFs, the cytokines that they release, and the composition of the patient’s bone marrow niche, have only been studied in a limited number of tumors. Microvascularization and angiogenesis have been investigated in numerous pediatric tumors, and the levels of angiogenic factors and tumor angiogenesis in situ have been found to correlate with metastatic disease and poor prognosis in neuroblastoma, osteosarcoma, and rhabdomyosarcoma [12,13,14,15,16]. The protein VEGF, which is known for its role in angiogenesis, has also been detected in several pediatric solid tumors, such as neuroblastoma, Wilms’ tumor, Ewing sarcoma, osteosarcoma, and rhabdomyosarcoma [15].
Furthermore, it has been found that the expression of VEGF can be regulated by Wnt/b-catenin activation in Ewing sarcoma cells [17]. In osteosarcoma, VEGF expression is associated with CXCR4 expression, which is found in 67% of osteosarcomas, and the co-expression of these two proteins is linked to decreased patient survival. A similar correlation has been observed in rhabdomyosarcoma patients [18].
In various tumor types, CAFs have been found to play a role in tumor progression and metastasis [2]. For example, CAFs expressing MMP-2 and MMP-9 have been identified in osteosarcoma [19,20], and their increased presence in the tumor area has been associated with MMP-2 and MMP-9 expression [21]. MMP-9 has been found to recruit bone-marrow-derived leukocytes in the tumor microenvironment [22]. These cells produce several soluble factors that help to recruit immune cells into the tumor. Transforming growth factor beta (TGF-β), fibroblast growth factor 2, platelet-derived growth factor, and epidermal growth factor (EGF) are secreted not only by stromal cells but also by cancer cells. CAFs physically support the tumor by secreting the ECM, and they can regulate the turnover of the ECM. Fibroblasts also secrete different soluble mediators, such as vascular endothelial growth factor (VEGF), interleukin (IL)-6, C-X-C motif chemokine ligand 12 (CXCL12), TGFβ, tumor necrosis factor (TNF)-α, IFN-γ, stromal cell-derived factor-1α, EGF, galectin-1, and the transcription factor NF-κB [23,24,25,26,27]. In osteosarcoma, the overexpression of a hyaluronidase called KIAA1199 has been identified as a prognostic factor due to its role in the development and maintenance of cancer metastasis [28]. Similarly, the high expression of fibronectin or αvβ3, either individually or in combination, has been associated with osteosarcoma [29].
Within the TME of a neuroblastoma, one finds nontumor cells called neural-crest-derived progenitors that give rise to the tumor stroma. Knowledge of this genetic signature correlates with the presence of CAFs and is useful for stratifying the most aggressive tumors (4M/neuroblastoma) to improve the therapeutic approach by targeting stroma-associated processes [30].
The major non-cellular component in the TME is the ECM, which is mainly composed of collagen. ECM is necessary to sustain the structure of the solid tumor and to store several soluble mediators, creating the typical immunosuppressive niche [31]. In Ewing sarcoma cells, as described by Hawkins et al. [17], Wnt/b-catenin activation is associated with enhanced ECM production and angiogenesis due to Wnt signaling and tumor/ECM crosstalk. In osteosarcoma, which has abundant ECM deposition, studies of patient samples have confirmed the prognostic usefulness of ECM-related markers [28,29,32]. The composition of the extracellular matrix (ECM) has also been studied in osteosarcoma. Mintz et al. [32] discovered that resistant tumors may have an increased ability to express osteoclastogenesis, tumor progression, and ECM remodeling genes. This suggests that chemotherapy-resistant osteosarcoma tumors mediate tumor growth and survival through altered proteolytic mechanisms that function in a multigenic fashion to activate osteoclasts, promote tumor survival, and modify the environment of the ECM.
Additionally, the inhibition of the collagen-crosslinking enzyme lysyl oxidase-like 2 reduces tumor growth and metastasis in preclinical models [33].

3.2. Cancer Stem Cells

Cancer stem cells (CSCs) are a subset of cancer cells that possess self-renewal and differentiation capabilities, contributing to tumor initiation, progression, metastasis, and resistance to therapy. In the TME of solid tumors, CSCs interact with various stromal cells, ECM components, and soluble factors, modulating the TME’s composition and function. CSCs can secrete cytokines, chemokines, growth factors, and ECM components, promoting angiogenesis, immune evasion, and ECM remodeling and creating a niche that facilitates their survival and expansion [34]. Furthermore, CSCs can communicate with immune cells, including T cells, natural killer (NK) cells, and myeloid-derived suppressor cells (MDSCs), leading to an immunosuppressive TME that impairs antitumor immune responses. A low concentration of CSCs is correlated with increased immunocyte infiltration [35]. Targeting CSCs and their interactions with the TME could provide new therapeutic approaches for solid tumors [36,37,38]. In pediatric solid tumors, CSCs have been identified in various types of cancers, including neuroblastoma, medulloblastoma, Ewing sarcoma, osteosarcoma, and rhabdomyosarcoma [39]. In neuroblastoma, the presence of CSCs modulates the TME in angiogenesis, in the formation of the ECM, in the presence of CAFs, and in immune cell interactions [40].

3.3. What Remains to Be Elucidated in the Study of the Non-Immune TME

In the study of pediatric tumors, the characterization of the stromal compartment and its contribution to pediatric tumor progression and metastasis is an understudied area that warrants further research. It is widely recognized that the crosstalk between tumor cells and stromal cells, such as fibroblasts and endothelial cells, contributes to tumor growth and progression. Increased expression/activity of the transcriptional co-regulator Yes-Associated Protein (YAP) following chemotherapy and relapse promotes resistance to therapy, including resistance to anti-disialoganglioside 2 (anti-GD2) immunotherapy, in high-risk neuroblastoma through the transcriptional repression of genes that play a role in the TME [41,42]. However, the role of YAP expression, as well as that of other factors in other solid tumors, has not been thoroughly evaluated.
The study of the hematopoietic niche of bone marrow cells has been primarily focused on patients with osteosarcoma due to the proximity of the tumor to the niche itself. It is known that the bone marrow microenvironment influences the dissemination of tumor cells from different origins [43,44]. Mesenchymal stem cells derived from the bone marrow have been shown to promote primary tumor growth and invasion [45], potentially inducing stemness and chemoresistance via the NFκB pathway and IL6 secretion [46]. Deepening the study of the hematopoietic bone marrow niche could be important in those tumors with secondary localizations or metastases to the bone marrow itself, such as in brain tumors [47], neuroblastoma [48,49], and sarcoma [47,50].

3.4. Immune Characteristics of the Tumor Microenvironment in Solid Tumors: Antitumor Properties

Tumor-infiltrating lymphocytes (TILs), which include CD4+ helper cells and CD8+ cytotoxic T-cells (CTLs), represent the adaptive immune response in the TME. CTLs have a potent antitumoral function, and their presence has been correlated with a better prognosis in several tumor settings [51]. Naive CD8+ T lymphocytes, which are primed and educated by professional antigen-presenting cells (APCs), can recognize tumor cells in an antigen-specific manner and mediate direct killing through the release of cytotoxic molecules, such as perforins or granzyme. Under physiological conditions, CD8+ activation occurs in secondary lymphoid organs, such as lymph nodes, but it can also occur in organized tertiary lymphoid structures within the tumor [52], where the antitumor immune response can be orchestrated [53]. CTLs are usually contained by a negative feedback loop once the cytotoxic function is completed. However, in cancer, there is persistent stimulation of CD8+ T cells in the TME, resulting in T cell exhaustion. There is a progressive loss of effector function, such as a decrease in IL-2, TNF-α, and IFN-γ production, and an increase in the expression of inhibitory receptors, such as PD-1, CTLA-4, Tim-3, LAG-3, B- and T-lymphocyte attenuator or BTLA [54]. For this reason, several therapeutic approaches that have been developed in the last twenty years are based on augmenting the natural immune response [55].
CD4+ T helper-1 cell population subsets may also contribute to tumor cell control through the induction of apoptosis and are responsible for sustaining the antitumor immune response of CD8+ T cells via the release of cytokines that are essential for T cell proliferation, as well as for macrophage recruitment and activation [56].
Tumor cells escape immune surveillance through the loss of class I major histocompatibility complex molecules on their surface. Class-I-associated antigen presentation is the cornerstone of CD8+ T cell effector functions; however, HLA class I downregulation promotes NK cell recognition and killing [57]. The NK subset belongs to the innate immune system and is highly efficient in identifying and killing undifferentiated or poorly differentiated tumor cells in both tumors and circulation [58,59]. NK cells can counteract the hostile TME [60,61,62] due to their ability to mediate cytotoxicity through both activating and inhibitory signals [63]. NK cells can kill tumor cells by releasing perforins and granzyme B, which induce necrotic or apoptotic cell death, and via the secretion of different antitumor cytokines, such as IL-10, IL-5, IL-13, granulocyte–macrophage colony-stimulating factor, IFN-γ, and TNF-α, which help to re-modulate the immunosuppressive environment present at the tumor site [64,65].

3.5. The Tumor Microenvironment in Solid Tumors: The Pro-Tumor Role

Within the immune landscape of the TME, cells belonging to the myeloid compartment appear to have a pro-tumor role. In general, both tumor-associated macrophages (TAMs) and tumor-associated neutrophils have a markedly immunosuppressive phenotypic profile. These cells, together with immature granulocytic and monocytic cells (myeloid-derived suppressor cells (MDSCs), favor tumor progression because they help orchestrate extracellular matrix remodeling, angiogenesis, tumor cell proliferation, metastasis, and immunosuppression, in addition to promoting resistance to chemotherapeutic agents and checkpoint blockade immunotherapy [66].
Macrophages (CD68+ cells) are specialized cells of the innate immune system that are characterized by their great plasticity. They are recruited within tumors via soluble factors produced by stromal and tumor cells, such as IL-3, colony-stimulating factor 1, and chemokine ligand-2 [67]. They are characterized by a high degree of plasticity and, as such, may be polarized towards more inflammatory functions, with antitumor activity (M1-like) or, conversely, anti-inflammatory activity with a pro-tumor role (M2-line; CD163+ or CD206+), although this distinction represents the extremes of a much broader spectrum of activation [68]. The cytokines that drive macrophages towards their inflammatory function the most are IL-2, IFN-γ, and TNF-α; however, other cytokines are present inside tumors, such as IL-4, IL-10, and IL-13, which lead macrophages to be more anti-inflammatory. In general, their role is related to the ability to impair CD8+ T cell infiltration, secrete IL-6, IL-8, and IL-10, and produce matrix metalloproteinases (MMPs). All of these events contribute to the creation of an immunosuppressive microenvironment that supports tumor growth and metastasis [69]. High infiltration of TAMs within the TME is associated with a poor prognosis in many tumor types, and their targeting or remodeling is considered a promising strategy [66].
Neutrophils also have a role in tumors; their phenotype depends on the chemokine/cytokine composition of the TME, and they may have both antitumor (N1) and pro-tumor (N2) phenotypes. Their antitumor functions include the production of reactive oxygen species, but in the later stages of tumor development, there is high infiltration of N2 neutrophils that support tumor growth and progression via the degradation of arginine, an activator of T cells, or suppress IL-18 production [70].
The cells assigned to prime CD8 T cells are mainly tumor-infiltrating dendritic cells (DCs) that can scan and phagocytize tumor cells, process tumor-associated antigens, and present antigen-derived peptides within HLA class II molecules. Although their function is usually associated with tumor inhibition, the presence of some cytokines drives them toward a pro-tumor role. The presence of IL-6, IL-10, IDO, macrophage colony-stimulating factor, TGF-β1, prostaglandin E2, and VEGF can impair the ability of DC to present antigens and give them an immunosuppressive phenotype [71]. DC-based therapeutic strategies strive to inhibit pro-tumor cytokines or are directed to the creation of personalized vaccines [72].
The only lymphoid subset that can promote tumor progression is the regulatory CD4+ T lymphocyte subset (Treg), which directly secretes or facilitates the formation of immunosuppressive molecules (e.g., IL-10, adenosine) and modulates the APC function (e.g., via CTLA-4–CD80/86 interactions) [73].

4. TME Immune Profiling in Pediatric Solid Tumors

Tumor immune profiling has proven useful in adult cancer to predict responses to immunotherapy, at least in some tumor types. However, data obtained from adults are not always transferable to the pediatric setting, as childhood cancers are biologically different. A high tumor mutation burden, a predictor of response in adults, is uncommon in pediatric tumors [74]. On the other hand, peculiar genomic features driving neoantigen generation and the high thymic output observed in children, with the potential for the emergence of new T cells, warrant specific studies in pediatric cohorts (Figure 2). So far, a limited number of immune profile studies have been performed on childhood solid tumors to guide stratification and predict responses to immunotherapy (as summarized in Table 1).

4.1. Brain Tumors

Glioma and medulloblastoma are the most common types of solid tumors in children [75]. Gliomas are a group of primary brain tumors of glial tissues that include astrocytoma, oligodendroglioma, and glioblastoma. Among these, glioblastoma is the most commonly occurring malignant primary brain carcinoma [76]. Analysis of immune cell infiltration in pediatric gliomas demonstrated that myeloid cells are major components of the TME and show enrichment of CD8+ T cells and CD45+ leukocytes in low-grade gliomas compared to high-grade gliomas [77]. While the percentage of tumor-associated CD68+ macrophages is comparable across subgroups, diffuse midline gliomas have the lowest number of infiltrating CD8+ T cells and CD163+ macrophages, which contributes to their immunosuppressive phenotype [78].
Medulloblastoma accounts for 15% to 20% of pediatric CNS neoplasms. Therapy for medulloblastoma has evolved into well-accepted multimodal regimens that include maximal surgical resection, craniospinal irradiation (CSI), and polychemotherapy based on the use of etoposide, methotrexate, platin, and thiotepa, depending on the risk stratification, with curing being observed in up to 70% to 80% of patients according to the subtype [79]. A medulloblastoma subgroup displayed activation of sonic hedgehog signaling, which is implicated in suppressing the immune system and promoting an immunosuppressive tumor microenvironment. The sonic hedgehog subgroup was the most enriched in CD163+ macrophages, suggesting differential roles of TAMs in this pathological entity.
Comparing immune cell infiltration in the peritumoral area and tumor core of glioblastomas showed that CD163+ cells were more abundant in the tumor core, similarly to the higher expression of the immunosuppressive markers PD-L1, IDO, and TIGIT [80].
Table 1. Studies on the immunoprofiles of pediatric solid tumors.
Table 1. Studies on the immunoprofiles of pediatric solid tumors.
Tumor TypeTechniqueFindingsSample n.Ref.
Brain
tumors
FCEnrichment of CD8+ T cells and CD45+ leukocytes in low-grade gliomas compared to high-grade gliomas.
Lowest number of infiltrating CD8+ T cells and CD163+ macrophages in diffuse midline gliomas.
62[77,78]
FC; CALow macrophage or T-cell infiltration and PD-1.59[81]
FCHigher immune cell infiltration, more immunosuppressive (HLA-DR+ and CD64+) in pilocytic astrocytoma and ependymoma than in glioblastoma and medulloblastoma.37[82]
IHC and MicroarrayLow-level PD-L1 in medulloblastoma patients.44[83]
rtPCR, IHC, FACS, WBPD-L1 expressed in both a tumor and myeloid in a subgroup of ependymoma patients; PD-1 levels found in both CD4 and CD8 T cells76[84]
FACS, rtPCRHigh rate of infiltrating Tregs expressing CTLA-410[85]
IHCPD-L1 expression in glioblastoma samples (36%)14[86]
NBLWTSHigh TIL infiltrate markers and higher expression of PD-1 in MYCN-A tumors657[87]
RNAseq
(Systematic analysis)
High T cells, CD8+ T cells, T17, NKT cells, T1 cells, Treg cells, and DCs in high-risk neuroblastomas without MYCN-A408[88]
RNAseqHigh levels of macrophages, B cells, and inflammation genes in neuroblastomas without MYCN-A129[89]
IHCPD-L1 expression in neuroblastoma samples (14%): associated with inferior survival and a higher number of macrophages118[86]
FACSPD-1 on αβ and γδ T lymphocytes and NK cells in metastasis samples19[90]
IHCLow–moderate levels of PD-1 and PDL-131[91]
SarcomasIHCHigher percentage of granulocytes and fewer lymphocytes.
Increased expression of CTLA-4, CD14+HLA-DRlo/neg, and TNFRII on CD14+.
19[92]
IHCPD-L1 expression found in epithelioid sarcoma (100%), synovial sarcoma (53%), rhabdomyosarcoma (38%), and Ewing sarcoma (33%); correlated with worse overall survival82[93]
IHCLow–moderate level of PD-1 and absence of PDL-168[91]
CIBER
SORT
43% macrophages, mainly M2 type
23% T cells
197[94]
FACS,
IHC
Elevated CD14+ HLA-DRlo/neg cells, elevated CTLA-4+ T cells, and decreased CD4 T cells74[92]
rtPCR, FACS, IHCHigher expression of CTLA-4 in circulating CD4 and CD8 T lymphocytes6[95]
Renal tumorsIHCLow–moderate level of PD-1 and absence of PDL-125[91]
FC = flow cytometry; CA = cytotoxic assay; WTS = whole transcriptome sequencing; NBL: neuroblastoma; MYCN-A: MYCN-amplified; IHC: Immuno-histochemistry.
Ependymomas are primary tumors of the central nervous system that arise along the ventricular system and spinal cord. In pediatric patients, ependymomas comprise ~10% of primary central nervous system tumors, with the majority arising in the posterior fossa [96]. Pediatric ependymomas with higher infiltration of CD3+ and CD8+ T cells in the microenvironment at diagnosis had a longer progression-free survival, while elevated Forkhead box P3 regulatory T cells and CD68+ macrophages were correlated with a shorter survival rate [78].
Griesinger et al. showed differences in immune infiltration and the degree of immune suppression in biopsy samples from patients diagnosed with pilocytic astrocytoma, ependymoma, glioblastoma, and medulloblastoma [82]. Compared with glioblastoma and medulloblastoma, pilocytic astrocytomas and ependymomas had significant myeloid (characterized as CD45+CD11b+) and lymphocyte infiltration. Low levels of PD-1 were exhibited by the infiltrating immune cells, which suggested a more permissive TME for immunotherapy. Overall, most brain tumors are cold from an immunological point of view, with high myeloid signatures and low T cell infiltration, as well as with particularly aggressive forms such as diffuse intrinsic pontine glioma and medulloblastoma. However, there is evidence that some subtypes are more inflamed than others and may respond to immune checkpoint inhibitors [97]. It will be critical to perform further studies on brain tumors to understand the complexities of the immune microenvironment more deeply and to provide therapeutic decisions and better outcomes.

