Next Article in Journal
Variable Induction of Pro-Inflammatory Cytokines by Commercial SARS CoV-2 Spike Protein Reagents: Potential Impacts of LPS on In Vitro Modeling and Pathogenic Mechanisms In Vivo
Next Article in Special Issue
Cells to the Rescue: Emerging Cell-Based Treatment Approaches for NMOSD and MOGAD
Previous Article in Journal
Post-Embryonic Phase Transitions Mediated by Polycomb Repressive Complexes in Plants
Previous Article in Special Issue
Transfection of Vitamin D3-Induced Tolerogenic Dendritic Cells for the Silencing of Potential Tolerogenic Genes. Identification of CSF1R-CSF1 Signaling as a Glycolytic Regulator
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Made to Measure: Patient-Tailored Treatment of Multiple Sclerosis Using Cell-Based Therapies

1
Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (Vaxinfectio), University of Antwerp, Middelheimlaan 1, B-2020 Antwerpen, Belgium
2
Department of Neurology, Antwerp University Hospital, Drie Eikenstraat 655, B-2650 Edegem, Belgium
3
Center for Cell Therapy and Regenerative Medicine (CCRG), Antwerp University Hospital, Drie Eikenstraat 655, B-2650 Edegem, Belgium
*
Author to whom correspondence should be addressed.
These authors contributed equally and are joint first authors.
These authors contributed equally and are joint senior authors.
Int. J. Mol. Sci. 2021, 22(14), 7536; https://doi.org/10.3390/ijms22147536
Submission received: 31 May 2021 / Revised: 25 June 2021 / Accepted: 28 June 2021 / Published: 14 July 2021
(This article belongs to the Special Issue Tolerogenic Cell-Based Therapy: Where We Stand?)

Abstract

:
Currently, there is still no cure for multiple sclerosis (MS), which is an autoimmune and neurodegenerative disease of the central nervous system. Treatment options predominantly consist of drugs that affect adaptive immunity and lead to a reduction of the inflammatory disease activity. A broad range of possible cell-based therapeutic options are being explored in the treatment of autoimmune diseases, including MS. This review aims to provide an overview of recent and future advances in the development of cell-based treatment options for the induction of tolerance in MS. Here, we will focus on haematopoietic stem cells, mesenchymal stromal cells, regulatory T cells and dendritic cells. We will also focus on less familiar cell types that are used in cell therapy, including B cells, natural killer cells and peripheral blood mononuclear cells. We will address key issues regarding the depicted therapies and highlight the major challenges that lie ahead to successfully reverse autoimmune diseases, such as MS, while minimising the side effects. Although cell-based therapies are well known and used in the treatment of several cancers, cell-based treatment options hold promise for the future treatment of autoimmune diseases in general, and MS in particular.

1. Introduction

Multiple sclerosis (MS) is an autoimmune and degenerative disease of the central nervous system (CNS) that is characterised by demyelination, axonal degeneration and gliosis [1]. It is the leading cause of non-traumatic neurological disability in young and middle-aged adults [2,3]; approximately 500,000 people in Europe and 2.5 million people worldwide have been diagnosed with MS. Intra- and interindividual heterogeneity in the presentation and evolution of the disease are common among patients with MS. According to Lublin et al., there are four disease courses of MS [4]. Relapsing–remitting MS (RRMS) is characterised by inflammatory attacks resulting in new or increasing neurologic symptoms (relapses) followed by periods of partial or complete recovery (remission). Secondary progressive MS (SPMS), which usually occurs within 15 years in approximately half of individuals with RRMS without treatment, is characterised by a continuous, irreversible neurological decline, reduction in brain volume and axonal loss. A primary progressive disease course (PPMS) is present in 10–15% of patients with MS and involves a steady worsening of symptoms with no periodic relapses or remissions. Progressive-relapsing MS (PRMS) is a rare form of MS that is aggressive at onset and involves frequent attacks without recovery of symptoms [1,5,6,7,8].
MS is a complex disease that results from a combination of genetic burden of several risk alleles and environmental factors, including low vitamin D levels, smoking and previous infection with Epstein–Barr virus, affecting immune homeostasis in MS patients [1]. Although the aetiology of MS remains to be elucidated, a dysregulated T cell immune response that involves T helper type 1 (Th1) and Th17 lymphocytes forms the pathophysiological basis of this autoimmune disease [5,9,10,11,12]. Hyperactive dendritic cells (DCs), proinflammatory T and B cells, and functionally impaired regulatory T cells (Tregs) are believed to contribute to the pathogenesis of the disease [13]. A significantly high number of peripheral immune cells enters the CNS through the disrupted blood–brain barrier (BBB), the blood–cerebrospinal fluid (CSF) barrier or the subarachnoid space [14], which results in the attack of self-antigens, including myelin-derived proteins and unknown antigens, in the CNS [15,16,17,18,19].
The strong involvement of the adaptive immune system in the pathophysiology of MS has given rise to the development of therapies that focus on immune modulation and are directed at reducing inflammation, thereby limiting neuronal and axonal damage. Currently, several disease-modifying treatments (DMTs) have been approved by regulatory authorities and are available for the treatment of MS. All DMTs, including classic injectable drugs, new oral substances, and monoclonal antibodies, are characterised by an immunomodulatory action, as reviewed by Hauser and Cree [20]. Although substantial progress has been made with current therapies, efficacy is associated with an increased risk of side effects. Indeed, treatment-related side effects or risks can be severe, including cardiac dysfunction, increased risk of autoimmune diseases and increased risk of infections and cancer [14,21]. Another drawback is that typically, current treatment modalities require life-long therapy, since they do not restore immune tolerance to the self-antigens targeted by the autoreactive immune response in MS patients. Therefore, cell-based therapy may provide an alternative or adjunctive approach. It is envisaged that cell-based therapy has the potential to provide a personalised and effective treatment option that lowers morbidity by uniting efficacy with reduced occurrence of side effects and less frequent hospitalisations, enhancing the quality of life of patients.
To date, various cell types have been investigated to determine if they establish long-term immune tolerance in MS (Figure 1). Some cell-based therapies aim to selectively restore the failed immune tolerance, which is the case for regulatory T cells (Tregs) and tolerogenic dendritic cells (tolDCs), while other cell-based therapies will be used for immune reconstitution after generalised strong immunosuppression, for instance following hematopoietic stem cell transplantation (HSCT). In this paper, we provide an overview of recent and future developments in cell-based therapy.

2. Cell Therapy Approaches for the Treatment of Multiple Sclerosis

2.1. Haematopoietic Stem Cells

Haematopoietic stem cells (HSCs) expressing CD34+CD38CD90+CD45RACD49f+ are immature pluripotent cells that can develop into all types of blood cells of both the lymphoid and myeloid lineages [22]. Hence, the aim of HSC transplantation (HSCT) is to give a one-time treatment that provides long-lasting disease stabilisation. Indeed, following immunoablation with immunosuppressive drugs, which are used to eliminate all pathogenic autoreactive lymphocytes and reduce inflammation in the CNS, patients are treated with HSCT to support haematopoiesis, thereby renewing the immune system and restoring self-tolerance. HSCs can be isolated from the bone marrow or peripheral blood after mobilisation with drugs, such as cyclophosphamide and/or granulocyte-colony stimulating factor (G-CSF), that enhance proliferation of HSCs and drive them from the bone marrow into the peripheral blood [23,24]. The following recommendations are made regarding collection of HSCs, according to the handbook of the European Society for Blood and Marrow Transplantation (EBMT) [25]. Bone marrow is the preferred source of HSCs. Multiple bone marrow aspirations of 5 mL each, with a maximum of 20 mL/kg donor bodyweight, are suggested to acquire a target dose of 3 × 106 CD34+ cells/kg. However, peripheral blood stem cell collection is favoured, as it is considered as less stressful for the patient and leads to faster engraftment and hematologic reconstitution. For this, the minimum target is 2 × 106 CD34+ cells/kg collected by leukapheresis. However, higher amounts of cells are aimed for, namely 4–5 × 106 CD34+ cells/kg, resulting in faster neutrophil and platelet recovery, and reduced hospitalisation, blood transfusion and antibiotic therapy. Autoimmune diseases, such as MS, are generally treated with autologous HSCT (AHSCT) for safety reasons [26].
At the clinical level, AHSCT is a rescue treatment in young patients with RRMS who have low or medium disability grades due to an aggressive inflammatory disease course and in whom other highly efficacious treatments have failed [27,28,29]. One study showed that the proportion of patients with MS who achieved no evidence of disease activity (NEDA) after AHSCT was very high compared with patients who received approved DMTs [28]. In a recent meta-analysis [30], 83% of patients who received AHSCT showed NEDA after 2 years and 67% maintained NEDA after 5 years. The main risk associated with AHSCT is treatment-related mortality, albeit that this risk has decreased from 3.6% to 0.3% in patients transplanted after 2005 [28]. A recent study from the Italian bone marrow transplantation (BMT)-MS Study Group reported that there were no deaths in patients transplanted after 2007 [31]. In a cohort of 210 MS patients with a median baseline expanded disability status scale (EDSS) of 6.0, a high proportion had a durable disease remission up to 5–10 years after the procedure; some of these patients had progressive MS [31]. The Swedish Board of Health and Welfare considers AHSCT as a valid treatment option for patients with active MS [29,32] and several consensus recommendations for the use of AHSCT in MS have been published in the past few years [26,33,34,35]. However, for patients with very advanced MS and high levels of disability, HSCT can neither reverse nor stop the progression of the disease [36] and, therefore, is not recommended.
Until recently, most studies on AHSCT were observational or prospective single-arm clinical trials (Table 1) [37,38,39,40,41,42]. In one randomised controlled trial, the researchers compared AHSCT with treatment with mitoxantrone, which is rarely used to treat MS today [38]. The MS International Stem Cell Transplant (MIST)-trial (NCT00273364) demonstrated the superiority of AHSCT versus DMTs in terms of the time to disease progression [43]. More recently, an observational cohort study compared outcomes after treatment with alemtuzumab and AHSCT and found that the chance of maintaining NEDA was significantly higher in the AHSCT-treated group [44]. Several clinical trials, comparing the effects of AHSCT with high efficacy DMTs in patients with active RRMS, are ongoing (Table 1). These include the BEAT-MS (NCT04047628), RAM-MS (NCT03477500) and STAR-MS (ISRCTN88667898) [27]. These trials will determine the comparative efficacy of AHSCT and currently available and highly efficacious DMTs, such as alemtuzumab, natalizumab and ocrelizumab.
The immunological effects that underlie the radical change in the disease course of MS following AHSCT are only partially understood. It has been observed that natural killer (NK) cells, CD8+ T cells and B cells repopulate within weeks to months, whereas the reconstitution of CD4+ T cells can take up to 2 years [62,63,64,65,66,67,68]. T cells generated after AHSCT undergo selection and maturation in the thymus and show a more diverse profile with new T cell receptor (TCR) clones compared with the dominant clones that were present before AHSCT and that were largely removed by the immunoablative treatment before the transplantation. It has been shown that more than 90% of pre-existing T cell clones are removed from the peripheral blood and the CSF and replaced with clonotypes from the graft [62]. This is predominantly the case for CD4+ T cells and, to a much lesser extent, for CD8+ T cells [63,64,65]. Whether this limited depletion of CD8+ T cells is associated with relapses or disease progression after AHSCT remains to be determined. In this context, mucosal-associated invariant T (MAIT) cells, a novel CD161highCD8+ cell population originating in the gut mucosa but expressing the CNS-homing receptor CCR6, have been found in lesions in the brains of patients with MS [65]. Nonetheless, myelin-specific T cells are still found after AHSCT, albeit with a strongly reduced capacity to differentiate into Th17 cells compared with their ability prior to the transplantation [67]. Interestingly, changes in the gene expression profiles of CD4+ and CD8+ T cells have been described, which suggests that the gene expression normalises in CD8+ T cells after AHSCT [68]. The rapid reconstitution of NK cells contributes to the suppression of Th17 cell reconstitution [66]; immune regulation is further enhanced by the expansion of Tregs [69]. Furthermore, although all B cells, except for plasma cells, are depleted during HSCT, one study demonstrated that oligoclonal bands persist after the transplantation, which suggests that immunoglobulin-producing cells are not depleted or are insufficiently depleted in the CNS [36]. This observation has been challenged by Larsson et al. [70] who showed that intrathecal immunoglobulin production and neurofilament light levels were lower after HSCT treatment and further decreased over time. Whereas differences in patient characteristics, such as disease duration, disease type, and disease heterogeneity, or treatment-related factors such as the conditioning regimen, may underly the observed discrepancies, studies involving larger cohorts as well as investigating the mechanisms of B cell reconstitution after HSCT are needed.
In conclusion, HSCT can be a treatment option in select young patients with aggressive RRMS who failed to respond to DMTs [26,27,71]. Immunological changes that occur after HSCT in MS are suggestive of long-term induction of immune tolerance. To date, no cellular biomarkers have been identified that can predict which patients will benefit most from this procedure.

2.2. Mesenchymal Stromal Cells

Mesenchymal stromal cells (MSCs) are multipotent cells that have the ability of self-renewal; MSCs can differentiate into various tissues of mesodermal origin, such as osteocytes, chondrocytes and adipocytes, and other embryonic lineages. MSCs are characterised by the expression of CD73, CD105 and CD90 and the absence of expression of haematopoietic markers (i.e., CD45, CD34 and HLA-DR) and vascular markers (i.e., CD31) markers [72,73]. Given their adult cell potency, MSCs are often called mesenchymal stem cells, although they are more accurately called multipotent mesenchymal stromal cells. MSCs were first described in the 1960s by Friedenstein who isolated them from rodent bone marrow through their inherent adherence to plastic [74]. Currently, MSCs can be isolated from blood, bone marrow, skeletal muscle, adipose tissue, synovial membranes, and other connective tissues. Regardless of the isolation procedure, quantities of MSC obtained from primary tissues are not sufficient for any application in clinical settings. Hence, in vitro propagation is almost always required to achieve a sufficient cell number for in vivo application. MSCs have generated great interest because of their therapeutic ability to induce a profound immunosuppressive and anti-inflammatory effect in vitro and in vivo [75]. The mechanisms by which MSCs exert their immunosuppressive effect are not completely understood. It is thought that they change the inflammatory environment into an anti-inflammatory environment directly by paracrine signals and by several secreted soluble factors, such as transforming growth factor beta (TGF-β) [76], hepatocyte growth factor [76], indoleamine 2,3-dioxygenase (IDO) [77], nitric oxide [78], interleukin (IL)-10 [79] and prostaglandin E2 [80], and through cell-to-cell contact via the inhibitory molecule programmed death 1 (PD-1) [81]. MSCs also work indirectly via the recruitment of other regulatory networks that involve antigen-presenting cells (APCs) [82] and Tregs [83]. However, it is evident that MSC-induced unresponsiveness lacks any selectivity. MSCs mainly affect the functions of T cells; for instance, MSCs induce a cell cycle arrest in anergic T cells or a cytokine profile shift in the Th1/Th2 balance towards the anti-inflammatory Th2 phenotype [84,85]. Furthermore, MSCs suppress the cytolytic effects of cytotoxic T cells [86]. MSCs are also capable of inhibiting NK cells [87,88], B cells and APCs. Furthermore, MSCs have been reported to promote the formation of potent CD4+CD25+ and CD8+ Tregs in vitro and in vivo [83,89].
Several phase I and II clinical trials used MSCs derived from allogeneic donors and evaluated their effect on autoimmune diseases, including type 1 diabetes (T1D), rheumatoid arthritis (RA) and MS (Table 1) [90]. Since MSCs represent only a small fraction (0.001–0.01%) of total nucleated cells in bone marrow and other tissues, it was mandatory for these studies that the MSCs were expanded ex vivo from a small bone marrow aspirate under clinical-grade conditions to significant numbers in 8–10 weeks [91,92]. Most of the reported trials, to date, were uncontrolled open-label phase I studies including patients with RR-MS, SP-MS, and PP-MS. A review of trials found that MSCs were safe and tolerated by patients with MS [93]. More recently, a randomised placebo-controlled phase II clinical trial found that five out of nine patients with MS who received an intravenous infusion of bone marrow-derived MSCs had a trend to lower cumulative numbers of gadolinium-enhancing lesions at 6 months following infusion, as shown by magnetic resonance imaging (MRI) [48]. However, there was no significant decrease in the frequency of Th1 cells in the peripheral blood of patients treated with MSCs. Interestingly, MSCs are likely to promote neuroprotection in addition to their immunomodulatory characteristics [94,95,96]. Indeed, MSCs could promote endogenous repair by recruiting local neural precursor cells, possibly through the secretion of neurotrophic factors, thereby driving neurogenesis and remyelination [97,98]. The migratory potential and homing capacity of these cells into the CNS still needs to be clarified.
The clinical results obtained using MSC therapy in patients with MS confirmed the feasibility and safety of an in vivo application of MSC without major adverse events. However, the migratory potential and homing capacity of these cells into the CNS as well as the clinical significance of these findings need to be corroborated.

