Neuroinflammation in Autoimmune Disease and Primary Brain Tumors: The Quest for Striking the Right Balance

Abstract

According to classical dogma, the central nervous system (CNS) is defined as an immune privileged space. The basis of this theory was rooted in an incomplete understanding of the CNS microenvironment, however, recent advances such as the identification of resident dendritic cells (DC) in the brain and the presence of CNS lymphatics have deepened our understanding of the neuro-immune axis and revolutionized the field of neuroimmunology. It is now understood that many pathological conditions induce an immune response in the CNS, and that in many ways, the CNS is an immunologically distinct organ. Hyperactivity of neuro-immune axis can lead to primary neuroinflammatory diseases such as multiple sclerosis and antibody-mediated encephalitis, whereas immunosuppressive mechanisms promote the development and survival of primary brain tumors. On the therapeutic front, attempts are being made to target CNS pathologies using various forms of immunotherapy. One of the most actively investigated areas of CNS immunotherapy is for the treatment of glioblastoma (GBM), the most common primary brain tumor in adults. In this review, we provide an up to date overview of the neuro-immune axis in steady state and discuss the mechanisms underlying neuroinflammation in autoimmune neuroinflammatory disease as well as in the development and progression of brain tumors. In addition, we detail the current understanding of the interactions that characterize the primary brain tumor microenvironment and the implications of the neuro-immune axis on the development of successful therapeutic strategies for the treatment of CNS malignancies.

Introduction

Inflammation is an adaptive response to infection or tissue injury that arises secondary to the activation of multifactorial networks comprising the innate and adaptive immune systems (Medzhitov, 2008). While historically highlighted for its role as a protector against invading pathogens, based on recent literature, it is now more appropriate to recognize inflammation as a response to any insult that disrupts normal tissue homeostasis (Medzhitov, 2008). The role of inflammation in defending against pathogens, responding to injury, tumor surveillance and maintaining homeostasis has been widely studied in the periphery. However, elucidating its contribution to central nervous system (CNS) homeostasis and, to some extent CNS pathologies, has lagged behind. This gap in knowledge is in part due to the previously held belief based on early experiments from mid 1900s (Medawar, 1948; Galea et al., 2007), that the CNS represented an immune-privileged environment protected behind an impenetrable blood-brain-barrier (BBB), devoid of any CNS resident professional antigen presenting cells (APC), with low expression of immune recognition molecules [e.g., major histocompatibility class (MHC- I and II) and the absence of classical lymphatic drainage system, Louveau et al., 2015a].

Since these initial studies, there has been significant advancement in our understanding of CNS micro-anatomy, physiology and immunology. Animal studies have clearly demonstrated that there are resident APCs in mouse brain (Dey et al., 2015) as well as the presence of a fully functional lymphatic system that lies within the meninges and drains into deep cervical lymph nodes (Andres et al., 1987; Aspelund et al., 2015; Louveau et al., 2015b) where CNS antigens have been shown to induce an immune response (Cserr et al., 1992). Together these studies have challenged the foundation of the old “immune privilege” dogma. A large body of recent literature suggests that inflammatory responses play a critical role in the maintenance of CNS homeostasis and response to injury (Gadani et al., 2015). However, immune responses in the CNS can have both beneficial or detrimental effects on CNS functionality based on the specific context in which they occur. Under physiologic conditions, transient inflammatory responses serve to facilitate CNS function, promote healing, and re-establish a homeostatic state (Coussens and Werb, 2002), while dysregulation of this response can result in exaggerated or chronic inflammatory states that potentiate disease pathogenesis (Coussens and Werb, 2002; Medzhitov, 2008). Within the CNS, pathological inflammation is associated with a wide range of conditions, including autoimmune neuroinflammatory disorders such as multiple sclerosis (MS) and antibody-mediated encephalitis (Ransohoff and Engelhardt, 2012; Dalmau and Graus, 2018; Brambilla, 2019). Furthermore, chronic inflammation or immune evasion is also known to drive tumorigenesis, and the same mechanisms that serve to maintain and restore CNS homeostasis can be hijacked to promote the initiation and propagation of primary CNS tumors such as glioblastoma (GBM) (Wang et al., 2018; Brandao et al., 2019; Piperi et al., 2019).

Despite their obvious differences, cancer and autoimmune disease share a similar fundamental mechanism of pathogenesis in which there is an excessive proliferation of pathogenic cells (e.g., tumor cells and autoreactive immune cells, respectively) occurring in combination with both local and systemic, chronic immune system dysfunction. In both settings, the scales have been tilted just enough to elicit such severe and chronic dysregulation that the physiologic regulatory mechanisms become incapable of restoring immunological balance. On a basic, fundamental level these two pathologies can be thought to represent the opposite extremes of the same spectrum, where on one end exists neuro-immune hyperactivity and on the other, suppression. However, the premise that these pathologies are characterized by polarization of the neuro-immune axis to either completely hypo- or hyper-activity is far too simplistic. Rather, the significant cellular heterogeneity, cellular plasticity, mechanistic non-redundancy (multiple, distinct mechanisms capable of producing same outcome) and functional redundancy (single mechanisms capable of producing multiple, distinct outcomes) of the neuro-immune axis permits for dynamic, context-specific responses that evolve over the course of both disease states. As such, the information gleaned from the study of autoimmune neuroinflammatory disorders may provide critical insight into how to most effectively manipulate the neuro-immune axis to mount an efficient anti-tumor response for the treatment of primary brain tumors such as GBM. Conversely, understanding how GBM so eloquently drives and maintains such profound immunosuppression in both the CNS and systemically may facilitate the development of treatments for autoimmune neuroinflammatory disorders.

In this review, we provide an overview of the neuro-immune axis in steady state and the mechanisms underlying chronic neuroinflammation in autoimmune neuroinflammatory disease as well as in the development and progression of primary brain tumors. While it should be noted that the neuro-immune axis plays an important role in a wide variety of CNS pathologies including, neurodegenerative diseases, metastasis and the spectrum of primary brain tumors, in this review, we highlight the complexities and context-specificity of neuro-immune axis disruption by focusing specifically on multiple sclerosis (MS) and glioblastoma, the most common neuroinflammatory disorder and primary brain tumor in adults, respectively. In addition, we detail the implications of therapeutically modulating neuro-immune axis in the development of successful immunotherapy for the treatment of CNS malignancies and autoimmune neuroinflammatory disorders by focusing on immunotherapeutic developments in the treatment of these two disease states.

Neuro-Immune Surveillance and CNS Steady State

The CNS microenvironment is comprised of unique anatomical and cellular components designed to minimize endogenous and exogenous threats that could compromise CNS function. To carry out this elegant task, the CNS microenvironment employs multiple distinct and parallel levels of regulation mediated by several anatomical interfaces that serve both unique and analogous functions as described in Figure 1.

FIGURE 1

Key Cellular Components

Although the anatomical interfaces limit access of many neuro toxic chemicals and cellular agents to the CNS parenchyma, there is still baseline immune surveillance and response to injury that occurs within the parenchymal compartment (Galea et al., 2007). This is largely carried out through concerted efforts of two CNS-resident specialized cell populations: microglia and astrocytes (Galea et al., 2007).

Astrocytes

Astrocytes are the most abundant glial cells in the CNS, and in steady state they perform a wide range of functions that are critical to CNS health (Sofroniew, 2009; Sofroniew and Vinters, 2010; Colombo and Farina, 2016; Linnerbauer et al., 2020). Notably, astrocytes are responsible for the maintenance of extracellular fluid, ion, and neurotransmitter homeostasis, as well as the modulation of synaptic function and remodeling (Sofroniew, 2009; Colombo and Farina, 2016). Astrocytes also play a critical role in supporting the integrity of the BBB and regulating immune cell trafficking within the CNS (Colombo and Farina, 2016; Linnerbauer et al., 2020). Furthermore, astrocytes themselves respond to disruptions of homeostasis through the secretion of cytokines and chemokines and, in response to CNS injury, also undergo a spectrum of heterogeneous morphological and functional changes (Sofroniew, 2009; Linnerbauer et al., 2020). This process, termed reactive astrogliosis, exists on a graded continuum in which the nature, severity, and type of CNS injury influences the outcome and, as such, reactive astrogliosis can have both beneficial and detrimental effects depending on specific context (Sofroniew, 2009, 2015; Colombo and Farina, 2016). Additionally, a recent elegant study conducted in adult mice and correlated with human astrocyte gene signatures suggests the existence of astrocytic subpopulations that demonstrate regional, cellular, molecular, and functional diversity (John Lin et al., 2017). Thus, it is likely a combination of timing, context, and the specific astrocyte subpopulation that determines how these cells contribute to the neuroinflammatory response (Sofroniew, 2009; Linnerbauer et al., 2020). Broadly, reactive astrocytes are classified as either pro-inflammatory/neurotoxic (A1) or anti-inflammatory/neuroprotective (A2) (Sofroniew, 2009, 2015; Sofroniew and Vinters, 2010; Liddelow et al., 2017). While much remains to be elucidated regarding the mechanisms underlying astrocytic phenotypic plasticity, the NF-kβ sphingosine 1-phosphate (S1P) receptor, JAK/STAT, and type 1 interferon (IFN-I) pathways have been implicated in the regulation of astroglial activation (Figure 2; Brambilla, 2019; Linnerbauer et al., 2020).

FIGURE 2

Microglia

Microglia, the resident macrophages of the CNS, are characterized by significant plasticity in both phenotype and function, which allows them to serve several critical roles in the maintenance of CNS homeostasis (Butovsky and Weiner, 2018). In resting state, microglia provide the baseline parenchymal immunity by surveilling the CNS for tissue damage and other threats to homeostasis (Suzumura et al., 1993; Colonna and Butovsky, 2017; Butovsky and Weiner, 2018; Prinz et al., 2019; Rodríguez-Gómez et al., 2020; Spittau et al., 2020; Zia et al., 2020). In response to disruptions of homeostasis, microglia were traditionally believed to assume either a pro-inflammatory/neurotoxic (M1) or anti-inflammatory/neuroprotective (M2) phenotype (Mosser and Edwards, 2008; Lawrence and Natoli, 2011; Landry et al., 2020). Recent evidence, however, suggests that the categorization of microglia into such polarized phenotypes is a drastic oversimplification. It is now understood that these phenotypes exist on a spectrum from neurotoxic (M1) to neuroprotective (M2) (Lawrence and Natoli, 2011; Hu et al., 2015). A more recent study in which single microglial cells isolated from multiple anatomical regions within the mouse CNS were analyzed, further identified distinct subpopulations of microglia present during homeostasis (Masuda et al., 2019). These microglial subpopulations are characterized by unique transcriptional programs that exist on a continuum rather than in discrete clusters (Masuda et al., 2019). While the precise molecular determinants responsible for this continuum of functional outcomes have not been completely elucidated, significant advances in our understanding of the transcriptional regulation of microglial polarization have been made as reviewed in Lawrence and Natoli (2011). Important factors and pathways that have been implicated in microglial polarization are illustrated in Figure 2. However, it is important to recognize that the process of microglial polarization is highly context-specific, and the spectrum of observed phenotypes may reflect activation of specific pathways by distinct stimuli, as well as crosstalk between various pathways (Lawrence and Natoli, 2011).

Neuroinflammation: A Systematic Protective Response or an Uncontrolled Destructive Phenomenon

The post-mitotic nature of the brain’s most vital constituents, the neurons, makes them extraordinarily vulnerable to damage from which recovery would require a significant degree of regenerative capacity. The uniquely protective CNS environment created by anatomical and cellular components serves not as an absolute barrier, but as a dynamic regulatory system that facilitates optimal CNS function through the maintenance of a homeostatic state. Disruptions of homeostasis or manipulation of the neuro-immune axis by pathological processes, however, trigger the adaptive response of neuroinflammation. Neuroinflammation, which is mediated by cytokines, chemokines, and other factors produced by CNS-resident as well as peripherally derived cells, occurs to varying degrees of severity and in a highly disease- and context-specific manner (DiSabato et al., 2016). While transient, acute inflammatory responses against CNS targeting pathogens such as bacteria and viruses can be life-saving, uncontrolled, dysregulated and misdirected neuroinflammatory responses against CNS pathogens and antigens can have devastating consequences such as bacterial/viral encephalitis and autoimmune diseases (DiSabato et al., 2016).

Autoimmune Neuroinflammatory Disorders

Multiple sclerosis (MS), the most common neuroinflammatory disorder in adults, is a chronic autoimmune disease in which immune-mediated pathological CNS inflammation results in focal regions of demyelination and diffuse neurodegeneration (Lassmann, 2018). The inciting events that trigger the development of MS and the corresponding murine disease, experimental autoimmune encephalomyelitis (EAE), are incompletely understood. Two major theories, however, attempt to explain MS/EAE pathogenesis: (1) the CNS-extrinsic model, which proposes that peripherally activated autoreactive T-cells enter into circulation and subsequently gain access to the CNS by breaching one of the regulatory interfaces and (2) the CNS-intrinsic model, where the autoreactive T lymphocytes are hypothesized to infiltrate the CNS secondary to an inflammatory response initially triggered within the brain parenchyma (Dendrou et al., 2015). While these theories posit that T-cells act as the drivers of neuroinflammation in this context, recent studies demonstrating the efficacy of B-cell depleting therapies in limiting MS relapses have shifted attention toward further understanding MS as a disease of both the T- and B-cell compartment (Bar-Or et al., 2008; Hauser et al., 2008). Recent literature suggests that the chronic neuroinflammation that occurs in MS is the result of deregulated inflammatory responses occurring in both the periphery and within the CNS (Lassmann, 2003; Magliozzi et al., 2010; Michel et al., 2015). These findings thus, highlight the close integration of the central and peripheral immune systems, which may serve both distinct and parallel functions within the two compartments. Systemic immunologic dysfunction in patients with MS is characterized by impaired regulatory T-cell (T_Reg) mediated suppression and the aberrant activation of peripheral immune cells, which subsequently infiltrate the CNS where they undergo reactivation (Kaskow and Baecher-Allan, 2018; Li et al., 2018).

The involvement of peripherally derived immune cells in MS/EAE pathogenesis is dependent on their ability to infiltrate the various compartments of the CNS, which can be accomplished by disrupting three routes: the BBB, the blood-meningeal barrier (BMB), and the blood-CSF barrier (BCSFB). It remains unknown, however, specifically which of these barriers is initially breached in MS/EAE. Disruption of the BBB is thought to be an early event in the development of MS/EAE, and episodes of recurrent BBB leakage occur over the course of the disease via multiple mechanisms (Argaw et al., 2012; Niu et al., 2019; Uchida et al., 2019; Zeitelhofer et al., 2020). Whether this impairment is an inciting event or secondary to another event that triggers pro-inflammatory cascade remains unknown. Recent evidence suggests that meningeal lymphoid aggregate formation may facilitate the production of inflammatory cytokines and chemokines which serve to activate CNS-resident astrocytes and microglia as well as facilitate the recruitment and activation of additional immune cells (Pikor et al., 2015). Given the evidence demonstrating microglial and astrocytic reactivity prior to appreciable immune infiltrate, it is possible that activation of these cells also provides the catalyst necessary to recruit peripheral immune cells into the brain parenchyma by way of compromised BBB and BMB integrity (D’Amelio et al., 1990; Wang et al., 2005; Pham et al., 2009; Zrzavy et al., 2017).

Key Cellular Components

Within the CNS, the neuroinflammatory response occurs in a compartmentalized fashion with chronically activated microglia and other immune cell (summarized in Table 1) aggregates within the meninges and brain parenchyma contributing uniquely to MS/EAE pathogenesis (Magliozzi et al., 2007, 2010; Zrzavy et al., 2017; Figure 3).

FIGURE 3

Astrocytes

Astrocyte reactivity begins during the earliest stages of MS lesion formation and persists even after immune cells retreat (Brambilla, 2019). In MS/EAE signs of astrocyte activation are noted even before CNS immune infiltration (D’Amelio et al., 1990; Wang et al., 2005; Pham et al., 2009). Astrocytes localized to the leading edges of active lesions exhibit intracellular lipid inclusions, reflective of their role in the phagocytosis of myelin debris, whereas those adjacent to immune cell infiltrates demonstrate increased reactivity (Ponath et al., 2017, 2018). In chronic lesions, astrocytes demonstrate a persistent, but diminished reactivity and concentrate at the lesion rim (Brosnan and Raine, 2013; Brambilla, 2019). As chronic lesions become inactive, the astrocytes acquire GFAP+ filaments suggesting astroglial scar formation, which serves as an attempt to limit neurotoxic inflammation (Brambilla et al., 2009; Brosnan and Raine, 2013; Ludwin et al., 2016; Ponath et al., 2018). Beyond the lesions, astrocytes of the adjacent gray and white matter also demonstrate persistent signs of subtle activation (Brambilla, 2019). Astrocytes play a neuroprotective role early in disease by restricting the infiltration of immune cells, likely through maintenance of BBB integrity and FasL-mediated T-cell apoptosis (Choi et al., 1999; Voskuhl et al., 2009; Wang et al., 2013; Mayo et al., 2014) and conversely, astrocyte depletion during the chronic phase of disease produces improved outcomes and decreased CNS leukocyte infiltration, suggesting a deleterious role later in disease pathogenesis (Mayo et al., 2014). A more recent study utilizing FACs-isolation of astrocytes from distinct anatomical regions in the setting of EAE, supports the above findings by providing additional evidence that, during the neuroinflammatory response, astrocytes exist as a heterogeneous population characterized by unique transcriptional profiles suggestive of distinct functions (Borggrewe et al., 2021). Furthermore, Borggrewe et al. (2021) found that the unique transcriptional response of astrocyte subsets exhibited additional variation depending on the stage of disease and anatomical location (e.g., acute vs. chronic). Astrocytes isolated from the spinal cord of mice with EAE demonstrated decreased expression of genes associated with a homeostatic signature including, those involved in maintenance of the BBB, cholesterol synthesis and neuronal support (Itoh et al., 2018; Borggrewe et al., 2021). Not surprisingly, genes involved in neuroinflammation and neurotoxicity were noted to be increased (Itoh et al., 2018; Wheeler et al., 2020; Borggrewe et al., 2021). Conversely, during chronic stages gene expression signatures were consistent with a proliferative profile, which may reflect the transition to a regenerative/protective phenotype (Borggrewe et al., 2021).