4.2. Neuroblastoma

Neuroblastoma is a neural crest-derived malignancy of the peripheral nervous system and is the most diagnosed extracranial solid tumor in infancy. It is characterized by clinical heterogeneity with a disease spectrum ranging from spontaneous regression without any medical intervention to treatment-resistant tumors with metastatic spread and poor patient survival [98]. Neuroblastoma patients are stratified into low-, intermediate-, and high-risk groups based on different parameters, including tumor histology, clinical stage, tumor cell ploidy, and MYCN oncogene amplification, which are present in 20–25% of the cases and are correlated with high-risk disease and poor prognosis [99]. Multimodal treatment is modulated according to risk stratification and is based on the use of surgical excision, chemotherapy, radiotherapy, hematopoietic stem cell transplantation, oral retinoic acid, and immunotherapy with anti-GD2 monoclonal antibodies, the latter being used both up front and in relapse.
MYCN amplification and ALK mutations promote tumor angiogenesis and vasculogenesis through the secretion of vascular endothelial cell growth factor (VEGF) by cancer cells and other cells residing in the TME, such as mesenchymal stromal cells (MSCs) and endothelial cells. In addition to these factors, the TME substantially contributes to the biology and outcome of neuroblastoma. It has been shown that patients with non-MYCN-amplified metastatic neuroblastomas had higher infiltration of TAMs than locoregional tumors did [100]. Moreover, infiltration with Th2-driven macrophages expressing CD163 and CD206 was also observed in a subset of high-risk neuroblastoma tumors with the deletion of chromosome 11q [100]. High telomerase activity and, consequently, replicative immortality could be controlled by the TME and, in particular, by inflammatory monocytes/macrophages through miR release, while the activation of STAT3 by IL-6 and sIL-6R produced by MSCs and TAMs induced the expression of several pro-survival proteins such as survivin, MCL-1, and Bcl-XL, which caused resistance to chemotherapeutic agents [101].
Several studies on immune profiling in neuroblastoma while also considering its risk classification have been published. A recent comprehensive study of deep RNA-seq for pretreatment diagnostic tumors from 129 high-risk and 21 low- or intermediate-risk patients revealed the complex microenvironment that may exist in high-risk neuroblastoma, and the patients could be layered into three groups based on their immune profiles. High-risk tumors that were not MYCN-amplified (clusters 3 and 4) had higher T-cell signatures and TCR heterogeneity and increased expression of immune checkpoints in comparison with those of high-risk MYCN-amplified tumors (cluster 1) [89]. Brohl et al. performed an immunogenomic analysis on a cohort of 657 tumor samples from 623 pediatric or young adult patients diagnosed with an extra-cranial solid malignancy, representing 14 diagnoses. They noticed that intra-tumoral clonal T-cell infiltration was correlated with patient survival in the cases of neuroblastoma and osteosarcoma [87]. From a systematic analysis of public RNA-seq data (TARGET) on the TME composition in neuroblastoma, it was found that CD8+ T cells, T-helper 17 cells, NKT cells, Tregs, and DCs were significantly more enriched in the group with high-risk neuroblastoma without MYCN amplification compared to the group with high-risk neuroblastoma with MYCN amplification (p < 0.05). Moreover, T follicular helper cells (TFHs) showed a significant positive association with survival in high-risk neuroblastoma without MYCN amplification [88].
CTLA4 (cytotoxic T-lymphocyte-associated protein 4) is a protein that plays a critical role in regulating immune responses. It is primarily expressed in T cells but can also be found in other immune cells. In neuroblastoma, CTLA4 expression has been detected in both tumor cells and immune cells within the tumor microenvironment. A study by Kushner et al. [102] demonstrated that neuroblastoma tumor cells expressed CTLA4, and higher levels of CTLA4 expression were associated with poorer patient outcomes. The study also showed that infiltrating immune cells in the tumor microenvironment, such as T cells and macrophages, expressed CTLA4, suggesting a potential role for CTLA4 in regulating the immune response to neuroblastoma.
With a better knowledge of the contribution of the TME to the progression of neuroblastoma and of its mechanisms, clinical trials testing TME-directed agents have been initiated; these have targeted TME cells that contribute to a pro-tumorigenic environment, signaling pathways of crosstalk between tumor cells and the TME, or cancer cells through immunotherapy.
Moreover, the study of the TME’s immunosuppressive features in this type of tumor has prompted research groups to explore techniques such as repolarization through mesenchymal stromal cell (MSC) delivery systems [103]. By studying immune populations, researchers have also been able to identify the resistance mechanism of Celyvir viral oncolytic therapy, which is mediated by T-cell exhaustion induced by intratumoral myeloid cells [104].

4.3. Sarcoma Family Tumors

Sarcomas are a heterogeneous group of tumors that can arise in bone or soft tissues around the body. Together, they account for about 10% of pediatric cancers [105]. Osteosarcoma, Ewing sarcoma, and rhabdomyosarcoma are the most common pediatric sarcomas.
Osteosarcoma is a high-grade primary skeletal malignancy characterized by spindle cells of mesenchymal origin depositing an immature osteoid matrix. With an annual incidence rate of 3.1 cases per million in the US, osteosarcoma accounts for less than 1% of all newly diagnosed cancers in adults and 3–5% of those in children, but it is the most common primary malignancy in adolescents besides leukemia and lymphoma [106]. Alveolar rhabdomyosarcoma and embryonal rhabdomyosarcoma are the most common soft tissue sarcomas, accounting for about 5% of childhood cancers [107]. Ewing’s sarcoma represents a rare, highly malignant disease, with most patients harboring a priori micro metastases, since, without systemic therapy, over 90% of patients die from disseminated disease [108].
Compared with other cancer types, osteosarcoma exhibits an immune-active phenotype characterized by increased mean enrichment of transcripts for immune cell infiltration [106]. Enrichment scores for some leukocyte populations, such as TFHs, DCs, neutrophils, macrophages, and monocytes, were associated with significantly improved prognosis, while B cell and gamma delta T-cell enrichment was associated with significantly worse survival in this cancer type [88]. Conversely, the most abundant cells in the TME of Ewing’s sarcoma were immunosuppressive M2-type macrophages, and increased numbers predicted a shorter event-free survival (EFS) [94]. Hingorani et al. studied the immune population present in the bloodstream of pediatric osteosarcoma and Ewing sarcoma patients and found an increased expression of CTLA-4 in both CD4+ and CD8+ T cells, together with a population of CD14(+) HLA-DR(lo/neg) immunosuppressive monocytes, which were correlated with advanced disease [92]. Looking at tumor tissue, they found massive infiltration of CD14+ monocytes in osteosarcoma compared to Ewing sarcoma but found limited T cell infiltration [92]. A study by Contardi et al. found that CTLA4 was also expressed on osteosarcoma tumor cells from six primary specimens that were examined [109], although the role of this molecule in tumor cells remains to be ascertained [109]. MSCs have been utilized in osteosarcoma to carry an oncolytic virus (O-Ad) along with G-CSF, leading to increased intratumoral TILs (tumor-infiltrating lymphocytes) and subsequent tumor reduction in in vivo experiments with mice [110].

4.4. Renal Tumors

Renal tumors in children include nephroblastoma (or Wilms tumor), which originates from nephrogenic progenitor cells from embryonic kidneys, and other rarer cancer types. The outcome for Wilms tumor is excellent for the majority of patients, but aggressive subtypes are challenging to treat and have a poorer prognosis, with a survival rate of approximately 50% or lower [111]. Data from the literature suggest that Wilms tumor is an immune-engaged tumor. An immune infiltrate analysis showed that CD8 and CD4 T cells were localized in a tumor and exhibited an activated phenotype [112], with the presence of activated CD8 T cells correlating with positive outcomes [113]. However, the TME may include immunosuppressive cells such as Tregs and increased plasmacytoid DCs. A high density of M2 macrophages within the TME was correlated with shorter overall survival and unfavorable histology [114], and the presence of immunosuppressive cytokines—in particular, TGFβ expression—was correlated with invasion/metastasis and disease progression [115]. Regarding other renal tumors, conventional and unconventional T cells were observed to infiltrate pediatric papillary renal cell carcinoma (PRCC) tumors and express CD1d, which presents potential therapeutic avenues [116].
Upregulation of PD-L1 is observed in 14–29% of Wilms tumors [117,118], and it is correlated with poor prognosis in aggressive subtypes, with a higher risk of recurrence in the case of favorable histology, independent of tumor stage [119]. Although a limited number of cases have been described, 50% of rhabdoid tumors show membranous expression of PD-L1 in 10–70% of tumor cells, with over 50% displaying high levels (>2/HPF) of tumor-infiltrating lymphocytes expressing PD-1 at levels ranging from 10 to 60%, which correlated significantly with tumor PD-L1 staining [120].

4.5. Retinoblastoma

Retinoblastoma is a rare intraocular malignancy representing approximately 3–4% of all pediatric malignancies [121]. Retinoblastoma typically develops in children under 5 years of age, and early diagnosis and prompt treatment can lead to a high cure rate. Late diagnosis, advanced clinical stage, and late age at presentation are the main risk factors for tumor-related mortality [122,123]. Enucleation is inevitable for tumors in the advanced group, despite the use of improved therapies, such as neoadjuvant chemotherapy [124].
The TME of retinoblastoma contains a range of immune cells, such as dendritic cells, monocytes, macrophages, and T-lymphocytes [125]. Studies have shown that decreased retinoblastoma cell proliferation is linked to increased immune cell infiltration [125]. Mao et al. identified two immunological subgroups of retinoblastoma based on the immune profiles of 28 types of immune cells. These subgroups of patients had different clinical characteristics and gene expression profiles [126]. By studying the distinct DNA methylation patterns between the two subgroups, Mao et al. found that immune cell infiltration was related to retinoblastoma migration and metastatic progression [126]. An integrative single-cell transcriptome and whole-exome sequencing analysis of retinoblastoma patients revealed that the TME in retinoblastoma was composed of tumor-associated macrophages (TAMs), astrocyte-like cells, and cancer-associated fibroblasts [127]. These TAMs created an immunosuppressive environment and could regulate tumor cells through specific signaling pathways. Chemotherapy modified the retinoblastoma microenvironment, as it was found to reorient the TME from an anergic state to an active, CD8+, PD-L1+ hot state [128].

4.6. Hepatoblastoma

Hepatoblastoma is a pediatric liver cancer that mainly occurs in the first three years after birth. It is characterized by β-catenin and Yap1 activation and overexpression, which may be involved in its pathogenesis. Despite an overall survival rate of up to 80%, hepatoblastoma remains a challenging disease, particularly in patients with advanced disease or poor prognostic factors. Recent studies have shed light on the immune modulation of hepatoblastoma patients [129]. Guo et al. found that children with hepatoblastoma had more NK cells and highly expressed killer cell immunoglobulin-like receptors, a protein that inhibits the cytotoxicity of NK cells, resulting in the immune escape of tumors [130]. Taurine Up-Regulated 1, an onco-lncRNA, mediates the infiltration of pro-tumor immunocytes in hepatoblastoma patients carrying the CTNNB1 mutation [131]. Methylation and epigenetic changes also influence the immune microenvironment in hepatoblastoma [132].

5. The Role of Immunomodulating Agents on TME

The immune response to cancer within the TME is regulated by a network of cells that secrete activating and inhibitory molecules. The final response derives from the net interactions within the network and can be modulated through therapeutic agents.
A crucial role is played by immune checkpoints (ICs), which are trans-membrane proteins expressed by immune cells that regulate the extent of a response. Among the ICs, those that have been more extensively studied are cytotoxic T-lymphocyte-associated antigen-4 (CTLA-4) and programmed cell death receptor 1 (PD-1), as well as its ligands PD-L1/2, but other molecules have also been investigated for their potential clinical use, such as lymphocyte-activating antigen-3 (LAG-3), T cell immunoglobulin and mucin-domain containing-3 (TIM-3), T cell immune receptor with Ig and ITIM domains (TIGIT), B7-H3, and indolamine dioxygenase (IDO) [54]. The development of ICIs represents an important milestone in the therapeutic control of cancer due to their ability to potentiate immune responses against tumor cells. In addition to ICIs, a few targeted therapies, including specific monoclonal antibodies directed to pediatric-tumor-associated antigens, have also been developed. One example is the chimeric monoclonal anti-GD2 antibodies dinutuximab and dinutuximab beta, which are considered to be the standard of care in the first-line treatment of children with high-risk neuroblastoma after induction chemotherapy and autologous hematopoietic stem cell transplantation, and they are used also to treat relapsed or refractory neuroblastoma patients with or without minimal residual disease positivity [133]. GD2 has restricted expression in normal tissues but is overexpressed across a wide range of tumors and has been discussed as a target in rare and aggressive pediatric malignancies such as Ewing’s sarcoma, osteosarcoma, and H3K27M-mutant diffuse midline glioma. However, anti-GD2 MoAb use in pediatric cancers other than neuroblastoma has been, so far, very limited [134].
The modulation of ICs is effective only in the presence of immune effector cells in the TME, but pediatric solid tumors often show a paucity of T cell infiltrate. For this reason, in addition to ICIs, adoptive cell therapy with tumor-directed natural T cells or gene-modified tumor-targeted cellular products may have an important role in cancer control. These novel therapeutics, which were proven effective in the control of hematologic cancer, are also being tested in the setting of pediatric solid tumors [135].