2.3. Regulatory T Cells

Tregs are a subset of CD4+ T cells that play an important role in the balance between immunity and tolerance. These cells are characterised by the expression of high levels of IL-2 receptor α chain (IL-2Rα/CD25) and Forkhead box P3 (FoxP3) [99], which is a master regulator that orchestrates the transcriptional machinery that induces Treg-relevant genes, such as il2ra (CD25) and ctla-4, by binding over 1400 genes and acting as a transcriptional repressor and activator [100,101,102]. Its expression is inversely correlated with the expression of IL-7R (CD127) [103]. FoxP3 Tregs are generally subdivided into thymic-derived or naturally occurring Tregs (nTregs) and peripheral-induced Tregs (iTregs), which have phenotypic and functional similarities, as well as differences in stability and gene expression [99,104]. It is currently accepted that nTregs control immune responses to self-antigens, while iTregs suppress inflammation at mucosal barriers [105]. A current study defined Tregs as a heterogenous mixture of cellular sub-phenotypes with a high degree of phenotypic complexity that reflected different states of maturation, differentiation and activation [106].
Tregs are responsible for minimising the damage to the body’s own cells and tissues during persistent immunity and for maintaining tolerance to self. For this, Tregs act predominantly by suppressing, eliminating, or inactivating effector T cells, including autoreactive T cells, in the periphery [99,107]. Consequently, it is believed that the disruption of Treg numbers and/or function gives free rein to self-reactive T cells, which may contribute to an increased susceptibility to autoimmune diseases [108]. Indeed, reduced numbers or the impaired functionality of Tregs have been associated with the development of different autoimmune diseases, including MS [5], RA [109], T1D [110], psoriasis [111], myasthenia gravis [112] and autoimmune polyglandular syndrome type II [113]. Hence, restoring tolerance in patients with these diseases could be the key to overcoming autoimmunity. In this regard, adoptive cell transfer of Tregs has proven to be effective in preventing autoimmunity [114,115] and graft-versus-host disease (GVHD) [116,117], and in delaying graft rejection in preclinical animal models [118,119].
The suppressive repertoire of Tregs involves the secretion of immunosuppressive cytokines, such as IL-10, IL-35 and TGF-β, and cytotoxic molecules, such as granzyme B and perforin, as well as contact-dependent suppression (e.g., CTLA-4). Additionally, Tregs can indirectly affect immune tolerance by suppression of APCs, such as DCs (extensively reviewed in [99]). Furthermore, Tregs can transfer their suppressive activity to conventional CD4+ T cells, which is termed infectious tolerance [120]. They create a local tolerogenic environment in which naïve T cells convert into cells with an induced Treg phenotype. These cells are responsible for bystander suppression [121] because they induce tolerance to cells involved in the immune reaction without direct interaction. Hence, adoptive cell transfer of Tregs may not require long-term survival of the administered cells and may be used to alleviate the autoimmune response in diseases where it is directed against different self-antigens.
Currently, there is a broad range of Treg isolation and expansion protocols [122]. For instance, effective isolation methods with high purity and efficient expansion protocols are required to preserve the desired cell characteristics. Although Tregs are present throughout the body, peripheral blood is the most commonly used source of Tregs [123]. However, since Tregs comprise only 5–7% of the CD4+ T cells that develop in the thymus and in the periphery [124], in vitro Treg expansion is mandatory following isolation of a highly pure Treg population to generate sufficient cells for clinical application [122]. Molecules, including rapamycin [125,126,127], TGF-β [128] and all-trans retinoic acid (ATRA) [129,130], can be used to boost Treg expansion and stability, while preventing outgrowth of contaminating cells.
Positive preclinical outcomes, a better understanding of the characteristics of Tregs and the possibility of obtaining enough of these cells have paved the way for more than 50 active and completed clinical studies. These studies have tested the safety, feasibility, and efficacy of adoptive cell transfer of Tregs in the context of both autoimmunity and transplantation [131]. Recently, also in MS, the clinical use of autologous CD4+CD25hiCD127FoxP3+ Tregs was evaluated in a phase I/IIa clinical study [57]. Tregs were administered intravenously or intrathecally in RRMS patients, and the safety of the approach was demonstrated (Table 1). Altogether, studies proved the safety of the clinical use of ex vivo expanded polyclonal Tregs and showed promising results in the delay and prevention of graft rejection and in the treatment of autoimmune responses [132].
However, the efficacy was not conclusive and often only modest clinical responses were obtained [133]. This could be, at least in part, due to the use of polyclonal Tregs which collectively target a broad mix of antigens that are not all related to the disease, thereby potentially weakening the clinical effect. This is further confirmed in studies in mice demonstrating limited effect of polyclonal Treg infusion in immunocompetent individuals unless high numbers of Tregs are administered [134,135]. Moreover, the use of polyclonal Tregs could cause a transient risk of generalised immunosuppression [136]. In contrast, Tregs isolated from pancreatic draining lymph nodes or pulsed with pancreatic islet antigen are significantly better at preventing disease onset or curing autoimmune-prone non-obese diabetic (NOD) mice compared with polyclonal Tregs [137,138,139,140,141]. Thus, the use of antigen-specific Tregs could help to achieve improved clinical benefit in cases where the disease-causing antigen is known.
More powerful Treg therapies could be engineered by enhancing Treg antigen-specificity or functionality based on the knowledge gained from T cell therapies in oncology [142]. Most efforts involve introducing transgenic TCRs or chimeric antigen receptors (CARs) into Tregs. Although TCRs and CARs are both synthetic receptors, transgenic TCRs maintain the structure of the native TCR, but are designed for antigen selectivity and high affinity. CARs are synthetic fusion molecules that express the antigen recognition domain of a monoclonal antibody and one or more TCR costimulatory signalling domains [99,124]. Both techniques have been tested in different animal models of autoimmune diseases and transplantation [99]. In MS, pathogenic self-reactive T cells are targeted by murine transgenic Tregs which express an extracellular myelin basic protein (MBP) peptide-bound major histocompatibility complex (MHC) that is linked to an intracellular TCR-chain signalling domain. Subsequently, this interaction mimics physiological TCR-signalling on Tregs, resulting in the activation of transgenic Tregs and in the subsequent secretion of high levels of anti-inflammatory cytokines [143]. Furthermore, adoptive transfer of transgenic Tregs was able to prevent and treat MBP-induced experimental autoimmune encephalomyelitis (EAE) [143,144]. Expanded human Tregs, transduced with an MBP-specific TCR, are able to suppress MBP-specific effector T cells effectively in vitro. These transduced cells ameliorate disease in myelin oligodendrocyte glycoprotein (MOG)-induced EAE, which is indicative of the in vivo effect of bystander suppression mediated by soluble factors [145]. Similarly, converting antigen-specific effector T cells into Tregs through the overexpression of FoxP3 is being investigated [146,147]. In one study, engineered Tregs, overexpressing a MOG-specific CAR in trans with the murine FoxP3 gene, demonstrated their suppressive function in vitro [148]. More recently, reestablishment of Treg functionality in patients with MS was reported following in vitro expansion and MBP-specific TCR transduction of Tregs [149].
Further research in Tregs as a cell therapy for MS, and other autoimmune diseases, will undoubtedly provide us with interesting new insights.

2.4. Tolerogenic Dendritic Cells

DCs are the most professional APCs and are the sentinels of our immune system. They capture and process exogenous antigens and self-antigens in peripheral tissues [150,151,152] and present them to other immune cells after migration to the secondary lymphoid organs [150,153]. Subsequently, DCs stimulate naïve T cells, effector T cells, memory T cells and B cells. In doing so, DCs bridge the innate and adaptive immune systems [154] and play an important role in the balance between immunity and tolerance [155,156]. In patients with MS, DCs are abundantly present in brain lesions, and display a pro-inflammatory state with an altered phenotype and/or function compared with healthy controls [157]. Specifically, the DCs of patients with MS show upregulated levels of activation markers, such as CD86, CD80 and HLA-DR, and fail to upregulate programmed death ligand 1 (PD-L1) [158,159,160] compared with their healthy counterparts. Moreover, DCs from patients with MS secrete higher levels of immune-stimulatory cytokines, including IL-12p70, IL-18 and IL-23 [157,161,162], compared with DCs from healthy individuals. These findings underscore a potentially important role for DCs in the pathogenesis of diseases, influencing the effector function of auto-reactive T and B cells [163].
Alternatively, deploying the tolerogenic potential of DCs could possibly have a positive impact on the balance between immunity and tolerance in MS. For this, DC function can be directly modulated in vivo before they can be used as an immunotherapeutic tool to treat MS [164], or tolerance-inducing or tolerogenic DCs (tolDC) can be generated in vitro from peripheral blood CD14+ monocytes [165]. For the latter, several immunosuppressive biologicals and pharmaceuticals, including corticosteroids, TGF-β, dexamethasone, vitamin D3 and cyclosporine have been used. These factors have been demonstrated to modulate the differentiation and function of DCs [166,167,168], as evidenced by the maturation-resistant phenotype, intermediate expression of co-stimulatory molecules, a shift towards anti-inflammatory cytokine production and a reduced capacity to stimulate T cell responses [169,170]. Interestingly, the use of vitamin D3 is one of the most widely established approaches, as it has significant immune regulatory properties both in vitro and in vivo [171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186]. These studies showed amongst others that myelin peptide-loaded tolDC, generated with vitamin D3, induced stable antigen-specific hyporesponsiveness in myelin-reactive T cells from MS patients in vitro.
In addition, to guarantee the efficiency and stability of antigen presentation by DCs, several antigen loading strategies have been developed to induce immune responses [152]. These include (1) the in vivo loading of antigens to circulating DCs in patients [187], (2) different ways of in vitro loading of DCs with antigens [188,189,190,191,192,193,194,195] and (3) DC transfection with mRNA-encoding antigens [196,197,198,199,200,201].
Although the use of immune-stimulatory DCs to reinforce immune responses against cancer and infectious diseases has been broadly described in multiple clinical trials [202,203,204,205], the use of tolDC as a treatment strategy for autoimmune disorders is still in its infancy. A limited number of studies have exploited the tolerogenic capacity of DCs to treat patients diagnosed with T1D, RA, Crohn’s disease, MS and Neuromyelitis optica (NMO) [58,156,179,206,207,208,209,210]. In particular, in MS (Table 1), one phase 1b clinical trial reported that the use of tolDC, generated with dexamethasone, was safe and feasible in this patient population [58]. In addition, two single-centre clinical phase I/IIa trials in Antwerp, Belgium (NCT02618902) and Badalona, Spain (NCT02903537) are currently investigating the safety and feasibility of tolDC in patients with MS; the studies are also comparing different modes of tolDC administration, i.e., intradermal and intranodal, respectively [59]. The results from these studies will provide new insights into the use of tolDC as a possible treatment option for MS and other autoimmune diseases.

2.5. Other Immune Cells

2.5.1. B Cells

B cells play a pleiotropic role in the induction of immune responses. They contribute to immunity through the production of antibodies, antigen presentation to T cells and the secretion of cytokines. There are different subsets of B cells. For instance, early lineage CD20+CD79+CD27+ B cells function primarily as APCs expressing MHC and costimulatory molecules thereby sustaining T cell-mediated cellular responses, whereas late lineage CD138+ mature plasma cells and CD38+ plasmablasts secrete antibodies, including auto-antibodies, related to the humoral response [211,212]. The role of B cells in autoimmunity has been underlined by the successful therapeutic effect of B cell depletion with anti-CD20 monoclonal antibodies [213]. Rituximab, a chimeric anti-CD20 monoclonal antibody, has proven to be highly beneficial for patients with certain autoimmune diseases, including RA, MS and T1D. However, while plasma cells and oligoclonal bands in the CSF remain unaffected by anti-CD20 therapies, B cell depletion aggravated the symptoms in some patients, which suggests that B cells also have a protective role in autoimmune pathology [214]. In this context, IL-10-producing regulatory CD1d+CD5+ B cells were found to be able to downregulate the initiation of autoimmune diseases and the onset or severity of EAE, collagen-induced arthritis, contact hypersensitivity and inflammatory bowel disease [215,216]. Therefore, B cell-mediated regulation of the immune system may be of great interest for the development of new cell-based therapies for immunosuppression in the field of autoimmune diseases. Several preclinical studies used different types of B cells as preventive and therapeutic treatment in EAE, which provided preclinical evidence for tolerance induction [217,218,219,220,221]. The adoptive transfer of splenic IL-10-producing CD1dhiCD5+ regulatory B cells, so-called B10 cells, isolated from mice treated with anti-CD20 monoclonal antibodies, resulted in limited disease severity when the B10 cells were administered before EAE induction [222,223]. More recently, administration of regulatory B cells (Bregs) also promoted oligodendrogenesis and remyelination in an EAE [224]. To our knowledge, no clinical trials have used B cell-based therapy in patients with MS or other autoimmune diseases to date.