Microglia

In active MS/EAE lesions, microglia with a pro-inflammatory/neurotoxic (M1) phenotype predominate in the early stages of demyelination (Zrzavy et al., 2017). These microglia express molecules involved in phagocytosis, antigen presentation, T-cell co-stimulation, and oxidative injury (Zrzavy et al., 2017; Böttcher et al., 2020). Additionally, they exhibit decreased expression of the homeostatic genes P2RY12, TMEM119, CX3CR1, and GPR56 (Zrzavy et al., 2017; Böttcher et al., 2020). Recent data suggests that IgG immune complexes (IgG-IC) bound to myelin may activate microglia by decreasing toll-like receptor (TLR) tolerance in an FcyRI and FCyRIIa-dependent manner (van der Poel et al., 2020). When stimulated with both the TLR3 agonist Poly I:C and IgG-IC these microglia demonstrate increased production of pro-inflammatory chemokines and cytokines (van der Poel et al., 2020). As the lesion progresses, peripheral macrophages are increasingly recruited and, along with resident microglia, adopt an intermediate phenotype between neurotoxic (M1) and neuroprotective (M2) (Zrzavy et al., 2017). Progression of the lesion to a slowly expanding or chronic lesion, is characterized by a decrease in the total density of microglia/macrophages with the remaining phagocytes localizing to the lesion rim where they are noted to contain products of myelin degradation and characterized predominantly by an M1-phenotype (Zrzavy et al., 2017; Jäckle et al., 2020). The density of macrophage- and microglia-like cells significantly decreases in completely inactive lesions and microglial P2RY12 expression reappears. Interestingly, despite P2RY12 expression, a majority of these cells also express markers associated with a neurotoxic (M1) activation phenotype (Zrzavy et al., 2017). These temporal and regional changes are reflective of the specific cellular functions. Early in disease, a neurotoxic (M1) phenotype predominates, reflecting microglial response to an acute disruption of CNS homeostasis (Zrzavy et al., 2017). Myelin phagocytosis promotes polarization to a neuroprotective (M2) phenotype, with the maximum expression of M2-like markers detected in the lesion core where re-myelination begins (Zrzavy et al., 2017). These microglia produce cytokines involved in the resolution of inflammation and tissue repair including interleukins (IL-) 4, 10, 13, and 33, as well as transforming growth factor beta (TGF-β) (Chu et al., 2018). Conversely, cells at the periphery possess a phagocytic phenotype (Zrzavy et al., 2017).

Interestingly, microglial reactivity is not restricted to MS lesions, as the normal appearing white matter (NAWM) of MS patients is characterized by a reduced number of microglia expressing P2RY12 and a moderate increase in pro-inflammatory markers (Zrzavy et al., 2017). While this may be reflective of the diffuse effects of a chronic inflammatory environment, it may also indicate adjacent leptomeningeal inflammation, which has shown to occur in some patients with MS and to be associated with adjacent cortical demyelination (Absinta et al., 2015). However, despite exhibiting an activated phenotype, studies have found that microglia within the NAWM of MS brains exhibit a decreased inflammatory responsiveness (Guerrero and Sicotte, 2020). This finding was true of both acute and chronic disease, suggesting that the chronic inflammatory environment may induce a persistent hypo-responsive activated state in microglia of the NAWM, distant from focal lesions (Zrzavy et al., 2017; Guerrero and Sicotte, 2020).

Elucidating the specific contributions of microglia to MS/EAE pathogenesis has been complicated by the inability to distinguish CNS-infiltrating bone marrow-derived monocytes (BMDM) from CNS-resident microglia (Böttcher et al., 2020). Recent technological advances permitting analysis at the single-cell level (reviewed in Papalexi and Satija, 2018) have not only allowed for this distinction, but have also provided greater insight into the mechanisms underlying the vast cellular plasticity and heterogeneity of CNS-resident microglia (Masuda et al., 2019; Böttcher et al., 2020). These studies, which are reviewed extensively in Miedema et al. (2020), provide additional evidence that discrete microglial subsets perform multiple, unique functions and contribute to MS/EAE disease pathogenesis through the temporal regulation of disease- and context-specific gene expression programs (Masuda et al., 2019; Böttcher et al., 2020).

Bone Marrow-Derived Monocytes

Bone marrow-derived monocytes are recruited to the inflamed CNS and, upon entry, assume a range of phenotypes that share extensive similarities with CNS-resident microglia (Plemel et al., 2020). While studies in EAE suggest that microglial activation is important for initiation of EAE, disease progression is reported to depend largely on BMDMs (Brosnan et al., 1981; Huitinga et al., 1990; Bauer et al., 1995; Ponomarev et al., 2005). These studies are in agreement with human data, which suggests that early disease is characterized by significant microglia activation with little to no bone marrow-derived phagocytes present in newly forming lesions (Barnett and Prineas, 2004). The concept of temporally distinct roles for microglia and BMDMs in disease pathogenesis is further supported by work of Ajami et al. (2011) which demonstrates that increased infiltration of BMDMs corresponds with a marked decrease in CNS-resident microglia in mice during more severe stages of EAE. Additionally, in the early stages of EAE, increased infiltration of BMDMs has been suggested to correlate with increased disease severity (Ajami et al., 2011; Lewis et al., 2014). Interestingly, Plemel et al. (2020) recently found that, while BMDMs acutely infiltrate the CNS in response to demyelinating injury, microglia demonstrate a progressive predominance within the lesions and their ablation results in the increased accumulation of BMDMs. The results of this study suggest that microglia may play a protective role by limiting the infiltration and function of BMDM through regulation of their recruitment, entry, proliferation and survival (Ajami et al., 2011; Plemel et al., 2020).

As with microglia, elucidating the specific contributions of BMDMs to MS/EAE pathogenesis has been complicated by their existence as a heterogeneous, highly plastic population that has proven difficult to distinguish from other cellular compartments (Plemel et al., 2020). Recent evidence suggests the possibility that previous studies may have misidentified CNS-resident microglia as BMDMs (Plemel et al., 2020). There is also evidence to suggest that early in development and during states of chronic neuroinflammation, CNS-infiltrating BMDMs may acquire expression of markers conventionally thought to be restricted to microglia (Caravagna et al., 2018; Grassivaro et al., 2020). Additionally, it was historically believed that BMDMs served as precursors to terminally differentiated macrophages (Mφ) and dendritic cells (DCs) (Guilliams et al., 2018). Recent advances in our understanding of monopoiesis, suggest that circulating monocytes possess functional properties prior to infiltrating the tissues and that monocyte-derived cells recruited to areas of inflammation represent a population of cells that is distinct from both DCs and tissue resident Mφs (Guilliams et al., 2018). Thus, studies in which peripherally derived monocytes and macrophages were evaluated as a single entity may suggest the presence of heterogeneous subsets rather than distinct cellular compartments.

Advances in both technology and understanding have begun to shed light on the contribution of BMDMs to the neuroinflammatory response. In vivo imaging studies suggest that BMDMs, like microglia and astrocytes, adapt their phenotype in a temporally and regionally dependent manner (Locatelli et al., 2018). Furthermore, through the use of massively parallel single-cell RNA-sequencing (MARS-seq) Giladi et al. (2020) identified eight distinct monocyte subsets infiltrating the inflamed CNS of mice with EAE in a disease stage-dependent manner and suggest that pathogenicity may be specific to certain monocyte subpopulations (e.g., Cxcl10+). This premise that specific BMDM subsets may assume divergent roles is in agreement with the finding that BMDMs may also adopt suppressive, immunoregulatory phenotypes (Zhu et al., 2007; Giladi et al., 2020). The results of these studies, in combination with the varied effects of BMDM depletion at different stages of EAE, further underscore the importance of understanding the context-specific contributions of this heterogeneous cellular compartment (Brosnan et al., 1981; Huitinga et al., 1990; Moreno et al., 2016).

T Lymphocytes

In steady-state, T-cells are essentially absent from the brain parenchyma and, thus their contribution to the maintenance of CNS homeostasis has remained relatively unexplored (Prinz and Priller, 2017). In MS, T cells are detected early within parenchymal lesions and autoreactive CD4⁺ T-cells are also present in the circulation and lymph nodes of MS patients (Bielekova et al., 2004; Prinz and Priller, 2017). Several distinct effector T-cell subsets have been implicated in the pathogenesis of MS/EAE, and details of their involvement are outlined in Table 1. Importantly, in human MS patients, MHC class I restricted CD8+ T cells predominate in lesions of all stages of human disease, whereas CD4+ T cells predominate in EAE (Machado-Santos et al., 2018). T cell infiltration is significantly higher in early stages of MS compared with progressive disease and also in active verses inactive lesions (Machado-Santos et al., 2018). Furthermore, features associated with tissue-resident memory cells, including CD8α/α double positivity, are noted to characterize a majority of CD8+ T cells in human MS lesions (Machado-Santos et al., 2018).

In addition to the autoreactivity of the CD4+ and CD8+ T-cells, effector T-cells isolated from MS patients demonstrate resistance to the suppressive functions of regulatory T-cells (Kaskow and Baecher-Allan, 2018). This is thought to occur as a result of both an intrinsic resistance of effector T-cells as well as suppression of regulatory T cell function by cytokines within the neuroinflammatory milleu (e.g., IL-6, IL-7, IL-18, IL-15, and TNF-α) (Walker, 2009). A recent study in EAE, found that Piezo1, a mechanosensitive ion channel known for its role in the inflammatory response to bacterial pathogens and cancer, may contribute to MS/EAE pathogenesis through selective repression of regulatory T cells (Jairaman et al., 2021). Accordingly, deletion of Piezo1 in regulatory T cells significantly attenuated EAE disease severity (Jairaman et al., 2021).

Dendritic Cells (DCs)

Dendritic cells, the professional antigen presenting cells, are thought to contribute to both the resolution and pathogenesis of autoimmune neuroinflammatory disease through functions in the periphery and within the CNS (Dittel et al., 1999; Bossù et al., 2015; Mitchell et al., 2018). In the periphery, activation of autoreactive CD4⁺ T-cells by classical DCs (cDCs) promotes their differentiation into effector T_h1 and T_h17 cells, which can subsequently infiltrate the CNS (Diebold, 2008). In contrast, plasmacytoid DCs (pDCs) appear to primarily limit neuroinflammation in the setting of MS/EAE. Specifically, pDCs have been shown to suppress cDC-dependent induction of T_h17 and T_h1 responses (Bailey et al., 2006, 2007; Stasiolek et al., 2006; Bailey-Bucktrout et al., 2008). Furthermore, pDCs isolated from the peripheral blood of patients with MS exhibited an immature phenotype characterized by impaired stimulatory capacity and IFN-α production, suggesting an immunosuppressive phenotype (Bailey et al., 2006, 2007; Stasiolek et al., 2006; Bailey-Bucktrout et al., 2008).

While the process of CNS antigen presentation remains poorly understood, recent evidence suggests that cDCs may contribute to autoimmune neuroinflammatory disorder pathogenesis by migrating from the brain parenchyma to the deep cervical lymph nodes where they prime autoreactive T-cells in a CCR7-dependent manner (Clarkson et al., 2017). Although the presence of resident DCs in the human CNS parenchyma at steady-state has not been proven conclusively, our group previously identified resident cDCs and pDCs in equal proportion in the brain parenchyma of mice at steady state (Dey et al., 2015). In response to disruptions of CNS homeostasis, cDCs and pDCs readily accumulate in the choroid plexus, leptomeninges, and perivascular space (McMenamin, 1999; Pashenkov et al., 2001; Bailey et al., 2007; Mitchell et al., 2018; Jordão et al., 2019). In the context of MS, in addition to the CSF, cDCs infiltrate white matter lesions and the leptomeninges (Serafini et al., 2006; Lande et al., 2008). The trafficking of DCs into the CNS is thought to primarily promote T-cell antigen reconfirmation upon CNS entry, which induces their production of pro-inflammatory cytokines (e.g., IL-2, IFNγ, and TNFα) and chemokines (e.g., CCL3 and CCL5) (Bailey et al., 2006, 2007; Goverman, 2009; Prodinger et al., 2011). A recent study utilizing single-cell analysis also found that CNS-cDCs demonstrated increased expression of MHCII compared to peripheral blood cDCs in patients with MS, suggesting that these CNS-cDCs are functionally primed for antigen-presentation and activation of autoreactive T-cells (Esaulova et al., 2020). In addition to their role as antigen-presenting cells, cDCs promote CD8⁺ T-cell responses and the differentiation of T_h17 through the secretion of pro-inflammatory cytokines including IL-1β, IL-6, IL-13, and TGF-β (Codarri et al., 2011; El-Behi et al., 2011; Luessi et al., 2016; Malo et al., 2018).

B Lymphocytes

In addition to immunoglobulin synthesis, B-cells can also function as antigen presenting cells, and they are especially critical for the priming of T-cells in the periphery when antigen concentrations are low (Pierce et al., 1988; Rivera et al., 2001). The success of B-cell depleting therapies in limiting relapses and the identification of B-cell-rich immune cell aggregates in the meninges, parenchyma and/or CSF in patients with MS has drawn attention to the potential role of B-cells as contributors to MS neuroinflammation in both the periphery and CNS (Magliozzi et al., 2007). The B-cells found within the CNS are largely class-switched memory B-cells and demonstrate increased clonal expansion in the CSF compared to the blood suggesting that an antigen-driven selection process drives the accumulation of B-cells in CNS compartments (Cepok et al., 2006). In the periphery, B-cells can drive aberrant activation of autoreactive T-cells that will subsequently infiltrate the CNS. Additionally, B-cells sharing clonality with those populating the CNS have been demonstrated in the draining cervical lymph nodes of MS patients (Palanichamy et al., 2014; Stern et al., 2014). This is of particular interest as it could provide a mechanism for the “epitope spread” seen in some patients with MS (McMahon et al., 2005; Quintana et al., 2014). Epitope spread refers to a phenomenon in which additional epitopes are released secondary to CNS damage resulting in a shift in the attack toward different antigenic targets and may explain the diffuse cortical damage and progressive nature some types of MS (McMahon et al., 2005; Quintana et al., 2014).

The above studies highlight the significant complexity of the neuroinflammatory response, which arises as a consequence of the vast heterogeneity and plasticity of the individual components comprising the neuro-immune axis. The contribution of the above cell types to MS/EAE pathogenesis is characterized by both marked temporal and regional heterogeneity, allowing for the acquisition of both protective and deleterious phenotypes in a highly context specific manner (Plastini et al., 2020). Accordingly, studies have demonstrated that the broad depletion or manipulation of specific cellular subsets can have both therapeutic and detrimental effects depending on a range of factors including, disease stage (Brosnan et al., 1981; Huitinga et al., 1990; Moreno et al., 2016). These and the above findings emphasize that the development of effective therapeutic strategies relying on the manipulation of components of the neuro-immune axis will greatly depend on understanding the development, recruitment, regulation, interactions and functions of above cellular components during specific stages of neuroinflammatory disease.

Primary Brain Tumor and Exploitation of Neuroinflammation

The contributions of the individual components of the neuro-immune axis to the neuroinflammatory response exhibit significant disease-specificity. However, despite these disease-specific differences, the fundamental characteristics of significant cellular heterogeneity, cellular plasticity, mechanistic non-redundancy (multiple, distinct mechanisms capable of producing same outcome) and functional redundancy (single mechanisms capable of producing multiple, distinct outcomes) are shared across the range of pathologies. Accordingly, when co-opted by tumors, the neuroinflammatory response can directly promote tumor progression and survival (Mantovani et al., 2008). Throughout the stages of tumor development, host inflammatory responses make distinct contributions through both pro- and anti-tumorigenic effects (Greten and Grivennikov, 2019). These complex interactions between the components of the host inflammatory response, surrounding stroma, and developing tumor create a survival niche known as the tumor microenvironment (TME) (Greten and Grivennikov, 2019).

Key Cellular Components

Glioblastoma (GBM), the most common primary brain tumor in adults, is one of the deadliest cancers and it develops in relatively “immune privileged” CNS environment behind the BBB where it is known to generate a highly immunosuppressive TME (DeCordova et al., 2020). Unlike autoimmune neuroinflammatory disease in which uncontrolled hyperactivity of the immune system results in neurotoxicity, in the context of GBM, the neoplastic cells induce structural and functional changes or damage to the surrounding CNS tissue by actively influencing and manipulating the neuro-immune axis towards a suppressive phenotype. In order to carry out such an elegant task, glioma cells secrete a variety of cytokines, chemokines, and growth factors, which allows them to recruit and hijack cells both within the CNS and the periphery (Table 2). These non-neoplastic cells work in concert to create a unique immunosuppressive microenvironment that promotes tumor growth, survival, and invasion (Hattermann et al., 2014; Broekman et al., 2018; Brandao et al., 2019; DeCordova et al., 2020; Mohme and Neidert, 2020; Wang et al., 2021) (Figure 4; summarized in Table 3).

FIGURE 4

Astrocytes

Although the exact sequence of events leading to the formation of GBM are unknown, GBM cells demonstrate morphological features and expression of lineage markers consistent with an immature astrocytic phenotype, thus suggesting that astrocytes or their progenitors, unbound by usual mechanisms of cell cycle regulation, may serve as the cell of GBM origin (Zong et al., 2012). Thus, the potential astrocytic origin of GBM tumors has complicated elucidating the contribution of non-neoplastic astrocytes to tumorigenesis. Studies, however, suggest a difference in transcriptional programs may allow for the distinction between GBM cells and non-neoplastic or glioma-associated astrocytes (GAAs) (Zhang et al., 2016; Henrik Heiland et al., 2019). In a recent study utilizing single cell RNA-seq based gene expression analysis, Henrik Heiland et al. (2019) characterized the transcriptional phenotype of reactive astrocytes isolated from the GBM tumor core and non-infiltrated brain regions of human GBM patients. To validate their findings, these results were compared to a previous report by Darmanis et al. (2017) and low rates of tumor cell contamination were determined by calling copy number variations in purified astrocytes and tumor cells (Henrik Heiland et al., 2019). Consistent with previous findings, the authors noted that GAAs fall into two clusters: (1) those resembling progenitors (progenitor phenotype) and (2) those consistent with a mature, anti-inflammatory (A2) phenotype (Zhang et al., 2016; Henrik Heiland et al., 2019). Furthermore, in a pattern similar to MS, these GAAs also demonstrate intratumoral regional specificity with those within the tumor core resembling progenitors, whereas those localized to the tumor periphery exhibiting a mature, anti-inflammatory astrocytic profile characterized by CD274⁺, glial fibrillary acidic protein (GFAP⁺) and upregulation of A2 associated genes (Zhang et al., 2016; Henrik Heiland et al., 2019).

Henrik Heiland et al. (2019) further demonstrated that GAAs exhibit a significant increase in both IFNγ-response and JAK/STAT3 signaling, and their interactions with microglia drive them toward a pro-tumor phenotype. STAT3-activated GAAs promote tumor progression by contributing to the immunosuppressive microenvironment through the secretion of pro-tumor cytokines, upregulation of programmed death ligand-1 (PD-L1/CD274), reprogramming of microglia toward an anti-inflammatory (M2) phenotype, and facilitating glioma cell adaption to exploit the hypoxic conditions of the surrounding TME (Malo et al., 2018; Brandao et al., 2019; Henrik Heiland et al., 2019). Additionally, STAT3 signaling is thought to be important for glial scar formation, suggesting the possibility that GAAs at the tumor periphery are attempting to contain the tumor, but their pro-tumor properties are hijacked instead (Sofroniew, 2009). Dysregulation of STAT3 signaling has been implicated in MS/EAE pathogenesis secondary to its role in TH17 cell differentiation and activation of autoreactive T cells (Lu et al., 2020). Accordingly, targeting distinct components of the STAT3 signaling cascade may be therapeutic in both disease states. Lastly, Biasoli et al. (2014) demonstrated that astrocytes grown in GBM-conditioned media exhibited reduced p53 expression in response to etoposide induced-DNA damage as well as in control conditions. This finding has important implications not only with respect to the role of GAAs in supporting tumor growth, but also poses the question of whether GBM-mediated astrocytic p53 dysfunction promotes the malignant transformation of astrocytes exposed to the TME.