5.1. Immune Checkpoint Inhibitors in Pediatric Solid Tumors

ICIs reverse the immune effector cell inhibition mediated by tumor cells and the TME so that an immune response can be mounted against cancer [136]. In adult patients, a better response to ICIs correlates with the presence of effector T cells and higher tumor mutational burden (TMB) [137]. However, pediatric tumors generally present very low TMB due to the presence of few driver mutations, as well as their low immunogenicity and antigenicity [138]. Moreover, pediatric tumors have low TIL numbers and limited expression of PD-1, PD-L1, and PD-L2 [91]. TIL function and infiltration are impaired by the immunosuppressive environment created by MDSCs, tumor-associated macrophages, tumor-associated fibroblasts, and Tregs [139].
CTLA-4, the first immune checkpoint receptor to be clinically targeted, is expressed on the surface of active T cells and provides an inhibitory signal for T cells [136,140,141]. The interaction of the T cell receptor (TCR)/CD3 complex, the CD28 co-stimulatory signal, and the co-inhibitory signal CTLA-4 is necessary for normal T cell activation and subsequent effector control. To dampen T cell activation, CTLA-4 outcompetes CD28 for the shared B7 molecule ligands through a higher binding affinity. In cancer cells, the expression of CTLA4 is induced to evade T cell antitumor activity, and its blockade potentiates active immune responses against tumor cells and decreases immunosuppression by Tregs [140,141]. In pediatric tumors, the expression of CTLA-4 was detected in glioblastoma, neuroblastoma, and sarcomas, particularly in osteosarcoma, suggesting its potential role as a target for immunotherapy [92,95,102,109]. Preclinical studies have shown that treatment with CTLA4 in combination with other therapies, such as radiotherapy and targeted therapies, such as those with anti-GD2 MoAbs or with anti-PD-1, yields better results in terms of overall survival and reduction of tumor growth in a human model of neuroblastoma [142] and glioblastoma [143], as well as in an orthotopic model of glioblastoma in which the greatest curative effect was obtained using a combination of anti-CTLA-4 and anti-PD-1 antibodies in addition to oncolytic viruses [144]. This success was due to macrophage polarization and the increased ratio between infiltrating effector T cells and Tregs [144]. Two humanized anti-CTLA-4 antibodies, Ipilimumab and Tremelimumab, have been approved as therapeutic options for the treatment of cancer [145,146]. In a pediatric setting, Ipilimumab treatment was studied in a phase I trial in 33 patients under the age of 21 who had advanced solid tumors, such as melanoma, bladder, and renal cancer, neuroblastoma, and sarcoma (Table 2). The spectrum of immune-related adverse events was similar to that described in adults, although it was frequently noticeable after a single dose. Despite the absence of objective tumor regression, stabilization of disease was registered in four patients, and a higher overall survival rate was observed in subjects with immune-related toxicities [147].
A different immune checkpoint pathway includes PD-1 and its ligands PD-L1 and PD-L2. PD-1 is a protein that belongs to the CD28 superfamily and is a key regulator of programmed cell death in lymphocytes, so it has a critical role in maintaining peripheral tolerance [153]. Upon activation, PD-1 is expressed in different T cell subsets, B lymphocytes, NK cells, some myeloid cells, and cancer cells [153]. In the TME, PD-1 is also highly expressed in Tregs, increasing their activity and proliferation. PD-L1 and PD-L2, which are ligands of PD-1, are members of the B7 family; while PD-L1 is found in different lymphoid organ resident cells and many non-hematopoietic tissues, PD-L2 expression is limited to APCs [154]. The interaction of PD1 with PD-L1 hampers T cell activation through the suppression of T cell proliferation, survival, and cytokine secretion, causing the inhibition of antitumor lymphocytes that are present in the TME [154]. Most tumor PD-1/PD-L1 expression studies were performed on adult specimens, and few studies were directly performed on pediatric solid tumor biopsies. The observed expression of PD-1 and PD-L1 was variable according to different reports. Expression of PD-L1 was observed in alveolar rhabdomyosarcoma (86%), rhabdomyosarcoma (2–50%), neuroblastoma (14–72%), Ewing sarcoma (0–57%), osteosarcoma (5–47%), and glioblastoma multiforme (36%) [155]. A higher expression of PD-L1 was correlated with a worse prognosis [84,86,93].
The use of the anti-PD-1 antibodies Pembrolizumab and Nivolumab and the anti-PD-L1 antibodies atezolizumab, avelumab, and durvalumab has so far been mostly limited to adult solid tumors [156,157]. Despite encouraging safety and efficacy in pediatric hematological cancer, the results in pediatric solid cancer are, so far, disappointing. A phase I/II study of nivolumab as a single agent in children and young adults with lymphomas or R/R ST showed no objective responses in ST, with 33% and 50% disease stabilization in sarcomas and neuroblastoma, respectively, and grade 3–4 toxicities at a rate of 36% [150]. In another phase I/II study that is still ongoing (NCT02992964), two partial responses of a long duration were observed in pediatric patients with hypermutated ST [152]. A phase I/II trial of pembrolizumab described eight partial remissions in R/R ST, with grade 3–5 toxicities at a rate of 8% [149]. Regarding anti-PD-L1 agents, a phase I/II study of atezolizumab in pediatric patients and young adults with refractory or relapsed solid tumors showed partial remission in 1/75 patients treated for ST, with a good toxicity profile [148]. Likewise, a phase I study of avelumab described four stabilizations of disease in 21 patients treated for R/R ST, without grade 4–5 adverse events [158].
As the use of single agents has not been encouraging in pediatric ST, the prevention of immune escape through dual checkpoint blockage has been attempted. In an implanted mouse model of metastatic osteosarcoma, treatment with anti-PD-L1 antibody reduced the expression of PD-L1, increased the expression of CD80/CD86 in tumor cells, and increased the expression of CTLA-4 in tumor-infiltrating CD8+ T cells. Additionally, 50% of treated mice experienced complete protection from metastasis and T cell memory protection against future tumor inoculation following PD-1/CTLA-4 signaling inhibition with combined therapy [159]. As observed with anti-CTLA4 and anti-PD-1, better results were obtained in animal models when more than one immune checkpoint was targeted [160,161,162] or when other immune activation mediators, such as agonists of Toll-like receptor 3 (TLR3), TGFbeta, or standard radiation or chemotherapy, were associated [163,164,165].
Combinations of CTLA-4 and PD-1/PD-L1 pathway blockages are actively being investigated in pediatric patients [166]. A phase II study conducted in 55 pediatric and young adult patients with R/R ST showed four partial remissions in the young adult cohort and four disease stabilizations in children, with 11% showing dose-limiting toxicities, demonstrating the good tolerability of ICI combinations [151]. However, a phase I/II randomized trial comparing nivolumab alone with nivolumab + ipilimumab in pediatric patients with R/R solid tumors of the central nervous system failed to demonstrate an advantage for the ICI association [167]. Further trials are underway to test the feasibility and efficacy of ICI combinations in association with standard chemotherapy, radiotherapy, or other immune-modulating agents (Table 2).

5.2. ATMPs in Pediatric Solid Tumors

Several ATMPs are under investigation in clinical trials against solid tumors, but only a few have involved pediatric patients [168,169]. Most of these therapies are based on the use of T cells, but NK cells and monocytes are gaining increasing attention [170,171]. For purposes of this review, we shall focus our attention on T cell products and just briefly mention NK cells and monocyte ATMPs. T cell therapies for solid tumors can be classified into two broad categories: somatic cell therapies, with tumor-infiltrating lymphocytes (TILs) as the main subtype, and gene therapies, which are mainly obtained through the transfer of antigenic specificity through chimeric antigen receptors (CARs) or natural T cell receptors (TCRs) isolated from high-avidity T cells that recognize cancer antigens [169]. Somatic cell therapy with TILs has shown promising results in solid tumors [172]. However, at present, clinical trials are ongoing for adult solid tumor patients but not in the pediatric setting, which is probably due to the scarce presence of TILs within the pediatric TME. Somatic cell therapy with virus-specific T cells was employed in patients with virus-associated hematologic and solid tumors, such as Epstein–Barr-virus-related nasopharyngeal carcinoma or human-papillomavirus-related carcinomas [169,170,171,172,173].
TCR therapy trials have mostly targeted overexpressed self/tumor antigens that are also expressed by healthy adult cells, such as gp100 and Melan-A/MART-1, or oncofetal antigens that are present on healthy cells exclusively during fetal development and are ectopically expressed in tumors, such as melanoma antigen E or NY-ESO-1 [169]. Early-phase clinical trials showed some good partial responses, but dose-limiting on-target, off-tumor toxicity was an important limitation [174,175,176,177]. NY-ESO-1 expression was also studied in different pediatric tumors together with other cancer–testis antigens [178], but no clinical trials are presently under investigation for pediatric patients.
The use of CAR-T cells for the treatment of pediatric cancer patients has been steadily increasing. Despite the success stories in the control of pediatric hematological cancers, the efficacy of CAR-T in the setting of solid tumors has been hampered by the complex TME network, which may favor immune escape and induce therapeutic resistance [179].
CAR-T studies focusing on malignant solid tumors are limited in number in comparison to those on hematological malignancies, and very few have targeted the pediatric population (Table 3).
The first pediatric solid tumor targeted with CAR-T cells was neuroblastoma. N cells, as well as glioma, melanoma, and sarcoma cells, uniformly express the ganglioside GD2, which is the target of monoclonal-antibody-based therapeutic interventions [133]. In recent years, genetically engineered T cells modified with CARs specific to GD2 antigen have been produced and evaluated in clinical trials [181,183,184,185,186,187]. Autologous virus-specific T cells that expressed anti-GD2 CAR were used to treat neuroblastoma patients in an early clinical trial. Despite the use of a first-generation CAR construct and CAR-T cell infusion without lymphodepletion, objective responses were observed, with three patients reaching CR without dose-limiting toxicities [180,181]. A subsequent trial in the same group using a third-generation GD2–CAR and modified T cell administration in the absence or presence of lymphodepletion did not show an improvement in terms of efficacy, as the treatment proved safe, but disease stabilization was observed in only four patients after CAR-T therapy [183]. Similar results were obtained in a phase I trial that treated 12 patients with second-generation GD2–CAR-T cells administered with lymphodepletion [184]. Recently, a phase I/II study conducted in 27 patients with R/R neuroblastoma that employed third-generation GD2–CAR-T cells and lymphodepleting chemotherapy described very encouraging results, with more than 60% showing objective responses and an event-free survival of 36% at 3 years in the absence of DLTs [185]. An ongoing trial in R/R neuroblastoma patients with GD2–CAR-NKT cells co-expressing IL-15 administered after lymphodepletion showed safety and good efficacy, as in one of the first three patients treated with dose level 1, a PR was observed, with no DLTs [186]. GD2–CAR-T cells are also being used to treat children and adults with GD2-positive gliomas [187] and osteosarcoma (NCT03721068), with some clinical benefit.
Human epidermal growth factor receptor 2 (HER2)/Neu antigen-directed CAR-T cells are being tested in the settings of glioma, osteosarcoma, and nephroblastoma. Even in the presence of low-level HER2 expression, HER2–CAR T cells effectively identify and destroy cancer cells [188] and have proved effective in a preclinical osteosarcoma model [189]. An ongoing phase I/II study of second-generation HER2–CAR-T cells conducted in 19 patients with HER2-positive sarcomas showed two CRs and some disease stabilizations with evidence of tumor necrosis in patients with osteosarcoma without DLTs [182]. Another member of the ErbB family of receptor tyrosine kinases, EGFR (or HER1), is also being tested in a phase I trial of second-generation EGFR-CAR-T cells in children and young adults with EGFR-positive solid tumors. Preliminary results in the first 11 patients treated so far demonstrated mixed responses on day 28 after administration and tolerated additional CAR-T infusion without dose-limiting toxicity [190].
Among other target antigens that were developed and tested in preclinical models, glypican 3 (GPC3) and B7H3 are being tested in clinical trials on pediatric solid tumors (Table 3). Two phase I trials are examining the safety of B7H3–CAR-T in children and young adults with B7H3-positive R/R solid tumors. For one of these studies, preliminary results are available, showing three stabilizations of disease with a partial metabolic response and without DLTs in the nine subjects treated so far [191].
The efforts to find the best targets for immune cells directed to the treatment of pediatric solid tumors have also been paralleled by studies aimed at increasing the persistence and expansion of cell products in vivo through the co-expression/secretion of homeostatic cytokines or TME-modulating factors or at conferring resistance to immunosuppressive molecules [169].

6. TME Modulation Using NK Cells or Macrophages

NK cells are effectors of innate immunity and enhancers of adaptive immune responses through cytokine secretion; in addition, they play a role in antitumor immunity alone or in combination with antibodies through antibody-dependent cell-mediated cytotoxicity. Thanks to their highly cytotoxic, non-MHC-restricted effector function, NK cells have high potential for development as immunotherapies against cancer and have, thus, been tested in clinical trials as alternative ATMPs—either unmanipulated or gene-modified [192]. In preclinical studies, Ewing sarcoma, rhabdomyosarcoma, and osteosarcoma cells were demonstrated to be sensitive to killing by NK cells [193]. Clinical trials have been conducted in hematologic and solid tumors, and they have mainly enrolled adult patients. The results of early trials showed good tolerability but limited efficacy; subsequent trials endeavored to increase efficacy by coupling NK-based ATMPs with ICIs or other agents, but the results are not yet available [194]. NK-cell-based CAR therapies represent a promising alternative to the limitations of CAR-T, since clinical-grade off-the-shelf products can be generated from multiple allogeneic sources with a favorable safety profile and low risk of GvHD, neurotoxicity, and CRS. Most clinical trials have been conducted for hematologic malignancies in adult cohorts [194], although studies of solid tumors are ongoing [192].
TAMs have a tumor-promoting role within the TME; thus, strategies for counteracting their effects are being investigated [195]. In addition to blocking the recruitment of TAMs or depleting them [196], macrophages can be re-polarized to increase tumor cell phagocytosis or exhibit an inflammatory phenotype. An alternative to TAM alteration/reprogramming is the hypothesis of educating macrophages through in vitro culture and employing them in vivo to repopulate the TME and alter the pro-tumor environment. Early trials of polarized myeloid-based ATMP had limited efficacy but did not show dose-limiting toxicities [195]. More recently, macrophage engineering has been proposed as a tool to obtain more potent antitumor activity. CAR–macrophages targeting HER2 have been demonstrated to reduce tumor growth in animal models [197,198] and are now being tested in a phase I study for HER2-expressing solid tumors in adults alone or in association with pembrolizumab (NCT04660929).

7. Combined Approaches

The clinical benefit of ICIs or ATMPs alone in pediatric solid tumors has generally been limited, which is likely due to the peculiar features of the TME, including the scarcity of TILs, which outbalances the immune network in favor of an immunosuppressive environment. Providing more effective tumor-specific T cells while modulating the immunosuppressive fractions of the TME with ICIs or with other repolarizing interventions may be a key factor in obtaining better clinical results in pediatric solid tumors.
For this reason, an effort to combine different agents to increase efficacy while reducing toxicity is ongoing. The administration of ICIs in patients with lymphomas that are refractory or relapsing after CD19–CAR-T cells has been shown to provide clinical benefit and revert the exhausted profile of circulating CAR and non-CAR T-cells [199]. Studies addressing a combined approach in pediatric solid tumors are not yet available but could provide a needed breakthrough.
The synergistic effect observed with combined CAR-T cells and ICIs has led to the development of armored CAR-T cells secreting checkpoint inhibitors. The secretion of PD-1 single-chain variable fragment (scFv) by PD-1-expressing CAR-T cells enhanced T cell proliferation and reduced PD-1 expression in vitro. Additionally, anti-PD-1 secretion was seen to enhance CAR-T cell antitumor function in a mouse model of gastric cancer [200]. Similar effects of anti-PD-1 scFv secretion by CAR T-cells were reported in another study, which showed increased T cell cytokine production and proliferation in vitro, while in vivo, there was enhanced antitumor efficacy and CAR-T cell accumulation in the TME [201]. Several clinical trials with ICI-expressing CAR-T cells are currently recruiting adult patients and will hopefully also be available for pediatric patients.
Efforts are needed not only to combine ICIs and ATMPs but also to find the best schedule for delivering conventional therapies and novel biologicals. Toward this aim, multicenter efforts are critical in designing clinical trials in the pediatric setting.

8. Conclusions

Immunotherapeutics are changing the outcomes of adult hematologic and solid tumors. Although they have been successfully employed in pediatric hematologic cancer, their use in pediatric solid tumors has met with limited success, and for this reason, excluding a few exceptions, immunotherapy has been reserved to resistant/relapsed cases so far. The challenges met so far are due to the peculiar characteristics of the pediatric tumor microenvironment, the limited knowledge of the TME in childhood cancer due to the rarity of many pediatric tumors, the lack of reliable biomarkers and clinical assays for informing treatment decisions, and the difficulties in conducting clinical trials in a pediatric setting. One such challenge is antigen escape due to the loss or mutation of the target antigen, which could be addressed through the use of pharmaceutical strategies that upregulate the expression of cell-surface target antigens on cancer cells or through the use of dual-target strategies. Furthermore, poor T cell trafficking and persistence contribute to the lack of success of immunotherapies against solid tumors. The therapeutic strategy that is most likely to succeed in pediatric patients is a multimodal approach that combines chemotherapy and targeted therapies with the use of cell therapy to recruit adaptive tumor-specific T cells and/or NK cells to the TME while modulating their function and neutralizing the role of suppressor cells through ICIs and other agents. Immunoprofiling may help in the identification of immune signatures that are predictive of response, which are currently lacking in children.
A deeper understanding of the TME can help expand therapeutic options, uncover causes of resistance, and favor the development of innovative functional models for testing therapeutic agents [202,203,204]. Moreover, insight into the composition of the TME in pediatric cancer may suggest more specific approaches to the modulation of the immunosuppressive tumor environment and provide a rational basis for different associations of biological therapies, as well as their integration with conventional anti-cancer treatments, to achieve a greater impact on the outcomes of pediatric solid tumors.

Funding

This work was supported by the Ministry of Health (grants from Ricerca Corrente number 08074522 to G.R., 08069119 to P.C., 08045823 to M.Z., 08067619 and 08067615 to P.P., and grant RF-2011-02351315 to P.P.), as well as a grant from Fondazione Just Italia (P.C.).

Conflicts of Interest

The authors have no conflicts of interest to declare.