2.5.2. Natural Killer Cells

Natural killer (NK) cells are innate cytotoxic lymphocytes derived from CD34+ haematopoietic progenitor cells which are involved in early defence mechanisms [225,226,227]. Human NK cells can be identified by the molecular marker CD56 in the absence of the expression of CD3, while the combination of the expression of CD56+ and CD3+ define a mixed population of NK-like T cells (NKT) and antigen-experienced T cells [228]. CD56bright NK cells are mostly present in secondary lymphoid tissue, while large numbers of CD56dim NK cells are found in the bone marrow, blood and spleen [225,229]. NK cells induce apoptosis of their target cells by utilising granzyme B and perforin, and by secreting inflammatory cytokines, such as IFN-γ, upon stimulation with IL-12 or other cytokines, which are released by monocytes, macrophages and/or DCs [225,226,227]. More recently, the generation of trained immunity, i.e., immune memory of the innate immune system, has been described [230]. In this perspective, similar functional properties as the adaptive immune system have been ascribed to NK cells, including the expansion of antigen-specific cells, the generation of long-lasting memory cells that are able to persist after encounter with an antigen, and the possible induction of a boosted secondary recall response.
In MS, NK cells play a dual role because they have protective and pathogenic properties, as evidenced by the contradictory results obtained in EAE [228,229]. This duality is illustrated by the fact that daclizumab, a humanized anti-CD25 monoclonal antibody, reduces the disease activity in many patients with MS, but has led to severe CNS inflammation in 12 patients worldwide [231]. The beneficial mechanism of action of daclizumab was mediated by the expansion of the CD56bright NK cell population, which led to the killing of activated T cells. Regarding the increased CNS autoimmunity on the other hand, it has been speculated that the mechanisms involved led to a decrease in Tregs [232]. Concerns about—potentially autoimmune—hepatotoxicity resulted in the withdrawal of daclizumab from the market in March 2018 [233,234,235].
Albeit that NK cell-based immunotherapy shows promising results in early stage clinical trials in haematological malignancies and solid cancers [236], more fundamental research is needed before NK cell-based therapies can be used in human clinical trials in MS. This includes the identification of a regulatory NK cell subset, the optimal procedures for cell isolation, differentiation and expansion protocols and the administration regimen [237].

2.5.3. Natural Killer T Cells

A T cell subset with regulatory properties that exhibits characteristics of NK cells has been identified in mice and humans (extensively reviewed elsewhere [238,239,240]). These NKT cells are a subset of innate lymphocytes that recognise endogenous or exogenous glycolipids in the context of CD1d molecules expressed by APCs, such as monocytes, DCs and myeloid-derived suppressor cells (MDSCs). Upon antigenic stimulation, NKT cells produce a variety of immunomodulatory cytokines, which endows the cells with potent immunoregulatory properties. Nonetheless, various subtypes of NKT cells may have different effects in the immune system [241]. Importantly, NKT cells in MS were described to have the potential to act as both protective and pathogenic lymphocytes [242]. The role of NKT cells in the pathophysiology of MS needs further clarification before they could be used as a cell-based therapy.
The role of NKT cells and their potential for modulation to increase tolerance towards self-antigens have been investigated in vitro and in animal models of various autoimmune diseases [243,244]. However, impaired NKT cell function in patients with autoimmune diseases could hamper the clinical use of autologous NKT cells, unless in vitro manipulation could change their function. Moreover, NKT cells constitute less than 1% of T cells in the peripheral blood [241]. Hence, in vitro expansion is needed to achieve a sufficient cell number for in vivo application [245].
Although NKT cell-based therapy has been investigated in the field of cancer research [241], there have been no studies in animal models of autoimmune diseases. Deciphering the roles of NKT subsets in tolerance induction, selecting the appropriate NKT cell subset and evaluating the effects on animal models of autoimmune disease will be necessary before these cells can prove their value in phase I clinical trials in humans.

2.5.4. Myeloid-Derived Suppressor Cells

MDSCs are innate immune cells from the myeloid linage and are important for creating an immunosuppressive environment in tumours [246]. They play a protective role in autoimmune diseases through the inhibition of T cell-mediated immune responses [246]. Two large groups of cells have been described (extensively reviewed in [247,248,249]). In brief, granulocytic or polymorphonuclear MDSCs (PMN-MDSCs) are similar to neutrophils, while monocytic MDSCs (M-MDSCs) are similar to monocytes. A third, less common population of MDSCs has been described in humans, which is called early-stage MDSCs.
The role of these cells is more complex in autoimmune diseases. Recently, numerical, phenotypical, and functional differences in MDSCs were demonstrated in patients with RRMS and SPMS [250]. Patients with SPMS had a decreased frequency of M-MDSCs and PMN-MDSCs compared with healthy controls, while the frequency of M-MDSCs and PMN-MDSCs was increased in patients with RRMS during relapse as compared with healthy controls. More importantly, M-MDSCs demonstrated the capacity to suppress T cells in patients with RRMS and healthy controls, while these cells promoted autologous T cell proliferation in patients with SPMS [250]. In EAE, the preventive and therapeutic administration of purified antigen-presenting MDSCs led to lower percentages of activated T cells and higher percentages of regulatory B cells, which implied that MDSCs had tolerogenic properties [251]. More research into MS is needed before MDSCs can be investigated as a therapeutic cell product in human clinical trials.

2.6. Use of Cells as Carriers of Antigens to Induce Tolerance

2.6.1. Peripheral Blood Mononuclear Cells

An alternative approach for effective immunosuppression in the treatment of autoimmune diseases involves the coupling of self-antigen-derived peptides to cellular vehicles using chemical fixatives [252]. The induction of immunosuppression using this method is indirect and implies that the fixed cells rapidly undergo apoptotic cell death following fixation and subsequently carry over intact peptides to tolerogenic APCs for processing and presentation [253,254]. Lutterotti et al. performed an open-label, single-centre, dose-escalating phase I/IIa study to evaluate the therapeutic use of autologous peripheral blood mononuclear cells (PBMCs) in nine patients with MS: two patients had SPMS and seven patients had RRMS (Table 1). The PBMCs were coupled with seven myelin-derived peptides that were associated with MS pathogenesis and against which demonstrable responses could be detected in the patients included in the trial [60,255]. Administration of the myelin-derived peptide-loaded PBMCs was reported to be feasible, safe and well tolerated. Interestingly, patients who received a high cell dose showed diminished antigen-specific T cell responses [60]. Despite the advantages associated with the limited time for the preparation of the cell product, the correct dose and frequency of the treatment remain unknown.

2.6.2. Erythrocytes

Erythrocytes, which are also known as red blood cells (RBCs), are the most common type of blood cell. Their main function is to deliver oxygen to body tissues. RBCs are continuously cleared from circulation through phagocytosis without eliciting an autoimmune response. Hence, the tolerogenic properties of these apoptotic cells can be used to engineer tolerance-inducing RBCs. Pishesha et al. described one such technique, called sortagging, sortase-mediated transpeptidation [256]. Engineered RBCs that were covalently linked to MOG35–55 protect against and reverse early signs of EAE [256]. A phase Ib clinical trial involving this approach started recruiting patients with MS in October 2017 (Table 1) [257]. Results were presented as a late-breaking abstract during ECTRIMS 2019 [61]. The investigators reported that there was a reduction in antigen-specific T cell responses to myelin peptides in the high-dose group, whereas the proportion of type 1 regulatory T cells (Tr1) and nTregs, and IL-10 levels increased providing evidence of immune tolerance induced by this treatment strategy.

3. Key Issues When Designing Cell-Based Therapies For MS

3.1. Autologous Versus Allogeneic Therapy

Cell products for tolerance induction can be derived from the same individual (autologous) or another individual (allogeneic). From a practical point of view, there are many advantages associated with the use of allogeneic cell therapy. For instance, allogeneic cell therapy has a lower production cost compared with the cost related to individualised autologous cell products. There is also a higher availability of allogeneic cell products because cryopreserved stocks can be used, which means that they are available as off-the-shelf products [258]. However, the risk of host immune rejection due to GVHD is substantial in allogeneic cell therapy and requires simultaneous strong immune suppression to allow cell engraftment for immune-modulatory purposes. Autoimmune patients are unlikely to undergo the same heavy lymphodepletion as patients with cancer, which makes it even harder to evade the immune system with an allogeneic product. In contrast, the risk is minimal in autologous therapy. Additionally, donor screening is much stricter for allogeneic cell therapy in terms of infectious screening, such as for (human leukocyte antigens) HLA typing, which results in increased costs [258]. In addition, because most patients with autoimmune diseases do not have the same urgency to begin cell therapy as patients with cancer, apart from a life-threatening flare-up, the benefits of an autologous patient-specific cell therapy product may outweigh the benefits of off-the-shelf therapy in the autoimmune setting. Given these issues, autologous therapy is often preferred over allogeneic therapy for tolerance induction, and its long-term persistence could justify its high price tag. For example, both European and American guidelines do not recommend allogeneic HSCT in patients with MS [259,260]. Moreover, also allogeneic Treg therapy has only been tested in immunosuppressed and immunocompromised individuals [122]. Nonetheless, future design of more universal cell-based therapies could potentially result from more knowledge and research using CRISPR-Cas9 technology to render cells HLA deficient or to induce the ectopic expression of non-canonical HLA-E or HLA-G genes, which are expressed during maternal–foetal tolerance [124].

3.2. Antigen-Specificity

General immune modulation may be accompanied by undesired side effects, such as opportunistic infections and secondary autoimmunity. Therefore, harnessing the immune system to restore immune tolerance using tolerance-inducing cell strategies requires loading the cell product with myelin antigens or receptors, depending on the cell type used, to acquire disease-related antigen specificity.
Although substituting only 15–30% of total myelin content [261], the myelin proteins are presumed to be the major antigenic targets of the MS-driving autoimmune response [262]. The protein content within the myelin sheath is predominantly composed of proteolipid protein and MBP, as well as other myelin proteins, such as MOG [261]. Irrespective of their abundance in the myelin sheath, epitopes from these three myelin proteins have been shown to be encephalitogenic in different animal models [263]. Thus, the reactivity towards a wide variety of myelin peptides can be detected in patients with MS [264,265]. Hence, directing myelin specificity to cell-based therapies for MS may represent a promising approach to tackle MS-related autoimmunity. In this way, the dysregulated myelin-directed immune response could be restored, without affecting the normal surveillance and effector function of the immune system.
To date, however, few clinical trials have investigated myelin-specific cell-based therapies. Indeed, many of the above-mentioned cellular treatments do not have a myelin-specific mode of action, although encouraging safety results have been demonstrated for several antigen-specific treatment approaches in phase I and II clinical trials for MS [58,60,266,267,268,269], including cell-based therapies with DC [58] and mononuclear cells [60].
Nevertheless, various pitfalls have limited the development of antigen-specific treatment. First, even though myelin proteins are suggested to be culprit antigens, no single antigenic target has been identified. Myelin reactivity in patients with MS is heterogeneous and possibly dynamic because of the emergence of neo-autoreactivities due to disease activity-related tissue damage, which is associated with epitope spreading [270,271,272]. Therefore, there is no obvious single peptide or peptide mix at which tolerance reconstitution can be aimed. Moreover, even though ex vivo reactivity can be directed towards a wide variety of myelin peptides, some are non-pathogenic, such as the so-called cryptic or not naturally processed epitopes [273]. These factors complicate the choice of targets for antigen-specific therapy. Nonetheless, few side effects were reported in clinical trials with antigen-specific therapies [16,274]. However, a risk of inducing MS exacerbation or hypersensitivity reactions when trying to modulate the immune system in a myelin-specific way remains. In this context, the administration of myelin antigens by means of carrier cells might represent a more controlled approach to induce stable and antigen-specific immune tolerance.
Several innovative antigen-specific treatment strategies are currently in the preclinical phase and may address some of the previously mentioned issues. New antigen-loading strategies are being investigated as alternatives to classical peptide pulsing. For instance, transfection with viral vectors or nucleic acids encoding full-length myelin proteins may lead to the presentation of a wide variety of naturally processed myelin peptides. These new strategies could be used to increase the efficacy of current cell-based antigen-specific treatment approaches, as well as to add antigen-specificity to cell therapies that are not yet specifically directed towards the myelin response, including MSC-, HSC- and Treg-based strategies. These new approaches may represent an intriguing opportunity for antigen-specific cell treatment.

3.3. Migration Across the Blood–Brain Barrier

The trafficking of cell-based therapies into the CNS can be used for targeted immunotherapy against various neuroinflammatory diseases [275,276,277,278]. Indeed, the triumph of cell-based immunotherapy in inducing immune tolerance depends on the accurate delivery and trafficking of the therapeutic, i.e., tolerance-inducing cells, to the inflammatory sites [279,280]. Hence, a clear understanding of the underlying mechanisms involved in cell migration is necessary to advance the development of new therapies. However, entry into the CNS is heavily restricted by the blood–brain barrier (BBB), a diffusion barrier that tightly regulates homeostasis of the CNS and impedes the influx of most compounds from the blood to the brain [281,282,283]. The restrictive nature of the BBB provides an obstacle for drug delivery to the CNS. Although there have been medical advances in the care of individuals with brain and CNS diseases, the treatment of these disorders remains challenging and insufficient because of the BBB, which prevents many drugs in circulation from reaching the brain. Hence, major efforts have been made in developing methods able to modulate or bypass the BBB for delivery of therapeutics [284]. Nonetheless, several cell types, including MSCs, Tregs and DCs, can migrate in and out of the BBB efficiently, and BBB-transmigratory capacity of the cells could be exploited for the therapeutic targeting of the inflammatory disease mechanism in the CNS. Moreover, these cells, owing to their ease of isolation, established safety and potential to target different pathways in neuronal regeneration [285,286,287], have proved to be attractive therapeutic agents and can secrete various cytokines and growth factors with anti-apoptotic, neuroprotective and immune-modulatory properties [277,288]. They can be used as vehicles to deliver antitumor therapeutics for brain tumour treatment and recent reports have demonstrated that they can interact and migrate across the BBB under injury or inflammation. They express a variety of leukocyte-like homing molecules, such as chemokine receptors and adhesion molecules [289,290,291] and they use a multistep homing cascade (i.e., rolling, adhesion, and transmigration) to engage with endothelial cells [292,293,294]. Indeed, these cells use adhesion molecules, including vascular cell adhesion molecule (VCAM)-1 and β1 integrin, to transmigrate through the endothelial barrier and preferentially transmigrate on TNF-α-activated endothelium rather than naïve endothelium [295,296]. Several chemokine receptors and their ligands, including CXCL9, CXCL16, CCL20 and CCL25, are known to be explicitly involved in the cell transmigration through the endothelial layer [285,295,296,297,298].
Although in general, these cells undertake the same migratory cascade to reach the CNS by moving across the BBB, they still require specific mechanisms for their mode of action. For instance, MSCs favourably transmigrate through the endothelial cells using G-protein-coupled receptor signalling-(GPCR-) dependent pathways [285]. MSCs migrate either by paracellular or transcellular diapedesis through discrete gaps or pores in the endothelial monolayer that are enriched for VCAM-1 (transmigratory cups). In contrast to leukocytes, their transmigration does not involve significant lateral crawling, presumably due to the lack of Mac-1 expression [289]. Similarly, Tregs tend to migrate across the brain endothelium and to suppress the effector T cell functions at the site of emerging inflammation. Recent studies have suggested that the detection of low numbers of Tregs in the CNS of patients with MS [299,300,301] and murine Tregs showed augmented migratory capacity in vitro and in vivo via the BBB [300,301]. In addition, human FoxP3+ Tregs migrate across in vitro human brain endothelium at higher rates than other cells. Tregs from patients with RRMS showed impaired migratory abilities in crossing the BBB under non-inflammatory conditions [293]. The integrin CD62L is a crucial lymphoid homing molecule for immune cells and is also an important migration associated molecule for Tregs [302]. The migratory capacity of Tregs, through the BBB is controlled by distinct signals from chemokines/chemokine receptors, such as CCR7 and CCR6 [296]. Additionally, DCs found within the CNS correlate with the severity of disease, and they exhibit more efficient transmigration than the T cells in in vitro models of the BBB [275]. Different chemokine receptors and ligands, including CCR5, are involved in the inflammatory migration of DCs [303] and, thus, should be targeted for the development of therapies. Crossing the BBB is a prerequisite for all these cells to exert their therapeutic effects in treating neurological diseases or CNS injury and is necessary for their use as vehicles for drug delivery to treat brain tumours. Hence, the selective targeting of the trafficking and compartmentalisation of these cell types into different sites to exert their apposite immune suppression would be therapeutically beneficial. In this regard, efforts have been made to increase CNS migratory capacity of cells, such as CCR5-encoding mRNA-electroporation of tolDC. Accordingly, the capacity of mRNA-electroporated tolDCs to transmigrate toward a chemokine gradient in an in vitro model of the BBB improved significantly, and neither the tolerogenic phenotype nor the T cell-stimulatory function of tolDCs was affected [304].
Furthermore, the ability to monitor the migration and fate of these cells under in vivo conditions is helpful in devising rational therapeutic strategies and is also critical for optimisation of these strategies. For this, some non-invasive in vivo cell tracking techniques are used such as in vivo bioluminescence imaging [305]. This is an indirect cell labelling technique with reporter genes which allows cell tracking in small animal models. The mobility of the cells, including MSCs, DCs and Tregs, to the target tissue can be easily verified using in vivo bioluminescence imaging reporter gene strategies as well [306,307,308].
There is a need for the ongoing and future clinical studies to focus on the use of various therapeutic strategies that exploit the migration-associated molecules for various cell types [47,309,310,311]. The majority of current clinical studies use intradermal or subcutaneous routes of administration with different outcomes [312,313]. Based on these reports, the effect of the administration route on the efficiency of the therapeutic vaccine remains unclear and a topic of debate. Further optimisation is required to enhance the overall vaccine outcome.