Tumor-Associated Microglia/Macrophages (TAMs)

Lineage-tracing experiments conducted in mice suggest that TAMs can arise from both CNS-resident microglia and BMDMs (Bowman et al., 2016; Chen et al., 2017). Previous studies have not always distinguished between microglial- or BMDM-derived TAMs and despite the identification of potential markers (e.g., CD49D, CD141, CD45A, and ICAM) emerging evidence suggests that accurately distinguishing microglia from BMDMs within the inflamed CNS may be particularly challenging (Bowman et al., 2016; Caravagna et al., 2018; Friebel et al., 2020; Grassivaro et al., 2020; Plemel et al., 2020). As such, unless otherwise specified, we will use TAM to refer to cells of both microglial- or BMDM origin in the remainder of this section. It is important to note, however, that microglial- and BMDM-derived TAMs are characterized by both overlapping and distinct transcriptional programs, resulting in unique tumor-mediated responses (Bowman et al., 2016; Friebel et al., 2020; Klemm et al., 2020). Thus, distinguishing between TAMs of specific origin will be important in future studies.

Tumor-associated microglia/macrophages comprise, on average, 45% (range: 8 to 78%) of the GBM tumor bulk and play a critical role in tumor initiation, proliferation, invasion and survival (Coniglio et al., 2012; Hattermann et al., 2014; Szulzewsky et al., 2015; Zeiner et al., 2019; Landry et al., 2020). In terms of polarization, TAMs that adopt an M2 phenotype within TME are shown to promote tumor survival through the secretion of the immunosuppressive cytokines, TGF-β, IL-4, and IL-10 (Mosser and Edwards, 2008). Accordingly, studies have shown that TAMs express markers of M2 polarization (i.e., CD206 and CD163) and produce anti-inflammatory cytokines IL-10 and TGF-β (Hambardzumyan et al., 2016). Recent studies, however, have described intratumoral TAMs exhibiting mixed M1/M2 gene signatures characterized by the upregulation of M2 molecule expression and a parallel predominance of M1 cytokine expression (Hattermann et al., 2014; Szulzewsky et al., 2015; Gabrusiewicz et al., 2016; Hambardzumyan et al., 2016; Zeiner et al., 2019; Yin et al., 2020) suggesting that TAMs exist in heterogeneous populations with phenotypes spanning the spectrum from M1 to M2.

Glioblastoma cells secrete several chemoattractants, which serve to recruit TAMs to the GME where other glioma-derived factors will subsequently drive these cells to assume pro-tumor phenotypes characterized by the production of tumor-promoting factors (Suzumura et al., 1993; Taniguchi et al., 2000; Mitrasinovic et al., 2001; Mantovani et al., 2002; Nakano et al., 2008; Held-Feindt et al., 2010; Li and Graeber, 2012; Pyonteck et al., 2013). While the specific mechanisms underlying the adoption of tumor-supporting TAM phenotypes are incompletely understood, activation of the STAT3 signaling pathway appears to play a predominant role (Li and Graeber, 2012). Multiple factors in the TME have been shown to activate STAT3-signaling, including IL-6 and IL-10 (Li and Graeber, 2012). Inhibition of STAT3 signaling in microglia is associated with a shift to an anti-tumor phenotype characterized by an increase in co-stimulatory molecule expression, decreased production of IL-10, and increased expression of pro-inflammatory cytokine TNF-α (Li and Graeber, 2012). Additionally, recent work has implicated peroxisome proliferator-activated receptor gamma (PPARγ) activation in the regulation of TAM tumor response (Wang et al., 2018). In one study, Wang et al. (2018) demonstrated that populations of CD206+ macrophages localized in close proximity to tumor-associated vascular endothelial cells, which, in combination with colony stimulating factor 1 (CSF-1), induce their polarization to a tumor-supportive phenotype through IL-6 induction of hypoxia inducible factor 1 alpha (H1F-1α)-dependent PPARγ activation. These findings also highlight the fact that, even within the tumor, microglia adapt their phenotypes in response to their local microenvironment. In a pattern reminiscent of MS lesions, microglia located within the tumor core and those localized to the rim exhibit different phenotypes (Morimura et al., 1990; Badie and Schartner, 2001; Li and Graeber, 2012; Zrzavy et al., 2017). Microglia within the area of tumor necrosis exhibit the highest expression of markers associated with antibody-dependent cell-mediated cytotoxicity, whereas those localized to the tumor periphery exhibit increased expression of molecules suggestive of phagocytic capacity, such as complement CR3 (Morimura et al., 1990; Badie and Schartner, 2001; Li and Graeber, 2012). Interestingly, the number of CR3-expressing cells positively correlates with the proliferative rate of GBM, suggesting that these phagocytic microglia are pro- rather than anti-tumor (Li and Graeber, 2012).

Microglia within the NAWM of MS brains exhibit a decreased inflammatory responsiveness, which is likely reflective of chronic stimulation (Guerrero and Sicotte, 2020). Not surprisingly, TAMs also exhibit an impaired pro-inflammatory response (Biswas et al., 2006; Li and Graeber, 2012). Under physiologic conditions, activation of microglial/macrophage toll-like receptors (TLRs) induces NF-kβ and mitogen-activated protein kinase (MAPK) signaling to stimulate the production of pro-inflammatory cytokines. However, despite expression of TLRs and their corresponding co-receptors (e.g., CD14, co-receptor for TLR4), glioma-associated TLR-expressing microglia do not produce anti-tumor cytokines (Li and Graeber, 2012) suggesting the possibility that, in addition to direct suppression of anti-tumor phenotypes, chronic stimulation of microglia likely contributes to an impaired anti-tumor response, perhaps in a mechanism shared with autoimmune neuroinflammatory disease.

Together these findings suggest that TAMs mirror the cellular plasticity and context-specificity of the microglia/BMDMs described in the neuroinflammatory response seen in MS/EAE. Accordingly, more recent studies suggest that TAMs are characterized by distinct transcription programs that are dependent on the underlying disease (e.g., type of tumor) and cellular origin (e.g., MG vs. BMDM) (Klemm et al., 2020). Furthermore, Klemm et al. (2020) found that distinct TAM subsets possessed unique functions which likely contribute to the immunosuppressive TME in a collective fashion. Glioma-associated microglia have also been reported to exhibit decreased expression of microglial homeostatic markers P2RY12 and TMEM119 and increased expression of inflammatory genes, findings consistent with those reported in microglia from NAWM in patients with MS (Zrzavy et al., 2017; Sankowski et al., 2019).

Despite the presence of TAMs with dual ontogeny, results from two recent studies suggest microglia-derived TAMs demonstrate a predominance in glioma tumors, findings reminiscent of those reported by Plemel et al. (2020) in which microglia were also shown to predominate in lesions of demyelination (Masuda et al., 2019; Friebel et al., 2020). Consistent with these findings, a recent study utilizing scRNA-seq and CITE-seq found that microglial-derived TAMs predominated in newly diagnosed tumors, whereas BMDM-derived TAMs predominated in recurrent tumors (Pombo Antunes et al., 2021). Interestingly, these TAM populations appear to compete with each other as interfering with monocyte infiltration triggered a compensatory increase in microglial-derived TAMs (Pombo Antunes et al., 2021). This phenomenon is also consistent with that reported by Plemel et al. (2020) in which the depletion of microglia resulted in an increased accumulation of BMDMs. These findings may explain the dichotomy between newly diagnosed and recurrent tumors as it is possible that either therapies, such as radiotherapy, used in the treatment of the initial tumor or changes in the TME associated with recurrent tumors may compromise microglia such that they cannot outcompete BMDM-derived TAMs (Plemel et al., 2020; Pombo Antunes et al., 2021).

T Lymphocytes

T lymphocytes play a critical role in initiating and maintaining efficient antitumor response. However, glioblastoma tumors are not characterized by abundant T-cell infiltrate and activated T-cells represent only 4-40% of immune cells present within the tumor (Woroniecka et al., 2018). As in MS, CD8+ Cytotoxic T-cells, CD4+ Helper T-cells, and regulatory T-cells have been identified within the GME (Mohme and Neidert, 2020). In stark contrast to autoimmune neuroinflammatory disorders, GBM sabotages effector T-cell responses by eliciting severe cellular dysfunction through the induction of senescence, tolerance, anergy, exhaustion, and ignorance (Table 4), which are extensively reviewed elsewhere (Woroniecka et al., 2018).

In addition to direct mechanisms of suppression, GBM can indirectly suppress anti-tumor T-cell responses through its influence on other cells of the TME. Though opposite in its outcome, like MS, regulatory T cell dysfunction is a critical contributor to the pro-tumor GBM microenvironment. Studies have demonstrated that patients with GBM exhibit increased proportion of both peripheral and tumor-associated T regulatory cells and several mechanisms are thought to contribute to the persistence and expansion of glioma associated T_Regs (El Andaloussi and Lesniak, 2006; Fecci et al., 2006; Woroniecka et al., 2018). Notably, STAT3 signaling in both GBM cells and T-cells is critical for T_Reg induction and function (Ooi et al., 2014). Phospho-STAT3 is upregulated in GBM cells and promotes the secretion of immunosuppressive factors that mediate T_Reg function, including IL-10, PGE2, and TGF-β (Williams et al., 2004; Kinjyo et al., 2006; Ooi et al., 2014). These factors, along with IL-2, subsequently activate STAT3 signaling in tumor associated-T_Regs to promote their expansion (Kortylewski et al., 2005; Ooi et al., 2014). Accordingly, inhibition of STAT3 in CD4+ T-cells has been shown to inhibit FOXP3 expression and the suppressive function of T_Regs (Pallandre et al., 2007; Ooi et al., 2014). Furthermore, STAT3 inhibition in glioma results in a decrease in T_Reg prevalence, enhanced T- and antigen-presenting cell activation, and increased production of anti-tumor cytokines (Woroniecka et al., 2018). Within the GME, regulatory T-cells also secrete the immunosuppressive cytokines TGF-β and IL-10, which suppress effector T-cell production of cytokines (e.g., IL-2 and IFN γ) and antigen-specific responses (Woroniecka et al., 2018). Depletion or functional interference of T regulatory cells rescues GBM-mediated T-cell dysfunction (Fecci et al., 2006; Woroniecka et al., 2018). The effects of GBM tumors on antigen-specific T cell responses is particularly important as a study has recently isolated naturally occurring CD4+ memory T cells from a patient with relapsed/refractory GBM (Leko et al., 2021). When stimulated in vitro, these CD4+ memory T cells were able to recognize a neoantigen specific to that patient’s tumor (Leko et al., 2021). While the physiologic effects of these neoantigen-specific memory T cells in GBM immunosurveillance remains unknown, their presence confirms the ability of the immune system mount an anti-GBM response.

Perhaps one of the most interesting findings with respect to T-cells in patients with GBM is that there is evidence to suggest that mature T-cells become trapped in the bone marrow secondary to a loss of sphingsosine-1-phosphate receptor 1 (S1PR1) expression on T-cell surfaces (Chongsathidkiet et al., 2018; Woroniecka et al., 2018). While this provides another mechanism by which GBM prevents T-cell-mediated anti-tumor response, it is also fascinating because this phenomenon seems to be characteristic of only tumors located within the intracranial compartment (Chongsathidkiet et al., 2018). Furthermore, drugs targeting the S1PR1 receptor have been approved for use in MS to prevent the egress of immune cells from lymphoid tissues (Chongsathidkiet et al., 2018; Chun et al., 2019). Thus, it is possible that the S1P–S1PR1 axis serves as another link between the peripheral immune system and CNS.

Dendritic Cells (DCs)

It has been proposed that tumor-associated cDCs (TA-cDCs) may elicit T-cell-mediated anti-tumor responses by presenting tumor-antigens within the brain and tumor-draining lymph nodes (Miller et al., 2007; Malo et al., 2018). However, infiltrating DCs are not immune to the suppressive influence of the GME, which is known to secrete factors that impair cDC differentiation and drive cDCs to adopt immunosuppressive phenotypes (Veglia et al., 2017; Yan et al., 2019; Ugolini et al., 2020). Immature DCs are involved in both inducing and maintaining immune tolerance (Patente et al., 2018). They express lower levels of co-stimulatory molecules and pro-inflammatory cytokines, but higher levels of immune checkpoint molecules including (PD-L1 and CTLA-4) and anti-inflammatory cytokines (Patente et al., 2018). These cells, however, are very efficient at antigen capture and, as a result, can engage T-cells through antigen presentation without co-stimulation, which drives the induction of T_Regs and promotion of T-cell anergy or apoptosis (Patente et al., 2018). Accordingly, TA-cDCs have been found to exhibit impairment in both differentiation and antigen presentation (Veglia et al., 2017; Yan et al., 2019; Ugolini et al., 2020). Furthermore, factors within the TME impair the cDC-mediated differentiation of T_h1 cells, recruitment of cytotoxic T-cells and promote activation of T regulatory cells through regulation of cDC production of IL-12, IL-10, and TGF-B (De Smedt et al., 1997; Hilkens et al., 1997; Kaliński et al., 1998; Platten et al., 2001; Zong et al., 2016; Flórez-Grau et al., 2018). Together these findings suggest that TA-cDCs likely contribute to both local and systemic immunosuppression through suppression of anti-tumor T-cell-mediated responses in the brain and deep cervical lymph nodes (Miller et al., 2007).

Cells of the TME secret high levels of pDC chemoattractant molecules, and we have previously demonstrated that pDCs were the major DC present in glioma (Dey et al., 2015). Despite their theoretical capability of inducing strong anti-tumor T-cell responses and priming CD4⁺ and CD8⁺ T-cells against tumor antigens, pDC infiltration is found to be associated with poor prognosis in several solid tumors (Hartmann et al., 2003; Salio et al., 2003; Conrad et al., 2012; Sawant et al., 2012). Tumor-associated pDCs (TA-pDCs) exhibit impaired function, and several mechanisms have been proposed to account for the functional defects induced by the GME, including the recruitment of immature pDCs with reduced expression of co-stimulatory molecules, a phenotype that is strikingly similar to that described in MS patients (Vermi et al., 2003; Beckebaum et al., 2004; Stasiolek et al., 2006). In glioma patients, both TA-pDCs and peripheral pDCs also exhibit an impaired ability to produce IFN-α (Mitchell et al., 2018). In addition to impaired IFN-α production, TApDCs also contribute to the immunosuppressive TME through PD-L1/PD-1-mediated inhibition of T-cell proliferation and survival as well as through inducible T-cell co-stimulator ligand (ICOS-L) mediated recruitment of ICOS+ T_Regs (Mitchell et al., 2018). Furthermore, pDCs can promote the accumulation of indoleamine 2,3-dioxygenase (IDO)-mediated activation of T_Regs (Munn et al., 2004; Sharma et al., 2007; Dey et al., 2015). In line with an immunosuppressive role of pDCs in the GME, we have demonstrated that depletion of pDCs during the early phase of tumor progression significantly decreased T_Regs within the microenvironment in a murine model of glioma (Dey et al., 2015).

B Lymphocytes

While the contribution of B cells to autoimmune neuroinflammatory disorders is more widely appreciated, until recently, the contribution of B-cells in the context of cancer has been relatively unexplored. Emerging evidence, however, suggests that regulatory B-cells, may contribute to the development and pathogenesis of a wide range of cancers (Horii and Matsushita, 2021). A recent study in the setting of GBM demonstrated that 40% of patients exhibited tumor infiltration of B-cells and that these GBM-associated B-cells (GABs) contribute to the immunosuppressive TME (Lee-Chang et al., 2019). In both humans and mice, these GABs demonstrated expression of PD-L1 and CD155 as well as production of the anti-inflammatory cytokines TGF-β and IL-10, which is consistent with an immunosuppressive phenotype (Lee-Chang et al., 2019). Interestingly, the overexpression of CD155, IL-10, and TGF-β demonstrated predominance in the early stages of tumor development, while PD-L1 expression peaked during the later stages (Lee-Chang et al., 2019). Myeloid derived suppressor cells (MDSCs), a heterogeneous population of cells arising from the myeloid lineage, contribute to the immunosuppressive TME by facilitating the transfer of PD-L1 to GABs through microvesicles (Lee-Chang et al., 2019). Furthermore, pre-treatment with the CSF-1R inhibitor BLZ945, which impairs the immunosuppressive effects of MDSCs, prevented the acquisition of PD-L1 by naïve B-cells transferred to B-cell deficient mice (Lee-Chang et al., 2019). Importantly, the immunosuppressive phenotype of GABs was not demonstrated by B-cells in the periphery (Lee-Chang et al., 2019). This is in stark contrast to T regulatory cells, in which similar phenotypes were demonstrated in the periphery and within the tumor microenvironment, further supporting the idea that the immunosuppressive phenotype of these B_Regs is a direct result of interactions within the TME. The authors found that intrathecal administration of B-cell depleting anti-CD20 antibodies resulted in significantly longer survival than the IgG control and this was accompanied by an increase in tumor-infiltrating granzyme B and IFNγ-expressing effector CD8+ T-cells (Lee-Chang et al., 2019). Importantly, no survival benefit was reported when B-cell depleting therapy was administered systemically, which likely reflects the poor BBB penetrability of anti-CD20 antibodies (Lee-Chang et al., 2019).

Mirroring the studies discussed with respect to MS/EAE, the above studies further highlight the profound complexity of the neuro-immune axis response to disruptions of homeostasis. While the significant cellular plasticity and context-dependent heterogeneity of the above cellular entities serve to limit the damage in MS/EAE, it is these same characteristics that allow tumors to hijack the components of the neuro-immune axis to promote their own growth and survival. Despite their obvious differences, aspects of the neuro-immune axis response in neuroinflammatory disorders and brain tumors share fundamental similarities, which allow them to uniquely contribute to the pathogenesis of both disease states. In addition to elucidating the distinct contributions of particular entities of the neuro-immune axis to GBM pathogenesis, understanding the complex interactions between the CNS and the peripheral immune system in steady state and across disease states will be vital for the development of targeted immunotherapies for the successful treatment of primary brain tumors, including GBM.