Abbreviations

AcronymDefinitionAcronymDefinition
APCAntigen-presenting cellNY-ESO-1New York esophageal squamous cell carcinoma 1
ATMPAdvanced-therapy medicinal product PD-1Programmed cell death protein 1
CAR-TChimeric antigen receptor–T cellPD-L1Programmed death ligand 1
CSCCancer stem cellscFvSingle-chain variable fragment
CTLA-4Cytotoxic T-lymphocyte-associated protein 4TAMTumor-associated macrophage
CTLsCytotoxic T lymphocytesTCRT cell receptor
ECMExtracellular matrixTFHT follicular helper
EGFEpidermal growth factor TGFTransforming growth factor
EGFREpidermal growth factor receptorTIGITT-cell immunoreceptor and ITIM domains
HER2Human epidermal growth factor receptor 2TILTumor-infiltrating lymphocyte
ICIImmune checkpoint inhibitorTim-3T cell immunoglobulin and mucin domain 3
IDOIndolamine-2,3-dioxygenaseTMBTumor mutational burden
LAG-3Lymphocyte activation gene-3TMETumor microenvironment
MDSCMyeloid-derived suppressor cellTNFTumor necrosis factor
MMPMatrix metalloproteaseTregRegulatory T cell
MYCNN-myc proto-oncogeneVEGFVascular endothelial growth factor