4. Discussion and Conclusions

Effective treatment of MS should target the causative mechanisms of disease and induce long-lasting effects. As immune-mediated demyelination and axonal degeneration are essential components of the neurodegenerative process of the disease, the ideal treatment for MS would convert the function of B and T lymphocytes from disease-causing to disease-regulating, without affecting the rest of the immune system. In this context, several cell-based, tolerance-inducing therapies have been developed, including MSCs, Tregs and DCs.
While translating cell-based therapies from the bench to the bedside, several challenges arise: manufacturing of the cell-product, administration route and time, dosing, etc. As most of the cells presented in this review are not abundantly present in the blood or tissues, in vitro propagation is almost always required to achieve a sufficient cell number for in vivo application. Different biological agents have been used to induce in vitro cell expansion, such as rapamycin [125,126,127]. Rapamycin, also known as sirolimus, is an immunosuppressant routinely used in preventing the rejection of kidney transplants. Interestingly, it has been demonstrated in patients treated with rapamycin that this agent also has a direct in vivo effect on immune-regulatory cells. For instance, rapamycin restored Treg function in six patients with IPEX syndrome treated with rapamycin [314], or induced the upregulation of ILT3 and ILT4 on DCs, thereby promoting the immunoregulatory function of DCs [315]. Similarly, also all-trans retinoid acid (ATRA), which has been used for in vitro expansion of Tregs [129,130], demonstrated a direct in vivo effect on the number of Tregs and IL-10 and FoxP3 expression levels [316].
When considering the route of delivery of these cell-based therapies, one needs to consider that different routes lead to different sites of accumulation of the cells administered. Cell-based therapies that can be directed to the lymph nodes and the site of inflammation present an effectual promise of innovative cell-based immunotherapies to battle diseases, such as MS, and to provide a long-lasting cure. In this perspective, we recently presented a novel method to facilitate the migration of cell therapeutic products. Indeed, by introducing messenger RNA (mRNA) encoding CCR5 by means of electroporation (EP), tolDCs transiently displayed increased levels of CCR5 protein expression [304]. Accordingly, the capacity of mRNA electroporated tolDCs to transmigrate toward a chemokine gradient in an in vitro model of the BBB improved significantly, indicative for improved migration of CCR5-expressing tolDCs to inflammatory sites and allowing in situ down-modulation of autoimmune responses in the CNS. In vivo “cell tracking” techniques can pave the way to further optimise current and upcoming cell-based therapies in MS, ranging from preclinical to clinical applications, by improving our understanding of complex mechanisms of action. In vivo bioluminescence imaging allows non-invasive imaging in cell biology and small animal studies [305,306,307,308]. Interestingly, imaging data obtained from mice receiving vitamin D3-generated tolDC which were labelled with NIR815 (n = 9), showed that the cells reached the lungs immediately after intravenous administration. Importantly, 24 h after tolDC administration, cells were also found at an elevated concentration in the liver and spleen, up to 7 days post administration [185]. In addition, also in vivo imaging can be deployed in different ways, for instance to stratify patients into responders and non-responders and to predict efficacy or indicate potential loss of efficacy in patients [317].
In addition, the heterogeneity in the pathology of MS as well as in its clinical course has presented challenges for the design of therapeutic trials. On top of that, disease heterogeneity has only been partially explained by genetic polymorphisms [318,319,320] and immunological differences in patients [321,322], which can be linked to a higher relapse rate or to a clinical phenotype with more spinal or brain lesions. Hence, well-defined patient selection will account for improved outcome measures. However, currently, there are no biomarkers that adequately predict the individual disease course [323], albeit that some biomarkers, such as neurofilament light, may exert that role in the future [324].
Another critical parameter in cell therapy research is the timing when the treatment starts. The window of opportunity for the treatment of patients with MS, directed at downregulating or even silencing the aberrant immune response towards myelin-antigens, is early in the disease course when there is a permeable BBB, a limited amount of axonal damage, before epitope spreading occurs and when the peripheral immune system drives the inflammation in the CNS [325,326,327]. Thus, all cell therapies that intervene with the peripheral-driven immune response should be applied in a timely manner. In addition, targeted cell therapy should ideally be given to patients who show an abnormal T cell response towards these antigens in vitro, which can be found in a subset of MS patients that show inflammatory disease activity [19]. Altogether, the adequate selection of patients for these treatments or for clinical trials is of utmost importance.
Ideally, cell-based therapies must induce increased durability along time. This means that the ability to regulate the autoimmune response must be permanent or at least persist for years following intervention. However, to date, only results demonstrating the safety of tolerance-inducing cell-based therapies in the short-term are available (Figure 2). Indeed, a recent systematic review and meta-analysis evaluating the safety of tolerance-inducing cell-based therapies in autoimmune diseases and transplantation showed that the occurrence of serious adverse events (SAE) is a rare event following treatment with cell-based therapeutic products [328]. Nonetheless, long-term follow-up of participants in well-designed and adequately powered controlled clinical trials is needed to provide evidence of efficacy and long-term safety.
While it can be hypothesised that reducing the autoreactive, inflammatory assaults in MS may allow for more repair, very little is known about the function of the above-mentioned cell-based therapies in remyelination. Interestingly, since inflammation resolving effects of Tregs frequently occur with tissue regeneration, Dombrowski and colleagues recently revealed a novel proregenerative function for Tregs, as drivers of oligodendrocyte differentiation and remyelination, beyond immunomodulation. This confers a regenerative role for Treg complementary to, but distinct from, known immunomodulatory functions [329,330]. In addition, also MSCs are likely to promote neuroprotection next to their immunomodulatory characteristics [94,95,96], by promoting endogenous repair via local neural precursor cells recruitment. This can possibly be facilitated by the secretion of neurotrophic factors, thereby driving neurogenesis and remyelination [97,98]. These findings will open doors to further optimise cell-based therapies in MS.
Although the first clinical trials reported promising results on the level of safety of administering the cell therapies, discussed in this review, in patients with autoimmune disease in general, and in patients with MS in particular, numerous questions remain unanswered. Ongoing and future studies will help to define the dose, treatment schedule and route of administration of antigen-specific cell therapy in patients with MS regarding safety, efficacy, and treatment-related costs. In conclusion, all aspects of the disease and therapeutic cell product should be considered during cell therapy research, especially within the context of personalised medicine.