Leveraging Neuroinflammation for Therapeutic Benefit: Immunotherapy

Despite aggressive treatment with surgery, radiotherapy and systemic chemotherapy, glioblastoma remains associated with a dismal prognosis and is invariably fatal (Lim et al., 2018). Likewise, while the treatment of relapsing MS has experienced great success, long-term or permanent drug-free remission is not guaranteed and trials of disease-modifying therapies for the treatment of the progressive form of the disease have been largely unsuccessful (Baecher-Allan et al., 2018; Lünemann et al., 2020). With the failure of conventional therapies, efforts have turned toward more effectively manipulating components of the neuro-immune axis to successfully treat both disease states.

Autoimmune Neuroinflammatory Disease

Clinically, MS is broadly categorized into three subtypes: relapsing-remitting MS (RRMS), progressive MS and clinically isolated syndromes (CIS) (Hauser and Cree, 2020). To date, there are 15 FDA-approved disease modifying treatments (DMTs) for patients with RRMS, while there are only three for progressive disease. Details of the most common DMTs are reviewed extensively elsewhere (McGinley et al., 2021). In general, these therapies act in a seemingly indiscriminant manner to shift the scales from a pro- to anti-inflammatory phenotype and broadly prevent lymphocyte infiltration into the CNS (Yednock et al., 1992; Yong et al., 1998; Selewski et al., 2010; Aharoni, 2014; Tsai and Han, 2016). In theory this could be beneficial, however, the protective and restorative capacity of the neuroinflammatory response relies on the ability of the neuro-immune axis to tightly regulate a delicate balance in a highly context-specific manner. With the rapid expansion of targeted immunotherapies, fully appreciating the contribution of distinct entities within the neuroinflammatory response to MS pathogenesis will be critical for the development of efficacious and individualized therapeutic strategies (Rotstein and Montalban, 2019). As mentioned previously, MS has historically been considered a T-cell-mediated disease, but emerging evidence also supports a significant role for the B-cell compartment (Hauser et al., 2008; Hauser and Cree, 2020; Kemmerer et al., 2020). This is a very important distinction as a recent study evaluating the most commonly used DMTs, found that these drugs have differential effects on distinct B-cell subsets, with some inducing an expansion of potentially pathogenic subtypes (Kemmerer et al., 2020). A role for the B-cell compartment in MS pathogenesis has been increasingly supported by the recent studies demonstrating efficacy of anti-CD20 antibody-mediated B-cell depletion in patients with both RRMS and progressive disease (Florou et al., 2020). Despite the understandable excitement regarding the efficacy of anti-CD20 antibodies in certain patients with MS, evidence has already begun to hint that this is unlikely to be a “magic bullet” (Krumbholz and Meinl, 2014). Following anti-CD20 depletion with rituximab, CSF IgG titers were unchanged and oligoclonal bands persisted, suggesting a persistence of antibody secreting cells not targeted by these therapies (Lee et al., 2021). Furthermore, findings from systemic autoimmune diseases have raised concerns regarding anti-CD20 therapy-mediated elevation in B-cell activating factor (BAFF) (Ehrenstein and Wing, 2016). BAFF, which has been shown to be elevated in MS lesions, can perpetuate pathogenic B-cells and plasmablasts potentially exacerbating disease in certain patients (Krumbholz and Meinl, 2014; Ehrenstein and Wing, 2016). To date, there are currently eight active clinical trials evaluating several anti-CD20 antibodies in all subsets of MS (Table 5). It will be important, however, to continue to elucidate the contribution of the neuro-immune axis components to MS disease pathology to identify patients for whom specific types of immunotherapy will be beneficial.

Glioblastoma

Given the immense effect of GBM on the immune system, there has been significant interest in therapeutically modulating the anti-tumor immune response to develop effective anti-GBM immunotherapy. While classically defined as a “cold” tumor, it is now known that the immune system is capable of recognizing GBM tumors and that these tumors are susceptible to immune-mediated attacks (Mitchell et al., 2015; Jackson et al., 2019). Several therapeutic strategies are currently under investigation to address these immunological challenges imposed by GBM, many of which exploit mechanisms underlying autoimmune neurological disease. One such strategy involves the direct targeting of tumor-specific antigens, also called neoantigens. While several studies in other cancers have demonstrated promise using this technique, the fundamental challenge lies in identifying a suitable target antigen (McGranahan and Swanton, 2019; Yamamoto et al., 2019). To serve as an ideal target, an antigen must not be expressed by normal tissue, but must be widely expressed on a large portion of tumor cells. Furthermore, the target antigen must also be vital to tumor cells in order to prevent immunoediting and subsequent treatment resistance (Rosenthal et al., 2019). The identification of neoantigens in the setting of GBM has proven challenging for multiple reasons, including intratumoral heterogeneity and tumor cell molecular plasticity (Londhe and Date, 2020; Woroniecka and Fecci, 2020). To address these challenges, multivalent vaccines targeting multiple tumor antigens are currently under clinical investigation (Woroniecka and Fecci, 2020).

The use of oncolytic viruses has also attempted to address this issue (Martikainen and Essand, 2019). Rather than directly targeting specific endogenous tumor-antigens, oncolytic viruses selectively infect and kill tumor cells, causing the release of tumor antigens upon tumor cell death (Martikainen and Essand, 2019). This spillage of tumor antigens subsequently stimulates an immune response (Martikainen and Essand, 2019). This phenomenon is similar to epitope spreading that is hypothesized to take place in some patients with MS (Tuohy and Kinkel, 2000). While the use of oncolytic viruses theoretically holds great promise, the immune response to tumor antigen spillage would require both adequate infiltration and function of immune effector cells. As previously discussed, both local and systemic immunosuppression are hallmarks of GBM that must be overcome for therapies relying on secondary immune responses to be successful. Conversely, in the absence of significant immunosuppression, it would be possible to trigger a pathologic inflammatory response that could be devastating to normal CNS tissue.

Even once a high-quality tumor-antigen has been identified and the suppression of effector immune cells has been overcome, there still remains the challenge of overcoming the adaptive resistance mechanisms possessed by the tumor cells themselves. One of the most widely appreciated of these mechanisms involves the upregulation of immune checkpoint molecules, including PD-L1, CTLA-4, and TIM-3 (Koyama et al., 2016; Jackson et al., 2019). These molecules are upregulated in response to significant immunologic pressure secondary to chronic stimulation from the TME or in response to the effects of immunotherapy (Topalian et al., 2015; Koyama et al., 2016; DeCordova et al., 2020). Given the relative failure of immune checkpoint inhibitor monotherapy, clinical efforts (NCT04225039) are currently investigating the simultaneous targeting of multiple immune checkpoint molecules, which has shown benefit in the preclinical setting (Kim et al., 2017). GBM, however, induces effector T-cell dysfunction through multiple mechanisms and while the upregulation of immune checkpoint inhibiting-proteins accounts for one of these, there is clearly extensive mechanistic non-redundancy underlying GBM’s ability to promote T-cell dysfunction (Woroniecka et al., 2018). Thus, this poses the question of whether inhibiting multiple immune checkpoints alone can restore T-cell function sufficiently to mount an effective and sustained anti-tumor response. A recent study evaluating the combined use of anti-GITR and anti-PD1 agonistic (α) antibodies suggests that this may, in fact, be an effective strategy (Amoozgar et al., 2021). Amoozgar et al. (2021) demonstrated that the use of αGITR promotes the differentiation of CD4+ regulatory T cells into CD4+ effector T cells and induces an effective anti-tumor response through amelioration of regulatory T cell-mediated suppression. Importantly, the use of αGITR and αPD1 antibodies proved synergistic and increased survival in three models of GBM (Amoozgar et al., 2021).

While great focus has been dedicated to directly eliciting T-cell-mediated anti-tumor responses, emerging evidence has shifted some of the attention to targeting other cells of the TME. Although impairing tumor associated macrophage (TAM) recruitment through the inhibition of CCR2, CCL2, and CSF-1R has demonstrated preclinical efficacy, these results were not reproduced in the clinical setting, as CSF-1R inhibition failed to improve overall survival in patients with recurrent GBM secondary to P13K-mediated resistance (Zhu et al., 2011; Coniglio et al., 2012; Pyonteck et al., 2013; Butowski et al., 2016). The use of therapies capable of shifting TAMs from a pro-tumor to an anti-tumor phenotype has also been proposed as an attractive option. IL-12 can promote macrophages to adopt a tumor suppressive phenotype, and efforts are being explored to manipulate this pathway within the TME (Trinchieri, 2003; Wang et al., 2017). While the direct targeting of TAMs may provide an attractive option, the physiologically critical role of microglia/macrophages in wide range of potentially beneficial and deleterious functions should be taken into consideration. In patients with traumatic brain injuries, the use of minocycline, a tetracycline antibiotic found to inhibit microglial M1 polarization, decreased chronic microglial activation but increased neurodegeneration (Kobayashi et al., 2013). Similar effects have been reported in preclinical studies of MS/EAE (Scott et al., 2018; Guerrero and Sicotte, 2020). Conversely, minocycline has demonstrated efficacy with respect to endpoints such as annual relapse rate in clinical trials for human patients with MS (Guerrero and Sicotte, 2020). Together these findings suggest that strictly driving microglia/macrophages to adopt polarized phenotypes could have both beneficial and detrimental effects depending on the specific context. Furthermore, it is unlikely that TAMs, or any single cell type, serve as the Achilles heel of GBM. Many tumor-supporting functions provided by microglia are reflected in parallel functions of astrocytes and peripherally derived macrophages (Badie and Schartner, 2001; Sofroniew and Vinters, 2010; Butovsky and Weiner, 2018; Brandao et al., 2019; DeCordova et al., 2020). Therefore, therapeutic strategies may be most effective if they focus on specific vital interactions between tumors and cells of the GME rather than broadly manipulating phenotypic polarization.

Another approach is the targeting of specific signaling pathways, which also presents several challenges. For example, the functional outcome of STAT3 pathway activation is highly context- and cell-specific (Yan et al., 2018). In T_h17 cells, STAT3 activation induces the production of pro-inflammatory cytokines, including IL-17A (Yan et al., 2018). Conversely, IL-10-mediated STAT3 activation drives microglia to adopt an anti-inflammatory phenotype (Yan et al., 2018). In astrocytes, STAT3 signaling can regulate programs associated with both cellular proliferation and the production of pro-inflammatory cytokines (Yan et al., 2018). Alternatively, the persistent activation of STAT3, has been shown to promote tumorigenesis through suppression of anti-tumor immune responses and through stimulation of proliferation, survival, and invasion of tumor cells (Yu et al., 2009). In the setting of GBM, STAT3 inhibition has demonstrated preclinical efficacy with respect to decreasing tumor cell proliferation, migration, and invasion (Piperi et al., 2019). However, other preclinical studies found that while STAT3 inhibitors induced GBM cell death when tumors were implanted into the flank, this efficacy was not reproduced when tumors were implanted intracranially (Assi et al., 2014). Furthermore, this study also observed non-specific dose-dependent inhibition of STAT1, STAT5 and NF-kβ (Assi et al., 2014). Taken together these findings suggest that the efficacy of therapies targeting distinct pathways within the GME is highly complex and will require a more thorough understanding of the contribution of these pathways in distinct contexts as well as the development of highly specific agents capable of penetrating the BBB.

Conclusion

Emerging evidence has begun to highlight the importance of the interactions between the CNS and the peripheral immune system in both steady state and disease. While no longer considered “immune privileged,” the CNS is certainly a distinct environment elegantly designed to protect the integrity of its highly delicate constituents, which possess limited regenerative capacity. Through complex, multifactorial interactions between CNS-resident and peripheral immune cells, the neuro-immune axis works to maintain balance in responding appropriately to homeostatic disruptions while minimizing potentially devastating neurotoxicity. Dysregulation of the mechanisms underlying this delicate balance can contribute to the development of autoimmune neurological diseases and promote tumorigenesis. Furthermore, the effects of this dysregulation extend beyond the local environment of the CNS into the periphery. As such, a more complete understanding of the interactions between the CNS and peripheral immune system in response to different types of homeostatic disruption will be vital to the development of effective treatments for a wide range of neurological disorders, including GBM.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

• 1

  AbbottN. J.RönnbäckL.HanssonE. (2006). Astrocyte-endothelial interactions at the blood-brain barrier.Nat. Rev. Neurosci.741–53. 10.1038/nrn1824

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 2

  AbsintaM.VuoloL.RaoA.NairG.SatiP.CorteseI. C.et al (2015). Gadolinium-based MRI characterization of leptomeningeal inflammation in multiple sclerosis.Neurology8518–28. 10.1212/wnl.0000000000001587

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 3

  AcharjeeS.GordonP. M. K.LeeB. H.ReadJ.WorkentineM. L.SharkeyK. A.et al (2021). Characterization of microglial transcriptomes in the brain and spinal cord of mice in early and late experimental autoimmune encephalomyelitis using a RiboTag strategy.Sci. Rep.11:14319.

  • Google Scholar

• 4

  AharoniR. (2014). Immunomodulation neuroprotection and remyelination - the fundamental therapeutic effects of glatiramer acetate: a critical review.J. Autoimmun.5481–92. 10.1016/j.jaut.2014.05.005

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 5

  AjamiB.BennettJ. L.KriegerC.McNagnyK. M.RossiF. M. (2011). Infiltrating monocytes trigger EAE progression, but do not contribute to the resident microglia pool.Nat. Neurosci.141142–1149. 10.1038/nn.2887

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 6

  AjamiB.SamusikN.WieghoferP.HoP. P.CrottiA.BjornsonZ.et al (2018). Single-cell mass cytometry reveals distinct populations of brain myeloid cells in mouse neuroinflammation and neurodegeneration models.Nat. Neurosci.21541–551. 10.1038/s41593-018-0100-x

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 7

  Alves de LimaK.RustenhovenJ.KipnisJ. (2020). Meningeal immunity and its function in maintenance of the central nervous system in health and disease.Annu. Rev. Immunol.38597–620. 10.1146/annurev-immunol-102319-103410

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 8

  AmoozgarZ.KloepperJ.RenJ.TayR. E.KazerS. W.KinerE.et al (2021). Targeting Treg cells with GITR activation alleviates resistance to immunotherapy in murine glioblastomas.Nat. Commun.12:2582.

  • Google Scholar

• 9

  AndresK. H.von DüringM.MuszynskiK.SchmidtR. F. (1987). Nerve fibres and their terminals of the dura mater encephali of the rat.Anat. Embryol.175289–301. 10.1007/bf00309843

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 10

  ArgawA. T.AspL.ZhangJ.NavrazhinaK.PhamT.MarianiJ. N.et al (2012). Astrocyte-derived VEGF-A drives blood-brain barrier disruption in CNS inflammatory disease.J. Clin. Invest.1222454–2468. 10.1172/jci60842

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 11

  AspelundA.AntilaS.ProulxS. T.KarlsenT. V.KaramanS.DetmarM.et al (2015). A dural lymphatic vascular system that drains brain interstitial fluid and macromolecules.J. Exp. Med.212991–999. 10.1084/jem.20142290

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 12

  AssiH. H.ParanC.VanderVeenN.SavakusJ.DohertyR.PetruzzellaE.et al (2014). Preclinical characterization of signal transducer and activator of transcription 3 small molecule inhibitors for primary and metastatic brain cancer therapy.J. Pharmacol. Exp. Ther.349458–469. 10.1124/jpet.114.214619

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 13

  BadieB.SchartnerJ. (2001). Role of microglia in glioma biology.Microsc. Res. Tech.54106–113. 10.1002/jemt.1125

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 14

  Baecher-AllanC.KaskowB. J.WeinerH. L. (2018). Multiple sclerosis: mechanisms and immunotherapy.Neuron97742–768. 10.1016/j.neuron.2018.01.021

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 15

  BaileyS. L.CarpentierP. A.McMahonE. J.BegolkaW. S.MillerS. D. (2006). Innate and adaptive immune responses of the central nervous system.Crit. Rev. Immunol.26149–188. 10.1615/critrevimmunol.v26.i2.40

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 16

  BaileyS. L.SchreinerB.McMahonE. J.MillerS. D. (2007). CNS myeloid DCs presenting endogenous myelin peptides ‘preferentially’ polarize CD4+ T(H)-17 cells in relapsing EAE.Nat. Immunol.8172–180. 10.1038/ni1430

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 17

  Bailey-BucktroutS. L.CaulkinsS. C.GoingsG.FischerJ. A.DzionekA.MillerS. D. (2008). Cutting edge: central nervous system plasmacytoid dendritic cells regulate the severity of relapsing experimental autoimmune encephalomyelitis.J. Immunol.1806457–6461. 10.4049/jimmunol.180.10.6457

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 18

  BamM.ChintalaS.FetckoK.WilliamsenB. C.SirajS.LiuS.et al (2021). Genome wide DNA methylation landscape reveals glioblastoma’s influence on epigenetic changes in tumor infiltrating CD4+ T cells.Oncotarget12967–981. 10.18632/oncotarget.27955

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 19

  BarnettM. H.PrineasJ. W. (2004). Relapsing and remitting multiple sclerosis: pathology of the newly forming lesion.Ann. Neurol.55458–468. 10.1002/ana.20016

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 20

  Bar-OrA.CalabresiP. A.ArnoldD.MarkowitzC.ShaferS.KasperL. H.et al (2008). Rituximab in relapsing-remitting multiple sclerosis: a 72-week, open-label, phase I trial.Ann. Neurol.63395–400. 10.1002/ana.21363

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 21

  Bar-OrA.FawazL.FanB.DarlingtonP. J.RiegerA.GhorayebC.et al (2010). Abnormal B-cell cytokine responses a trigger of T-cell-mediated disease in MS?Ann. Neurol.67452–461. 10.1002/ana.21939

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 22

  BartholomäusI.KawakamiN.OdoardiF.SchlägerC.MiljkovicD.EllwartJ. W.et al (2009). Effector T cell interactions with meningeal vascular structures in nascent autoimmune CNS lesions.Nature46294–98. 10.1038/nature08478

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 23

  BauerJ.HuitingaI.ZhaoW.LassmannH.HickeyW. F.DijkstraC. D. (1995). The role of macrophages, perivascular cells, and microglial cells in the pathogenesis of experimental autoimmune encephalomyelitis.Glia15437–446. 10.1002/glia.440150407

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 24

  BaughmanE. J.MendozaJ. P.OrtegaS. B.AyersC. L.GreenbergB. M.FrohmanE. M.et al (2011). Neuroantigen-specific CD8+ regulatory T-cell function is deficient during acute exacerbation of multiple sclerosis.J. Autoimmun.36115–124. 10.1016/j.jaut.2010.12.003

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 25

  BeckebaumS.ZhangX.ChenX.YuZ.FrillingA.DworackiG.et al (2004). Increased levels of interleukin-10 in serum from patients with hepatocellular carcinoma correlate with profound numerical deficiencies and immature phenotype of circulating dendritic cell subsets.Clin. Cancer Res.107260–7269. 10.1158/1078-0432.ccr-04-0872

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 26

  BenvenisteH.LiuX.KoundalS.SanggaardS.LeeH.WardlawJ. (2019). The glymphatic system and waste clearance with brain aging: a review.Gerontology65106–119. 10.1159/000490349

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 27

  BiasoliD.SobrinhoM. F.da FonsecaA. C.de MatosD. G.RomãoL.de Moraes MacielR.et al (2014). Glioblastoma cells inhibit astrocytic p53-expression favoring cancer malignancy.Oncogenesis3:e123. 10.1038/oncsis.2014.36

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 28

  BielekovaB.SungM. H.KadomN.SimonR.McFarlandH.MartinR. (2004). Expansion and functional relevance of high-avidity myelin-specific CD4+ T cells in multiple sclerosis.J. Immunol.1723893–3904. 10.4049/jimmunol.172.6.3893

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 29

  BiswasS. K.GangiL.PaulS.SchioppaT.SaccaniA.SironiM.et al (2006). A distinct and unique transcriptional program expressed by tumor-associated macrophages (defective NF-kappaB and enhanced IRF-3/STAT1 activation).Blood1072112–2122. 10.1182/blood-2005-01-0428

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 30

  BorggreweM.GritC.VainchteinI. D.BrouwerN.WesselingE. M.LamanJ. D.et al (2021). Regionally diverse astrocyte subtypes and their heterogeneous response to EAE.Glia691140–1154. 10.1002/glia.23954

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 31

  BossùP.SpallettaG.CaltagironeC.CiaramellaA. (2015). Myeloid dendritic cells are potential players in human neurodegenerative diseases.Front. Immunol.6:632. 10.3389/fimmu.2015.00632

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 32

  BöttcherC.van der PoelM.Fernández-ZapataC.SchlickeiserS.LemanJ. K. H.HsiaoC. C.et al (2020). Single-cell mass cytometry reveals complex myeloid cell composition in active lesions of progressive multiple sclerosis.Acta Neuropathol. Commun.8:136.