References

  1. Bonini, C.; Mondino, A. Adoptive T-Cell Therapy for Cancer: The Era of Engineered T Cells. Eur. J. Immunol. 2015, 45, 2457–2469. [Google Scholar] [CrossRef] [PubMed]
  2. Mantovani, A.; Allavena, P.; Sica, A.; Balkwill, F. Cancer-Related Inflammation. Nature 2008, 454, 436–444. [Google Scholar] [CrossRef] [PubMed]
  3. Topalian, S.L.; Weiner, G.J.; Pardoll, D.M. Cancer Immunotherapy Comes of Age. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 2011, 29, 4828–4836. [Google Scholar] [CrossRef]
  4. Maude, S.L.; Laetsch, T.W.; Buechner, J.; Rives, S.; Boyer, M.; Bittencourt, H.; Bader, P.; Verneris, M.R.; Stefanski, H.E.; Myers, G.D.; et al. Tisagenlecleucel in Children and Young Adults with B-Cell Lymphoblastic Leukemia. N. Engl. J. Med. 2018, 378, 439–448. [Google Scholar] [CrossRef]
  5. Byron, S.A.; Hendricks, W.P.D.; Nagulapally, A.B.; Kraveka, J.M.; Ferguson, W.S.; Brown, V.I.; Eslin, D.E.; Mitchell, D.; Cornelius, A.; Roberts, W.; et al. Genomic and Transcriptomic Analysis of Relapsed and Refractory Childhood Solid Tumors Reveals a Diverse Molecular Landscape and Mechanisms of Immune Evasion. Cancer Res. 2021, 81, 5818–5832. [Google Scholar] [CrossRef]
  6. Ferrari, A.; Brecht, I.B.; Gatta, G.; Schneider, D.T.; Orbach, D.; Cecchetto, G.; Godzinski, J.; Reguerre, Y.; Bien, E.; Stachowicz-Stencel, T.; et al. Defining and Listing Very Rare Cancers of Paediatric Age: Consensus of the Joint Action on Rare Cancers in Cooperation with the European Cooperative Study Group for Pediatric Rare Tumors. Eur. J. Cancer 2019, 110, 120–126. [Google Scholar] [CrossRef]
  7. Dome, J.S.; Rodriguez-Galindo, C.; Spunt, S.L.; Santana, V.M. Pediatric Solid Tumors. In Abeloff’s Clinical Oncology; Elsevier: Amsterdam, The Netherlands, 2020; pp. 1703–1747.e11. ISBN 978-0-323-47674-4. [Google Scholar]
  8. Lawrence, M.S.; Stojanov, P.; Polak, P.; Kryukov, G.V.; Cibulskis, K.; Sivachenko, A.; Carter, S.L.; Stewart, C.; Mermel, C.H.; Roberts, S.A.; et al. Mutational Heterogeneity in Cancer and the Search for New Cancer-Associated Genes. Nature 2013, 499, 214–218. [Google Scholar] [CrossRef]
  9. Vogelstein, B.; Papadopoulos, N.; Velculescu, V.E.; Zhou, S.; Diaz, L.A.; Kinzler, K.W. Cancer Genome Landscapes. Science 2013, 339, 1546–1558. [Google Scholar] [CrossRef]
  10. Blattner-Johnson, M.; Jones, D.T.W.; Pfaff, E. Precision Medicine in Pediatric Solid Cancers. Semin. Cancer Biol. 2022, 84, 214–227. [Google Scholar] [CrossRef] [PubMed]
  11. Ma, X.; Liu, Y.; Liu, Y.; Alexandrov, L.B.; Edmonson, M.N.; Gawad, C.; Zhou, X.; Li, Y.; Rusch, M.C.; Easton, J.; et al. Pan-Cancer Genome and Transcriptome Analyses of 1,699 Paediatric Leukaemias and Solid Tumours. Nature 2018, 555, 371–376. [Google Scholar] [CrossRef] [PubMed]
  12. Meitar, D.; Crawford, S.E.; Rademaker, A.W.; Cohn, S.L. Tumor Angiogenesis Correlates with Metastatic Disease, N-Myc Amplification, and Poor Outcome in Human Neuroblastoma. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 1996, 14, 405–414. [Google Scholar] [CrossRef] [PubMed]
  13. Kreuter, M.; Bieker, R.; Bielack, S.S.; Auras, T.; Buerger, H.; Gosheger, G.; Jurgens, H.; Berdel, W.E.; Mesters, R.M. Prognostic Relevance of Increased Angiogenesis in Osteosarcoma. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2004, 10, 8531–8537. [Google Scholar] [CrossRef] [PubMed]
  14. Yudoh, K.; Kanamori, M.; Ohmori, K.; Yasuda, T.; Aoki, M.; Kimura, T. Concentration of Vascular Endothelial Growth Factor in the Tumour Tissue as a Prognostic Factor of Soft Tissue Sarcomas. Br. J. Cancer 2001, 84, 1610–1615. [Google Scholar] [CrossRef] [PubMed]
  15. Glade Bender, J.; Yamashiro, D.J.; Fox, E. Clinical Development of VEGF Signaling Pathway Inhibitors in Childhood Solid Tumors. Oncologist 2011, 16, 1614–1625. [Google Scholar] [CrossRef] [PubMed]
  16. Blavier, L.; Yang, R.-M.; DeClerck, Y.A. The Tumor Microenvironment in Neuroblastoma: New Players, New Mechanisms of Interaction and New Perspectives. Cancers 2020, 12, 2912. [Google Scholar] [CrossRef] [PubMed]
  17. Hawkins, A.G.; Pedersen, E.A.; Treichel, S.; Temprine, K.; Sperring, C.; Read, J.A.; Magnuson, B.; Chugh, R.; Lawlor, E.R. Wnt/β-Catenin–Activated Ewing Sarcoma Cells Promote the Angiogenic Switch. JCI Insight 2020, 5, e135188. [Google Scholar] [CrossRef]
  18. Diomedi-Camassei, F.; McDowell, H.P.; De Ioris, M.A.; Uccini, S.; Altavista, P.; Raschellà, G.; Vitali, R.; Mannarino, O.; De Sio, L.; Cozzi, D.A.; et al. Clinical Significance of CXC Chemokine Receptor-4 and c-Met in Childhood Rhabdomyosarcoma. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2008, 14, 4119–4127. [Google Scholar] [CrossRef]
  19. Zhang, M.; Zhang, X. Association of MMP-2 Expression and Prognosis in Osteosarcoma Patients. Int. J. Clin. Exp. Pathol. 2015, 8, 14965–14970. [Google Scholar]
  20. Zhou, J.; Liu, T.; Wang, W. Prognostic Significance of Matrix Metalloproteinase 9 Expression in Osteosarcoma: A Meta-Analysis of 16 Studies. Medicine 2018, 97, e13051. [Google Scholar] [CrossRef]
  21. Sugiura, Y.; Shimada, H.; Seeger, R.C.; Laug, W.E.; DeClerck, Y.A. Matrix Metalloproteinases-2 and -9 Are Expressed in Human Neuroblastoma: Contribution of Stromal Cells to Their Production and Correlation with Metastasis. Cancer Res. 1998, 58, 2209–2216. [Google Scholar]
  22. Jodele, S.; Chantrain, C.F.; Blavier, L.; Lutzko, C.; Crooks, G.M.; Shimada, H.; Coussens, L.M.; Declerck, Y.A. The Contribution of Bone Marrow-Derived Cells to the Tumor Vasculature in Neuroblastoma Is Matrix Metalloproteinase-9 Dependent. Cancer Res. 2005, 65, 3200–3208. [Google Scholar] [CrossRef]
  23. Bhowmick, N.A.; Chytil, A.; Plieth, D.; Gorska, A.E.; Dumont, N.; Shappell, S.; Washington, M.K.; Neilson, E.G.; Moses, H.L. TGF-Beta Signaling in Fibroblasts Modulates the Oncogenic Potential of Adjacent Epithelia. Science 2004, 303, 848–851. [Google Scholar] [CrossRef] [PubMed]
  24. Tang, D.; Yuan, Z.; Xue, X.; Lu, Z.; Zhang, Y.; Wang, H.; Chen, M.; An, Y.; Wei, J.; Zhu, Y.; et al. High Expression of Galectin-1 in Pancreatic Stellate Cells Plays a Role in the Development and Maintenance of an Immunosuppressive Microenvironment in Pancreatic Cancer. Int. J. Cancer 2012, 130, 2337–2348. [Google Scholar] [CrossRef] [PubMed]
  25. Fukumura, D.; Xavier, R.; Sugiura, T.; Chen, Y.; Park, E.C.; Lu, N.; Selig, M.; Nielsen, G.; Taksir, T.; Jain, R.K.; et al. Tumor Induction of VEGF Promoter Activity in Stromal Cells. Cell 1998, 94, 715–725. [Google Scholar] [CrossRef] [PubMed]
  26. Orimo, A.; Gupta, P.B.; Sgroi, D.C.; Arenzana-Seisdedos, F.; Delaunay, T.; Naeem, R.; Carey, V.J.; Richardson, A.L.; Weinberg, R.A. Stromal Fibroblasts Present in Invasive Human Breast Carcinomas Promote Tumor Growth and Angiogenesis through Elevated SDF-1/CXCL12 Secretion. Cell 2005, 121, 335–348. [Google Scholar] [CrossRef] [PubMed]
  27. LeBedis, C.; Chen, K.; Fallavollita, L.; Boutros, T.; Brodt, P. Peripheral Lymph Node Stromal Cells Can Promote Growth and Tumorigenicity of Breast Carcinoma Cells through the Release of IGF-I and EGF. Int. J. Cancer 2002, 100, 2–8. [Google Scholar] [CrossRef]
  28. Ito, K.; Nishida, Y.; Ikuta, K.; Urakawa, H.; Koike, H.; Sakai, T.; Zhang, J.; Shimoyama, Y.; Imagama, S. Overexpression of KIAA1199, a Novel Strong Hyaluronidase, Is a Poor Prognostic Factor in Patients with Osteosarcoma. J. Orthop. Surg. 2021, 16, 439. [Google Scholar] [CrossRef]
  29. Shi, K.; Wang, S.; Shen, B.; Yu, F.; Weng, D.; Lin, J. Clinicopathological and Prognostic Values of Fibronectin and Integrin Avβ3 Expression in Primary Osteosarcoma. World J. Surg. Oncol. 2019, 17, 23. [Google Scholar] [CrossRef]
  30. Linares-Clemente, P.; Aguilar-Morante, D.; Rodríguez-Prieto, I.; Ramírez, G.; de Torres, C.; Santamaría, V.; Pascual-Vaca, D.; Colmenero-Repiso, A.; Vega, F.M.; Mora, J.; et al. Neural Crest Derived Progenitor Cells Contribute to Tumor Stroma and Aggressiveness in Stage 4/M Neuroblastoma. Oncotarget 2017, 8, 89775–89792. [Google Scholar] [CrossRef]
  31. Henke, E.; Nandigama, R.; Ergün, S. Extracellular Matrix in the Tumor Microenvironment and Its Impact on Cancer Therapy. Front. Mol. Biosci. 2019, 6, 160. [Google Scholar] [CrossRef]
  32. Mintz, M.B.; Sowers, R.; Brown, K.M.; Hilmer, S.C.; Mazza, B.; Huvos, A.G.; Meyers, P.A.; Lafleur, B.; McDonough, W.S.; Henry, M.M.; et al. An Expression Signature Classifies Chemotherapy-Resistant Pediatric Osteosarcoma. Cancer Res. 2005, 65, 1748–1754. [Google Scholar] [CrossRef]
  33. Matsuoka, K.; Bakiri, L.; Wolff, L.I.; Linder, M.; Mikels-Vigdal, A.; Patiño-García, A.; Lecanda, F.; Hartmann, C.; Sibilia, M.; Wagner, E.F. Wnt Signaling and Loxl2 Promote Aggressive Osteosarcoma. Cell Res. 2020, 30, 885–901. [Google Scholar] [CrossRef]
  34. Al-Hajj, M.; Wicha, M.S.; Benito-Hernandez, A.; Morrison, S.J.; Clarke, M.F. Prospective Identification of Tumorigenic Breast Cancer Cells. Proc. Natl. Acad. Sci. USA 2003, 100, 3983–3988. [Google Scholar] [CrossRef]
  35. Guo, L.; Yan, T.; Guo, W.; Niu, J.; Wang, W.; Ren, T.; Huang, Y.; Xu, J.; Wang, B. Molecular Subtypes of Osteosarcoma Classified by Cancer Stem Cell Related Genes Define Immunological Cell Infiltration and Patient Survival. Front. Immunol. 2022, 13, 986785. [Google Scholar] [CrossRef]
  36. Batlle, E.; Clevers, H. Cancer Stem Cells Revisited. Nat. Med. 2017, 23, 1124–1134. [Google Scholar] [CrossRef] [PubMed]
  37. Visvader, J.E.; Lindeman, G.J. Cancer Stem Cells in Solid Tumours: Accumulating Evidence and Unresolved Questions. Nat. Rev. Cancer 2008, 8, 755–768. [Google Scholar] [CrossRef]
  38. de Sousa E Melo, F.; Vermeulen, L. Wnt Signaling in Cancer Stem Cell Biology. Cancers 2016, 8, 60. [Google Scholar] [CrossRef]
  39. Friedman, G.K.; Yancey Gillespie, G. Cancer Stem Cells and Pediatric Solid Tumors. Cancers 2011, 3, 298–318. [Google Scholar] [CrossRef] [PubMed]
  40. Garner, E.F.; Beierle, E.A. Cancer Stem Cells and Their Interaction with the Tumor Microenvironment in Neuroblastoma. Cancers 2016, 8, 5. [Google Scholar] [CrossRef]
  41. Shim, J.; Goldsmith, K.C. A New Player in Neuroblastoma: YAP and Its Role in the Neuroblastoma Microenvironment. Cancers 2021, 13, 4650. [Google Scholar] [CrossRef] [PubMed]
  42. Pilgrim, A.A.; Jonus, H.C.; Ho, A.; Cole, A.C.; Shim, J.; Goldsmith, K.C. The Yes-Associated Protein (YAP) Is Associated with Resistance to Anti-GD2 Immunotherapy in Neuroblastoma through Downregulation of ST8SIA1. Oncoimmunology 2023, 12, 2240678. [Google Scholar] [CrossRef] [PubMed]
  43. Kaplan, R.N.; Riba, R.D.; Zacharoulis, S.; Bramley, A.H.; Vincent, L.; Costa, C.; MacDonald, D.D.; Jin, D.K.; Shido, K.; Kerns, S.A.; et al. VEGFR1-Positive Haematopoietic Bone Marrow Progenitors Initiate the Pre-Metastatic Niche. Nature 2005, 438, 820–827. [Google Scholar] [CrossRef]
  44. Cersosimo, F.; Lonardi, S.; Bernardini, G.; Telfer, B.; Mandelli, G.E.; Santucci, A.; Vermi, W.; Giurisato, E. Tumor-Associated Macrophages in Osteosarcoma: From Mechanisms to Therapy. Int. J. Mol. Sci. 2020, 21, 5207. [Google Scholar] [CrossRef]
  45. Yu, F.-X.; Hu, W.-J.; He, B.; Zheng, Y.-H.; Zhang, Q.-Y.; Chen, L. Bone Marrow Mesenchymal Stem Cells Promote Osteosarcoma Cell Proliferation and Invasion. World J. Surg. Oncol. 2015, 13, 52. [Google Scholar] [CrossRef]
  46. Avnet, S.; Lemma, S.; Cortini, M.; Di Pompo, G.; Perut, F.; Lipreri, M.V.; Roncuzzi, L.; Columbaro, M.; Errani, C.; Longhi, A.; et al. The Release of Inflammatory Mediators from Acid-Stimulated Mesenchymal Stromal Cells Favours Tumour Invasiveness and Metastasis in Osteosarcoma. Cancers 2021, 13, 5855. [Google Scholar] [CrossRef]
  47. Taylor, M.; Rössler, J.; Geoerger, B.; Laplanche, A.; Hartmann, O.; Vassal, G.; Farace, F. High Levels of Circulating VEGFR2+ Bone Marrow-Derived Progenitor Cells Correlate with Metastatic Disease in Patients with Pediatric Solid Malignancies. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2009, 15, 4561–4571. [Google Scholar] [CrossRef] [PubMed]
  48. Hochheuser, C.; Windt, L.J.; Kunze, N.Y.; de Vos, D.L.; Tytgat, G.A.M.; Voermans, C.; Timmerman, I. Mesenchymal Stromal Cells in Neuroblastoma: Exploring Crosstalk and Therapeutic Implications. Stem Cells Dev. 2021, 30, 59–78. [Google Scholar] [CrossRef]
  49. Lazic, D.; Kromp, F.; Rifatbegovic, F.; Repiscak, P.; Kirr, M.; Mivalt, F.; Halbritter, F.; Bernkopf, M.; Bileck, A.; Ussowicz, M.; et al. Landscape of Bone Marrow Metastasis in Human Neuroblastoma Unraveled by Transcriptomics and Deep Multiplex Imaging. Cancers 2021, 13, 4311. [Google Scholar] [CrossRef]
  50. Huang, C.; Jian, B.; Su, Y.; Xu, N.; Yu, T.; He, L.; Zhang, X.; Liu, Y.; Jin, M.; Ma, X. Clinical Features and Prognosis of Paediatric Rhabdomyosarcoma with Bone Marrow Metastasis: A Single Centre Experiences in China. BMC Pediatr. 2021, 21, 463. [Google Scholar] [CrossRef]
  51. Li, F.; Li, C.; Cai, X.; Xie, Z.; Zhou, L.; Cheng, B.; Zhong, R.; Xiong, S.; Li, J.; Chen, Z.; et al. The Association between CD8+ Tumor-Infiltrating Lymphocytes and the Clinical Outcome of Cancer Immunotherapy: A Systematic Review and Meta-Analysis. EClinicalMedicine 2021, 41, 101134. [Google Scholar] [CrossRef]
  52. Dieu-Nosjean, M.-C.; Giraldo, N.A.; Kaplon, H.; Germain, C.; Fridman, W.H.; Sautès-Fridman, C. Tertiary Lymphoid Structures, Drivers of the Anti-Tumor Responses in Human Cancers. Immunol. Rev. 2016, 271, 260–275. [Google Scholar] [CrossRef] [PubMed]
  53. Di Caro, G.; Castino, G.F.; Bergomas, F.; Cortese, N.; Chiriva-Internati, M.; Grizzi, F.; Mantovani, A.; Marchesi, F. Tertiary Lymphoid Tissue in the Tumor Microenvironment: From Its Occurrence to Immunotherapeutic Implications. Int. Rev. Immunol. 2015, 34, 123–133. [Google Scholar] [CrossRef] [PubMed]
  54. Waldman, A.D.; Fritz, J.M.; Lenardo, M.J. A Guide to Cancer Immunotherapy: From T Cell Basic Science to Clinical Practice. Nat. Rev. Immunol. 2020, 20, 651–668. [Google Scholar] [CrossRef]
  55. Shiravand, Y.; Khodadadi, F.; Kashani, S.M.A.; Hosseini-Fard, S.R.; Hosseini, S.; Sadeghirad, H.; Ladwa, R.; O’Byrne, K.; Kulasinghe, A. Immune Checkpoint Inhibitors in Cancer Therapy. Curr. Oncol. 2022, 29, 3044–3060. [Google Scholar] [CrossRef]
  56. Haabeth, O.A.W.; Lorvik, K.B.; Hammarström, C.; Donaldson, I.M.; Haraldsen, G.; Bogen, B.; Corthay, A. Inflammation Driven by Tumour-Specific Th1 Cells Protects against B-Cell Cancer. Nat. Commun. 2011, 2, 240. [Google Scholar] [CrossRef]
  57. Morvan, M.G.; Lanier, L.L. NK Cells and Cancer: You Can Teach Innate Cells New Tricks. Nat. Rev. Cancer 2016, 16, 7–19. [Google Scholar] [CrossRef]
  58. Bellora, F.; Castriconi, R.; Dondero, A.; Carrega, P.; Mantovani, A.; Ferlazzo, G.; Moretta, A.; Bottino, C. Human NK Cells and NK Receptors. Immunol. Lett. 2014, 161, 168–173. [Google Scholar] [CrossRef]
  59. Cantoni, C.; Huergo-Zapico, L.; Parodi, M.; Pedrazzi, M.; Mingari, M.C.; Moretta, A.; Sparatore, B.; Gonzalez, S.; Olive, D.; Bottino, C.; et al. NK Cells, Tumor Cell Transition, and Tumor Progression in Solid Malignancies: New Hints for NK-Based Immunotherapy? J. Immunol. Res. 2016, 2016, 4684268. [Google Scholar] [CrossRef]
  60. Abel, A.M.; Yang, C.; Thakar, M.S.; Malarkannan, S. Natural Killer Cells: Development, Maturation, and Clinical Utilization. Front. Immunol. 2018, 9, 1869. [Google Scholar] [CrossRef]
  61. Omer, N.; Nicholls, W.; Ruegg, B.; Souza-Fonseca-Guimaraes, F.; Rossi, G.R. Enhancing Natural Killer Cell Targeting of Pediatric Sarcoma. Front. Immunol. 2021, 12, 791206. [Google Scholar] [CrossRef]
  62. Rezvani, K.; Rouce, R.; Liu, E.; Shpall, E. Engineering Natural Killer Cells for Cancer Immunotherapy. Mol. Ther. J. Am. Soc. Gene Ther. 2017, 25, 1769–1781. [Google Scholar] [CrossRef]