Author Contributions

Conceptualization, I.W., I.J. and N.C.; resources, I.W., I.J., B.W., N.C.; writing—original draft preparation, I.W., I.J., J.D., M.M., B.W. and N.C.; writing—review and editing, I.W., I.J. and N.C.; visualization, I.J.; supervision, N.C.; funding acquisition, I.W., I.J., B.W. and N.C. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by grants from the following funding agencies: Research Foundation Flanders (FWO: G049320N) and Charcot Foundation. In addition, this work received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement 779316 (ReSToRe). Furthermore, Ibo Janssens is funded by a Sb-fellowship from the Research Foundation Flanders (FWO grant number: 1S37319N). Barbara Willekens was supported by a clinical PhD fellowship from the Research Foundation Flanders from 2018 to 2020 (FWO grant number: 1701919N).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest. In addition, the funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. Reich, D.S.; Lucchinetti, C.F.; Calabresi, P.A. Multiple Sclerosis. N. Engl. J. Med. 2018, 378, 169–180. [Google Scholar] [CrossRef] [PubMed]
  2. Koch-Henriksen, N.; Sorensen, P.S. The changing demographic pattern of multiple sclerosis epidemiology. Lancet Neurol. 2010, 9, 520–532. [Google Scholar] [CrossRef]
  3. Logroscino, G.; Piccininni, M.; Marin, B.; Nichols, E.; Abd-Allah, F.; Abdelalim, A.; Alahdab, F.; Asgedom, S.W.; Awasthi, A.; Chaiah, Y.; et al. Global, regional, and national burden of motor neuron diseases 1990–2016: A systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2018, 17, 1083–1097. [Google Scholar] [CrossRef] [Green Version]
  4. Lublin, F.D.; Reingold, S.C.; Cohen, J.A.; Cutter, G.R.; Sørensen, P.S.; Thompson, A.J.; Wolinsky, J.S.; Balcer, L.J.; Banwell, B.; Barkhof, F.; et al. Defining the clinical course of multiple sclerosis: The 2013 revisions. Neurology 2014, 83, 278–286. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Viglietta, V.; Baecher-Allan, C.; Weiner, H.L.; Hafler, D.A. Loss of functional suppression by CD4+CD25+ regulatory T cells in patients with multiple sclerosis. J. Exp. Med. 2004, 199, 971–979. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Pugliatti, M.; Rosati, G.; Carton, H.; Riise, T.; Drulovic, J.; Vecsei, L.; Milanov, I. The epidemiology of multiple sclerosis in Europe. Eur. J. Neurol. 2006, 13, 700–722. [Google Scholar] [CrossRef] [Green Version]
  7. Dendrou, C.A.; Fugger, L.; Friese, M.A. Immunopathology of multiple sclerosis. Nat. Rev. Immunol. 2015, 15, 545–558. [Google Scholar] [CrossRef]
  8. Scalfari, A.; Neuhaus, A.; Daumer, M.; Muraro, P.A.; Ebers, G.C. Onset of secondary progressive phase and long-term evolution of multiple sclerosis. J. Neurol. Neurosurg. Psychiatry 2014, 85, 67–75. [Google Scholar] [CrossRef] [Green Version]
  9. Dos Passos, G.R.; Sato, D.K.; Becker, J.; Fujihara, K. Th17 Cells Pathways in Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorders: Pathophysiological and Therapeutic Implications. Mediat. Inflamm. 2016, 2016, 5314541. [Google Scholar] [CrossRef] [PubMed]
  10. Rostami, A.; Ciric, B. Role of Th17 cells in the pathogenesis of CNS inflammatory demyelination. J. Neurol. Sci. 2013, 333, 76–87. [Google Scholar] [CrossRef] [Green Version]
  11. Fletcher, J.M.; Lalor, S.J.; Sweeney, C.M.; Tubridy, N.; Mills, K.H. T cells in multiple sclerosis and experimental autoimmune encephalomyelitis. Clin. Exp. Immunol. 2010, 162, 1–11. [Google Scholar] [CrossRef] [PubMed]
  12. Murphy, A.C.; Lalor, S.J.; Lynch, M.A.; Mills, K.H. Infiltration of Th1 and Th17 cells and activation of microglia in the CNS during the course of experimental autoimmune encephalomyelitis. Brain Behav. Immun. 2010, 24, 641–651. [Google Scholar] [CrossRef]
  13. Bar-Or, A.; Li, R. Cellular immunology of relapsing multiple sclerosis: Interactions, checks, and balances. Lancet Neurol. 2021, 20, 470–483. [Google Scholar] [CrossRef]
  14. Dendrou, C.A.; Fugger, L. Immunomodulation in multiple sclerosis: Promises and pitfalls. Curr. Opin. Immunol. 2017, 49, 37–43. [Google Scholar] [CrossRef]
  15. Elong Ngono, A.; Lepetit, M.; Reindl, M.; Garcia, A.; Guillot, F.; Genty, A.; Chesneau, M.; Salou, M.; Michel, L.; Lefrere, F.; et al. Decreased Frequency of Circulating Myelin Oligodendrocyte Glycoprotein B Lymphocytes in Patients with Relapsing-Remitting Multiple Sclerosis. J. Immunol. Res. 2015, 2015, 673503. [Google Scholar] [CrossRef]
  16. Bielekova, B.; Goodwin, B.; Richert, N.; Cortese, I.; Kondo, T.; Afshar, G.; Gran, B.; Eaton, J.; Antel, J.; Frank, J.A.; et al. Encephalitogenic potential of the myelin basic protein peptide (amino acids 83-99) in multiple sclerosis: Results of a phase II clinical trial with an altered peptide ligand. Nat. Med. 2000, 6, 1167–1175. [Google Scholar] [CrossRef]
  17. Bielekova, B.; Sung, M.H.; Kadom, N.; Simon, R.; McFarland, H.; Martin, R. Expansion and functional relevance of high-avidity myelin-specific CD4+ T cells in multiple sclerosis. J. Immunol. 2004, 172, 3893–3904. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  18. Wallstrom, E.; Khademi, M.; Andersson, M.; Weissert, R.; Linington, C.; Olsson, T. Increased reactivity to myelin oligodendrocyte glycoprotein peptides and epitope mapping in HLA DR2(15)+ multiple sclerosis. Eur. J. Immunol. 1998, 28, 3329–3335. [Google Scholar] [CrossRef]
  19. Grau-Lopez, L.; Raich, D.; Ramo-Tello, C.; Naranjo-Gomez, M.; Davalos, A.; Pujol-Borrell, R.; Borras, F.E.; Martinez-Caceres, E. Specific T-cell proliferation to myelin peptides in relapsing-remitting multiple sclerosis. Eur. J. Neurol. 2011, 18, 1101–1104. [Google Scholar] [CrossRef]
  20. Hauser, S.L.; Cree, B.A.C. Treatment of Multiple Sclerosis: A Review. Am. J. Med. 2020, 133, 1380–1390.e1382. [Google Scholar] [CrossRef] [PubMed]
  21. Klotz, L.; Havla, J.; Schwab, N.; Hohlfeld, R.; Barnett, M.; Reddel, S.; Wiendl, H. Risks and risk management in modern multiple sclerosis immunotherapeutic treatment. Ther. Adv. Neurol. Disord. 2019, 12, 1756286419836571. [Google Scholar] [CrossRef]
  22. Nakajima, H. Guest editorial: Hematopoietic stem cells. Int. J. Hematol. 2017, 106, 16–17. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Blank, N.; Lisenko, K.; Pavel, P.; Bruckner, T.; Ho, A.D.; Wuchter, P. Low-dose cyclophosphamide effectively mobilizes peripheral blood stem cells in patients with autoimmune disease. Eur. J. Haematol. 2016, 97, 78–82. [Google Scholar] [CrossRef] [PubMed]
  24. Salvino, M.A.; Ruiz, J. Hematopoietic progenitor cell mobilization for autologous transplantation—A literature review. Rev. Bras. Hematol. Hemoter. 2016, 38, 28–36. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Hübel, K. Mobilization and Collection of HSC. EBMT Handb. 2019, 117–122. [Google Scholar] [CrossRef]
  26. Sharrack, B.; Saccardi, R.; Alexander, T.; Badoglio, M.; Burman, J.; Farge, D.; Greco, R.; Jessop, H.; Kazmi, M.; Kirgizov, K.; et al. Autologous haematopoietic stem cell transplantation and oTher. cellular therapy in multiple sclerosis and immune-mediated neurological diseases: Updated guidelines and recommendations from the EBMT Autoimmune Diseases Working Party (ADWP) and the Joint Accreditation Committee of EBMT and ISCT (JACIE). Bone Marrow Transplant. 2020, 55, 283–306. [Google Scholar] [CrossRef] [Green Version]
  27. Mancardi, G.; Sormani, M.P.; Muraro, P.A.; Boffa, G.; Saccardi, R. Intense immunosuppression followed by autologous haematopoietic stem cell transplantation as a therapeutic strategy in aggressive forms of multiple sclerosis. Mult. Scler. 2018, 24, 245–255. [Google Scholar] [CrossRef]
  28. Muraro, P.A.; Martin, R.; Mancardi, G.L.; Nicholas, R.; Sormani, M.P.; Saccardi, R. Autologous haematopoietic stem cell transplantation for treatment of multiple sclerosis. Nat. Rev. Neurol. 2017, 13, 391–405. [Google Scholar] [CrossRef]
  29. Burman, J.; Tolf, A.; Hagglund, H.; Askmark, H. Autologous haematopoietic stem cell transplantation for neurological diseases. J. Neurol. Neurosurg. Psychiatry 2018, 89, 147–155. [Google Scholar] [CrossRef]
  30. Sormani, M.P.; Muraro, P.A.; Schiavetti, I.; Signori, A.; Laroni, A.; Saccardi, R.; Mancardi, G.L. Autologous hematopoietic stem cell transplantation in multiple sclerosis: A meta-analysis. Neurology 2017, 88, 2115–2122. [Google Scholar] [CrossRef]
  31. Boffa, G.; Massacesi, L.; Inglese, M.; Mariottini, A.; Capobianco, M.; Lucia, M.; Amato, M.P.; Cottone, S.; Gualandi, F.; De Gobbi, M.; et al. Long-Term Clinical Outcomes of Hematopoietic Stem Cell Transplantation in Multiple Sclerosis. Neurology 2021. [Google Scholar] [CrossRef]
  32. Sboha, W. (Ed.) Vård vid Multipel Skleros och Parkinsons Sjukdo; Socialstyrelsen: Falun, Sweden, 2016; pp. 26–30. [Google Scholar]
  33. Laureys, G.; Willekens, B.; Vanopdenbosch, L.; Deryck, O.; Selleslag, D.; D’Haeseleer, M.; De Becker, A.; Dubois, B.; Dierickx, D.; Perrotta, G.; et al. A Belgian consensus protocol for autologous hematopoietic stem cell transplantation in multiple sclerosis. Acta Neurol. Belg. 2018, 118, 161–168. [Google Scholar] [CrossRef] [PubMed]
  34. Zephir, H.; Puyade, M.; Gueguen, A.; Michel, L.; Terriou, L.; Dive, D.; Laureys, G.; Mathey, G.; Labauge, P.; Marjanovic, Z.; et al. Indications and follow-up for autologous hematopoietic stem cell transplantation in multiple sclerosis: Guidelines from the Francophone Society of Bone Marrow Transplantation and Cellular Therapy (SFGM-TC) in association with the Francophone Society of Multiple Sclerosis. Bull. Cancer 2019, 106, S92–S101. [Google Scholar] [CrossRef] [Green Version]
  35. Cohen, J.A.; Baldassari, L.E.; Atkins, H.L.; Bowen, J.D.; Bredeson, C.; Carpenter, P.A.; Corboy, J.R.; Freedman, M.S.; Griffith, L.M.; Lowsky, R.; et al. Autologous Hematopoietic Cell Transplantation for Treatment-Refractory Relapsing Multiple Sclerosis: Position Statement from the American Society for Blood and Marrow Transplantation. Biol. Blood Marrow Transplant. 2019, 25, 845–854. [Google Scholar] [CrossRef] [Green Version]
  36. Bowen, J.D.; Kraft, G.H.; Wundes, A.; Guan, Q.; Maravilla, K.R.; Gooley, T.A.; McSweeney, P.A.; Pavletic, S.Z.; Openshaw, H.; Storb, R.; et al. Autologous hematopoietic cell transplantation following high-dose immunosuppressive therapy for advanced multiple sclerosis: Long-term results. Bone Marrow Transplant. 2012, 47, 946–951. [Google Scholar] [CrossRef]
  37. Curro, D.; Vuolo, L.; Gualandi, F.; Bacigalupo, A.; Roccatagliata, L.; Capello, E.; Uccelli, A.; Saccardi, R.; Sormani, M.P.; Mancardi, G. Low intensity lympho-ablative regimen followed by autologous hematopoietic stem cell transplantation in severe forms of multiple sclerosis: A MRI-based clinical study. Mult. Scler. 2015, 21, 1423–1430. [Google Scholar] [CrossRef]
  38. Mancardi, G.L.; Sormani, M.P.; Gualandi, F.; Saiz, A.; Carreras, E.; Merelli, E.; Donelli, A.; Lugaresi, A.; Di Bartolomeo, P.; Rottoli, M.R.; et al. Autologous hematopoietic stem cell transplantation in multiple sclerosis: A phase II trial. Neurology 2015, 84, 981–988. [Google Scholar] [CrossRef]
  39. Burman, J.; Iacobaeus, E.; Svenningsson, A.; Lycke, J.; Gunnarsson, M.; Nilsson, P.; Vrethem, M.; Fredrikson, S.; Martin, C.; Sandstedt, A.; et al. Autologous haematopoietic stem cell transplantation for aggressive multiple sclerosis: The Swedish experience. J. Neurol. Neurosurg. Psychiatry 2014, 85, 1116–1121. [Google Scholar] [CrossRef]
  40. Atkins, H.L.; Bowman, M.; Allan, D.; Anstee, G.; Arnold, D.L.; Bar-Or, A.; Bence-Bruckler, I.; Birch, P.; Bredeson, C.; Chen, J.; et al. Immunoablation and autologous haemopoietic stem-cell transplantation for aggressive multiple sclerosis: A multicentre single-group phase 2 trial. Lancet 2016, 388, 576–585. [Google Scholar] [CrossRef]
  41. Nash, R.A.; Hutton, G.J.; Racke, M.K.; Popat, U.; Devine, S.M.; Steinmiller, K.C.; Griffith, L.M.; Muraro, P.A.; Openshaw, H.; Sayre, P.H.; et al. High-dose immunosuppressive therapy and autologous HCT for relapsing-remitting MS. Neurology 2017, 88, 842–852. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Burt, R.K.; Loh, Y.; Cohen, B.; Stefoski, D.; Balabanov, R.; Katsamakis, G.; Oyama, Y.; Russell, E.J.; Stern, J.; Muraro, P.; et al. Autologous non-myeloablative haemopoietic stem cell transplantation in relapsing-remitting multiple sclerosis: A phase I/II study. Lancet Neurol. 2009, 8, 244–253. [Google Scholar] [CrossRef]
  43. Burt, R.K.; Balabanov, R.; Burman, J.; Sharrack, B.; Snowden, J.A.; Oliveira, M.C.; Fagius, J.; Rose, J.; Nelson, F.; Barreira, A.A.; et al. Effect of Nonmyeloablative Hematopoietic Stem Cell Transplantation vs. Continued Disease-Modifying Therapy on Disease Progression in Patients With Relapsing-Remitting Multiple Sclerosis: A Randomized Clinical Trial. JAMA 2019, 321, 165–174. [Google Scholar] [CrossRef] [PubMed]
  44. Zhukovsky, C.; Sandgren, S.; Silfverberg, T.; Einarsdottir, S.; Tolf, A.; Landtblom, A.M.; Novakova, L.; Axelsson, M.; Malmestrom, C.; Cherif, H.; et al. Autologous haematopoietic stem cell transplantation compared with alemtuzumab for relapsing-remitting multiple sclerosis: An observational study. J. Neurol. Neurosurg. Psychiatry 2020. [Google Scholar] [CrossRef]
  45. Ruiz-Argüelles, G.J.; León-Peña, A.A.; León-González, M.; Nuñez-Cortes, A.K.; Olivares-Gazca, J.C.; Murrieta-Alvarez, I.; Vargas-Espinosa, J.; Medina-Ceballos, E.; Cantero-Fortiz, Y.; Ruiz-Argüelles, A.; et al. A Feasibility Study of the Full Outpatient Conduction of Hematopoietic Transplants in Persons with Multiple Sclerosis Employing Autologous Non-Cryopreserved Peripheral Blood Stem Cells. Acta Haematol. 2017, 137, 214–219. [Google Scholar] [CrossRef]