  • Google Scholar

• 33

  BowmanR. L.KlemmF.AkkariL.PyonteckS. M.SevenichL.QuailD. F.et al (2016). Macrophage ontogeny underlies differences in tumor-specific education in brain malignancies.Cell Rep.172445–2459. 10.1016/j.celrep.2016.10.052

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 34

  BrambillaR. (2019). The contribution of astrocytes to the neuroinflammatory response in multiple sclerosis and experimental autoimmune encephalomyelitis.Acta Neuropathol.137757–783. 10.1007/s00401-019-01980-7

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 35

  BrambillaR.PersaudT.HuX.KarmallyS.ShestopalovV. I.DvoriantchikovaG.et al (2009). Transgenic inhibition of astroglial NF-kappa B improves functional outcome in experimental autoimmune encephalomyelitis by suppressing chronic central nervous system inflammation.J. Immunol.1822628–2640. 10.4049/jimmunol.0802954

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 36

  BrandaoM.SimonT.CritchleyG.GiamasG. (2019). Astrocytes, the rising stars of the glioblastoma microenvironment.Glia67779–790. 10.1002/glia.23520

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 37

  BroekmanM. L.MaasS. L. N.AbelsE. R.MempelT. R.KrichevskyA. M.BreakefieldX. O. (2018). Multidimensional communication in the microenvirons of glioblastoma.Nat. Rev. Neurol.14482–495. 10.1038/s41582-018-0025-8

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 38

  BrosnanC. F.BornsteinM. B.BloomB. R. (1981). The effects of macrophage depletion on the clinical and pathologic expression of experimental allergic encephalomyelitis.J. Immunol.126614–620.

  • Google Scholar

• 39

  BrosnanC. F.RaineC. S. (2013). The astrocyte in multiple sclerosis revisited.Glia61453–465. 10.1002/glia.22443

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 40

  ButovskyO.WeinerH. L. (2018). Microglial signatures and their role in health and disease.Nat. Rev. Neurosci.19622–635. 10.1038/s41583-018-0057-5

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 41

  ButowskiN.ColmanH.De GrootJ. F.OmuroA. M.NayakL.WenP. Y.et al (2016). Orally administered colony stimulating factor 1 receptor inhibitor PLX3397 in recurrent glioblastoma: an ivy foundation early phase clinical trials consortium phase II study.Neuro Oncol.18557–564. 10.1093/neuonc/nov245

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 42

  CaoJ. Y.GuoQ.GuanG. F.ZhuC.ZouC. Y.ZhangL. Y.et al (2020). Elevated lymphocyte specific protein 1 expression is involved in the regulation of leukocyte migration and immunosuppressive microenvironment in glioblastoma.Aging121656–1684. 10.18632/aging.102706

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 43

  CaravagnaC.JaouënA.Desplat-JégoS.FenrichK. K.BergotE.LucheH.et al (2018). Diversity of innate immune cell subsets across spatial and temporal scales in an EAE mouse model.Sci. Rep.8:5146.

  • Google Scholar

• 44

  CepokS.von GeldernG.GrummelV.HochgesandS.CelikH.HartungH.et al (2006). Accumulation of class switched IgD-IgM- memory B cells in the cerebrospinal fluid during neuroinflammation.J. Neuroimmunol.18033–39. 10.1016/j.jneuroim.2006.06.031

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 45

  CeyzériatK.AbjeanL.Carrillo-de SauvageM. A.Ben HaimL.EscartinC. (2016). The complex STATes of astrocyte reactivity: how are they controlled by the JAK-STAT3 pathway?Neuroscience330205–218. 10.1016/j.neuroscience.2016.05.043

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 46

  ChenZ.FengX.HertingC. J.GarciaV. A.NieK.PongW. W.et al (2017). Cellular and molecular identity of tumor-associated macrophages in glioblastoma.Cancer Res.772266–2278. 10.1158/0008-5472.can-16-2310

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 47

  ChoiC.ParkJ. Y.LeeJ.LimJ. H.ShinE. C.AhnY. S.et al (1999). Fas ligand and Fas are expressed constitutively in human astrocytes and the expression increases with IL-1, IL-6, TNF-alpha, or IFN-gamma.J. Immunol.1621889–1895.

  • Google Scholar

• 48

  ChoiJ. W.GardellS. E.HerrD. R.RiveraR.LeeC. W.NoguchiK.et al (2011). FTY720 (fingolimod) efficacy in an animal model of multiple sclerosis requires astrocyte sphingosine 1-phosphate receptor 1 (S1P1) modulation.Proc. Natl. Acad. Sci. U.S.A.108751–756. 10.1073/pnas.1014154108

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 49

  ChongsathidkietP.JacksonC.KoyamaS.LoebelF.CuiX.FarberS. H.et al (2018). Sequestration of T cells in bone marrow in the setting of glioblastoma and other intracranial tumors.Nat. Med.241459–1468. 10.1038/s41591-018-0135-2

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 50

  ChuF.ShiM.ZhengC.ShenD.ZhuJ.ZhengX.et al (2018). The roles of macrophages and microglia in multiple sclerosis and experimental autoimmune encephalomyelitis.J. Neuroimmunol.3181–7. 10.1016/j.jneuroim.2018.02.015

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 51

  ChunJ.KiharaY.JonnalagaddaD.BlahoV. A. (2019). Fingolimod: lessons learned and new opportunities for treating multiple sclerosis and other disorders.Annu. Rev. Pharmacol. Toxicol.59149–170. 10.1146/annurev-pharmtox-010818-021358

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 52

  ClarksonB. D.WalkerA.HarrisM. G.RayasamA.HsuM.SandorM.et al (2017). CCR7 deficient inflammatory dendritic cells are retained in the central nervous system.Sci. Rep.7:42856.

  • Google Scholar

• 53

  CodarriL.GyülvésziG.TosevskiV.HesskeL.FontanaA.MagnenatL.et al (2011). RORγt drives production of the cytokine GM-CSF in helper T cells, which is essential for the effector phase of autoimmune neuroinflammation.Nat. Immunol.12560–567. 10.1038/ni.2027

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 54

  ColomboE.FarinaC. (2016). Astrocytes: key regulators of neuroinflammation.Trends Immunol.37608–620. 10.1016/j.it.2016.06.006

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 55

  ColonnaM.ButovskyO. (2017). Microglia function in the central nervous system during health and neurodegeneration.Annu. Rev. Immunol.35441–468. 10.1146/annurev-immunol-051116-052358

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 56

  ConiglioS. J.EugeninE.DobrenisK.StanleyE. R.WestB. L.SymonsM. H.et al (2012). Microglial stimulation of glioblastoma invasion involves epidermal growth factor receptor (EGFR) and colony stimulating factor 1 receptor (CSF-1R) signaling.Mol. Med.18519–527. 10.2119/molmed.2011.00217

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 57

  ConradC.GregorioJ.WangY. H.ItoT.MellerS.HanabuchiS.et al (2012). Plasmacytoid dendritic cells promote immunosuppression in ovarian cancer via ICOS costimulation of Foxp3(+) T-regulatory cells.Cancer Res.725240–5249. 10.1158/0008-5472.can-12-2271

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 58

  CorrealeJ.VillaA. (2008). Isolation and characterization of CD8+ regulatory T cells in multiple sclerosis.J. Neuroimmunol.195121–134. 10.1016/j.jneuroim.2007.12.004

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 59

  CoussensL. M.WerbZ. (2002). Inflammation and cancer.Nature420860–867.

  • Google Scholar

• 60

  CserrH. F.Harling-BergC. J.KnopfP. M. (1992). Drainage of brain extracellular fluid into blood and deep cervical lymph and its immunological significance.Brain Pathol.2269–276. 10.1111/j.1750-3639.1992.tb00703.x

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 61

  DalmauJ.GrausF. (2018). Antibody-mediated encephalitis.N. Engl. J. Med.378840–851.

  • Google Scholar

• 62

  D’AmelioF. E.SmithM. E.EngL. F. (1990). Sequence of tissue responses in the early stages of experimental allergic encephalomyelitis (EAE): immunohistochemical, light microscopic, and ultrastructural observations in the spinal cord.Glia3229–240. 10.1002/glia.440030402

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 63

  DarmanisS.SloanS. A.CrooteD.MignardiM.ChernikovaS.SamghababiP.et al (2017). Single-cell RNA-Seq analysis of infiltrating neoplastic cells at the migrating front of human glioblastoma.Cell Rep.211399–1410. 10.1016/j.celrep.2017.10.030

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 64

  De SmedtT.Van MechelenM.De BeckerG.UrbainJ.LeoO.MoserM. (1997). Effect of interleukin-10 on dendritic cell maturation and function.Eur. J. Immunol.271229–1235. 10.1002/eji.1830270526

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 65

  DeBerardinisR. J.MancusoA.DaikhinE.NissimI.YudkoffM.WehrliS.et al (2007). Beyond aerobic glycolysis: transformed cells can engage in glutamine metabolism that exceeds the requirement for protein and nucleotide synthesis.Proc. Natl. Acad. Sci. U.S.A.10419345–19350. 10.1073/pnas.0709747104

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 66

  DeCordovaS.ShastriA.TsolakiA. G.YasminH.KleinL.SinghS. K.et al (2020). Molecular heterogeneity and immunosuppressive microenvironment in glioblastoma.Front. Immunol.11:1402. 10.3389/fimmu.2020.01402

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 67

  DemeestereD.LibertC.VandenbrouckeR. E. (2015). Clinical implications of leukocyte infiltration at the choroid plexus in (neuro)inflammatory disorders.Drug Discov. Today20928–941. 10.1016/j.drudis.2015.05.003

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 68

  DendrouC. A.FuggerL.FrieseM. A. (2015). Immunopathology of multiple sclerosis.Nat. Rev. Immunol.15545–558.

  • Google Scholar

• 69

  DeyM.ChangA. L.MiskaJ.WainwrightD. A.AhmedA. U.BalyasnikovaI. V.et al (2015). Dendritic cell-based vaccines that utilize myeloid rather than plasmacytoid cells offer a superior survival advantage in malignant glioma.J. Immunol.195367–376. 10.4049/jimmunol.1401607

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 70

  DieboldS. S. (2008). Determination of T-cell fate by dendritic cells.Immunol. Cell Biol.86389–397. 10.1038/icb.2008.26

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 71

  DiSabatoD. J.QuanN.GodboutJ. P. (2016). Neuroinflammation: the devil is in the details.J. Neurochem.139(Suppl. 2), 136–153. 10.1111/jnc.13607

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 72

  DittelB. N.VisintinI.MerchantR. M.JanewayC. A.Jr. (1999). Presentation of the self antigen myelin basic protein by dendritic cells leads to experimental autoimmune encephalomyelitis.J. Immunol.16332–39.

  • Google Scholar

• 73

  DixonG. A.PérezC. A. (2020). Multiple sclerosis and the choroid plexus: emerging concepts of disease immunopathophysiology.Pediatr. Neurol.10365–75. 10.1016/j.pediatrneurol.2019.08.007

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 74

  DongY.YongV. W. (2019). When encephalitogenic T cells collaborate with microglia in multiple sclerosis.Nat. Rev. Neurol.15704–717. 10.1038/s41582-019-0253-6

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 75

  EhrensteinM. R.WingC. (2016). The BAFFling effects of rituximab in lupus: danger ahead?Nat. Rev. Rheumatol.12367–372. 10.1038/nrrheum.2016.18

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 76

  El AndaloussiA.LesniakM. S. (2006). An increase in CD4+CD25+FOXP3+ regulatory T cells in tumor-infiltrating lymphocytes of human glioblastoma multiforme.Neuro Oncol.8234–243. 10.1215/15228517-2006-006

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 77

  El-BehiM.CiricB.DaiH.YanY.CullimoreM.SafaviF.et al (2011). The encephalitogenicity of T(H)17 cells is dependent on IL-1- and IL-23-induced production of the cytokine GM-CSF.Nat. Immunol.12568–575. 10.1038/ni.2031

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 78

  EngelhardtB.RansohoffR. M. (2005). The ins and outs of T-lymphocyte trafficking to the CNS: anatomical sites and molecular mechanisms.Trends Immunol.26485–495. 10.1016/j.it.2005.07.004

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 79

  EsaulovaE.CantoniC.ShchukinaI.ZaitsevK.BucelliR. C.WuG. F.et al (2020). Single-cell RNA-seq analysis of human CSF microglia and myeloid cells in neuroinflammation.Neurol. Neuroimmunol. Neuroinflamm.7:e732. 10.1212/nxi.0000000000000732

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 80

  FallarinoF.GrohmannU.YouS.McGrathB. C.CavenerD. R.VaccaC.et al (2006). Tryptophan catabolism generates autoimmune-preventive regulatory T cells.Transpl. Immunol.1758–60. 10.1016/j.trim.2006.09.017

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 81

  FecciP. E.MitchellD. A.WhitesidesJ. F.XieW.FriedmanA. H.ArcherG. E.et al (2006). Increased regulatory T-cell fraction amidst a diminished CD4 compartment explains cellular immune defects in patients with malignant glioma.Cancer Res.663294–3302. 10.1158/0008-5472.can-05-3773

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 82

  FitzpatrickZ.FrazerG.FerroA.ClareS.BouladouxN.FerdinandJ.et al (2020). Gut-educated IgA plasma cells defend the meningeal venous sinuses.Nature587472–476. 10.1038/s41586-020-2886-4

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 83

  Flórez-GrauG.ZubizarretaI.CabezónR.VillosladaP.Benitez-RibasD. (2018). Tolerogenic dendritic cells as a promising antigen-specific therapy in the treatment of multiple sclerosis and neuromyelitis optica from preclinical to clinical trials.Front. Immunol.9:1169. 10.3389/fimmu.2018.01169

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 84

  FlorouD.KatsaraM.FeehanJ.DardiotisE.ApostolopoulosV. (2020). Anti-CD20 agents for multiple sclerosis: spotlight on ocrelizumab and ofatumumab.Brain Sci.10:758. 10.3390/brainsci10100758

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 85

  ForstreuterF.LuciusR.MentleinR. (2002). Vascular endothelial growth factor induces chemotaxis and proliferation of microglial cells.J. Neuroimmunol.13293–98. 10.1016/s0165-5728(02)00315-6

  • CrossRef
  • Google Scholar

• 86

  FrederickN.LouveauA. (2020). Meningeal lymphatics, immunity and neuroinflammation.Curr. Opin. Neurobiol.6241–47. 10.1016/j.conb.2019.11.010

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 87

  FriebelE.KapolouK.UngerS.NúñezN. G.UtzS.RushingE. J.et al (2020). Single-cell mapping of human brain cancer reveals tumor-specific instruction of tissue-invading leukocytes.Cell1811626–1642. 10.1016/j.cell.2020.04.055

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 88

  GabrusiewiczK.Ellert-MiklaszewskaA.LipkoM.SielskaM.FrankowskaM.KaminskaB. (2011). Characteristics of the alternative phenotype of microglia/macrophages and its modulation in experimental gliomas.PLoS One6:e23902. 10.1371/journal.pone.0023902

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 89

  GabrusiewiczK.RodriguezB.WeiJ.HashimotoY.HealyL. M.MaitiS. N.et al (2016). Glioblastoma-infiltrated innate immune cells resemble M0 macrophage phenotype.JCI Insight1:e85841.

  • Google Scholar

• 90

  GadaniS. P.WalshJ. T.LukensJ. R.KipnisJ. (2015). Dealing with danger in the CNS: the response of the immune system to injury.Neuron8747–62. 10.1016/j.neuron.2015.05.019

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 91

  GaleaI.BechmannI.PerryV. H. (2007). What is immune privilege (not)?Trends Immunol.2812–18. 10.1016/j.it.2006.11.004

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 92

  GaleaI.PerryV. H. (2018). The blood-brain interface: a culture change.Brain Behav. Immun.6811–16. 10.1016/j.bbi.2017.10.014

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 93

  GieryngA.PszczolkowskaD.WalentynowiczK. A.RajanW. D.KaminskaB. (2017). Immune microenvironment of gliomas.Lab. Invest.97498–518. 10.1038/labinvest.2017.19

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 94

  GiladiA.WagnerL. K.LiH.DörrD.MedagliaC.PaulF.et al (2020). Cxcl10(+) monocytes define a pathogenic subset in the central nervous system during autoimmune neuroinflammation.Nat. Immunol.21525–534. 10.1038/s41590-020-0661-1

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 95

  GiraudS. N.CaronC. M.Pham-DinhD.KitabgiP.NicotA. B. (2010). Estradiol inhibits ongoing autoimmune neuroinflammation and NFkappaB-dependent CCL2 expression in reactive astrocytes.Proc. Natl. Acad. Sci. U.S.A.1078416–8421. 10.1073/pnas.0910627107

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 96

  GovermanJ. (2009). Autoimmune T cell responses in the central nervous system.Nat. Rev. Immunol.9393–407. 10.1038/nri2550

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 97

  GrassivaroF.MenonR.AcquavivaM.OttoboniL.RuffiniF.BergamaschiA.et al (2020). Convergence between microglia and peripheral macrophages phenotype during development and neuroinflammation.J. Neurosci.40784–795. 10.1523/jneurosci.1523-19.2019

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 98

  GretenF. R.GrivennikovS. I. (2019). Inflammation and cancer: triggers, mechanisms, and consequences.Immunity5127–41. 10.1016/j.immuni.2019.06.025

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 99

  GrossC. C.Schulte-MecklenbeckA.RünziA.KuhlmannT.Posevitz-FejfárA.SchwabN.et al (2016). Impaired NK-mediated regulation of T-cell activity in multiple sclerosis is reconstituted by IL-2 receptor modulation.Proc. Natl. Acad. Sci. U.S.A.113E2973–E2982.