  63. Bryceson, Y.T.; March, M.E.; Ljunggren, H.-G.; Long, E.O. Activation, Coactivation, and Costimulation of Resting Human Natural Killer Cells. Immunol. Rev. 2006, 214, 73–91. [Google Scholar] [CrossRef]
  64. Wu, S.-Y.; Fu, T.; Jiang, Y.-Z.; Shao, Z.-M. Natural Killer Cells in Cancer Biology and Therapy. Mol. Cancer 2020, 19, 120. [Google Scholar] [CrossRef]
  65. Roda, J.M.; Parihar, R.; Magro, C.; Nuovo, G.J.; Tridandapani, S.; Carson, W.E. Natural Killer Cells Produce T Cell-Recruiting Chemokines in Response to Antibody-Coated Tumor Cells. Cancer Res. 2006, 66, 517–526. [Google Scholar] [CrossRef]
  66. Mantovani, A.; Allavena, P.; Marchesi, F.; Garlanda, C. Macrophages as Tools and Targets in Cancer Therapy. Nat. Rev. Drug Discov. 2022, 21, 799–820. [Google Scholar] [CrossRef] [PubMed]
  67. Qian, B.-Z.; Pollard, J.W. Macrophage Diversity Enhances Tumor Progression and Metastasis. Cell 2010, 141, 39–51. [Google Scholar] [CrossRef]
  68. Xue, J.; Schmidt, S.V.; Sander, J.; Draffehn, A.; Krebs, W.; Quester, I.; De Nardo, D.; Gohel, T.D.; Emde, M.; Schmidleithner, L.; et al. Transcriptome-Based Network Analysis Reveals a Spectrum Model of Human Macrophage Activation. Immunity 2014, 40, 274–288. [Google Scholar] [CrossRef]
  69. Allavena, P.; Sica, A.; Solinas, G.; Porta, C.; Mantovani, A. The Inflammatory Micro-Environment in Tumor Progression: The Role of Tumor-Associated Macrophages. Crit. Rev. Oncol. Hematol. 2008, 66, 1–9. [Google Scholar] [CrossRef] [PubMed]
  70. McFarlane, A.J.; Fercoq, F.; Coffelt, S.B.; Carlin, L.M. Neutrophil Dynamics in the Tumor Microenvironment. J. Clin. Investig. 2021, 131, e143759. [Google Scholar] [CrossRef] [PubMed]
  71. Del Prete, A.; Sozio, F.; Barbazza, I.; Salvi, V.; Tiberio, L.; Laffranchi, M.; Gismondi, A.; Bosisio, D.; Schioppa, T.; Sozzani, S. Functional Role of Dendritic Cell Subsets in Cancer Progression and Clinical Implications. Int. J. Mol. Sci. 2020, 21, 3930. [Google Scholar] [CrossRef]
  72. Perez, C.R.; De Palma, M. Engineering Dendritic Cell Vaccines to Improve Cancer Immunotherapy. Nat. Commun. 2019, 10, 5408. [Google Scholar] [CrossRef] [PubMed]
  73. Josefowicz, S.Z.; Lu, L.-F.; Rudensky, A.Y. Regulatory T Cells: Mechanisms of Differentiation and Function. Annu. Rev. Immunol. 2012, 30, 531–564. [Google Scholar] [CrossRef] [PubMed]
  74. Campbell, B.B.; Light, N.; Fabrizio, D.; Zatzman, M.; Fuligni, F.; de Borja, R.; Davidson, S.; Edwards, M.; Elvin, J.A.; Hodel, K.P.; et al. Comprehensive Analysis of Hypermutation in Human Cancer. Cell 2017, 171, 1042–1056.e10. [Google Scholar] [CrossRef] [PubMed]
  75. Dolecek, T.A.; Propp, J.M.; Stroup, N.E.; Kruchko, C. CBTRUS Statistical Report: Primary Brain and Central Nervous System Tumors Diagnosed in the United States in 2005–2009. Neuro Oncol. 2012, 14 (Suppl. S5), v1-49. [Google Scholar] [CrossRef] [PubMed]
  76. Geraldo, L.H.M.; Garcia, C.; da Fonseca, A.C.C.; Dubois, L.G.F.; de Sampaio E Spohr, T.C.L.; Matias, D.; de Camargo Magalhães, E.S.; do Amaral, R.F.; da Rosa, B.G.; Grimaldi, I.; et al. Glioblastoma Therapy in the Age of Molecular Medicine. Trends Cancer 2019, 5, 46–65. [Google Scholar] [CrossRef]
  77. Plant, A.S.; Koyama, S.; Sinai, C.; Solomon, I.H.; Griffin, G.K.; Ligon, K.L.; Bandopadhayay, P.; Betensky, R.; Emerson, R.; Dranoff, G.; et al. Immunophenotyping of Pediatric Brain Tumors: Correlating Immune Infiltrate with Histology, Mutational Load, and Survival and Assessing Clonal T Cell Response. J. Neurooncol. 2018, 137, 269–278. [Google Scholar] [CrossRef] [PubMed]
  78. Rozowsky, J.S.; Meesters-Ensing, J.I.; Lammers, J.A.S.; Belle, M.L.; Nierkens, S.; Kranendonk, M.E.G.; Kester, L.A.; Calkoen, F.G.; van der Lugt, J. A Toolkit for Profiling the Immune Landscape of Pediatric Central Nervous System Malignancies. Front. Immunol. 2022, 13, 864423. [Google Scholar] [CrossRef]
  79. Salloum, R.; Chen, Y.; Yasui, Y.; Packer, R.; Leisenring, W.; Wells, E.; King, A.; Howell, R.; Gibson, T.M.; Krull, K.R.; et al. Late Morbidity and Mortality Among Medulloblastoma Survivors Diagnosed Across Three Decades: A Report From the Childhood Cancer Survivor Study. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 2019, 37, 731–740. [Google Scholar] [CrossRef]
  80. Teo, W.-Y.; Elghetany, M.T.; Shen, J.; Man, T.-K.; Li, X.; Chintagumpala, M.; Su, J.M.F.; Dauser, R.; Whitehead, W.; Adesina, A.M.; et al. Therapeutic Implications of CD1d Expression and Tumor-Infiltrating Macrophages in Pediatric Medulloblastomas. J. Neurooncol. 2014, 120, 293–301. [Google Scholar] [CrossRef]
  81. Lieberman, N.A.P.; DeGolier, K.; Kovar, H.M.; Davis, A.; Hoglund, V.; Stevens, J.; Winter, C.; Deutsch, G.; Furlan, S.N.; Vitanza, N.A.; et al. Characterization of the Immune Microenvironment of Diffuse Intrinsic Pontine Glioma: Implications for Development of Immunotherapy. Neuro Oncol. 2019, 21, 83–94. [Google Scholar] [CrossRef] [PubMed]
  82. Griesinger, A.M.; Birks, D.K.; Donson, A.M.; Amani, V.; Hoffman, L.M.; Waziri, A.; Wang, M.; Handler, M.H.; Foreman, N.K. Characterization of Distinct Immunophenotypes across Pediatric Brain Tumor Types. J. Immunol. 2013, 191, 4880–4888. [Google Scholar] [CrossRef]
  83. Martin, A.M.; Nirschl, C.J.; Polanczyk, M.J.; Bell, W.R.; Nirschl, T.R.; Harris-Bookman, S.; Phallen, J.; Hicks, J.; Martinez, D.; Ogurtsova, A.; et al. PD-L1 Expression in Medulloblastoma: An Evaluation by Subgroup. Oncotarget 2018, 9, 19177–19191. [Google Scholar] [CrossRef] [PubMed]
  84. Witt, D.A.; Donson, A.M.; Amani, V.; Moreira, D.C.; Sanford, B.; Hoffman, L.M.; Handler, M.H.; Levy, J.M.M.; Jones, K.L.; Nellan, A.; et al. Specific Expression of PD-L1 in RELA-Fusion Supratentorial Ependymoma: Implications for PD-1-Targeted Therapy. Pediatr. Blood Cancer 2018, 65, e26960. [Google Scholar] [CrossRef]
  85. El Andaloussi, A.; Lesniak, M.S. An Increase in CD4+CD25+FOXP3+ Regulatory T Cells in Tumor-Infiltrating Lymphocytes of Human Glioblastoma Multiforme. Neuro Oncol. 2006, 8, 234–243. [Google Scholar] [CrossRef] [PubMed]
  86. Majzner, R.G.; Simon, J.S.; Grosso, J.F.; Martinez, D.; Pawel, B.R.; Santi, M.; Merchant, M.S.; Geoerger, B.; Hezam, I.; Marty, V.; et al. Assessment of Programmed Death-Ligand 1 Expression and Tumor-Associated Immune Cells in Pediatric Cancer Tissues. Cancer 2017, 123, 3807–3815. [Google Scholar] [CrossRef] [PubMed]
  87. Brohl, A.S.; Sindiri, S.; Wei, J.S.; Milewski, D.; Chou, H.-C.; Song, Y.K.; Wen, X.; Kumar, J.; Reardon, H.V.; Mudunuri, U.S.; et al. Immuno-Transcriptomic Profiling of Extracranial Pediatric Solid Malignancies. Cell Rep. 2021, 37, 110047. [Google Scholar] [CrossRef] [PubMed]
  88. Sherif, S.; Roelands, J.; Mifsud, W.; Ahmed, E.I.; Raynaud, C.M.; Rinchai, D.; Sathappan, A.; Maaz, A.; Saleh, A.; Ozer, E.; et al. The Immune Landscape of Solid Pediatric Tumors. J. Exp. Clin. Cancer Res. 2022, 41, 199. [Google Scholar] [CrossRef]
  89. Wei, J.S.; Kuznetsov, I.B.; Zhang, S.; Song, Y.K.; Asgharzadeh, S.; Sindiri, S.; Wen, X.; Patidar, R.; Najaraj, S.; Walton, A.; et al. Clinically Relevant Cytotoxic Immune Cell Signatures and Clonal Expansion of T-Cell Receptors in High-Risk MYCN-Not-Amplified Human Neuroblastoma. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2018, 24, 5673–5684. [Google Scholar] [CrossRef]
  90. Dondero, A.; Pastorino, F.; Della Chiesa, M.; Corrias, M.V.; Morandi, F.; Pistoia, V.; Olive, D.; Bellora, F.; Locatelli, F.; Castellano, A.; et al. PD-L1 Expression in Metastatic Neuroblastoma as an Additional Mechanism for Limiting Immune Surveillance. OncoImmunology 2016, 5, e1064578. [Google Scholar] [CrossRef]
  91. Pinto, N.; Park, J.R.; Murphy, E.; Yearley, J.; McClanahan, T.; Annamalai, L.; Hawkins, D.S.; Rudzinski, E.R. Patterns of PD-1, PD-L1, and PD-L2 Expression in Pediatric Solid Tumors. Pediatr. Blood Cancer 2017, 64, e26613. [Google Scholar] [CrossRef]
  92. Hingorani, P.; Maas, M.L.; Gustafson, M.P.; Dickman, P.; Adams, R.H.; Watanabe, M.; Eshun, F.; Williams, J.; Seidel, M.J.; Dietz, A.B. Increased CTLA-4(+) T Cells and an Increased Ratio of Monocytes with Loss of Class II (CD14(+) HLA-DR(Lo/Neg)) Found in Aggressive Pediatric Sarcoma Patients. J. Immunother. Cancer 2015, 3, 35. [Google Scholar] [CrossRef]
  93. Kim, C.; Kim, E.K.; Jung, H.; Chon, H.J.; Han, J.W.; Shin, K.-H.; Hu, H.; Kim, K.S.; Choi, Y.D.; Kim, S.; et al. Prognostic Implications of PD-L1 Expression in Patients with Soft Tissue Sarcoma. BMC Cancer 2016, 16, 434. [Google Scholar] [CrossRef]
  94. Stahl, D.; Gentles, A.J.; Thiele, R.; Gütgemann, I. Prognostic Profiling of the Immune Cell Microenvironment in Ewing’s Sarcoma Family of Tumors. Oncoimmunology 2019, 8, e1674113. [Google Scholar] [CrossRef]
  95. Contardi, E.; Palmisano, G.L.; Tazzari, P.L.; Martelli, A.M.; Falà, F.; Fabbi, M.; Kato, T.; Lucarelli, E.; Donati, D.; Polito, L.; et al. CTLA-4 Is Constitutively Expressed on Tumor Cells and Can Trigger Apoptosis upon Ligand Interaction. Int. J. Cancer 2005, 117, 538–550. [Google Scholar] [CrossRef]
  96. Torre, M.; Alexandrescu, S.; Dubuc, A.M.; Ligon, A.H.; Hornick, J.L.; Meredith, D.M. Characterization of Molecular Signatures of Supratentorial Ependymomas. Mod. Pathol. Off. J. U. S. Can. Acad. Pathol. Inc. 2020, 33, 47–56. [Google Scholar] [CrossRef] [PubMed]
  97. Terry, R.L.; Meyran, D.; Ziegler, D.S.; Haber, M.; Ekert, P.G.; Trapani, J.A.; Neeson, P.J. Immune Profiling of Pediatric Solid Tumors. J. Clin. Investig. 2020, 130, 3391–3402. [Google Scholar] [CrossRef] [PubMed]
  98. Johnsen, J.I.; Dyberg, C.; Wickström, M. Neuroblastoma-A Neural Crest Derived Embryonal Malignancy. Front. Mol. Neurosci. 2019, 12, 9. [Google Scholar] [CrossRef] [PubMed]
  99. Huang, M.; Weiss, W.A. Neuroblastoma and MYCN. Cold Spring Harb. Perspect. Med. 2013, 3, a014415. [Google Scholar] [CrossRef] [PubMed]
  100. Asgharzadeh, S.; Salo, J.A.; Ji, L.; Oberthuer, A.; Fischer, M.; Berthold, F.; Hadjidaniel, M.; Liu, C.W.-Y.; Metelitsa, L.S.; Pique-Regi, R.; et al. Clinical Significance of Tumor-Associated Inflammatory Cells in Metastatic Neuroblastoma. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 2012, 30, 3525–3532. [Google Scholar] [CrossRef]
  101. Ara, T.; Nakata, R.; Sheard, M.A.; Shimada, H.; Buettner, R.; Groshen, S.G.; Ji, L.; Yu, H.; Jove, R.; Seeger, R.C.; et al. Critical Role of STAT3 in IL-6-Mediated Drug Resistance in Human Neuroblastoma. Cancer Res. 2013, 73, 3852–3864. [Google Scholar] [CrossRef] [PubMed]
  102. Kushner, B.H.; Cheung, I.Y.; Modak, S.; Kramer, K.; Ragupathi, G.; Cheung, N.-K.V. Phase I Trial of a Bivalent Gangliosides Vaccine in Combination with β-Glucan for High-Risk Neuroblastoma in Second or Later Remission. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2014, 20, 1375–1382. [Google Scholar] [CrossRef] [PubMed]
  103. Relation, T.; Yi, T.; Guess, A.J.; La Perle, K.; Otsuru, S.; Hasgur, S.; Dominici, M.; Breuer, C.; Horwitz, E.M. Intratumoral Delivery of Interferonγ-Secreting Mesenchymal Stromal Cells Repolarizes Tumor-Associated Macrophages and Suppresses Neuroblastoma Proliferation In Vivo. Stem Cells 2018, 36, 915–924. [Google Scholar] [CrossRef] [PubMed]
  104. Franco-Luzón, L.; García-Mulero, S.; Sanz-Pamplona, R.; Melen, G.; Ruano, D.; Lassaletta, Á.; Madero, L.; González-Murillo, Á.; Ramírez, M. Genetic and Immune Changes Associated with Disease Progression under the Pressure of Oncolytic Therapy in A Neuroblastoma Outlier Patient. Cancers 2020, 12, 1104. [Google Scholar] [CrossRef]
  105. Steliarova-Foucher, E.; Colombet, M.; Ries, L.A.G.; Moreno, F.; Dolya, A.; Bray, F.; Hesseling, P.; Shin, H.Y.; Stiller, C.A. IICC-3 contributors International Incidence of Childhood Cancer, 2001–2010: A Population-Based Registry Study. Lancet Oncol. 2017, 18, 719–731. [Google Scholar] [CrossRef] [PubMed]
  106. Durfee, R.A.; Mohammed, M.; Luu, H.H. Review of Osteosarcoma and Current Management. Rheumatol. Ther. 2016, 3, 221–243. [Google Scholar] [CrossRef] [PubMed]
  107. Chisholm, J.C.; Marandet, J.; Rey, A.; Scopinaro, M.; de Toledo, J.S.; Merks, J.H.M.; O’Meara, A.; Stevens, M.C.G.; Oberlin, O. Prognostic Factors after Relapse in Nonmetastatic Rhabdomyosarcoma: A Nomogram to Better Define Patients Who Can Be Salvaged with Further Therapy. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 2011, 29, 1319–1325. [Google Scholar] [CrossRef]
  108. Zöllner, S.K.; Amatruda, J.F.; Bauer, S.; Collaud, S.; de Álava, E.; DuBois, S.G.; Hardes, J.; Hartmann, W.; Kovar, H.; Metzler, M.; et al. Ewing Sarcoma-Diagnosis, Treatment, Clinical Challenges and Future Perspectives. J. Clin. Med. 2021, 10, 1685. [Google Scholar] [CrossRef]
  109. Quezada, S.A.; Peggs, K.S.; Curran, M.A.; Allison, J.P. CTLA4 Blockade and GM-CSF Combination Immunotherapy Alters the Intratumor Balance of Effector and Regulatory T Cells. J. Clin. Investig. 2006, 116, 1935–1945. [Google Scholar] [CrossRef]
  110. Morales-Molina, A.; Gambera, S.; Leo, A.; García-Castro, J. Combination Immunotherapy Using G-CSF and Oncolytic Virotherapy Reduces Tumor Growth in Osteosarcoma. J. Immunother. Cancer 2021, 9, e001703. [Google Scholar] [CrossRef]
  111. Groenendijk, A.; Spreafico, F.; de Krijger, R.R.; Drost, J.; Brok, J.; Perotti, D.; van Tinteren, H.; Venkatramani, R.; Godziński, J.; Rübe, C.; et al. Prognostic Factors for Wilms Tumor Recurrence: A Review of the Literature. Cancers 2021, 13, 3142. [Google Scholar] [CrossRef] [PubMed]
  112. Hont, A.B.; Dumont, B.; Sutton, K.S.; Anderson, J.; Kentsis, A.; Drost, J.; Hong, A.L.; Verschuur, A. The Tumor Microenvironment and Immune Targeting Therapy in Pediatric Renal Tumors. Pediatr. Blood Cancer 2022, 70, e30110. [Google Scholar] [CrossRef]
  113. Palmisani, F.; Kovar, H.; Kager, L.; Amann, G.; Metzelder, M.; Bergmann, M. Systematic Review of the Immunological Landscape of Wilms Tumors. Mol. Ther. Oncolytics 2021, 22, 454–467. [Google Scholar] [CrossRef] [PubMed]
  114. Tian, K.; Wang, X.; Wu, Y.; Wu, X.; Du, G.; Liu, W.; Wu, R. Relationship of Tumour-Associated Macrophages with Poor Prognosis in Wilms’ Tumour. J. Pediatr. Urol. 2020, 16, 376.e1–376.e8. [Google Scholar] [CrossRef] [PubMed]
  115. Maturu, P.; Overwijk, W.W.; Hicks, J.; Ekmekcioglu, S.; Grimm, E.A.; Huff, V. Characterization of the Inflammatory Microenvironment and Identification of Potential Therapeutic Targets in Wilms Tumors. Transl. Oncol. 2014, 7, 484–492. [Google Scholar] [CrossRef]
  116. Lehmann, N.; Paret, C.; El Malki, K.; Russo, A.; Neu, M.A.; Wingerter, A.; Seidmann, L.; Foersch, S.; Ziegler, N.; Roth, L.; et al. Tumor Lipids of Pediatric Papillary Renal Cell Carcinoma Stimulate Unconventional T Cells. Front. Immunol. 2020, 11, 1819. [Google Scholar] [CrossRef] [PubMed]
  117. Zhang, L.; Jiao, H.; Shen, M.; Liu, W.; Li, Z.; Lin, J. Clinical Significance of Tumoral PD-L1 Expression in Wilms Tumors. J. Pediatr. Urol. 2022, 18, 14.e1–14.e8. [Google Scholar] [CrossRef] [PubMed]
  118. Routh, J.C.; Ashley, R.A.; Sebo, T.J.; Lohse, C.M.; Husmann, D.A.; Kramer, S.A.; Kwon, E.D. B7-H1 Expression in Wilms Tumor: Correlation With Tumor Biology and Disease Recurrence. J. Urol. 2008, 179, 1954–1960. [Google Scholar] [CrossRef]
  119. Routh, J.C.; Grundy, P.E.; Anderson, J.R.; Retik, A.B.; Kurek, K.C. B7-H1 as a Biomarker for Therapy Failure in Patients with Favorable Histology Wilms Tumor. J. Urol. 2013, 189, 1487–1492. [Google Scholar] [CrossRef] [PubMed]
  120. Tumor Mutation Burden, DNA Mismatch Repair Status and Checkpoint Immunotherapy Markers in Primary and Relapsed Malignant Rhabdoid Tumors—PubMed. Available online: https://pubmed.ncbi.nlm.nih.gov/31047727/ (accessed on 23 February 2024).