  46. Riordan, N.H.; Morales, I.; Fernández, G.; Allen, N.; Fearnot, N.E.; Leckrone, M.E.; Markovich, D.J.; Mansfield, D.; Avila, D.; Patel, A.N.; et al. Clinical feasibility of umbilical cord tissue-derived mesenchymal stem cells in the treatment of multiple sclerosis. J. Transl. Med. 2018, 16, 57. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Uccelli, A.; Laroni, A.; Brundin, L.; Clanet, M.; Fernandez, O.; Nabavi, S.M.; Muraro, P.A.; Oliveri, R.S.; Radue, E.W.; Sellner, J.; et al. MEsenchymal StEm cells for Multiple Sclerosis (MESEMS): A randomized, double blind, cross-over phase I/II clinical trial with autologous mesenchymal stem cells for the therapy of multiple sclerosis. Trials 2019, 20, 263. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  48. Llufriu, S.; Sepulveda, M.; Blanco, Y.; Marin, P.; Moreno, B.; Berenguer, J.; Gabilondo, I.; Martinez-Heras, E.; Sola-Valls, N.; Arnaiz, J.A.; et al. Randomized placebo-controlled phase II trial of autologous mesenchymal stem cells in multiple sclerosis. PLoS ONE 2014, 9, e113936. [Google Scholar] [CrossRef] [PubMed]
  49. Connick, P.; Kolappan, M.; Crawley, C.; Webber, D.J.; Patani, R.; Michell, A.W.; Du, M.Q.; Luan, S.L.; Altmann, D.R.; Thompson, A.J.; et al. Autologous mesenchymal stem cells for the treatment of secondary progressive multiple sclerosis: An open-label phase 2a proof-of-concept study. Lancet Neurol. 2012, 11, 150–156. [Google Scholar] [CrossRef] [Green Version]
  50. Cohen, J.A.; Imrey, P.B.; Planchon, S.M.; Bermel, R.A.; Fisher, E.; Fox, R.J.; Bar-Or, A.; Sharp, S.L.; Skaramagas, T.T.; Jagodnik, P.; et al. Pilot trial of intravenous autologous culture-expanded mesenchymal stem cell transplantation in multiple sclerosis. Mult. Scler. 2018, 24, 501–511. [Google Scholar] [CrossRef] [Green Version]
  51. Fernández, O.; Izquierdo, G.; Fernández, V.; Leyva, L.; Reyes, V.; Guerrero, M.; León, A.; Arnaiz, C.; Navarro, G.; Páramo, M.D.; et al. Adipose-derived mesenchymal stem cells (AdMSC) for the treatment of secondary-progressive multiple sclerosis: A triple blinded, placebo controlled, randomized phase I/II safety and feasibility study. PLoS ONE 2018, 13, e0195891. [Google Scholar] [CrossRef] [Green Version]
  52. Alghwiri, A.A.; Jamali, F.; Aldughmi, M.; Khalil, H.; Al-Sharman, A.; Alhattab, D.; Al-Radaideh, A.; Awidi, A. The effect of stem cell therapy and comprehensive physical therapy in motor and non-motor symptoms in patients with multiple sclerosis: A comparative study. Medicine 2020, 99, e21646. [Google Scholar] [CrossRef]
  53. Rice, C.M.; Marks, D.I.; Ben-Shlomo, Y.; Evangelou, N.; Morgan, P.S.; Metcalfe, C.; Walsh, P.; Kane, N.M.; Guttridge, M.G.; Miflin, G.; et al. Assessment of bone marrow-derived Cellular Therapy in progressive Multiple Sclerosis (ACTiMuS): Study protocol for a randomised controlled trial. Trials 2015, 16, 463. [Google Scholar] [CrossRef] [PubMed]
  54. Petrou, P.; Kassis, I.; Levin, N.; Paul, F.; Backner, Y.; Benoliel, T.; Oertel, F.C.; Scheel, M.; Hallimi, M.; Yaghmour, N.; et al. Beneficial effects of autologous mesenchymal stem cell transplantation in active progressive multiple sclerosis. Brain 2020, 143, 3574–3588. [Google Scholar] [CrossRef]
  55. Karussis, D.; Karageorgiou, C.; Vaknin-Dembinsky, A.; Gowda-Kurkalli, B.; Gomori, J.M.; Kassis, I.; Bulte, J.W.; Petrou, P.; Ben-Hur, T.; Abramsky, O.; et al. Safety and immunological effects of mesenchymal stem cell transplantation in patients with multiple sclerosis and amyotrophic lateral sclerosis. Arch. Neurol. 2010, 67, 1187–1194. [Google Scholar] [CrossRef] [PubMed]
  56. Rice, C.M.; Marks, D.I.; Walsh, P.; Kane, N.M.; Guttridge, M.G.; Redondo, J.; Sarkar, P.; Owen, D.; Wilkins, A.; Scolding, N.J. Repeat infusion of autologous bone marrow cells in multiple sclerosis: Protocol for a phase I extension study (SIAMMS-II). BMJ Open 2015, 5, e009090. [Google Scholar] [CrossRef] [Green Version]
  57. Chwojnicki, K.; Iwaszkiewicz-Grześ, D.; Jankowska, A.; Zieliński, M.; Łowiec, P.; Gliwiński, M.; Grzywińska, M.; Kowalczyk, K.; Konarzewska, A.; Glasner, P.; et al. Administration of CD4(+)CD25(high)CD127(-)FoxP3(+) Regulatory T Cells for Relapsing-Remitting Multiple Sclerosis: A Phase 1 Study. BioDrugs 2021, 35, 47–60. [Google Scholar] [CrossRef] [PubMed]
  58. Zubizarreta, I.; Flórez-Grau, G.; Vila, G.; Cabezón, R.; España, C.; Andorra, M.; Saiz, A.; Llufriu, S.; Sepulveda, M.; Sola-Valls, N.; et al. Immune tolerance in multiple sclerosis and neuromyelitis optica with peptide-loaded tolerogenic dendritic cells in a phase 1b trial. Proc. Natl. Acad. Sci. USA 2019, 116, 8463–8470. [Google Scholar] [CrossRef] [Green Version]
  59. Willekens, B.; Presas-Rodríguez, S.; Mansilla, M.J.; Derdelinckx, J.; Lee, W.P.; Nijs, G.; De Laere, M.; Wens, I.; Cras, P.; Parizel, P.; et al. Tolerogenic dendritic cell-based treatment for multiple sclerosis (MS): A harmonised study protocol for two phase I clinical trials comparing intradermal and intranodal cell administration. BMJ Open 2019, 9, e030309. [Google Scholar] [CrossRef] [Green Version]
  60. Lutterotti, A.; Yousef, S.; Sputtek, A.; Sturner, K.H.; Stellmann, J.P.; Breiden, P.; Reinhardt, S.; Schulze, C.; Bester, M.; Heesen, C.; et al. Antigen-specific tolerance by autologous myelin peptide-coupled cells: A phase 1 trial in multiple sclerosis. Sci. Transl. Med. 2013, 5, 188ra175. [Google Scholar] [CrossRef] [Green Version]
  61. Lutterotti, A.; Ludersdorfer, T.; Docampo, M.; Hohmann, M.; Moreno, C.S.; Hayward-Koennecke, H.; Pfender, N.; Jelcic, I.; Mueller, T.; Blumer, C. Establish Tolerance in MS with myelin-peptide coupled red blood cells-the Phase Ib ETIMSredtrial. Mult. Scler. J. 2019, 25, 894. [Google Scholar]
  62. Harris, K.M.; Lim, N.; Lindau, P.; Robins, H.; Griffith, L.M.; Nash, R.A.; Turka, L.A.; Muraro, P.A. Extensive intrathecal T cell renewal following hematopoietic transplantation for multiple sclerosis. JCI Insight 2020, 5. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  63. Arruda, L.C.M.; de Azevedo, J.T.C.; de Oliveira, G.L.V.; Scortegagna, G.T.; Rodrigues, E.S.; Palma, P.V.B.; Brum, D.G.; Guerreiro, C.T.; Marques, V.D.; Barreira, A.A.; et al. Immunological correlates of favorable long-term clinical outcome in multiple sclerosis patients after autologous hematopoietic stem cell transplantation. Clin. Immunol. 2016, 169, 47–57. [Google Scholar] [CrossRef] [Green Version]
  64. Muraro, P.A.; Robins, H.; Malhotra, S.; Howell, M.; Phippard, D.; Desmarais, C.; de Paula Alves Sousa, A.; Griffith, L.M.; Lim, N.; Nash, R.A.; et al. T cell repertoire following autologous stem cell transplantation for multiple sclerosis. J. Clin. Investig. 2014, 124, 1168–1172. [Google Scholar] [CrossRef] [PubMed]
  65. Abrahamsson, S.V.; Angelini, D.F.; Dubinsky, A.N.; Morel, E.; Oh, U.; Jones, J.L.; Carassiti, D.; Reynolds, R.; Salvetti, M.; Calabresi, P.A.; et al. Non-myeloablative autologous haematopoietic stem cell transplantation expands regulatory cells and depletes IL-17 producing mucosal-associated invariant T cells in multiple sclerosis. Brain 2013, 136, 2888–2903. [Google Scholar] [CrossRef] [Green Version]
  66. Darlington, P.J.; Stopnicki, B.; Touil, T.; Doucet, J.S.; Fawaz, L.; Roberts, M.E.; Boivin, M.N.; Arbour, N.; Freedman, M.S.; Atkins, H.L.; et al. Natural Killer Cells Regulate Th17 Cells After Autologous Hematopoietic Stem Cell Transplantation for Relapsing Remitting Multiple Sclerosis. Front. Immunol. 2018, 9, 834. [Google Scholar] [CrossRef]
  67. Darlington, P.J.; Touil, T.; Doucet, J.S.; Gaucher, D.; Zeidan, J.; Gauchat, D.; Corsini, R.; Kim, H.J.; Duddy, M.; Jalili, F.; et al. Diminished Th17 (not Th1) responses underlie multiple sclerosis disease abrogation after hematopoietic stem cell transplantation. Ann. Neurol. 2013, 73, 341–354. [Google Scholar] [CrossRef] [PubMed]
  68. de Paula, A.S.A.; Malmegrim, K.C.; Panepucci, R.A.; Brum, D.S.; Barreira, A.A.; Carlos Dos Santos, A.; Araujo, A.G.; Covas, D.T.; Oliveira, M.C.; Moraes, D.A.; et al. Autologous haematopoietic stem cell transplantation reduces abnormalities in the expression of immune genes in multiple sclerosis. Clin. Sci. 2015, 128, 111–120. [Google Scholar] [CrossRef]
  69. Hendrawan, K.; Visweswaran, M.; Ma, D.D.F.; Moore, J.J. Tolerance regeneration by T regulatory cells in autologous haematopoietic stem cell transplantation for autoimmune diseases. Bone Marrow Transplant. 2020, 55, 857–866. [Google Scholar] [CrossRef]
  70. Larsson, D.; Åkerfeldt, T.; Carlson, K.; Burman, J. Intrathecal immunoglobulins and neurofilament light after autologous haematopoietic stem cell transplantation for multiple sclerosis. Mult. Scler. 2020, 26, 1351–1359. [Google Scholar] [CrossRef]
  71. Bertolotto, A.; Martire, S.; Mirabile, L.; Capobianco, M.; De Gobbi, M.; Cilloni, D. Autologous Hematopoietic Stem Cell Transplantation (AHSCT): Standard of Care for Relapsing-Remitting Multiple Sclerosis Patients. Neurol. Ther. 2020, 9, 197–203. [Google Scholar] [CrossRef]
  72. Pittenger, M.F.; Mackay, A.M.; Beck, S.C.; Jaiswal, R.K.; Douglas, R.; Mosca, J.D.; Moorman, M.A.; Simonetti, D.W.; Craig, S.; Marshak, D.R. Multilineage potential of adult human mesenchymal stem cells. Science 1999, 284, 143–147. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  73. Dominici, M.; Le Blanc, K.; Mueller, I.; Slaper-Cortenbach, I.; Marini, F.; Krause, D.; Deans, R.; Keating, A.; Prockop, D.; Horwitz, E. Minimal criteria for defining multipotent mesenchymal stromal cells. The International Society for Cellular Therapy position statement. Cytotherapy 2006, 8, 315–317. [Google Scholar] [CrossRef] [PubMed]
  74. Friedenstein, A.J.; Chailakhyan, R.K.; Latsinik, N.V.; Panasyuk, A.F.; Keiliss-Borok, I.V. Stromal cells responsible for transferring the microenvironment of the hemopoietic tissues. Cloning in vitro and retransplantation in vivo. Transplantation 1974, 17, 331–340. [Google Scholar] [CrossRef] [PubMed]
  75. Marigo, I.; Dazzi, F. The immunomodulatory properties of mesenchymal stem cells. Semin. Immunopathol. 2011, 33, 593–602. [Google Scholar] [CrossRef]
  76. Di Nicola, M.; Carlo-Stella, C.; Magni, M.; Milanesi, M.; Longoni, P.D.; Matteucci, P.; Grisanti, S.; Gianni, A.M. Human bone marrow stromal cells suppress T-lymphocyte proliferation induced by cellular or nonspecific mitogenic stimuli. Blood 2002, 99, 3838–3843. [Google Scholar] [CrossRef]
  77. Meisel, R.; Zibert, A.; Laryea, M.; Gobel, U.; Daubener, W.; Dilloo, D. Human bone marrow stromal cells inhibit allogeneic T-cell responses by indoleamine 2,3-dioxygenase-mediated tryptophan degradation. Blood 2004, 103, 4619–4621. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  78. Sato, K.; Ozaki, K.; Oh, I.; Meguro, A.; Hatanaka, K.; Nagai, T.; Muroi, K.; Ozawa, K. Nitric oxide plays a critical role in suppression of T-cell proliferation by mesenchymal stem cells. Blood 2007, 109, 228–234. [Google Scholar] [CrossRef]
  79. Batten, P.; Sarathchandra, P.; Antoniw, J.W.; Tay, S.S.; Lowdell, M.W.; Taylor, P.M.; Yacoub, M.H. Human mesenchymal stem cells induce T cell anergy and downregulate T cell allo-responses via the TH2 pathway: Relevance to tissue engineering human heart valves. Tissue Eng. 2006, 12, 2263–2273. [Google Scholar] [CrossRef]
  80. Aggarwal, S.; Pittenger, M.F. Human mesenchymal stem cells modulate allogeneic immune cell responses. Blood 2005, 105, 1815–1822. [Google Scholar] [CrossRef] [Green Version]
  81. Augello, A.; Tasso, R.; Negrini, S.M.; Amateis, A.; Indiveri, F.; Cancedda, R.; Pennesi, G. Bone marrow mesenchymal progenitor cells inhibit lymphocyte proliferation by activation of the programmed death 1 pathway. Eur. J. Immunol. 2005, 35, 1482–1490. [Google Scholar] [CrossRef]
  82. Beyth, S.; Borovsky, Z.; Mevorach, D.; Liebergall, M.; Gazit, Z.; Aslan, H.; Galun, E.; Rachmilewitz, J. Human mesenchymal stem cells alter antigen-presenting cell maturation and induce T-cell unresponsiveness. Blood 2005, 105, 2214–2219. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  83. Prevosto, C.; Zancolli, M.; Canevali, P.; Zocchi, M.R.; Poggi, A. Generation of CD4+ or CD8+ regulatory T cells upon mesenchymal stem cell-lymphocyte interaction. Haematologica 2007, 92, 881–888. [Google Scholar] [CrossRef] [PubMed]
  84. Haniffa, M.A.; Wang, X.N.; Holtick, U.; Rae, M.; Isaacs, J.D.; Dickinson, A.M.; Hilkens, C.M.; Collin, M.P. Adult human fibroblasts are potent immunoregulatory cells and functionally equivalent to mesenchymal stem cells. J. Immunol. 2007, 179, 1595–1604. [Google Scholar] [CrossRef] [Green Version]
  85. Zhou, H.; Jin, Z.; Liu, J.; Yu, S.; Cui, Q.; Yi, D. Mesenchymal stem cells might be used to induce tolerance in heart transplantation. Med. Hypotheses 2008, 70, 785–787. [Google Scholar] [CrossRef] [PubMed]
  86. Rasmusson, I.; Uhlin, M.; Le Blanc, K.; Levitsky, V. Mesenchymal stem cells fail to trigger effector functions of cytotoxic T lymphocytes. J. Leukoc. Biol. 2007, 82, 887–893. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  87. Sotiropoulou, P.A.; Perez, S.A.; Gritzapis, A.D.; Baxevanis, C.N.; Papamichail, M. Interactions between human mesenchymal stem cells and natural killer cells. Stem Cells 2006, 24, 74–85. [Google Scholar] [CrossRef]