  • Google Scholar

• 100

  GuanX.HasanM. N.ManiarS.JiaW.SunD. (2018). Reactive astrocytes in glioblastoma multiforme.Mol. Neurobiol.556927–6938. 10.1007/s12035-018-0880-8

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 101

  GuerreroB. L.SicotteN. L. (2020). Microglia in multiple sclerosis: friend or foe?Front. Immunol.11:374. 10.3389/fimmu.2020.00374

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 102

  GuilliamsM.MildnerA.YonaS. (2018). Developmental and functional heterogeneity of monocytes.Immunity49595–613. 10.1016/j.immuni.2018.10.005

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 103

  HambardzumyanD.GutmannD. H.KettenmannH. (2016). The role of microglia and macrophages in glioma maintenance and progression.Nat. Neurosci.1920–27. 10.1038/nn.4185

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 104

  HaoC.ParneyI. F.RoaW. H.TurnerJ.PetrukK. C.RamsayD. A. (2002). Cytokine and cytokine receptor mRNA expression in human glioblastomas: evidence of Th1, Th2 and Th3 cytokine dysregulation.Acta Neuropathol.103171–178. 10.1007/s004010100448

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 105

  HartmannE.WollenbergB.RothenfusserS.WagnerM.WellischD.MackB.et al (2003). Identification and functional analysis of tumor-infiltrating plasmacytoid dendritic cells in head and neck cancer.Cancer Res.636478–6487.

  • Google Scholar

• 106

  HattermannK.SebensS.HelmO.SchmittA. D.MentleinR.MehdornH. M.et al (2014). Chemokine expression profile of freshly isolated human glioblastoma-associated macrophages/microglia.Oncol. Rep.32270–276. 10.3892/or.2014.3214

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 107

  HauserS. L.CreeB. A. C. (2020). Treatment of multiple sclerosis: a review.Am. J. Med.1331380–1390.

  • Google Scholar

• 108

  HauserS. L.WaubantE.ArnoldD. L.VollmerT.AntelJ.FoxR. J.et al (2008). B-cell depletion with rituximab in relapsing-remitting multiple sclerosis.N. Engl. J. Med.358676–688.

  • Google Scholar

• 109

  Häusser-KinzelS.WeberM. S. (2019). The Role of B cells and antibodies in multiple sclerosis, neuromyelitis optica, and related disorders.Front. Immunol.10:201. 10.3389/fimmu.2019.00201

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 110

  Held-FeindtJ.HattermannK.MüerkösterS. S.WedderkoppH.Knerlich-LukoschusF.UngefrorenH.et al (2010). CX3CR1 promotes recruitment of human glioma-infiltrating microglia/macrophages (GIMs).Exp. Cell Res.3161553–1566. 10.1016/j.yexcr.2010.02.018

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 111

  Henrik HeilandD.RaviV. M.BehringerS. P.FrenkingJ. H.WurmJ.JosephK.et al (2019). Tumor-associated reactive astrocytes aid the evolution of immunosuppressive environment in glioblastoma.Nat. Commun.10:2541.

  • Google Scholar

• 112

  HilkensC. M.KalinskiP.de BoerM.KapsenbergM. L. (1997). Human dendritic cells require exogenous interleukin-12-inducing factors to direct the development of naive T-helper cells toward the Th1 phenotype.Blood901920–1926. 10.1182/blood.v90.5.1920

  • CrossRef
  • Google Scholar

• 113

  HoriiM.MatsushitaT. (2021). Regulatory B cells and T cell regulation in cancer.J. Mol. Biol.433:166685. 10.1016/j.jmb.2020.10.019

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 114

  HuD.NotarbartoloS.CroonenborghsT.PatelB.CialicR.YangT. H.et al (2017). Transcriptional signature of human pro-inflammatory T(H)17 cells identifies reduced IL10 gene expression in multiple sclerosis.Nat. Commun.8:1600.

  • Google Scholar

• 115

  HuX.LeakR. K.ShiY.SuenagaJ.GaoY.ZhengP.et al (2015). Microglial and macrophage polarization—new prospects for brain repair.Nat. Rev. Neurol.1156–64. 10.1038/nrneurol.2014.207

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 116

  HuffW. X.KwonJ. H.HenriquezM.FetckoK.DeyM. (2019). The evolving role of CD8(+)CD28(-) immunosenescent T cells in cancer immunology.Int. J. Mol. Sci.20:2810. 10.3390/ijms20112810

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 117

  HuitingaI.van RooijenN.de GrootC. J.UitdehaagB. M.DijkstraC. D. (1990). Suppression of experimental allergic encephalomyelitis in Lewis rats after elimination of macrophages.J. Exp. Med.1721025–1033. 10.1084/jem.172.4.1025

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 118

  ItohN.ItohY.TassoniA.RenE.KaitoM.OhnoA.et al (2018). Cell-specific and region-specific transcriptomics in the multiple sclerosis model: focus on astrocytes.Proc. Natl. Acad. Sci. U.S.A.115E302–E309.

  • Google Scholar

• 119

  IwataR.Hyoung LeeJ.HayashiM.DianzaniU.OfuneK.MaruyamaM.et al (2020). ICOSLG-mediated regulatory T-cell expansion and IL-10 production promote progression of glioblastoma.Neuro Oncol.22333–344.

  • Google Scholar

• 120

  JäckleK.ZeisT.Schaeren-WiemersN.JunkerA.van der MeerF.KramannN.et al (2020). Molecular signature of slowly expanding lesions in progressive multiple sclerosis.Brain1432073–2088. 10.1093/brain/awaa158

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 121

  JacksonC. M.ChoiJ.LimM. (2019). Mechanisms of immunotherapy resistance: lessons from glioblastoma.Nat. Immunol.201100–1109. 10.1038/s41590-019-0433-y

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 122

  JairamanA.OthyS.DynesJ. L.YerominA. V.ZavalaA.GreenbergM. L.et al (2021). Piezo1 channels restrain regulatory T cells but are dispensable for effector CD4(+) T cell responses.Sci. Adv.7:eabg5859. 10.1126/sciadv.abg5859

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 123

  JinP.ShinS. H.ChunY. S.ShinH. W.ShinY. J.LeeY.et al (2018). Astrocyte-derived CCL20 reinforces HIF-1-mediated hypoxic responses in glioblastoma by stimulating the CCR6-NF-κB signaling pathway.Oncogene373070–3087. 10.1038/s41388-018-0182-7

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 124

  John LinC. C.YuK.HatcherA.HuangT. W.LeeH. K.CarlsonJ.et al (2017). Identification of diverse astrocyte populations and their malignant analogs.Nat. Neurosci.20396–405. 10.1038/nn.4493

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 125

  JordãoM. J. C.SankowskiR.BrendeckeS. M.SagarG. LocatelliTaiY. H.TayT. L.et al (2019). Single-cell profiling identifies myeloid cell subsets with distinct fates during neuroinflammation.Science363:eaat7554. 10.1126/science.aat7554

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 126

  KalińskiP.SchuitemakerJ. H.HilkensC. M.KapsenbergM. L. (1998). Prostaglandin E2 induces the final maturation of IL-12-deficient CD1a+CD83+ dendritic cells: the levels of IL-12 are determined during the final dendritic cell maturation and are resistant to further modulation.J. Immunol.1612804–2809.

  • Google Scholar

• 127

  KaskowB. J.Baecher-AllanC. (2018). Effector T cells in multiple sclerosis.Cold Spring Harb. Perspect. Med.8:a029025.

  • Google Scholar

• 128

  KemmererC. L.PernpeintnerV.RuschilC.AbdelhakA.SchollM.ZiemannU.et al (2020). Differential effects of disease modifying drugs on peripheral blood B cell subsets: a cross sectional study in multiple sclerosis patients treated with interferon-β, glatiramer acetate, dimethyl fumarate, fingolimod or natalizumab.PLoS One15:e0235449. 10.1371/journal.pone.0235449

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 129

  KimJ. E.PatelM. A.MangravitiA.KimE. S.TheodrosD.VelardeE.et al (2017). Combination therapy with Anti-PD-1, Anti-TIM-3, and focal radiation results in regression of murine gliomas.Clin. Cancer Res.23124–136. 10.1158/1078-0432.ccr-15-1535

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 130

  KinjyoI.InoueH.HamanoS.FukuyamaS.YoshimuraT.KogaK.et al (2006). Loss of SOCS3 in T helper cells resulted in reduced immune responses and hyperproduction of interleukin 10 and transforming growth factor-beta 1.J. Exp. Med.2031021–1031. 10.1084/jem.20052333

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 131

  KlemmF.MaasR. R.BowmanR. L.KorneteM.SoukupK.NassiriS.et al (2020). Interrogation of the microenvironmental landscape in brain tumors reveals disease-specific alterations of immune cells.Cell1811643.e17–1660.e17.

  • Google Scholar

• 132

  KobayashiK.ImagamaS.OhgomoriT.HiranoK.UchimuraK.SakamotoK.et al (2013). Minocycline selectively inhibits M1 polarization of microglia.Cell Death Dis.4:e525. 10.1038/cddis.2013.54

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 133

  KorinB.Ben-ShaananT. L.SchillerM.DubovikT.Azulay-DebbyH.BoshnakN. T.et al (2017). High-dimensional, single-cell characterization of the brain’s immune compartment.Nat. Neurosci.201300–1309. 10.1038/nn.4610

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 134

  KortylewskiM.KujawskiM.WangT.WeiS.ZhangS.Pilon-ThomasS.et al (2005). Inhibiting Stat3 signaling in the hematopoietic system elicits multicomponent antitumor immunity.Nat. Med.111314–1321. 10.1038/nm1325

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 135

  KoyamaS.AkbayE. A.LiY. Y.Herter-SprieG. S.BuczkowskiK. A.RichardsW. G.et al (2016). Adaptive resistance to therapeutic PD-1 blockade is associated with upregulation of alternative immune checkpoints.Nat. Commun.7:10501.

  • Google Scholar

• 136

  KrumbholzM.MeinlE. (2014). B cells in MS and NMO: pathogenesis and therapy.Semin. Immunopathol.36339–350. 10.1007/s00281-014-0424-x

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 137

  KumarV.PatelS.TcyganovE.GabrilovichD. I. (2016). The nature of myeloid-derived suppressor cells in the tumor microenvironment.Trends Immunol.37208–220.

  • Google Scholar

• 138

  LandeR.GafaV.SerafiniB.GiacominiE.ViscontiA.RemoliM. E.et al (2008). Plasmacytoid dendritic cells in multiple sclerosis: intracerebral recruitment and impaired maturation in response to interferon-beta.J. Neuropathol. Exp. Neurol.67388–401. 10.1097/nen.0b013e31816fc975

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 139

  LandryA. P.BalasM.AlliS.SpearsJ.ZadorZ. (2020). Distinct regional ontogeny and activation of tumor associated macrophages in human glioblastoma.Sci. Rep.10:19542.

  • Google Scholar

• 140

  LassmannH. (2003). Hypoxia-like tissue injury as a component of multiple sclerosis lesions.J. Neurol. Sci.206187–191. 10.1016/s0022-510x(02)00421-5

  • CrossRef
  • Google Scholar

• 141

  LassmannH. (2018). Pathogenic mechanisms associated with different clinical courses of multiple sclerosis.Front. Immunol.9:3116. 10.3389/fimmu.2018.03116

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 142

  LawrenceT.NatoliG. (2011). Transcriptional regulation of macrophage polarization: enabling diversity with identity.Nat. Rev. Immunol.11750–761. 10.1038/nri3088

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 143

  LeccoV. (1953). [Probable modification of the lymphatic fissures of the walls of the venous sinuses of the dura mater].Arch Ital. Otol. Rinol. Laringol.64287–296.

  • Google Scholar

• 144

  LeeD. S. W.RojasO. L.GommermanJ. L. (2021). B cell depletion therapies in autoimmune disease: advances and mechanistic insights.Nat. Rev. Drug Discov.20179–199. 10.1038/s41573-020-00092-2

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 145

  Lee-ChangC.RashidiA.MiskaJ.ZhangP.PituchK. C.HouD.et al (2019). Myeloid-derived suppressive cells promote B cell-mediated immunosuppression via transfer of PD-L1 in glioblastoma.Cancer Immunol. Res.71928–1943. 10.1158/2326-6066.cir-19-0240

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 146

  LekoV.CafriG.YossefR.PariaB.HillV.GurusamyD.et al (2021). Identification of neoantigen-reactive T lymphocytes in the peripheral blood of a patient with glioblastoma.J. Immunother. Cancer9:e002882. 10.1136/jitc-2021-002882

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 147

  LewisN. D.HillJ. D.JuchemK. W.StefanopoulosD. E.ModisL. K. (2014). RNA sequencing of microglia and monocyte-derived macrophages from mice with experimental autoimmune encephalomyelitis illustrates a changing phenotype with disease course.J. Neuroimmunol.27726–38. 10.1016/j.jneuroim.2014.09.014

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 148

  LiR.PattersonK. R.Bar-OrA. (2018). Reassessing B cell contributions in multiple sclerosis.Nat. Immunol.19696–707. 10.1038/s41590-018-0135-x

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 149

  LiT.LiuT.ChenX.LiL.FengM.ZhangY.et al (2020). Microglia induce the transformation of A1/A2 reactive astrocytes via the CXCR7/PI3K/Akt pathway in chronic post-surgical pain.J. Neuroinflammation17:211.

  • Google Scholar

• 150

  LiW.GraeberM. B. (2012). The molecular profile of microglia under the influence of glioma.Neuro Oncol.14958–978. 10.1093/neuonc/nos116

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 151

  LiddelowS. A.GuttenplanK. A.ClarkeL. E.BennettF. C.BohlenC. J.SchirmerL.et al (2017). Neurotoxic reactive astrocytes are induced by activated microglia.Nature541481–487.

  • Google Scholar

• 152

  LimM.XiaY.BettegowdaC.WellerM. (2018). Current state of immunotherapy for glioblastoma.Nat. Rev. Clin. Oncol.15422–442. 10.1038/s41571-018-0003-5

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 153

  LinnerbauerM.WheelerM. A.QuintanaF. J. (2020). Astrocyte crosstalk in CNS inflammation.Neuron108608–622. 10.1016/j.neuron.2020.08.012

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 154

  LocatelliG.TheodorouD.KendirliA.JordãoM. J. C.StaszewskiO.PhulphagarK.et al (2018). Mononuclear phagocytes locally specify and adapt their phenotype in a multiple sclerosis model.Nat. Neurosci.211196–1208. 10.1038/s41593-018-0212-3

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 155

  LohrJ.RatliffT.HuppertzA.GeY.DictusC.AhmadiR.et al (2011). Effector T-cell infiltration positively impacts survival of glioblastoma patients and is impaired by tumor-derived TGF-β.Clin. Cancer Res.174296–4308. 10.1158/1078-0432.ccr-10-2557

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 156

  LondheV. Y.DateV. (2020). Personalized neoantigen vaccines: a glimmer of hope for glioblastoma.Expert Rev. Vaccines19407–417. 10.1080/14760584.2020.1750376

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 157

  LouveauA.HarrisT. H.KipnisJ. (2015a). Revisiting the mechanisms of CNS immune privilege.Trends Immunol.36569–577. 10.1016/j.it.2015.08.006

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 158

  LouveauA.SmirnovI.KeyesT. J.EcclesJ. D.RouhaniS. J.PeskeJ. D.et al (2015b). Structural and functional features of central nervous system lymphatic vessels.Nature523337–341. 10.1038/nature14432

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 159

  LouveauA.HerzJ.AlmeM. N.SalvadorA. F.DongM. Q.ViarK. E.et al (2018). CNS lymphatic drainage and neuroinflammation are regulated by meningeal lymphatic vasculature.Nat. Neurosci.211380–1391. 10.1038/s41593-018-0227-9

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 160

  LouveauA.PlogB. A.AntilaS.AlitaloK.NedergaardM.KipnisJ. (2017). Understanding the functions and relationships of the glymphatic system and meningeal lymphatics.J. Clin. Invest.1273210–3219. 10.1172/jci90603

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 161

  LuH. C.KimS.SteelmanA. J.TracyK.ZhouB.MichaudD.et al (2020). STAT3 signaling in myeloid cells promotes pathogenic myelin-specific T cell differentiation and autoimmune demyelination.Proc. Natl. Acad. Sci. U.S.A.1175430–5441. 10.1073/pnas.1913997117

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 162

  LuchettiS.van EdenC. G.SchuurmanK.van StrienM. E.SwaabD. F.HuitingaI. (2014). Gender differences in multiple sclerosis: induction of estrogen signaling in male and progesterone signaling in female lesions.J. Neuropathol. Exp. Neurol.73123–135. 10.1097/nen.0000000000000037

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 163

  LudwinS. K.RaoV.MooreC. S.AntelJ. P. (2016). Astrocytes in multiple sclerosis.Mult. Scler.221114–1124. 10.1177/1352458516643396

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 164

  LuessiF.ZippF.WitschE. (2016). Dendritic cells as therapeutic targets in neuroinflammation.Cell Mol. Life Sci.732425–2450. 10.1007/s00018-016-2170-9

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 165

  LünemannJ. D.RuckT.MuraroP. A.Bar-OrA.WiendlH. (2020). Immune reconstitution therapies: concepts for durable remission in multiple sclerosis.Nat. Rev. Neurol.1656–62. 10.1038/s41582-019-0268-z

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 166

  LynchC. N.WangY. C.LundJ. K.ChenY. W.LealJ. A.WileyS. R. (1999). TWEAK induces angiogenesis and proliferation of endothelial cells.J. Biol. Chem.2748455–8459. 10.1074/jbc.274.13.8455

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 167

  Machado-SantosJ.SajiE.TröscherA. R.PaunovicM.LiblauR.GabrielyG.et al (2018). The compartmentalized inflammatory response in the multiple sclerosis brain is composed of tissue-resident CD8+ T lymphocytes and B cells.Brain1412066–2082. 10.1093/brain/awy151

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 168

  MagliozziR.HowellO.VoraA.SerafiniB.NicholasR.PuopoloM.et al (2007). Meningeal B-cell follicles in secondary progressive multiple sclerosis associate with early onset of disease and severe cortical pathology.Brain130(Pt 4), 1089–1104. 10.1093/brain/awm038

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 169

  MagliozziR.HowellO. W.ReevesC.RoncaroliF.NicholasR.SerafiniB.et al (2010). A Gradient of neuronal loss and meningeal inflammation in multiple sclerosis.Ann. Neurol.68477–493. 10.1002/ana.22230

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 170

  MahataB.BiswasS.RaymanP.ChahlaviA.KoJ.BhattacharjeeA.et al (2015). GBM derived gangliosides induce T cell apoptosis through activation of the caspase cascade involving both the extrinsic and the intrinsic pathway.PLoS One10:e0134425. 10.1371/journal.pone.0134425

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 171

  MaloC. S.HugginsM. A.GodderyE. N.TolcherH. M. A.RennerD. N.JinF.et al (2018). Non-equivalent antigen presenting capabilities of dendritic cells and macrophages in generating brain-infiltrating CD8 (+) T cell responses.Nat. Commun.9:633.