  121. Kivelä, T. The Epidemiological Challenge of the Most Frequent Eye Cancer: Retinoblastoma, an Issue of Birth and Death. Br. J. Ophthalmol. 2009, 93, 1129–1131. [Google Scholar] [CrossRef]
  122. Stacey, A.W.; Bowman, R.; Foster, A.; Kivelä, T.T.; Munier, F.L.; Cassoux, N.; Fabian, I.D.; Global Retinoblastoma Study Group. Incidence of Retinoblastoma Has Increased: Results from 40 European Countries. Ophthalmology 2021, 128, 1369–1371. [Google Scholar] [CrossRef]
  123. Fabian, I.D.; Sagoo, M.S. Understanding Retinoblastoma: Epidemiology and Genetics. Community Eye Health 2018, 31, 7. [Google Scholar]
  124. Munier, F.L.; Beck-Popovic, M.; Chantada, G.L.; Cobrinik, D.; Kivelä, T.T.; Lohmann, D.; Maeder, P.; Moll, A.C.; Carcaboso, A.M.; Moulin, A.; et al. Conservative Management of Retinoblastoma: Challenging Orthodoxy without Compromising the State of Metastatic Grace. “Alive, with Good Vision and No Comorbidity”. Prog. Retin. Eye Res. 2019, 73, 100764. [Google Scholar] [CrossRef]
  125. Sarver, A.L.; Xie, C.; Riddle, M.J.; Forster, C.L.; Wang, X.; Lu, H.; Wagner, W.; Tolar, J.; Hallstrom, T.C. Retinoblastoma Tumor Cell Proliferation Is Negatively Associated with an Immune Gene Expression Signature and Increased Immune Cells. Lab. Investig. J. Tech. Methods Pathol. 2021, 101, 701–718. [Google Scholar] [CrossRef]
  126. Mao, P.; Shen, Y.; Xu, X.; Zhong, J. Comprehensive Analysis of the Immune Cell Infiltration Landscape and Immune-Related Methylation in Retinoblastoma. Front. Genet. 2022, 13, 864473. [Google Scholar] [CrossRef]
  127. Wu, C.; Yang, J.; Xiao, W.; Jiang, Z.; Chen, S.; Guo, D.; Zhang, P.; Liu, C.; Yang, H.; Xie, Z. Single-Cell Characterization of Malignant Phenotypes and Microenvironment Alteration in Retinoblastoma. Cell Death Dis. 2022, 13, 438. [Google Scholar] [CrossRef] [PubMed]
  128. Miracco, C.; Toti, P.; Gelmi, M.C.; Aversa, S.; Baldino, G.; Galluzzi, P.; De Francesco, S.; Petrelli, F.; Sorrentino, E.; Belmonte, G.; et al. Retinoblastoma Is Characterized by a Cold, CD8+ Cell Poor, PD-L1− Microenvironment, Which Turns into Hot, CD8+ Cell Rich, PD-L1+ after Chemotherapy. Investig. Ophthalmol. Vis. Sci. 2021, 62, 6. [Google Scholar] [CrossRef]
  129. Tao, J.; Calvisi, D.F.; Ranganathan, S.; Cigliano, A.; Zhou, L.; Singh, S.; Jiang, L.; Fan, B.; Terracciano, L.; Armeanu-Ebinger, S.; et al. Activation of β-Catenin and Yap1 in Human Hepatoblastoma and Induction of Hepatocarcinogenesis in Mice. Gastroenterology 2014, 147, 690–701. [Google Scholar] [CrossRef]
  130. Guo, J.-J.; Ye, Y.-Q.; Liu, Y.-D.; Wu, W.-F.; Mei, Q.-Q.; Zhang, X.-Y.; Lao, J.; Wang, B.; Wang, J.-Y. Interaction between Human Leukocyte Antigen (HLA-C) and Killer Cell Ig-like Receptors (KIR2DL) Inhibits the Cytotoxicity of Natural Killer Cells in Patients with Hepatoblastoma. Front. Med. 2022, 9, 947729. [Google Scholar] [CrossRef]
  131. Xie, F.; Zhang, L.; Yao, Q.; Shan, L.; Liu, J.; Dong, N.; Liang, J. TUG1 Promoted Tumor Progression by Sponging miR-335-5p and Regulating CXCR4-Mediated Infiltration of Pro-Tumor Immunocytes in CTNNB1-Mutated Hepatoblastoma. OncoTargets Ther. 2020, 13, 3105–3115. [Google Scholar] [CrossRef] [PubMed]
  132. Zhang, Y.; Zhang, T.; Yin, Q.; Luo, H. Development and Validation of Genomic and Epigenomic Signatures Associated with Tumor Immune Microenvironment in Hepatoblastoma. BMC Cancer 2021, 21, 1156. [Google Scholar] [CrossRef] [PubMed]
  133. Yu, A.L.; Gilman, A.L.; Ozkaynak, M.F.; London, W.B.; Kreissman, S.G.; Chen, H.X.; Smith, M.; Anderson, B.; Villablanca, J.G.; Matthay, K.K.; et al. Anti-GD2 Antibody with GM-CSF, Interleukin-2, and Isotretinoin for Neuroblastoma. N. Engl. J. Med. 2010, 363, 1324–1334. [Google Scholar] [CrossRef] [PubMed]
  134. Wingerter, A.; El Malki, K.; Sandhoff, R.; Seidmann, L.; Wagner, D.-C.; Lehmann, N.; Vewinger, N.; Frauenknecht, K.B.M.; Sommer, C.J.; Traub, F.; et al. Exploiting Gangliosides for the Therapy of Ewing’s Sarcoma and H3K27M-Mutant Diffuse Midline Glioma. Cancers 2021, 13, 520. [Google Scholar] [CrossRef] [PubMed]
  135. Sadeghi Rad, H.; Monkman, J.; Warkiani, M.E.; Ladwa, R.; O’Byrne, K.; Rezaei, N.; Kulasinghe, A. Understanding the Tumor Microenvironment for Effective Immunotherapy. Med. Res. Rev. 2021, 41, 1474–1498. [Google Scholar] [CrossRef]
  136. Kabir, T.F.; Chauhan, A.; Anthony, L.; Hildebrandt, G.C. Immune Checkpoint Inhibitors in Pediatric Solid Tumors: Status in 2018. Ochsner J. 2018, 18, 370–376. [Google Scholar] [CrossRef] [PubMed]
  137. Samstein, R.M.; Lee, C.-H.; Shoushtari, A.N.; Hellmann, M.D.; Shen, R.; Janjigian, Y.Y.; Barron, D.A.; Zehir, A.; Jordan, E.J.; Omuro, A.; et al. Tumor Mutational Load Predicts Survival after Immunotherapy across Multiple Cancer Types. Nat. Genet. 2019, 51, 202–206. [Google Scholar] [CrossRef]
  138. Downing, J.R.; Wilson, R.K.; Zhang, J.; Mardis, E.R.; Pui, C.-H.; Ding, L.; Ley, T.J.; Evans, W.E. The Pediatric Cancer Genome Project. Nat. Genet. 2012, 44, 619–622. [Google Scholar] [CrossRef]
  139. Binnewies, M.; Roberts, E.W.; Kersten, K.; Chan, V.; Fearon, D.F.; Merad, M.; Coussens, L.M.; Gabrilovich, D.I.; Ostrand-Rosenberg, S.; Hedrick, C.C.; et al. Understanding the Tumor Immune Microenvironment (TIME) for Effective Therapy. Nat. Med. 2018, 24, 541–550. [Google Scholar] [CrossRef]
  140. Leach, D.R.; Krummel, M.F.; Allison, J.P. Enhancement of Antitumor Immunity by CTLA-4 Blockade. Science 1996, 271, 1734–1736. [Google Scholar] [CrossRef]
  141. Walker, L.S.K. Treg and CTLA-4: Two Intertwining Pathways to Immune Tolerance. J. Autoimmun. 2013, 45, 49–57. [Google Scholar] [CrossRef]
  142. Morris, Z.S.; Guy, E.I.; Francis, D.M.; Gressett, M.M.; Werner, L.R.; Carmichael, L.L.; Yang, R.K.; Armstrong, E.A.; Huang, S.; Navid, F.; et al. In Situ Tumor Vaccination by Combining Local Radiation and Tumor-Specific Antibody or Immunocytokine Treatments. Cancer Res. 2016, 76, 3929–3941. [Google Scholar] [CrossRef]
  143. Reardon, D.A.; Gokhale, P.C.; Klein, S.R.; Ligon, K.L.; Rodig, S.J.; Ramkissoon, S.H.; Jones, K.L.; Conway, A.S.; Liao, X.; Zhou, J.; et al. Glioblastoma Eradication Following Immune Checkpoint Blockade in an Orthotopic, Immunocompetent Model. Cancer Immunol. Res. 2016, 4, 124–135. [Google Scholar] [CrossRef]
  144. Saha, D.; Martuza, R.L.; Rabkin, S.D. Macrophage Polarization Contributes to Glioblastoma Eradication by Combination Immunovirotherapy and Immune Checkpoint Blockade. Cancer Cell 2017, 32, 253–267.e5. [Google Scholar] [CrossRef]
  145. Hodi, F.S.; O’Day, S.J.; McDermott, D.F.; Weber, R.W.; Sosman, J.A.; Haanen, J.B.; Gonzalez, R.; Robert, C.; Schadendorf, D.; Hassel, J.C.; et al. Improved Survival with Ipilimumab in Patients with Metastatic Melanoma. N. Engl. J. Med. 2010, 363, 711–723. [Google Scholar] [CrossRef]
  146. Camacho, L.H.; Antonia, S.; Sosman, J.; Kirkwood, J.M.; Gajewski, T.F.; Redman, B.; Pavlov, D.; Bulanhagui, C.; Bozon, V.A.; Gomez-Navarro, J.; et al. Phase I/II Trial of Tremelimumab in Patients with Metastatic Melanoma. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 2009, 27, 1075–1081. [Google Scholar] [CrossRef] [PubMed]
  147. Merchant, M.S.; Wright, M.; Baird, K.; Wexler, L.H.; Rodriguez-Galindo, C.; Bernstein, D.; Delbrook, C.; Lodish, M.; Bishop, R.; Wolchok, J.D.; et al. Phase I Clinical Trial of Ipilimumab in Pediatric Patients with Advanced Solid Tumors. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2016, 22, 1364–1370. [Google Scholar] [CrossRef] [PubMed]
  148. Geoerger, B.; Zwaan, C.M.; Marshall, L.V.; Michon, J.; Bourdeaut, F.; Casanova, M.; Corradini, N.; Rossato, G.; Farid-Kapadia, M.; Shemesh, C.S.; et al. Atezolizumab for Children and Young Adults with Previously Treated Solid Tumours, Non-Hodgkin Lymphoma, and Hodgkin Lymphoma (iMATRIX): A Multicentre Phase 1-2 Study. Lancet Oncol. 2020, 21, 134–144. [Google Scholar] [CrossRef] [PubMed]
  149. Geoerger, B.; Kang, H.J.; Yalon-Oren, M.; Marshall, L.V.; Vezina, C.; Pappo, A.; Laetsch, T.W.; Petrilli, A.S.; Ebinger, M.; Toporski, J.; et al. Pembrolizumab in Paediatric Patients with Advanced Melanoma or a PD-L1-Positive, Advanced, Relapsed, or Refractory Solid Tumour or Lymphoma (KEYNOTE-051): Interim Analysis of an Open-Label, Single-Arm, Phase 1–2 Trial. Lancet Oncol. 2020, 21, 121–133. [Google Scholar] [CrossRef] [PubMed]
  150. Davis, K.L.; Fox, E.; Merchant, M.S.; Reid, J.M.; Kudgus, R.A.; Liu, X.; Minard, C.G.; Voss, S.; Berg, S.L.; Weigel, B.J.; et al. Nivolumab in Children and Young Adults with Relapsed or Refractory Solid Tumours or Lymphoma (ADVL1412): A Multicentre, Open-Label, Single-Arm, Phase 1–2 Trial. Lancet Oncol. 2020, 21, 541–550. [Google Scholar] [CrossRef] [PubMed]
  151. Davis, K.L.; Fox, E.; Isikwei, E.; Reid, J.M.; Liu, X.; Minard, C.G.; Voss, S.; Berg, S.L.; Weigel, B.J.; Mackall, C.L. A Phase I/II Trial of Nivolumab plus Ipilimumab in Children and Young Adults with Relapsed/Refractory Solid Tumors: A Children’s Oncology Group Study ADVL1412. Clin. Cancer Res. 2022, 28, 5088–5097. [Google Scholar] [CrossRef] [PubMed]
  152. Henderson, J.J.; Das, A.; Morgenstern, D.A.; Sudhaman, S.; Bianchi, V.; Chung, J.; Negm, L.; Edwards, M.; Kram, D.E.; Osborn, M.; et al. Immune Checkpoint Inhibition as Single Therapy for Synchronous Cancers Exhibiting Hypermutation: An IRRDC Study. JCO Precis. Oncol. 2022, 6, e2100286. [Google Scholar] [CrossRef]
  153. Sun, C.; Mezzadra, R.; Schumacher, T.N. Regulation and Function of the PD-L1 Checkpoint. Immunity 2018, 48, 434–452. [Google Scholar] [CrossRef]
  154. Brahmer, J.R.; Tykodi, S.S.; Chow, L.Q.M.; Hwu, W.-J.; Topalian, S.L.; Hwu, P.; Drake, C.G.; Camacho, L.H.; Kauh, J.; Odunsi, K.; et al. Safety and Activity of Anti-PD-L1 Antibody in Patients with Advanced Cancer. N. Engl. J. Med. 2012, 366, 2455–2465. [Google Scholar] [CrossRef]
  155. Pardoll, D.M. The Blockade of Immune Checkpoints in Cancer Immunotherapy. Nat. Rev. Cancer 2012, 12, 252–264. [Google Scholar] [CrossRef]
  156. Robert, C.; Schachter, J.; Long, G.V.; Arance, A.; Grob, J.J.; Mortier, L.; Daud, A.; Carlino, M.S.; McNeil, C.; Lotem, M.; et al. Pembrolizumab versus Ipilimumab in Advanced Melanoma. N. Engl. J. Med. 2015, 372, 2521–2532. [Google Scholar] [CrossRef] [PubMed]
  157. Topalian, S.L.; Hodi, F.S.; Brahmer, J.R.; Gettinger, S.N.; Smith, D.C.; McDermott, D.F.; Powderly, J.D.; Carvajal, R.D.; Sosman, J.A.; Atkins, M.B.; et al. Safety, Activity, and Immune Correlates of Anti-PD-1 Antibody in Cancer. N. Engl. J. Med. 2012, 366, 2443–2454. [Google Scholar] [CrossRef] [PubMed]
  158. Loeb, D.M.; Lee, J.W.; Morgenstern, D.A.; Samson, Y.; Uyttebroeck, A.; Lyu, C.J.; Van Damme, A.; Nysom, K.; Macy, M.E.; Zorzi, A.P.; et al. Avelumab in Paediatric Patients with Refractory or Relapsed Solid Tumours: Dose-Escalation Results from an Open-Label, Single-Arm, Phase 1/2 Trial. Cancer Immunol. Immunother. 2022, 71, 2485–2495. [Google Scholar] [CrossRef] [PubMed]
  159. Lussier, D.M.; Johnson, J.L.; Hingorani, P.; Blattman, J.N. Combination Immunotherapy with α-CTLA-4 and α-PD-L1 Antibody Blockade Prevents Immune Escape and Leads to Complete Control of Metastatic Osteosarcoma. J. Immunother. Cancer 2015, 3, 21. [Google Scholar] [CrossRef] [PubMed]
  160. Wainwright, D.A.; Chang, A.L.; Dey, M.; Balyasnikova, I.V.; Kim, C.K.; Tobias, A.; Cheng, Y.; Kim, J.W.; Qiao, J.; Zhang, L.; et al. Durable Therapeutic Efficacy Utilizing Combinatorial Blockade against IDO, CTLA-4, and PD-L1 in Mice with Brain Tumors. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2014, 20, 5290–5301. [Google Scholar] [CrossRef]
  161. Hung, A.L.; Maxwell, R.; Theodros, D.; Belcaid, Z.; Mathios, D.; Luksik, A.S.; Kim, E.; Wu, A.; Xia, Y.; Garzon-Muvdi, T.; et al. TIGIT and PD-1 Dual Checkpoint Blockade Enhances Antitumor Immunity and Survival in GBM. Oncoimmunology 2018, 7, e1466769. [Google Scholar] [CrossRef] [PubMed]
  162. Kim, J.E.; Patel, M.A.; Mangraviti, A.; Kim, E.S.; Theodros, D.; Velarde, E.; Liu, A.; Sankey, E.W.; Tam, A.; Xu, H.; et al. Combination Therapy with Anti-PD-1, Anti-TIM-3, and Focal Radiation Results in Regression of Murine Gliomas. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2017, 23, 124–136. [Google Scholar] [CrossRef]
  163. Garzon-Muvdi, T.; Theodros, D.; Luksik, A.S.; Maxwell, R.; Kim, E.; Jackson, C.M.; Belcaid, Z.; Ganguly, S.; Tyler, B.; Brem, H.; et al. Dendritic Cell Activation Enhances Anti-PD-1 Mediated Immunotherapy against Glioblastoma. Oncotarget 2018, 9, 20681–20697. [Google Scholar] [CrossRef]
  164. Lan, Y.; Zhang, D.; Xu, C.; Hance, K.W.; Marelli, B.; Qi, J.; Yu, H.; Qin, G.; Sircar, A.; Hernández, V.M.; et al. Enhanced Preclinical Antitumor Activity of M7824, a Bifunctional Fusion Protein Simultaneously Targeting PD-L1 and TGF-β. Sci. Transl. Med. 2018, 10, eaan5488. [Google Scholar] [CrossRef]
  165. Wu, S.; Calero-Pérez, P.; Arús, C.; Candiota, A.P. Anti-PD-1 Immunotherapy in Preclinical GL261 Glioblastoma: Influence of Therapeutic Parameters and Non-Invasive Response Biomarker Assessment with MRSI-Based Approaches. Int. J. Mol. Sci. 2020, 21, 8775. [Google Scholar] [CrossRef] [PubMed]
  166. Twyman-Saint Victor, C.; Rech, A.J.; Maity, A.; Rengan, R.; Pauken, K.E.; Stelekati, E.; Benci, J.L.; Xu, B.; Dada, H.; Odorizzi, P.M.; et al. Radiation and Dual Checkpoint Blockade Activate Non-Redundant Immune Mechanisms in Cancer. Nature 2015, 520, 373–377. [Google Scholar] [CrossRef]
  167. Dunkel, I.J.; Doz, F.; Foreman, N.K.; Hargrave, D.; Lassaletta, A.; André, N.; Hansford, J.R.; Hassall, T.; Eyrich, M.; Gururangan, S.; et al. Nivolumab with or without Ipilimumab in Pediatric Patients with High-Grade CNS Malignancies: Safety, Efficacy, Biomarker, and Pharmacokinetics—CheckMate 908. Neuro Oncol. 2023, 25, 1530–1545. [Google Scholar] [CrossRef] [PubMed]
  168. Ligon, J.A.; Wessel, K.M.; Shah, N.N.; Glod, J. Adoptive Cell Therapy in Pediatric and Young Adult Solid Tumors: Current Status and Future Directions. Front. Immunol. 2022, 13, 846346. [Google Scholar] [CrossRef]
  169. Comoli, P.; Chabannon, C.; Koehl, U.; Lanza, F.; Urbano-Ispizua, A.; Hudecek, M.; Ruggeri, A.; Secondino, S.; Bonini, C.; Pedrazzoli, P.; et al. Development of Adaptive Immune Effector Therapies in Solid Tumors. Ann. Oncol. Off. J. Eur. Soc. Med. Oncol. 2019, 30, 1740–1750. [Google Scholar] [CrossRef]
  170. Laskowski, T.J.; Biederstädt, A.; Rezvani, K. Natural Killer Cells in Antitumour Adoptive Cell Immunotherapy. Nat. Rev. Cancer 2022, 22, 557–575. [Google Scholar] [CrossRef] [PubMed]
  171. Poltavets, A.S.; Vishnyakova, P.A.; Elchaninov, A.V.; Sukhikh, G.T.; Fatkhudinov, T.K. Macrophage Modification Strategies for Efficient Cell Therapy. Cells 2020, 9, 1535. [Google Scholar] [CrossRef]
  172. Tas, L.; Jedema, I.; Haanen, J.B.A.G. Novel Strategies to Improve Efficacy of Treatment with Tumor-Infiltrating Lymphocytes (TILs) for Patients with Solid Cancers. Curr. Opin. Oncol. 2023, 35, 107–113. [Google Scholar] [CrossRef]
  173. Comoli, P.; Pedrazzoli, P.; Maccario, R.; Basso, S.; Carminati, O.; Labirio, M.; Schiavo, R.; Secondino, S.; Frasson, C.; Perotti, C.; et al. Cell Therapy of Stage IV Nasopharyngeal Carcinoma with Autologous Epstein-Barr Virus-Targeted Cytotoxic T Lymphocytes. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 2005, 23, 8942–8949. [Google Scholar] [CrossRef]