  88. Spaggiari, G.M.; Capobianco, A.; Becchetti, S.; Mingari, M.C.; Moretta, L. Mesenchymal stem cell-natural killer cell interactions: Evidence that activated NK cells are capable of killing MSCs, whereas MSCs can inhibit IL-2-induced NK-cell proliferation. Blood 2006, 107, 1484–1490. [Google Scholar] [CrossRef]
  89. Maccario, R.; Podesta, M.; Moretta, A.; Cometa, A.; Comoli, P.; Montagna, D.; Daudt, L.; Ibatici, A.; Piaggio, G.; Pozzi, S.; et al. Interaction of human mesenchymal stem cells with cells involved in alloantigen-specific immune response favors the differentiation of CD4+ T-cell subsets expressing a regulatory/suppressive phenotype. Haematologica 2005, 90, 516–525. [Google Scholar] [PubMed]
  90. Zappia, E.; Casazza, S.; Pedemonte, E.; Benvenuto, F.; Bonanni, I.; Gerdoni, E.; Giunti, D.; Ceravolo, A.; Cazzanti, F.; Frassoni, F.; et al. Mesenchymal stem cells ameliorate experimental autoimmune encephalomyelitis inducing T-cell anergy. Blood 2005, 106, 1755–1761. [Google Scholar] [CrossRef] [Green Version]
  91. Digirolamo, C.M.; Stokes, D.; Colter, D.; Phinney, D.G.; Class, R.; Prockop, D.J. Propagation and senescence of human marrow stromal cells in culture: A simple colony-forming assay identifies samples with the greatest potential to propagate and differentiate. Br. J. Haematol. 1999, 107, 275–281. [Google Scholar] [CrossRef] [PubMed]
  92. Sekiya, I.; Larson, B.L.; Smith, J.R.; Pochampally, R.; Cui, J.G.; Prockop, D.J. Expansion of human adult stem cells from bone marrow stroma: Conditions that maximize the yields of early progenitors and evaluate their quality. Stem Cells 2002, 20, 530–541. [Google Scholar] [CrossRef]
  93. Ardeshiry Lajimi, A.; Hagh, M.F.; Saki, N.; Mortaz, E.; Soleimani, M.; Rahim, F. Feasibility of cell therapy in multiple sclerosis: A systematic review of 83 studies. Int. J. Hematol. Oncol. Stem Cell Res. 2013, 7, 15–33. [Google Scholar]
  94. Zhang, J.; Li, Y.; Lu, M.; Cui, Y.; Chen, J.; Noffsinger, L.; Elias, S.B.; Chopp, M. Bone marrow stromal cells reduce axonal loss in experimental autoimmune encephalomyelitis mice. J. Neurosci. Res. 2006, 84, 587–595. [Google Scholar] [CrossRef]
  95. Bai, L.; Lennon, D.P.; Eaton, V.; Maier, K.; Caplan, A.I.; Miller, S.D.; Miller, R.H. Human bone marrow-derived mesenchymal stem cells induce Th2-polarized immune response and promote endogenous repair in animal models of multiple sclerosis. Glia 2009, 57, 1192–1203. [Google Scholar] [CrossRef] [Green Version]
  96. Wilkins, A.; Kemp, K.; Ginty, M.; Hares, K.; Mallam, E.; Scolding, N. Human bone marrow-derived mesenchymal stem cells secrete brain-derived neurotrophic factor which promotes neuronal survival in vitro. Stem Cell Res. 2009, 3, 63–70. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  97. Li, D.; Chai, J.; Shen, C.; Han, Y.; Sun, T. Human umbilical cord-derived mesenchymal stem cells differentiate into epidermal-like cells using a novel co-culture technique. Cytotechnology 2014, 66, 699–708. [Google Scholar] [CrossRef] [Green Version]
  98. Kopen, G.C.; Prockop, D.J.; Phinney, D.G. Marrow stromal cells migrate throughout forebrain and cerebellum, and they differentiate into astrocytes after injection into neonatal mouse brains. Proc. Natl. Acad. Sci. USA 1999, 96, 10711–10716. [Google Scholar] [CrossRef] [Green Version]
  99. Janssens, I.; Cools, N. Regulating the regulators: Is introduction of an antigen-specific approach in regulatory T cells the next step to treat autoimmunity? Cell. Immunol. 2020, 358, 104236. [Google Scholar] [CrossRef] [PubMed]
  100. Arvey, A.; van der Veeken, J.; Samstein, R.M.; Feng, Y.; Stamatoyannopoulos, J.A.; Rudensky, A.Y. Inflammation-induced repression of chromatin bound by the transcription factor Foxp3 in regulatory T cells. Nat. Immunol. 2014, 15, 580–587. [Google Scholar] [CrossRef] [Green Version]
  101. Ohkura, N.; Kitagawa, Y.; Sakaguchi, S. Development and maintenance of regulatory T cells. Immunity 2013, 38, 414–423. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  102. Samstein, R.M.; Arvey, A.; Josefowicz, S.Z.; Peng, X.; Reynolds, A.; Sandstrom, R.; Neph, S.; Sabo, P.; Kim, J.M.; Liao, W.; et al. Foxp3 exploits a pre-existent enhancer landscape for regulatory T cell lineage specification. Cell 2012, 151, 153–166. [Google Scholar] [CrossRef] [Green Version]
  103. Liu, W.; Putnam, A.L.; Xu-Yu, Z.; Szot, G.L.; Lee, M.R.; Zhu, S.; Gottlieb, P.A.; Kapranov, P.; Gingeras, T.R.; Fazekas de St Groth, B.; et al. CD127 expression inversely correlates with FoxP3 and suppressive function of human CD4+ T reg cells. J. Exp. Med. 2006, 203, 1701–1711. [Google Scholar] [CrossRef] [Green Version]
  104. Curotto de Lafaille, M.A.; Lafaille, J.J. Natural and Adaptive Foxp3+ Regulatory T Cells: More of the Same or a Division of Labor? Immunity 2009, 30, 626–635. [Google Scholar] [CrossRef] [Green Version]
  105. Josefowicz, S.Z.; Niec, R.E.; Kim, H.Y.; Treuting, P.; Chinen, T.; Zheng, Y.; Umetsu, D.T.; Rudensky, A.Y. Extrathymically generated regulatory T cells control mucosal TH2 inflammation. Nature 2012, 482, 395–399. [Google Scholar] [CrossRef] [PubMed]
  106. Mason, G.M.; Lowe, K.; Melchiotti, R.; Ellis, R.; de Rinaldis, E.; Peakman, M.; Heck, S.; Lombardi, G.; Tree, T.I.M. Phenotypic Complexity of the Human Regulatory T Cell Compartment Revealed by Mass Cytometry. J. Immunol. 2015, 195, 2030–2037. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  107. Apostolou, I.; Verginis, P.; Kretschmer, K.; Polansky, J.; Huhn, J.; von Boehmer, H. Peripherally induced Treg: Mode, stability, and role in specific tolerance. J. Clin. Immunol. 2008, 28, 619–624. [Google Scholar] [CrossRef] [PubMed]
  108. Sakaguchi, S. Regulatory T cells: Key controllers of immunologic self-tolerance. Cell 2000, 101, 455–458. [Google Scholar] [CrossRef] [Green Version]
  109. Ehrenstein, M.R. Compromised Function of Regulatory T Cells in Rheumatoid Arthritis and Reversal by Anti-TNFα Therapy. J. Exp. Med. 2004, 200, 277–285. [Google Scholar] [CrossRef] [PubMed]
  110. Lindley, S.; Dayan, C.M.; Bishop, A.; Roep, B.O.; Peakman, M.; Tree, T.I. Defective suppressor function in CD4(+)CD25(+) T-cells from patients with type 1 diabetes. Diabetes 2005, 54, 92–99. [Google Scholar] [CrossRef] [Green Version]
  111. Sugiyama, H.; Gyulai, R.; Toichi, E.; Garaczi, E.; Shimada, S.; Stevens, S.R.; McCormick, T.S.; Cooper, K.D. Dysfunctional blood and target tissue CD4+CD25high regulatory T cells in psoriasis: Mechanism underlying unrestrained pathogenic effector T cell proliferation. J. Immunol. 2005, 174, 164–173. [Google Scholar] [CrossRef] [Green Version]
  112. Balandina, A.; Lecart, S.; Dartevelle, P.; Saoudi, A.; Berrih-Aknin, S. Functional defect of regulatory CD4(+)CD25+ T cells in the thymus of patients with autoimmune myasthenia gravis. Blood 2005, 105, 735–741. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  113. Kriegel, M.A.; Lohmann, T.; Gabler, C.; Blank, N.; Kalden, J.R.; Lorenz, H.M. Defective suppressor function of human CD4+ CD25+ regulatory T cells in autoimmune polyglandular syndrome type II. J. Exp. Med. 2004, 199, 1285–1291. [Google Scholar] [CrossRef] [PubMed]
  114. Kohm, A.P.; Carpentier, P.A.; Anger, H.A.; Miller, S.D. Cutting edge: CD4+CD25+ regulatory T cells suppress antigen-specific autoreactive immune responses and central nervous system inflammation during active experimental autoimmune encephalomyelitis. J. Immunol. 2002, 169, 4712–4716. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  115. Tanaka, H.; Zhang, W.; Yang, G.X.; Ando, Y.; Tomiyama, T.; Tsuneyama, K.; Leung, P.; Coppel, R.L.; Ansari, A.A.; Lian, Z.X.; et al. Successful immunotherapy of autoimmune cholangitis by adoptive transfer of forkhead box protein 3(+) regulatory T cells. Clin. Exp. Immunol. 2014, 178, 253–261. [Google Scholar] [CrossRef]
  116. Edinger, M. Regulatory T cells for the prevention of graft-versus-host disease: Professionals defeat amateurs. Eur. J. Immunol. 2009, 39, 2966–2968. [Google Scholar] [CrossRef] [PubMed]
  117. Trenado, A.; Sudres, M.; Tang, Q.; Maury, S.; Charlotte, F.; Gregoire, S.; Bonyhadi, M.; Klatzmann, D.; Salomon, B.L.; Cohen, J.L. Ex vivo-expanded CD4+CD25+ immunoregulatory T cells prevent graft-versus-host-disease by inhibiting activation/differentiation of pathogenic T cells. J. Immunol. 2006, 176, 1266–1273. [Google Scholar] [CrossRef] [Green Version]
  118. Xiao, F.; Ma, L.; Zhao, M.; Huang, G.; Mirenda, V.; Dorling, A.; Lechler, R.; Lombardi, G. Ex vivo expanded human regulatory T cells delay islet allograft rejection via inhibiting islet-derived monocyte chemoattractant protein-1 production in CD34+ stem cells-reconstituted NOD-scid IL2rgammanull mice. PLoS ONE 2014, 9, e90387. [Google Scholar] [CrossRef]
  119. Sagoo, P.; Ali, N.; Garg, G.; Nestle, F.O.; Lechler, R.I.; Lombardi, G. Human regulatory T cells with alloantigen specificity are more potent inhibitors of alloimmune skin graft damage than polyclonal regulatory T cells. Sci. Transl. Med. 2011, 3, 83ra42. [Google Scholar] [CrossRef] [Green Version]
  120. Jonuleit, H.; Schmitt, E.; Kakirman, H.; Stassen, M.; Knop, J.; Enk, A.H. Infectious tolerance: Human CD25(+) regulatory T cells convey suppressor activity to conventional CD4(+) T helper cells. J. Exp. Med. 2002, 196, 255–260. [Google Scholar] [CrossRef] [Green Version]
  121. Thornton, A.M.; Shevach, E.M. Suppressor effector function of CD4+CD25+ immunoregulatory T cells is antigen nonspecific. J. Immunol. 2000, 164, 183–190. [Google Scholar] [CrossRef] [Green Version]
  122. MacDonald, K.N.; Piret, J.M.; Levings, M.K. Methods to manufacture regulatory T cells for cell therapy. Clin. Exp. Immunol. 2019, 197, 52–63. [Google Scholar] [CrossRef] [Green Version]
  123. Seay, H.R.; Putnam, A.L.; Cserny, J.; Posgai, A.L.; Rosenau, E.H.; Wingard, J.R.; Girard, K.F.; Kraus, M.; Lares, A.P.; Brown, H.L.; et al. Expansion of Human Tregs from Cryopreserved Umbilical Cord Blood for GMP-Compliant Autologous Adoptive Cell Transfer Therapy. Mol. Ther. Methods Clin. Dev. 2017, 4, 178–191. [Google Scholar] [CrossRef]
  124. Raffin, C.; Vo, L.T.; Bluestone, J.A. T(reg) cell-based therapies: Challenges and perspectives. Nat. Rev. Immunol. 2020, 20, 158–172. [Google Scholar] [CrossRef]
  125. Safinia, N.; Vaikunthanathan, T.; Fraser, H.; Thirkell, S.; Lowe, K.; Blackmore, L.; Whitehouse, G.; Martinez-Llordella, M.; Jassem, W.; Sanchez-Fueyo, A.; et al. Successful expansion of functional and stable regulatory T cells for immunotherapy in liver transplantation. Oncotarget 2016, 7, 7563–7577. [Google Scholar] [CrossRef] [PubMed]
  126. Thomson, A.W.; Turnquist, H.R.; Raimondi, G. Immunoregulatory functions of mTOR inhibition. Nat. Rev. Immunol. 2009, 9, 324–337. [Google Scholar] [CrossRef] [Green Version]
  127. Battaglia, M.; Stabilini, A.; Migliavacca, B.; Horejs-Hoeck, J.; Kaupper, T.; Roncarolo, M.G. Rapamycin promotes expansion of functional CD4+CD25+FOXP3+ regulatory T cells of both healthy subjects and type 1 diabetic patients. J. Immunol. 2006, 177, 8338–8347. [Google Scholar] [CrossRef] [Green Version]
  128. Mathew, J.M.; Jessica, H.; LeFever, A.; Konieczna, I.; Stratton, C.; He, J.; Huang, X.; Gallon, L.; Skaro, A.; Ansari, M.J.; et al. A Phase I Clinical Trial with Ex Vivo Expanded Recipient Regulatory T cells in Living Donor Kidney Transplants. Sci. Rep. 2018, 8, 7428. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  129. Schiavinato, J.; Haddad, R.; Saldanha-Araujo, F.; Baiochi, J.; Araujo, A.G.; Santos Scheucher, P.; Covas, D.T.; Zago, M.A.; Panepucci, R.A. TGF-beta/atRA-induced Tregs express a selected set of microRNAs involved in the repression of transcripts related to Th17 differentiation. Sci. Rep. 2017, 7, 3627. [Google Scholar] [CrossRef] [PubMed]
  130. Scotta, C.; Esposito, M.; Fazekasova, H.; Fanelli, G.; Edozie, F.C.; Ali, N.; Xiao, F.; Peakman, M.; Afzali, B.; Sagoo, P.; et al. Differential effects of rapamycin and retinoic acid on expansion, stability and suppressive qualities of human CD4(+)CD25(+)FOXP3(+) T regulatory cell subpopulations. Haematologica 2013, 98, 1291–1299. [Google Scholar] [CrossRef]
  131. Esensten, J.H.; Muller, Y.D.; Bluestone, J.A.; Tang, Q. Regulatory T-cell therapy for autoimmune and autoinflammatory diseases: The next frontier. J. Allergy Clin. Immunol. 2018, 142, 1710–1718. [Google Scholar] [CrossRef] [Green Version]
  132. Romano, M.; Fanelli, G.; Albany, C.J.; Giganti, G.; Lombardi, G. Past, Present, and Future of Regulatory T Cell Therapy in Transplantation and Autoimmunity. Front. Immunol. 2019, 10. [Google Scholar] [CrossRef] [Green Version]
  133. Marek-Trzonkowska, N.; Mysliwiec, M.; Dobyszuk, A.; Grabowska, M.; Derkowska, I.; Juscinska, J.; Owczuk, R.; Szadkowska, A.; Witkowski, P.; Mlynarski, W.; et al. Therapy of type 1 diabetes with CD4(+)CD25(high)CD127-regulatory T cells prolongs survival of pancreatic islets—Results of one year follow-up. Clin. Immunol. 2014, 153, 23–30. [Google Scholar] [CrossRef]
  134. Morgan, M.E.; Flierman, R.; van Duivenvoorde, L.M.; Witteveen, H.J.; van Ewijk, W.; van Laar, J.M.; de Vries, R.R.; Toes, R.E. Effective treatment of collagen-induced arthritis by adoptive transfer of CD25+ regulatory T cells. Arthritis Rheum. 2005, 52, 2212–2221. [Google Scholar] [CrossRef]
  135. Mottet, C.; Uhlig, H.H.; Powrie, F. Cutting Edge: Cure of Colitis by CD4+CD25+ Regulatory T Cells. J. Immunol. 2003, 170, 3939. [Google Scholar] [CrossRef] [Green Version]