  • Google Scholar

• 172

  ManninoM. H.ZhuZ.XiaoH.BaiQ.WakefieldM. R.FangY. (2015). The paradoxical role of IL-10 in immunity and cancer.Cancer Lett.367103–107. 10.1016/j.canlet.2015.07.009

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 173

  MantovaniA.AllavenaP.SicaA.BalkwillF. (2008). Cancer-related inflammation.Nature454436–444.

  • Google Scholar

• 174

  MantovaniA.SozzaniS.LocatiM.AllavenaP.SicaA. (2002). Macrophage polarization: tumor-associated macrophages as a paradigm for polarized M2 mononuclear phagocytes.Trends Immunol.23549–555. 10.1016/s1471-4906(02)02302-5

  • CrossRef
  • Google Scholar

• 175

  MartikainenM.EssandM. (2019). Virus-based immunotherapy of glioblastoma.Cancers11:186. 10.3390/cancers11020186

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 176

  MascagniP. (1787). Vasorum Lymphaticorum Corporis Humani Historia Et Ichnographia.Oristano: Ex typographia Pazzini Carli.

  • Google Scholar

• 177

  MasudaT.SankowskiR.StaszewskiO.BöttcherC.AmannL.Sagaret al (2019). Spatial and temporal heterogeneity of mouse and human microglia at single-cell resolution.Nature566388–392. 10.1038/s41586-019-0924-x

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 178

  MasudaT.SankowskiR.StaszewskiO.PrinzM. (2020). Microglia heterogeneity in the single-cell Era.Cell Rep.301271–1281. 10.1016/j.celrep.2020.01.010

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 179

  MathewsonN. D.AshenbergO.TiroshI.GritschS.PerezE. M.MarxS.et al (2021). Inhibitory CD161 receptor identified in glioma-infiltrating T cells by single-cell analysis.Cell1841281–1298. 10.1016/j.cell.2021.01.022

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 180

  MayoL.TraugerS. A.BlainM.NadeauM.PatelB.AlvarezJ. I.et al (2014). Regulation of astrocyte activation by glycolipids drives chronic CNS inflammation.Nat. Med.201147–1156. 10.1038/nm.3681

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 181

  McGinleyA. M.SuttonC. E.EdwardsS. C.LeaneC. M.DeCourceyJ.TeijeiroA.et al (2020). Interleukin-17A serves a priming role in autoimmunity by recruiting IL-1β-producing myeloid cells that promote pathogenic T cells.Immunity52342.e6–356.e6.

  • Google Scholar

• 182

  McGinleyM. P.GoldschmidtC. H.Rae-GrantA. D. (2021). Diagnosis and treatment of multiple sclerosis: a review.JAMA325765–779. 10.1001/jama.2020.26858

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 183

  McGranahanN.SwantonC. (2019). Neoantigen quality, not quantity.Sci. Transl. Med.11:eaax7918. 10.1126/scitranslmed.aax7918

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 184

  McMahonE. J.BaileyS. L.CastenadaC. V.WaldnerH.MillerS. D. (2005). Epitope spreading initiates in the CNS in two mouse models of multiple sclerosis.Nat. Med.11335–339. 10.1038/nm1202

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 185

  McMenaminP. G. (1999). Distribution and phenotype of dendritic cells and resident tissue macrophages in the dura mater, leptomeninges, and choroid plexus of the rat brain as demonstrated in wholemount preparations.J. Comp. Neurol.405553–562. 10.1002/(sici)1096-9861(19990322)405:4<553::aid-cne8>3.0.co;2-6

  • CrossRef
  • Google Scholar

• 186

  MedawarP. B. (1948). Immunity to homologous grafted skin; the fate of skin homografts transplanted to the brain, to subcutaneous tissue, and to the anterior chamber of the eye.Br. J. Exp. Pathol.2958–69.

  • Google Scholar

• 187

  MedzhitovR. (2008). Origin and physiological roles of inflammation.Nature454428–435. 10.1038/nature07201

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 188

  MichelL.TouilH.PikorN. B.GommermanJ. L.PratA.Bar-OrA. (2015). B cells in the multiple sclerosis central nervous system: trafficking and contribution to CNS-compartmentalized inflammation.Front. Immunol.6:636. 10.3389/fimmu.2015.00636

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 189

  MiedemaA.WijeringM. H. C.EggenB. J. L.KooistraS. M. (2020). High-resolution transcriptomic and proteomic profiling of heterogeneity of brain-derived microglia in multiple sclerosis.Front. Mol. Neurosci.13:583811. 10.3389/fnmol.2020.583811

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 190

  MillerS. D.McMahonE. J.SchreinerB.BaileyS. L. (2007). Antigen presentation in the CNS by myeloid dendritic cells drives progression of relapsing experimental autoimmune encephalomyelitis.Ann. N.Y. Acad. Sci.1103179–191. 10.1196/annals.1394.023

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 191

  MirzaeiR.SarkarS.DzikowskiL.RawjiK. S.KhanL.FaissnerA.et al (2018). Brain tumor-initiating cells export tenascin-C associated with exosomes to suppress T cell activity.Oncoimmunology7:e1478647. 10.1080/2162402x.2018.1478647

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 192

  MirzaeiR.SarkarS.YongV. W. (2017). T cell exhaustion in glioblastoma: intricacies of immune checkpoints.Trends Immunol.38104–115. 10.1016/j.it.2016.11.005

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 193

  MiskaJ.Lee-ChangC.RashidiA.MuroskiM. E.ChangA. L.Lopez-RosasA.et al (2019). HIF-1α is a metabolic switch between glycolytic-driven migration and oxidative phosphorylation-driven immunosuppression of tregs in glioblastoma.Cell Rep.27226.e4–237.e4.

  • Google Scholar

• 194

  MitchellD.ChintalaS.DeyM. (2018). Plasmacytoid dendritic cell in immunity and cancer.J. Neuroimmunol.32263–73. 10.1016/j.jneuroim.2018.06.012

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 195

  MitchellD. A.BatichK. A.GunnM. D.HuangM. N.Sanchez-PerezL.NairS. K.et al (2015). Tetanus toxoid and CCL3 improve dendritic cell vaccines in mice and glioblastoma patients.Nature519366–369. 10.1038/nature14320

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 196

  MitrasinovicO. M.PerezG. V.ZhaoF.LeeY. L.PoonC.MurphyG. M.Jr. (2001). Overexpression of macrophage colony-stimulating factor receptor on microglial cells induces an inflammatory response.J. Biol. Chem.27630142–30149. 10.1074/jbc.m104265200

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 197

  MohmeM.NeidertM. C. (2020). Tumor-specific T cell activation in malignant brain tumors.Front. Immunol.11:205. 10.3389/fimmu.2020.00205

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 198

  MonaghanK. L.ZhengW.HuG.WanE. C. K. (2019). Monocytes and monocyte-derived antigen-presenting cells have distinct gene signatures in experimental model of multiple sclerosis.Front. Immunol.10:2779. 10.3389/fimmu.2019.02779

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 199

  MorenoM. A.BurnsT.YaoP.MiersL.PleasureD.SoulikaA. M. (2016). Therapeutic depletion of monocyte-derived cells protects from long-term axonal loss in experimental autoimmune encephalomyelitis.J. Neuroimmunol.29036–46. 10.1016/j.jneuroim.2015.11.004

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 200

  MorimuraT.NeuchristC.KitzK.BudkaH.ScheinerO.KraftD.et al (1990). Monocyte subpopulations in human gliomas: expression of Fc and complement receptors and correlation with tumor proliferation.Acta Neuropathol.80287–294. 10.1007/bf00294647

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 201

  MosserD. M.EdwardsJ. P. (2008). Exploring the full spectrum of macrophage activation.Nat. Rev. Immunol.8958–969. 10.1038/nri2448

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 202

  MuesM.BartholomäusI.ThestrupT.GriesbeckO.WekerleH.KawakamiN.et al (2013). Real-time in vivo analysis of T cell activation in the central nervous system using a genetically encoded calcium indicator.Nat. Med.19778–783. 10.1038/nm.3180

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 203

  MundtS.GreterM.FlügelA.BecherB. (2019). The CNS immune landscape from the viewpoint of a T cell.Trends Neurosci.42667–679. 10.1016/j.tins.2019.07.008

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 204

  MunnD. H.SharmaM. D.HouD.BabanB.LeeJ. R.AntoniaS. J.et al (2004). Expression of indoleamine 2,3-dioxygenase by plasmacytoid dendritic cells in tumor-draining lymph nodes.J. Clin. Invest.114280–290. 10.1172/jci200421583

  • CrossRef
  • Google Scholar

• 205

  NakanoY.KurodaE.KitoT.UematsuS.AkiraS.YokotaA.et al (2008). Induction of prostaglandin E2 synthesis and microsomal prostaglandin E synthase-1 expression in murine microglia by glioma-derived soluble factors. Laboratory investigation.J. Neurosurg.108311–319. 10.3171/jns/2008/108/2/0311

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 206

  NielsenN.ØdumN.UrsøB.LanierL. L.SpeeP. (2012). Cytotoxicity of CD56(bright) NK cells towards autologous activated CD4+ T cells is mediated through NKG2D, LFA-1 and TRAIL and dampened via CD94/NKG2A.PLoS One7:e31959. 10.1371/journal.pone.0031959

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 207

  NiuJ.TsaiH. H.HoiK. K.HuangN.YuG.KimK.et al (2019). Aberrant oligodendroglial-vascular interactions disrupt the blood-brain barrier, triggering CNS inflammation.Nat. Neurosci.22709–718. 10.1038/s41593-019-0369-4

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 208

  OhS. A.LiM. O. (2013). TGF-β: guardian of T cell function.J. Immunol.1913973–3979. 10.4049/jimmunol.1301843

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 209

  OoiY. C.TranP.UngN.ThillK.TrangA.FongB. M.et al (2014). The role of regulatory T-cells in glioma immunology.Clin. Neurol. Neurosurg.119125–132.

  • Google Scholar

• 210

  PalanichamyA.ApeltsinL.KuoT. C.SirotaM.WangS.PittsS. J.et al (2014). Immunoglobulin class-switched B cells form an active immune axis between CNS and periphery in multiple sclerosis.Sci. Transl. Med.6:248ra106. 10.1126/scitranslmed.3008930

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 211

  PallandreJ. R.BrillardE.CréhangeG.RadlovicA.Remy-MartinJ. P.SaasP.et al (2007). Role of STAT3 in CD4+CD25+FOXP3+ regulatory lymphocyte generation: implications in graft-versus-host disease and antitumor immunity.J. Immunol.1797593–7604. 10.4049/jimmunol.179.11.7593

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 212

  PanekW. K.PituchK. C.MiskaJ.KimJ. W.RashidiA.KanojiaD.et al (2019). Local application of autologous platelet-rich fibrin patch (PRF-P) suppresses regulatory T cell recruitment in a murine glioma model.Mol. Neurobiol.565032–5040. 10.1007/s12035-018-1430-0

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 213

  PapadopoulosZ.HerzJ.KipnisJ. (2020). Meningeal lymphatics: from anatomy to central nervous system immune surveillance.J. Immunol.204286–293. 10.4049/jimmunol.1900838

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 214

  PapalexiE.SatijaR. (2018). Single-cell RNA sequencing to explore immune cell heterogeneity.Nat. Rev. Immunol.1835–45. 10.1038/nri.2017.76

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 215

  PashenkovM.HuangY. M.KostulasV.HaglundM.SöderströmM.LinkH. (2001). Two subsets of dendritic cells are present in human cerebrospinal fluid.Brain124(Pt 3), 480–492. 10.1093/brain/124.3.480

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 216

  PatenteT. A.PinhoM. P.OliveiraA. A.EvangelistaG. C. M.Bergami-SantosP. C.BarbutoJ. A. M. (2018). Human dendritic cells: their heterogeneity and clinical application potential in cancer immunotherapy.Front. Immunol.9:3176. 10.3389/fimmu.2018.03176

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 217

  PhamH.RampA. A.KlonisN.NgS. W.KlopsteinA.AyersM. M.et al (2009). The astrocytic response in early experimental autoimmune encephalomyelitis occurs across both the grey and white matter compartments.J. Neuroimmunol.20830–39. 10.1016/j.jneuroim.2008.12.010

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 218

  PierceS. K.MorrisJ. F.GrusbyM. J.KaumayaP.van BuskirkA.SrinivasanM.et al (1988). Antigen-presenting function of B lymphocytes.Immunol. Rev.106149–180.

  • Google Scholar

• 219

  PikorN. B.PratA.Bar-OrA.GommermanJ. L. (2015). Meningeal tertiary lymphoid tissues and multiple sclerosis: a gathering place for diverse types of immune cells during CNS autoimmunity.Front. Immunol.6:657. 10.3389/fimmu.2015.00657

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 220

  PiperiC.PapavassiliouK. A.PapavassiliouA. G. (2019). Pivotal role of STAT3 in shaping glioblastoma immune microenvironment.Cells8:1398. 10.3390/cells8111398

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 221

  PlastiniM. J.DesuH. L.BrambillaR. (2020). Dynamic responses of microglia in animal models of multiple sclerosis.Front. Cell Neurosci.14:269. 10.3389/fncel.2020.00269

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 222

  PlattenM.WickW.WellerM. (2001). Malignant glioma biology: role for TGF-beta in growth, motility, angiogenesis, and immune escape.Microsc. Res. Tech.52401–410. 10.1002/1097-0029(20010215)52:4<401::aid-jemt1025>3.0.co;2-c

  • CrossRef
  • Google Scholar

• 223

  PlemelJ. R.StrattonJ. A.MichaelsN. J.RawjiK. S.ZhangE.SinhaS.et al (2020). Microglia response following acute demyelination is heterogeneous and limits infiltrating macrophage dispersion.Sci. Adv.6:eaay6324. 10.1126/sciadv.aay6324

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 224

  Pombo AntunesA. R.ScheyltjensI.LodiF.MessiaenJ.AntoranzA.DuerinckJ.et al (2021). Single-cell profiling of myeloid cells in glioblastoma across species and disease stage reveals macrophage competition and specialization.Nat. Neurosci.24595–610. 10.1038/s41593-020-00789-y

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 225

  PonathG.ParkC.PittD. (2018). The role of astrocytes in multiple sclerosis.Front. Immunol.9:217. 10.3389/fimmu.2018.00217

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 226

  PonathG.RamananS.MubarakM.HousleyW.LeeS.SahinkayaF. R.et al (2017). Myelin phagocytosis by astrocytes after myelin damage promotes lesion pathology.Brain140399–413. 10.1093/brain/aww298

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 227

  PonomarevE. D.ShriverL. P.MareszK.DittelB. N. (2005). Microglial cell activation and proliferation precedes the onset of CNS autoimmunity.J. Neurosci. Res.81374–389. 10.1002/jnr.20488

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 228

  PrinzM.JungS.PrillerJ. (2019). Microglia biology: one century of evolving concepts.Cell179292–311. 10.1016/j.cell.2019.08.053

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 229

  PrinzM.PrillerJ. (2017). The role of peripheral immune cells in the CNS in steady state and disease.Nat. Neurosci.20136–144. 10.1038/nn.4475

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 230

  ProdingerC.BunseJ.KrügerM.SchiefenhövelF.BrandtC.LamanJ. D.et al (2011). CD11c-expressing cells reside in the juxtavascular parenchyma and extend processes into the glia limitans of the mouse nervous system.Acta Neuropathol.121445–458. 10.1007/s00401-010-0774-y

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 231

  PyonteckS. M.AkkariL.SchuhmacherA. J.BowmanR. L.SevenichL.QuailD. F.et al (2013). CSF-1R inhibition alters macrophage polarization and blocks glioma progression.Nat. Med.191264–1272.

  • Google Scholar

• 232

  QuintanaF. J.PatelB.YesteA.NyirendaM.KenisonJ.RahbariR.et al (2014). Epitope spreading as an early pathogenic event in pediatric multiple sclerosis.Neurology832219–2226. 10.1212/wnl.0000000000001066

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 233

  RadjaviA.SmirnovI.DereckiN.KipnisJ. (2014). Dynamics of the meningeal CD4(+) T-cell repertoire are defined by the cervical lymph nodes and facilitate cognitive task performance in mice.Mol. Psychiatry19531–533. 10.1038/mp.2013.79

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 234

  RameshA.SchubertR. D.GreenfieldA. L.DandekarR.LoudermilkR.SabatinoJ. J.Jr.et al (2020). A pathogenic and clonally expanded B cell transcriptome in active multiple sclerosis.Proc. Natl. Acad. Sci. U.S.A.11722932–22943. 10.1073/pnas.2008523117

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 235

  RansohoffR. M.EngelhardtB. (2012). The anatomical and cellular basis of immune surveillance in the central nervous system.Nat. Rev. Immunol.12623–635. 10.1038/nri3265

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 236

  RiveraA.ChenC. C.RonN.DoughertyJ. P.RonY. (2001). Role of B cells as antigen-presenting cells in vivo revisited: antigen-specific B cells are essential for T cell expansion in lymph nodes and for systemic T cell responses to low antigen concentrations.Int. Immunol.131583–1593. 10.1093/intimm/13.12.1583

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 237

  Rodríguez-GómezJ. A.KavanaghE.Engskog-VlachosP.EngskogM. K. R.HerreraA. J.Espinosa-OlivaA. M.et al (2020). Microglia: agents of the CNS pro-inflammatory response.Cells9:1717. 10.3390/cells9071717

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 238

  RomaniM.PistilloM. P.CarosioR.MorabitoA.BanelliB. (2018). Immune checkpoints and innovative therapies in glioblastoma.Front. Oncol.8:464. 10.3389/fonc.2018.00464

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 239

  RosenthalR.CadieuxE. L.SalgadoR.BakirM. A.MooreD. A.HileyC. T.et al (2019). Neoantigen-directed immune escape in lung cancer evolution.Nature567479–485.