  174. Robbins, P.F.; Kassim, S.H.; Tran, T.L.N.; Crystal, J.S.; Morgan, R.A.; Feldman, S.A.; Yang, J.C.; Dudley, M.E.; Wunderlich, J.R.; Sherry, R.M.; et al. A Pilot Trial Using Lymphocytes Genetically Engineered with an NY-ESO-1–Reactive T-Cell Receptor: Long-Term Follow-up and Correlates with Response. Clin. Cancer Res. 2015, 21, 1019–1027. [Google Scholar] [CrossRef] [PubMed]
  175. D’Angelo, S.P.; Melchiori, L.; Merchant, M.S.; Bernstein, D.; Glod, J.; Kaplan, R.; Grupp, S.; Tap, W.D.; Chagin, K.; Binder, G.K.; et al. Antitumor Activity Associated with Prolonged Persistence of Adoptively Transferred NY-ESO-1 c259T Cells in Synovial Sarcoma. Cancer Discov. 2018, 8, 944–957. [Google Scholar] [CrossRef]
  176. Chen, Y.-T.; Scanlan, M.J.; Sahin, U.; Türeci, Ö.; Gure, A.O.; Tsang, S.; Williamson, B.; Stockert, E.; Pfreundschuh, M.; Old, L.J. A Testicular Antigen Aberrantly Expressed in Human Cancers Detected by Autologous Antibody Screening. Proc. Natl. Acad. Sci. USA 1997, 94, 1914–1918. [Google Scholar] [CrossRef] [PubMed]
  177. Jungbluth, A.A.; Chen, Y.-T.; Stockert, E.; Busam, K.J.; Kolb, D.; Iversen, K.; Coplan, K.; Williamson, B.; Altorki, N.; Old, L.J. Immunohistochemical Analysis of NY-ESO-1 Antigen Expression in Normal and Malignant Human Tissues. Int. J. Cancer 2001, 92, 856–860. [Google Scholar] [CrossRef] [PubMed]
  178. Orentas, R.; Lee, D.; Mackall, C. Immunotherapy Targets in Pediatric Cancer. Front. Oncol. 2012, 2, 3. [Google Scholar] [CrossRef] [PubMed]
  179. Vanichapol, T.; Chutipongtanate, S.; Anurathapan, U.; Hongeng, S. Immune Escape Mechanisms and Future Prospects for Immunotherapy in Neuroblastoma. BioMed Res. Int. 2018, 2018, 1812535. [Google Scholar] [CrossRef]
  180. Louis, C.U.; Savoldo, B.; Dotti, G.; Pule, M.; Yvon, E.; Myers, G.D.; Rossig, C.; Russell, H.V.; Diouf, O.; Liu, E.; et al. Antitumor Activity and Long-Term Fate of Chimeric Antigen Receptor-Positive T Cells in Patients with Neuroblastoma. Blood 2011, 118, 6050–6056. [Google Scholar] [CrossRef]
  181. Pule, M.A.; Savoldo, B.; Myers, G.D.; Rossig, C.; Russell, H.V.; Dotti, G.; Huls, M.H.; Liu, E.; Gee, A.P.; Mei, Z.; et al. Virus-Specific T Cells Engineered to Coexpress Tumor-Specific Receptors: Persistence and Antitumor Activity in Individuals with Neuroblastoma. Nat. Med. 2008, 14, 1264–1270. [Google Scholar] [CrossRef]
  182. Ahmed, N.; Brawley, V.S.; Hegde, M.; Robertson, C.; Ghazi, A.; Gerken, C.; Liu, E.; Dakhova, O.; Ashoori, A.; Corder, A.; et al. Human Epidermal Growth Factor Receptor 2 (HER2) -Specific Chimeric Antigen Receptor-Modified T Cells for the Immunotherapy of HER2-Positive Sarcoma. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 2015, 33, 1688–1696. [Google Scholar] [CrossRef]
  183. Heczey, A.; Louis, C.U.; Savoldo, B.; Dakhova, O.; Durett, A.; Grilley, B.; Liu, H.; Wu, M.F.; Mei, Z.; Gee, A.; et al. CAR T Cells Administered in Combination with Lymphodepletion and PD-1 Inhibition to Patients with Neuroblastoma. Mol. Ther. J. Am. Soc. Gene Ther. 2017, 25, 2214–2224. [Google Scholar] [CrossRef]
  184. Straathof, K.; Flutter, B.; Wallace, R.; Jain, N.; Loka, T.; Depani, S.; Wright, G.; Thomas, S.; Cheung, G.W.-K.; Gileadi, T.; et al. Antitumor Activity without On-Target off-Tumor Toxicity of GD2-Chimeric Antigen Receptor T Cells in Patients with Neuroblastoma. Sci. Transl. Med. 2020, 12, eabd6169. [Google Scholar] [CrossRef] [PubMed]
  185. Del Bufalo, F.; De Angelis, B.; Caruana, I.; Del Baldo, G.; De Ioris, M.A.; Serra, A.; Mastronuzzi, A.; Cefalo, M.G.; Pagliara, D.; Amicucci, M.; et al. GD2-CART01 for Relapsed or Refractory High-Risk Neuroblastoma. N. Engl. J. Med. 2023, 388, 1284–1295. [Google Scholar] [CrossRef] [PubMed]
  186. Heczey, A.; Courtney, A.N.; Montalbano, A.; Robinson, S.; Liu, K.; Li, M.; Ghatwai, N.; Dakhova, O.; Liu, B.; Raveh-Sadka, T.; et al. Anti-GD2 CAR-NKT Cells in Patients with Relapsed or Refractory Neuroblastoma: An Interim Analysis. Nat. Med. 2020, 26, 1686–1690. [Google Scholar] [CrossRef]
  187. Majzner, R.G.; Ramakrishna, S.; Yeom, K.W.; Patel, S.; Chinnasamy, H.; Schultz, L.M.; Richards, R.M.; Jiang, L.; Barsan, V.; Mancusi, R.; et al. GD2-CAR T Cell Therapy for H3K27M-Mutated Diffuse Midline Gliomas. Nature 2022, 603, 934–941. [Google Scholar] [CrossRef]
  188. Hegde, M.; Moll, A.J.; Byrd, T.T.; Louis, C.U.; Ahmed, N. Cellular Immunotherapy for Pediatric Solid Tumors. Cytotherapy 2015, 17, 3–17. [Google Scholar] [CrossRef]
  189. Rainusso, N.; Brawley, V.S.; Ghazi, A.; Hicks, M.J.; Gottschalk, S.; Rosen, J.M.; Ahmed, N. Immunotherapy Targeting HER2 with Genetically Modified T Cells Eliminates Tumor-Initiating Cells in Osteosarcoma. Cancer Gene Ther. 2012, 19, 212–217. [Google Scholar] [CrossRef]
  190. Albert, C.M.; Pinto, N.R.; Taylor, M.; Wilson, A.; Rawlings-Rhea, S.; Mgebroff, S.; Brown, C.; Lindgren, C.; Huang, W.; Seidel, K.; et al. STRIvE-01: Phase I Study of EGFR806 CAR T-Cell Immunotherapy for Recurrent/Refractory Solid Tumors in Children and Young Adults. J. Clin. Oncol. 2022, 40, 2541. [Google Scholar] [CrossRef]
  191. STRIVE-02: A First-in-Human Phase 1 Trial of Systemic B7H3 CAR T Cells for Children and Young Adults with Relapsed/Refractory Solid Tumors.|Journal of Clinical Oncology. Available online: https://ascopubs.org/doi/10.1200/JCO.2022.40.16_suppl.10011 (accessed on 23 February 2024).
  192. Lamers-Kok, N.; Panella, D.; Georgoudaki, A.-M.; Liu, H.; Özkazanc, D.; Kučerová, L.; Duru, A.D.; Spanholtz, J.; Raimo, M. Natural Killer Cells in Clinical Development as Non-Engineered, Engineered, and Combination Therapies. J. Hematol. Oncol. 2022, 15, 164. [Google Scholar] [CrossRef]
  193. Cho, D.; Shook, D.R.; Shimasaki, N.; Chang, Y.-H.; Fujisaki, H.; Campana, D. Cytotoxicity of Activated Natural Killer Cells against Pediatric Solid Tumors. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2010, 16, 3901–3909. [Google Scholar] [CrossRef]
  194. Liu, E.; Marin, D.; Banerjee, P.; Macapinlac, H.A.; Thompson, P.; Basar, R.; Nassif Kerbauy, L.; Overman, B.; Thall, P.; Kaplan, M.; et al. Use of CAR-Transduced Natural Killer Cells in CD19-Positive Lymphoid Tumors. N. Engl. J. Med. 2020, 382, 545–553. [Google Scholar] [CrossRef] [PubMed]
  195. Anderson, N.R.; Minutolo, N.G.; Gill, S.; Klichinsky, M. Macrophage-Based Approaches for Cancer Immunotherapy. Cancer Res. 2021, 81, 1201–1208. [Google Scholar] [CrossRef] [PubMed]
  196. Germano, G.; Frapolli, R.; Belgiovine, C.; Anselmo, A.; Pesce, S.; Liguori, M.; Erba, E.; Uboldi, S.; Zucchetti, M.; Pasqualini, F.; et al. Role of Macrophage Targeting in the Antitumor Activity of Trabectedin. Cancer Cell 2013, 23, 249–262. [Google Scholar] [CrossRef]
  197. Klichinsky, M.; Ruella, M.; Shestova, O.; Lu, X.M.; Best, A.; Zeeman, M.; Schmierer, M.; Gabrusiewicz, K.; Anderson, N.R.; Petty, N.E.; et al. Human Chimeric Antigen Receptor Macrophages for Cancer Immunotherapy. Nat. Biotechnol. 2020, 38, 947–953. [Google Scholar] [CrossRef]
  198. Kaczanowska, S.; Beury, D.W.; Gopalan, V.; Tycko, A.K.; Qin, H.; Clements, M.E.; Drake, J.; Nwanze, C.; Murgai, M.; Rae, Z.; et al. Genetically Engineered Myeloid Cells Rebalance the Core Immune Suppression Program in Metastasis. Cell 2021, 184, 2033–2052.e21. [Google Scholar] [CrossRef] [PubMed]
  199. Chong, E.A.; Melenhorst, J.J.; Lacey, S.F.; Ambrose, D.E.; Gonzalez, V.; Levine, B.L.; June, C.H.; Schuster, S.J. PD-1 Blockade Modulates Chimeric Antigen Receptor (CAR)-Modified T Cells: Refueling the CAR. Blood 2017, 129, 1039–1041. [Google Scholar] [CrossRef]
  200. Zhou, J.-T.; Liu, J.-H.; Song, T.-T.; Ma, B.; Amidula, N.; Bai, C. EGLIF-CAR-T Cells Secreting PD-1 Blocking Antibodies Significantly Mediate the Elimination of Gastric Cancer. Cancer Manag. Res. 2020, 12, 8893–8902. [Google Scholar] [CrossRef]
  201. Ping, Y.; Li, F.; Nan, S.; Zhang, D.; Shi, X.; Shan, J.; Zhang, Y. Augmenting the Effectiveness of CAR-T Cells by Enhanced Self-Delivery of PD-1-Neutralizing scFv. Front. Cell Dev. Biol. 2020, 8, 803. [Google Scholar] [CrossRef]
  202. Nothdurfter, D.; Ploner, C.; Coraça-Huber, D.C.; Wilflingseder, D.; Müller, T.; Hermann, M.; Hagenbuchner, J.; Ausserlechner, M.J. 3D Bioprinted, Vascularized Neuroblastoma Tumor Environment in Fluidic Chip Devices for Precision Medicine Drug Testing. Biofabrication 2022, 14, 035002. [Google Scholar] [CrossRef]
  203. Gallagher, C.; Murphy, C.; O’Brien, F.J.; Piskareva, O. Three-Dimensional In Vitro Biomimetic Model of Neuroblastoma Using Collagen-Based Scaffolds. J. Vis. Exp. JoVE 2021, e62627. [Google Scholar] [CrossRef]
  204. Quinn, C.H.; Beierle, A.M.; Beierle, E.A. Artificial Tumor Microenvironments in Neuroblastoma. Cancers 2021, 13, 1629. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Characteristics of the TME in pediatric cancers. TAM: tumor-associated macrophage; DCs: dendritic cells; Treg: regulatory T cells; CD4: CD4+ tumor-infiltrating lymphocyte; CD8: CD8+ tumor-infiltrating lymphocyte; NK: natural killer cell; Bcells: B lymphocytes; PD-1: programmed cell death protein-1; CTLA-4: Cytotoxic T-lymphocyte antigen 4; PDL-1: Programmed death-ligand 1.
Figure 1. Characteristics of the TME in pediatric cancers. TAM: tumor-associated macrophage; DCs: dendritic cells; Treg: regulatory T cells; CD4: CD4+ tumor-infiltrating lymphocyte; CD8: CD8+ tumor-infiltrating lymphocyte; NK: natural killer cell; Bcells: B lymphocytes; PD-1: programmed cell death protein-1; CTLA-4: Cytotoxic T-lymphocyte antigen 4; PDL-1: Programmed death-ligand 1.
Ijms 25 03225 g001
Figure 2. Tools for studying the TME in cancer. TILs: tumor-infiltrating lymphocytes; TME: tumor microenvironment; scRNA seq: single-cell RNA sequencing; bulkRNA seq: bulk cell population RNA sequencing.
Figure 2. Tools for studying the TME in cancer. TILs: tumor-infiltrating lymphocytes; TME: tumor microenvironment; scRNA seq: single-cell RNA sequencing; bulkRNA seq: bulk cell population RNA sequencing.
Ijms 25 03225 g002
Table 2. Published and ongoing clinical trials of ICIs registered on clinicaltrials.gov as of January 2023 for pediatric solid tumors.
Table 2. Published and ongoing clinical trials of ICIs registered on clinicaltrials.gov as of January 2023 for pediatric solid tumors.
TargetCompoundStudy
Phase
Disease Clinical Results/
Toxicity
Reference/
NCT#
CTLA-4IpilimumabPhase IAdvanced ST4 SD/33 pts enrolled;
27% grade 3–4 toxicities
[147]
PD-L1AtezolizumabPhase I/IIPediatric ST and
HD or NHL
4 PR/87 pts enrolled;
1 PR in 75 ST
Good tolerability
[148]
PD-1PembrolizumabPhase I/IIPediatric ST and
HD or NHL
2 CR, 15 PR/155 pts enrolled;
8 PR in ST
8% grade 3–5 toxicities
[149]
PD-1NivolumabPhase I/IIChildren/AYA
ST
HD or NHL
No objective responses in ST; 33% SD in sarcomas and 50% SD in neuroblastoma
36% grade 3–4 toxicities
[150]
PD1 +
CTLA-4
Nivolumab +
Ipilimumab
Phase IIR/R Pediatric ST2 PR in young adults;
4 SD
6 DLTs/55 eligible pts
[151]
PD1 +
CTLA-4
Nivolumab vs. Nivolumab +
Ipilimumab
Phase I/IIHigh-grade
pediatric CNS ST
No advantage of combined treatment
Acceptable toxicity
[151]
PD-1NivolumabPhase I/II
(active, not recruiting)
Pediatric patients with hypermutated ST 2 patients with adenoCa and astrocytoma with prolonged PR 02992964
[152]
PD-1Nivolumab +
Metronomic CY
Phase I/II
Pediatric patients with
R/R ST
2 unconfirmed PR
acceptable toxicity, mostly hematological
[152]
PD-L1AvelumabPhase IPediatric patients with
R/R ST
4 SD/21 pts enrolled;
no grade 4–5 toxicities
[152]
PD-L1AvelumabPhase IPediatric patients with
R/P osteosarcoma
n.a.03006848
PD-1Nivolumab +
Dinutuximab +
131-mIBG
Phase IPediatric patients with
neuroblastoma
n.a.02914405
PD-1NivolumabPhase I/IIPediatric and adult patients receiving allo-HSCT for Sarcomas n.a.03465592
PD-1Nivolumab +
chemotherapy
Phase I/IIPediatric patients with
R/R ST
n.a.03585465
PD-1NivolumabPhase I/IIR/R Pediatric STn.a.02901145
PD1 +
CTLA-4
Nivolumab +
Ipilimumab+ cryoablation
Phase IIR/R Pediatric STn.a.05302921
PD-1/
PD-L1
Anti PD-1 or PD-L1 + levantinibPhase II/IIIChildren with hepatoblastoman.a.05322187
#: number; ST: solid tumor; SD: stable disease; HD: Hodgkin’s disease; NHL: non-Hodgkin lymphoma; PR: partial response; AYA: adolescents and young adults; R/R: refractory/relapsed; DLT: dose-limiting toxicity; CNS: central nervous system; CY: cyclophosphamide; allo-HSCT: allogeneic hematopoietic stem cell transplantation; R/P: recurrent/progressive.
Table 3. Published (ref.) or ongoing (NCT number) clinical trials registered on clinicaltrials.gov as of January 2023 for representative CAR-T cell therapies in pediatric solid tumors.
Table 3. Published (ref.) or ongoing (NCT number) clinical trials registered on clinicaltrials.gov as of January 2023 for representative CAR-T cell therapies in pediatric solid tumors.
TargetPatient
Nr.
Study
Phase
Disease Clinical Results/
Toxicity
Reference/
NCT#
GD211Phase IR/R neuroblastoma3/11 CR
no DLT
[180,181]
GD211Phase IR/R neuroblastomano objective responses, 4 SD
(2 CR after additional treatment)
no DLT
[155]
GD212Phase IR/R neuroblastomano objective responses, 3 SD
no DLT
[180,181]
GD227Phase I/IIR/R neuroblastoma9 CR, 8 PR (36% 3-y EFS)
74% CRS (94% grade 1–2);
hematologic toxicities
[182]
GD2 * 3 **Phase IR/R neuroblastoma1 PR;
no DLT; hematologic toxicities
03294954
[180,181]
GD24 **Phase IChildren and adults with H3K27M-mutated gliomas3/4 pts had radiological/clinical benefit
Mild CRS; no on-target, off-tumor toxicity
04196413 [182]
GD2 * n.a.Phase IChildren and adults with R/R neuroblastoma or osteosarcoman.a. 03721068
HER219 **Phase I/IIChildren or AYA with R/R HER2+ sarcomasStudy ongoing;
2 CR (ongoing), 3 SD
no DLT
00902044
[182]
GPC3n.a.Phase IChildren or AYA with R/R GPC3-positive STn.a.
currently enrolling liver tumors
02932956
GPC3 * n.a.Phase IChildren or AYA with R/R GPC3-positive STn.a.04377932
GPC3 *** n.a.Phase IChildren or AYA with R/R GPC3-positive STn.a.04715191
EGFR11 **Phase IChildren or AYA with R/R EGFR-positive ST3 mixed responses;
no DLT
03618381
[163]
B7H39 **Phase IChildren or AYA with R/R STno objective responses; 3 SD
no DLT
04483778
[164]
B7H3n.a.Phase IChildren or AYA with R/R STn.a.04897321
#: number; * IL-15 expressing CAR-T; ** study ongoing; *** IL-15/IL-21 expressing CAR-T. GD2: disialoganglioside GD2; R/R: refractory/relapsed; CR: complete response; SD: stable disease; DLT: dose-limiting toxicity; PR: partial response; CRS: cytokine release syndrome; HER2: human epidermal growth factor receptor 2; AYA: adolescents and young adults; GPC3: glypican 3; ST: solid tumors; EGFR: epidermal growth factor receptor; B7H3: B7 homolog 3.
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Belgiovine, C.; Mebelli, K.; Raffaele, A.; De Cicco, M.; Rotella, J.; Pedrazzoli, P.; Zecca, M.; Riccipetitoni, G.; Comoli, P. Pediatric Solid Cancers: Dissecting the Tumor Microenvironment to Improve the Results of Clinical Immunotherapy. Int. J. Mol. Sci. 2024, 25, 3225. https://doi.org/10.3390/ijms25063225

AMA Style

Belgiovine C, Mebelli K, Raffaele A, De Cicco M, Rotella J, Pedrazzoli P, Zecca M, Riccipetitoni G, Comoli P. Pediatric Solid Cancers: Dissecting the Tumor Microenvironment to Improve the Results of Clinical Immunotherapy. International Journal of Molecular Sciences. 2024; 25(6):3225. https://doi.org/10.3390/ijms25063225

Chicago/Turabian Style

Belgiovine, Cristina, Kristiana Mebelli, Alessandro Raffaele, Marica De Cicco, Jessica Rotella, Paolo Pedrazzoli, Marco Zecca, Giovanna Riccipetitoni, and Patrizia Comoli. 2024. "Pediatric Solid Cancers: Dissecting the Tumor Microenvironment to Improve the Results of Clinical Immunotherapy" International Journal of Molecular Sciences 25, no. 6: 3225. https://doi.org/10.3390/ijms25063225

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