  • Google Scholar

• 240

  RothhammerV.KenisonJ. E.TjonE.TakenakaM. C.de LimaK. A.BoruckiD. M.et al (2017). Sphingosine 1-phosphate receptor modulation suppresses pathogenic astrocyte activation and chronic progressive CNS inflammation.Proc. Natl. Acad. Sci. U.S.A.1142012–2017. 10.1073/pnas.1615413114

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 241

  RothhammerV.MascanfroniI. D.BunseL.TakenakaM. C.KenisonJ. E.MayoL.et al (2016). Type I interferons and microbial metabolites of tryptophan modulate astrocyte activity and central nervous system inflammation via the aryl hydrocarbon receptor.Nat. Med.22586–597. 10.1038/nm.4106

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 242

  RotsteinD.MontalbanX. (2019). Reaching an evidence-based prognosis for personalized treatment of multiple sclerosis.Nat. Rev. Neurol.15287–300. 10.1038/s41582-019-0170-8

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 243

  SalioM.CellaM.VermiW.FacchettiF.PalmowskiM. J.SmithC. L.et al (2003). Plasmacytoid dendritic cells prime IFN-gamma-secreting melanoma-specific CD8 lymphocytes and are found in primary melanoma lesions.Eur. J. Immunol.331052–1062. 10.1002/eji.200323676

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 244

  SankowskiR.BöttcherC.MasudaT.GeirsdottirL.SagarE. SindramSeredeninaT.et al (2019). Mapping microglia states in the human brain through the integration of high-dimensional techniques.Nat. Neurosci.222098–2110. 10.1038/s41593-019-0532-y

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 245

  SawantA.HenselJ. A.ChandaD.HarrisB. A.SiegalG. P.MaheshwariA.et al (2012). Depletion of plasmacytoid dendritic cells inhibits tumor growth and prevents bone metastasis of breast cancer cells.J. Immunol.1894258–4265. 10.4049/jimmunol.1101855

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 246

  SchettersS. T. T.Gomez-NicolaD.Garcia-VallejoJ. J.Van KooykY. (2017). Neuroinflammation: microglia and T cells get ready to tango.Front. Immunol.8:1905. 10.3389/fimmu.2017.01905

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 247

  SchlägerC.KörnerH.KruegerM.VidoliS.HaberlM.MielkeD.et al (2016). Effector T-cell trafficking between the leptomeninges and the cerebrospinal fluid.Nature530349–353. 10.1038/nature16939

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 248

  ScottG.ZetterbergH.JollyA.ColeJ. H.De SimoniS.JenkinsP. O.et al (2018). Minocycline reduces chronic microglial activation after brain trauma but increases neurodegeneration.Brain141459–471. 10.1093/brain/awx339

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 249

  SelewskiD. T.ShahG. V.SegalB. M.RajdevP. A.MukherjiS. K. (2010). Natalizumab (Tysabri).AJNR Am. J. Neuroradiol.311588–1590.

  • Google Scholar

• 250

  SerafiniB.RosicarelliB.MagliozziR.StiglianoE.CapelloE.MancardiG. L.et al (2006). Dendritic cells in multiple sclerosis lesions: maturation stage, myelin uptake, and interaction with proliferating T cells.J. Neuropathol. Exp. Neurol.65124–141. 10.1093/jnen/65.2.124

  • CrossRef
  • Google Scholar

• 251

  SharmaM. D.BabanB.ChandlerP.HouD. Y.SinghN.YagitaH.et al (2007). Plasmacytoid dendritic cells from mouse tumor-draining lymph nodes directly activate mature Tregs via indoleamine 2,3-dioxygenase.J. Clin. Invest.1172570–2582. 10.1172/jci31911

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 252

  ShenP.FillatreauS. (2015). Antibody-independent functions of B cells: a focus on cytokines.Nat. Rev. Immunol.15441–451. 10.1038/nri3857

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 253

  ShimatoS.MaierL. M.MaierR.BruceJ. N.AndersonR. C.AndersonD. E. (2012). Profound tumor-specific Th2 bias in patients with malignant glioma.BMC Cancer12:561. 10.1186/1471-2407-12-561

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 254

  ShipleyF. B.DaniN.XuH.DeisterC.CuiJ.HeadJ. P.et al (2020). Tracking calcium dynamics and immune surveillance at the choroid plexus blood-cerebrospinal fluid interface.Neuron108623.e10–639.e10.

  • Google Scholar

• 255

  SiffrinV.BrandtA. U.RadbruchH.HerzJ.BoldakowaN.LeuenbergerT.et al (2009). Differential immune cell dynamics in the CNS cause CD4+ T cell compartmentalization.Brain132(Pt 5), 1247–1258. 10.1093/brain/awn354

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 256

  SofroniewM. V. (2009). Molecular dissection of reactive astrogliosis and glial scar formation.Trends Neurosci.32638–647. 10.1016/j.tins.2009.08.002

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 257

  SofroniewM. V. (2015). Astrocyte barriers to neurotoxic inflammation.Nat. Rev. Neurosci.16249–263. 10.1038/nrn3898

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 258

  SofroniewM. V.VintersH. V. (2010). Astrocytes: biology and pathology.Acta Neuropathol.1197–35. 10.1007/s00401-009-0619-8

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 259

  SpittauB.DokalisN.PrinzM. (2020). The role of TGFβ signaling in microglia maturation and activation.Trends Immunol.41836–848. 10.1016/j.it.2020.07.003

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 260

  StasiolekM.BayasA.KruseN.WieczarkowieczA.ToykaK. V.GoldR.et al (2006). Impaired maturation and altered regulatory function of plasmacytoid dendritic cells in multiple sclerosis.Brain129(Pt 5), 1293–1305. 10.1093/brain/awl043

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 261

  StephanD.SbaiO.WenJ.CouraudP. O.PuttermanC.KhrestchatiskyM.et al (2013). TWEAK/Fn14 pathway modulates properties of a human microvascular endothelial cell model of blood brain barrier.J. Neuroinflammation.10:9.

  • Google Scholar

• 262

  SternJ. N.YaariG.Vander HeidenJ. A.ChurchG.DonahueW. F.HintzenR. Q.et al (2014). B cells populating the multiple sclerosis brain mature in the draining cervical lymph nodes.Sci. Transl. Med.6:248ra107. 10.1126/scitranslmed.3008879

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 263

  Stojić-VukanićZ.HadžibegovićS.NicoleO.Nacka-AleksićM.LeštarevićS.LeposavićG. (2020). CD8+ T cell-mediated mechanisms contribute to the progression of neurocognitive impairment in both multiple sclerosis and Alzheimer’s disease?Front. Immunol.11:566225. 10.3389/fimmu.2020.566225

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 264

  SuzumuraA.SawadaM.YamamotoH.MarunouchiT. (1993). Transforming growth factor-beta suppresses activation and proliferation of microglia in vitro.J. Immunol.1512150–2158.

  • Google Scholar

• 265

  SzulzewskyF.PelzA.FengX.SynowitzM.MarkovicD.LangmannT.et al (2015). Glioma-associated microglia/macrophages display an expression profile different from M1 and M2 polarization and highly express Gpnmb and Spp1.PLoS One10:e0116644. 10.1371/journal.pone.0116644

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 266

  TakashimaY.KawaguchiA.KanayamaT.HayanoA.YamanakaR. (2018). Correlation between lower balance of Th2 helper T-cells and expression of PD-L1/PD-1 axis genes enables prognostic prediction in patients with glioblastoma.Oncotarget919065–19078. 10.18632/oncotarget.24897

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 267

  TakenakaM. C.GabrielyG.RothhammerV.MascanfroniI. D.WheelerM. A.ChaoC. C.et al (2019). Control of tumor-associated macrophages and T cells in glioblastoma via AHR and CD39.Nat. Neurosci.22729–740. 10.1038/s41593-019-0370-y

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 268

  TaniguchiY.OnoK.YoshidaS.TanakaR. (2000). Antigen-presenting capability of glial cells under glioma-harboring conditions and the effect of glioma-derived factors on antigen presentation.J. Neuroimmunol.111177–185. 10.1016/s0165-5728(00)00361-1

  • CrossRef
  • Google Scholar

• 269

  TarditoS.OudinA.AhmedS. U.FackF.KeunenO.ZhengL.et al (2015). Glutamine synthetase activity fuels nucleotide biosynthesis and supports growth of glutamine-restricted glioblastoma.Nat. Cell Biol.171556–1568. 10.1038/ncb3272

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 270

  TopalianS. L.DrakeC. G.PardollD. M. (2015). Immune checkpoint blockade: a common denominator approach to cancer therapy.Cancer Cell27450–461. 10.1016/j.ccell.2015.03.001

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 271

  TrinchieriG. (2003). Interleukin-12 and the regulation of innate resistance and adaptive immunity.Nat. Rev. Immunol.3133–146. 10.1038/nri1001

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 272

  TsaiH. C.HanM. H. (2016). Sphingosine-1-phosphate (S1P) and S1P signaling pathway: therapeutic targets in autoimmunity and inflammation.Drugs761067–1079. 10.1007/s40265-016-0603-2

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 273

  TuohyV. K.KinkelR. P. (2000). Epitope spreading: a mechanism for progression of autoimmune disease.Arch. Immunol. Ther. Exp.48347–351.

  • Google Scholar

• 274

  UchidaY.SumiyaT.TachikawaM.YamakawaT.MurataS.YagiY.et al (2019). Involvement of claudin-11 in disruption of blood-brain, -spinal cord, and -arachnoid barriers in multiple sclerosis.Mol. Neurobiol.562039–2056. 10.1007/s12035-018-1207-5

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 275

  UgoliniA.TyurinV. A.TyurinaY. Y.TcyganovE. N.DonthireddyL.KaganV. E.et al (2020). Polymorphonuclear myeloid-derived suppressor cells limit antigen cross-presentation by dendritic cells in cancer.JCI Insight5:e138581.

  • Google Scholar

• 276

  van der PoelM.HoepelW.HamannJ.HuitingaI.DunnenJ. D. (2020). IgG immune complexes break immune tolerance of human microglia.J. Immunol.2052511–2518. 10.4049/jimmunol.2000130

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 277

  Van DoornR.Van HorssenJ.VerzijlD.WitteM.RonkenE.Van Het HofB.et al (2010). Sphingosine 1-phosphate receptor 1 and 3 are upregulated in multiple sclerosis lesions.Glia581465–1476. 10.1002/glia.21021

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 278

  Van HoveH.MartensL.ScheyltjensI.De VlaminckK.Pombo AntunesA. R.De PrijckS.et al (2019). A single-cell atlas of mouse brain macrophages reveals unique transcriptional identities shaped by ontogeny and tissue environment.Nat. Neurosci.221021–1035. 10.1038/s41593-019-0393-4

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 279

  VegliaF.TyurinV. A.MohammadyaniD.BlasiM.DuperretE. K.DonthireddyL.et al (2017). Lipid bodies containing oxidatively truncated lipids block antigen cross-presentation by dendritic cells in cancer.Nat. Commun.8:2122.

  • Google Scholar

• 280

  VermiW.BonecchiR.FacchettiF.BianchiD.SozzaniS.FestaS.et al (2003). Recruitment of immature plasmacytoid dendritic cells (plasmacytoid monocytes) and myeloid dendritic cells in primary cutaneous melanomas.J. Pathol.200255–268. 10.1002/path.1344

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 281

  VoskuhlR. R.PetersonR. S.SongB.AoY.MoralesL. B.Tiwari-WoodruffS.et al (2009). Reactive astrocytes form scar-like perivascular barriers to leukocytes during adaptive immune inflammation of the CNS.J. Neurosci.2911511–11522. 10.1523/jneurosci.1514-09.2009

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 282

  WalkerD. G.ChuahT.RistM. J.PenderM. P. (2006). T-cell apoptosis in human glioblastoma multiforme: implications for immunotherapy.J. Neuroimmunol.17559–68. 10.1016/j.jneuroim.2006.03.006

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 283

  WalkerL. S. (2009). Regulatory T cells overturned: the effectors fight back.Immunology126466–474. 10.1111/j.1365-2567.2009.03053.x

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 284

  WangD.AyersM. M.CatmullD. V.HazelwoodL. J.BernardC. C.OrianJ. M. (2005). Astrocyte-associated axonal damage in pre-onset stages of experimental autoimmune encephalomyelitis.Glia51235–240. 10.1002/glia.20199

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 285

  WangH.ZhouH.XuJ.LuY.JiX.YaoY.et al (2021). Different T-cell subsets in glioblastoma multiforme and targeted immunotherapy.Cancer Lett.496134–143. 10.1016/j.canlet.2020.09.028

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 286

  WangQ.HeZ.HuangM.LiuT.WangY.XuH.et al (2018). Vascular niche IL-6 induces alternative macrophage activation in glioblastoma through HIF-2α.Nat. Commun.9:559.

  • Google Scholar

• 287

  WangX.HaroonF.KarrayS.MartinaD.SchlüterD. (2013). Astrocytic Fas ligand expression is required to induce T-cell apoptosis and recovery from experimental autoimmune encephalomyelitis.Eur. J. Immunol.43115–124. 10.1002/eji.201242679

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 288

  WangY.LinY. X.QiaoS. L.AnH. W.MaY.QiaoZ. Y.et al (2017). Polymeric nanoparticles promote macrophage reversal from M2 to M1 phenotypes in the tumor microenvironment.Biomaterials112153–163. 10.1016/j.biomaterials.2016.09.034

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 289

  WheelerM. A.ClarkI. C.TjonE. C.LiZ.ZandeeS. E. J.CouturierC. P.et al (2020). MAFG-driven astrocytes promote CNS inflammation.Nature578593–599. 10.1038/s41586-020-1999-0

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 290

  WherryE. J.KurachiM. (2015). Molecular and cellular insights into T cell exhaustion.Nat. Rev. Immunol.15486–499. 10.1038/nri3862

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 291

  WilliamsL.BradleyL.SmithA.FoxwellB. (2004). Signal transducer and activator of transcription 3 is the dominant mediator of the anti-inflammatory effects of IL-10 in human macrophages.J. Immunol.172567–576. 10.4049/jimmunol.172.1.567

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 292

  WolburgH.PaulusW. (2010). Choroid plexus: biology and pathology.Acta Neuropathol.11975–88. 10.1007/s00401-009-0627-8

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 293

  WoronieckaK.FecciP. E. (2020). Immuno-synergy? Neoantigen vaccines and checkpoint blockade in glioblastoma.Neuro Oncol.221233–1234. 10.1093/neuonc/noaa170

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 294

  WoronieckaK. I.RhodinK. E.ChongsathidkietP.KeithK. A.FecciP. E. (2018). T-cell dysfunction in glioblastoma: applying a new framework.Clin. Cancer Res.243792–3802. 10.1158/1078-0432.ccr-18-0047

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 295

  YamamotoT. N.KishtonR. J.RestifoN. P. (2019). Developing neoantigen-targeted T cell-based treatments for solid tumors.Nat. Med.251488–1499. 10.1038/s41591-019-0596-y

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 296

  YanJ.ZhaoQ.GabrusiewiczK.KongL. Y.XiaX.WangJ.et al (2019). FGL2 promotes tumor progression in the CNS by suppressing CD103(+) dendritic cell differentiation.Nat. Commun.10:448.

  • Google Scholar

• 297

  YanZ.GibsonS. A.BuckleyJ. A.QinH.BenvenisteE. N. (2018). Role of the JAK/STAT signaling pathway in regulation of innate immunity in neuroinflammatory diseases.Clin. Immunol.1894–13. 10.1016/j.clim.2016.09.014

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 298

  YednockT. A.CannonC.FritzL. C.Sanchez-MadridF.SteinmanL.KarinN. (1992). Prevention of experimental autoimmune encephalomyelitis by antibodies against alpha 4 beta 1 integrin.Nature35663–66. 10.1038/356063a0

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 299

  YepesM. (2007). TWEAK and the central nervous system.Mol. Neurobiol.35255–265. 10.1007/s12035-007-0024-z

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 300

  YinJ.KimS. S.ChoiE.OhY. T.LinW.KimT. H.et al (2020). ARS2/MAGL signaling in glioblastoma stem cells promotes self-renewal and M2-like polarization of tumor-associated macrophages.Nat. Commun.11:2978.

  • Google Scholar

• 301

  YongV. W.ChabotS.StuveO.WilliamsG. (1998). Interferon beta in the treatment of multiple sclerosis: mechanisms of action.Neurology51682–689. 10.1212/wnl.51.3.682

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 302

  YuH.PardollD.JoveR. (2009). STATs in cancer inflammation and immunity: a leading role for STAT3.Nat. Rev. Cancer9798–809. 10.1038/nrc2734

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 303

  ZeinerP. S.PreusseC.GolebiewskaA.ZinkeJ.IriondoA.MullerA.et al (2019). Distribution and prognostic impact of microglia/macrophage subpopulations in gliomas.Brain Pathol.29513–529. 10.1111/bpa.12690

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 304

  ZeitelhoferM.AdzemovicM. Z.MoessingerC.StefanitschC.StrellC.MuhlL.et al (2020). Blocking PDGF-CC signaling ameliorates multiple sclerosis-like neuroinflammation by inhibiting disruption of the blood-brain barrier.Sci. Rep.10:22383.

  • Google Scholar

• 305

  ZhangY.MudgalP.WangL.WuH.HuangN.AlexanderP. B.et al (2020). T cell receptor repertoire as a prognosis marker for heat shock protein peptide complex-96 vaccine trial against newly diagnosed glioblastoma.Oncoimmunology9:1749476. 10.1080/2162402x.2020.1749476

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 306

  ZhangY.SloanS. A.ClarkeL. E.CanedaC.PlazaC. A.BlumenthalP. D.et al (2016). Purification and characterization of progenitor and mature human astrocytes reveals transcriptional and functional differences with mouse.Neuron8937–53. 10.1016/j.neuron.2015.11.013

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 307

  ZhuB.BandoY.XiaoS.YangK.AndersonA. C.KuchrooV. K.et al (2007). CD11b+Ly-6C(hi) suppressive monocytes in experimental autoimmune encephalomyelitis.J. Immunol.1795228–5237. 10.4049/jimmunol.179.8.5228

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 308

  ZhuX.FujitaM.SnyderL. A.OkadaH. (2011). Systemic delivery of neutralizing antibody targeting CCL2 for glioma therapy.J. Neurooncol.10483–92. 10.1007/s11060-010-0473-5

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 309

  ZiaS.RawjiK. S.MichaelsN. J.BurrM.KerrB. J.HealyL. M.et al (2020). Microglia diversity in health and multiple sclerosis.Front. Immunol.11:588021. 10.3389/fimmu.2020.588021

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 310

  ZongH.VerhaakR. G.CanollP. (2012). The cellular origin for malignant glioma and prospects for clinical advancements.Expert Rev. Mol. Diagn.12383–394. 10.1586/erm.12.30

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 311

  ZongJ.KeskinovA. A.ShurinG. V.ShurinM. R. (2016). Tumor-derived factors modulating dendritic cell function.Cancer Immunol. Immunother.65821–833. 10.1007/s00262-016-1820-y

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 312

  ZrzavyT.HametnerS.WimmerI.ButovskyO.WeinerH. L.LassmannH. (2017). Loss of ‘homeostatic’ microglia and patterns of their activation in active multiple sclerosis.Brain1401900–1913. 10.1093/brain/awx113

  • Pubmed Abstract
  • CrossRef
  • Google Scholar