  136. Brunstein, C.G.; Blazar, B.R.; Miller, J.S.; Cao, Q.; Hippen, K.L.; McKenna, D.H.; Curtsinger, J.; McGlave, P.B.; Wagner, J.E. Adoptive transfer of umbilical cord blood-derived regulatory T cells and early viral reactivation. Biol. Blood Marrow Transplant. 2013, 19, 1271–1273. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  137. Green, E.A.; Choi, Y.; Flavell, R.A. Pancreatic lymph node-derived CD4(+)CD25(+) Treg cells: Highly potent regulators of diabetes that require TRANCE-RANK signals. Immunity 2002, 16, 183–191. [Google Scholar] [CrossRef] [Green Version]
  138. Tang, Q.; Henriksen, K.J.; Bi, M.; Finger, E.B.; Szot, G.; Ye, J.; Masteller, E.L.; McDevitt, H.; Bonyhadi, M.; Bluestone, J.A. In vitro-expanded antigen-specific regulatory T cells suppress autoimmune diabetes. J. Exp. Med. 2004, 199, 1455–1465. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  139. Tarbell, K.V.; Yamazaki, S.; Olson, K.; Toy, P.; Steinman, R.M. CD25+ CD4+ T cells, expanded with dendritic cells presenting a single autoantigenic peptide, suppress autoimmune diabetes. J. Exp. Med. 2004, 199, 1467–1477. [Google Scholar] [CrossRef] [PubMed]
  140. Masteller, E.L.; Warner, M.R.; Tang, Q.; Tarbell, K.V.; McDevitt, H.; Bluestone, J.A. Expansion of functional endogenous antigen-specific CD4+CD25+ regulatory T cells from nonobese diabetic mice. J. Immunol. 2005, 175, 3053–3059. [Google Scholar] [CrossRef] [Green Version]
  141. Tarbell, K.V.; Petit, L.; Zuo, X.; Toy, P.; Luo, X.; Mqadmi, A.; Yang, H.; Suthanthiran, M.; Mojsov, S.; Steinman, R.M. Dendritic cell-expanded, islet-specific CD4+ CD25+ CD62L+ regulatory T cells restore normoglycemia in diabetic NOD mice. J. Exp. Med. 2007, 204, 191–201. [Google Scholar] [CrossRef] [Green Version]
  142. Ferreira, L.M.R.; Muller, Y.D.; Bluestone, J.A.; Tang, Q. Next-generation regulatory T cell therapy. Nat. Rev. Drug Discov. 2019, 18, 749–769. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  143. Mekala, D.J.; Geiger, T.L. Immunotherapy of autoimmune encephalomyelitis with redirected CD4+CD25+ T lymphocytes. Blood 2005, 105, 2090–2092. [Google Scholar] [CrossRef] [Green Version]
  144. Mekala, D.J.; Alli, R.S.; Geiger, T.L. IL-10-dependent infectious tolerance after the treatment of experimental allergic encephalomyelitis with redirected CD4+CD25+ T lymphocytes. Proc. Natl. Acad. Sci. USA 2005, 102, 11817–11822. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  145. Kim, Y.C.; Zhang, A.H.; Yoon, J.; Culp, W.E.; Lees, J.R.; Wucherpfennig, K.W.; Scott, D.W. Engineered MBP-specific human Tregs ameliorate MOG-induced EAE through IL-2-triggered inhibition of effector T cells. J. Autoimmun. 2018. [Google Scholar] [CrossRef]
  146. Allan, S.E.; Alstad, A.N.; Merindol, N.; Crellin, N.K.; Amendola, M.; Bacchetta, R.; Naldini, L.; Roncarolo, M.G.; Soudeyns, H.; Levings, M.K. Generation of potent and stable human CD4+ T regulatory cells by activation-independent expression of FOXP3. Mol. Ther. J. Am. Soc. Gene Ther. 2008, 16, 194–202. [Google Scholar] [CrossRef]
  147. Aarts-Riemens, T.; Emmelot, M.E.; Verdonck, L.F.; Mutis, T. Forced overexpression of eiTher. of the two common human Foxp3 isoforms can induce regulatory T cells from CD4(+)CD25(-) cells. Eur. J. Immunol. 2008, 38, 1381–1390. [Google Scholar] [CrossRef] [PubMed]
  148. Fransson, M.; Piras, E.; Burman, J.; Nilsson, B.; Essand, M.; Lu, B.; Harris, R.A.; Magnusson, P.U.; Brittebo, E.; Loskog, A.S. CAR/FoxP3-engineered T regulatory cells target the CNS and suppress EAE upon intranasal delivery. J. Neuroinflamm. 2012, 9, 112. [Google Scholar] [CrossRef] [Green Version]
  149. De Paula Pohl, A.; Schmidt, A.; Zhang, A.H.; Maldonado, T.; Königs, C.; Scott, D.W. Engineered regulatory T cells expressing myelin-specific chimeric antigen receptors suppress EAE progression. Cell. Immunol. 2020, 358, 104222. [Google Scholar] [CrossRef] [PubMed]
  150. Granucci, F.; Zanoni, I.; Ricciardi-Castagnoli, P. Central role of dendritic cells in the regulation and deregulation of immune responses. Cell. Mol. life Sci. CMLS 2008, 65, 1683–1697. [Google Scholar] [CrossRef] [PubMed]
  151. Steinman, R.M. Lasker Basic Medical Research Award. Dendritic cells: Versatile controllers of the immune system. Nat. Med. 2007, 13, 1155–1159. [Google Scholar] [CrossRef]
  152. Van Brussel, I.; Berneman, Z.N.; Cools, N. Optimizing dendritic cell-based immunotherapy: Tackling the complexity of different arms of the immune system. Mediators Inflamm. 2012, 2012, 690643. [Google Scholar] [CrossRef]
  153. Banchereau, J.; Briere, F.; Caux, C.; Davoust, J.; Lebecque, S.; Liu, Y.J.; Pulendran, B.; Palucka, K. Immunobiology of dendritic cells. Annu. Rev. Immunol. 2000, 18, 767–811. [Google Scholar] [CrossRef]
  154. Banchereau, J.; Steinman, R.M. Dendritic cells and the control of immunity. Nature 1998, 392, 245–252. [Google Scholar] [CrossRef] [PubMed]
  155. Boltjes, A.; van Wijk, F. Human dendritic cell functional specialization in steady-state and inflammation. Front. Immunol. 2014, 5, 131. [Google Scholar] [CrossRef] [Green Version]
  156. Moser, M. Dendritic cells in immunity and tolerance-do they display opposite functions? Immunity 2003, 19, 5–8. [Google Scholar] [CrossRef]
  157. Thewissen, K.; Nuyts, A.H.; Deckx, N.; Van Wijmeersch, B.; Nagels, G.; D’Hooghe, M.; Willekens, B.; Cras, P.; Eijnde, B.O.; Goossens, H.; et al. Circulating dendritic cells of multiple sclerosis patients are proinflammatory and their frequency is correlated with MS-associated genetic risk factors. Mult. Scler. 2014, 20, 548–557. [Google Scholar] [CrossRef] [PubMed]
  158. Huang, Y.M.; Stoyanova, N.; Jin, Y.P.; Teleshova, N.; Hussien, Y.; Xiao, B.G.; Fredrikson, S.; Link, H. Altered phenotype and function of blood dendritic cells in multiple sclerosis are modulated by IFN-beta and IL-10. Clin. Exp. Immunol. 2001, 124, 306–314. [Google Scholar] [CrossRef]
  159. Karni, A.; Abraham, M.; Monsonego, A.; Cai, G.; Freeman, G.J.; Hafler, D.; Khoury, S.J.; Weiner, H.L. Innate immunity in multiple sclerosis: Myeloid dendritic cells in secondary progressive multiple sclerosis are activated and drive a proinflammatory immune response. J. Immunol. 2006, 177, 4196–4202. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  160. Huang, Y.M.; Kouwenhoven, M.; Jin, Y.P.; Press, R.; Huang, W.X.; Link, H. Dendritic cells derived from patients with multiple sclerosis show high CD1a and low CD86 expression. Mult. Scler. 2001, 7, 95–99. [Google Scholar] [CrossRef]
  161. Vaknin-Dembinsky, A.; Balashov, K.; Weiner, H.L. IL-23 is increased in dendritic cells in multiple sclerosis and down-regulation of IL-23 by antisense oligos increases dendritic cell IL-10 production. J. Immunol. 2006, 176, 7768–7774. [Google Scholar] [CrossRef]
  162. Vaknin-Dembinsky, A.; Murugaiyan, G.; Hafler, D.A.; Astier, A.L.; Weiner, H.L. Increased IL-23 secretion and altered chemokine production by dendritic cells upon CD46 activation in patients with multiple sclerosis. J. Neuroimmunol. 2008, 195, 140–145. [Google Scholar] [CrossRef] [Green Version]
  163. Nuyts, A.H.; Lee, W.P.; Bashir-Dar, R.; Berneman, Z.N.; Cools, N. Dendritic cells in multiple sclerosis: Key players in the immunopathogenesis, key players for new cellular immunotherapies? Mult. Scler. 2013, 19, 995–1002. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  164. Van Brussel, I.; Lee, W.P.; Rombouts, M.; Nuyts, A.H.; Heylen, M.; De Winter, B.Y.; Cools, N.; Schrijvers, D.M. Tolerogenic dendritic cell vaccines to treat autoimmune diseases: Can the unattainable dream turn into reality? Autoimmun. Rev. 2014, 13, 138–150. [Google Scholar] [CrossRef]
  165. Tkachenko, N.; Wojas, K.; Tabarkiewicz, J.; Rolinski, J. Generation of dendritic cells from human peripheral blood monocytes—Comparison of different culture media. Folia Histochem. Cytobiol. 2005, 43, 25–30. [Google Scholar]
  166. Hackstein, H.; Thomson, A.W. Dendritic cells: Emerging pharmacological targets of immunosuppressive drugs. Nat. Rev. Immunol. 2004, 4, 24–34. [Google Scholar] [CrossRef] [PubMed]
  167. van Kooten, C.; Stax, A.S.; Woltman, A.M.; Gelderman, K.A. The use of dexamethasone in the induction of tolerogenic DCs. In Dendritic Cells; Handbook of Experimental Pharmacology; Springer: Berlin/Heidelberg, Germany, 2009; pp. 233–249. [Google Scholar] [CrossRef]
  168. Florez-Grau, G.; Zubizarreta, I.; Cabezon, R.; Villoslada, P.; Benitez-Ribas, D. 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. 2018, 9, 1169. [Google Scholar] [CrossRef] [Green Version]
  169. Kalantari, T.; Kamali-Sarvestani, E.; Ciric, B.; Karimi, M.H.; Kalantari, M.; Faridar, A.; Xu, H.; Rostami, A. Generation of immunogenic and tolerogenic clinical-grade dendritic cells. Immunol. Res. 2011, 51, 153–160. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  170. Garcia-Gonzalez, P.; Morales, R.; Hoyos, L.; Maggi, J.; Campos, J.; Pesce, B.; Garate, D.; Larrondo, M.; Gonzalez, R.; Soto, L.; et al. A short protocol using dexamethasone and monophosphoryl lipid A generates tolerogenic dendritic cells that display a potent migratory capacity to lymphoid chemokines. J. Transl. Med. 2013, 11, 128. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  171. Naranjo-Gómez, M.; Raïch-Regué, D.; Oñate, C.; Grau-López, L.; Ramo-Tello, C.; Pujol-Borrell, R.; Martínez-Cáceres, E.; Borràs, F.E. Comparative study of clinical grade human tolerogenic dendritic cells. J. Transl. Med. 2011, 9, 89. [Google Scholar] [CrossRef] [Green Version]
  172. Adorini, L.; Penna, G.; Giarratana, N.; Roncari, A.; Amuchastegui, S.; Daniel, K.C.; Uskokovic, M. Dendritic cells as key targets for immunomodulation by Vitamin D receptor ligands. J. Steroid Biochem. Mol. Biol. 2004, 89–90, 437–441. [Google Scholar] [CrossRef]
  173. Penna, G.; Roncari, A.; Amuchastegui, S.; Daniel, K.C.; Berti, E.; Colonna, M.; Adorini, L. Expression of the inhibitory receptor ILT3 on dendritic cells is dispensable for induction of CD4+Foxp3+ regulatory T cells by 1,25-dihydroxyvitamin D3. Blood 2005, 106, 3490–3497. [Google Scholar] [CrossRef]
  174. Adorini, L.; Penna, G. Induction of tolerogenic dendritic cells by vitamin D receptor agonists. In Dendritic Cells; Handbook of Experimental Pharmacology; Springer: Berlin/Heidelberg, Germany, 2009; pp. 251–273. [Google Scholar] [CrossRef]
  175. Pedersen, A.W.; Holmstrøm, K.; Jensen, S.S.; Fuchs, D.; Rasmussen, S.; Kvistborg, P.; Claesson, M.H.; Zocca, M.B. Phenotypic and functional markers for 1alpha,25-dihydroxyvitamin D(3)-modified regulatory dendritic cells. Clin. Exp. Immunol. 2009, 157, 48–59. [Google Scholar] [CrossRef] [PubMed]
  176. Széles, L.; Keresztes, G.; Töröcsik, D.; Balajthy, Z.; Krenács, L.; Póliska, S.; Steinmeyer, A.; Zuegel, U.; Pruenster, M.; Rot, A.; et al. 1,25-dihydroxyvitamin D3 is an autonomous regulator of the transcriptional changes leading to a tolerogenic dendritic cell phenotype. J. Immunol. 2009, 182, 2074–2083. [Google Scholar] [CrossRef] [Green Version]
  177. Ferreira, G.B.; Kleijwegt, F.S.; Waelkens, E.; Lage, K.; Nikolic, T.; Hansen, D.A.; Workman, C.T.; Roep, B.O.; Overbergh, L.; Mathieu, C. Differential protein pathways in 1,25-dihydroxyvitamin d(3) and dexamethasone modulated tolerogenic human dendritic cells. J. Proteome Res. 2012, 11, 941–971. [Google Scholar] [CrossRef] [PubMed]
  178. Raïch-Regué, D.; Naranjo-Gómez, M.; Grau-López, L.; Ramo, C.; Pujol-Borrell, R.; Martínez-Cáceres, E.; Borràs, F.E. Differential effects of monophosphoryl lipid A and cytokine cocktail as maturation stimuli of immunogenic and tolerogenic dendritic cells for immunotherapy. Vaccine 2012, 30, 378–387. [Google Scholar] [CrossRef] [PubMed]
  179. Raϊch-Regué, D.; Grau-López, L.; Naranjo-Gómez, M.; Ramo-Tello, C.; Pujol-Borrell, R.; Martínez-Cáceres, E.; Borràs, F.E. Stable antigen-specific T-cell hyporesponsiveness induced by tolerogenic dendritic cells from multiple sclerosis patients. Eur. J. Immunol. 2012, 42, 771–782. [Google Scholar] [CrossRef] [PubMed]
  180. Ferreira, G.B.; Vanherwegen, A.S.; Eelen, G.; Gutiérrez, A.C.F.; Van Lommel, L.; Marchal, K.; Verlinden, L.; Verstuyf, A.; Nogueira, T.; Georgiadou, M.; et al. Vitamin D3 Induces Tolerance in Human Dendritic Cells by Activation of Intracellular Metabolic Pathways. Cell Rep. 2015, 10, 711–725. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  181. Malaguarnera, L.; Marsullo, A.; Zorena, K.; Musumeci, G.; Di Rosa, M. Vitamin D(3) regulates LAMP3 expression in monocyte derived dendritic cells. Cell. Immunol. 2017, 311, 13–21. [Google Scholar] [CrossRef]
  182. Lee, W.P.; Willekens, B.; Cras, P.; Goossens, H.; Martínez-Cáceres, E.; Berneman, Z.N.; Cools, N. Immunomodulatory Effects of 1,25-Dihydroxyvitamin D(3) on Dendritic Cells Promote Induction of T Cell Hyporesponsiveness to Myelin-Derived Antigens. J. Immunol. Res. 2016, 2016, 5392623. [Google Scholar] [CrossRef]
  183. Navarro-Barriuso, J.; Mansilla, M.J.; Quirant-Sánchez, B.; Ardiaca-Martínez, A.; Teniente-Serra, A.; Presas-Rodríguez, S.; Ten Brinke, A.; Ramo-Tello, C.; Martínez-Cáceres, E.M. MAP7 and MUCL1 Are Biomarkers of Vitamin D3-Induced Tolerogenic Dendritic Cells in Multiple Sclerosis Patients. Front. Immunol. 2019, 10, 1251. [Google Scholar] [CrossRef]
  184. Farias, A.S.; Spagnol, G.S.; Bordeaux-Rego, P.; Oliveira, C.O.; Fontana, A.G.; de Paula, R.F.; Santos, M.P.; Pradella, F.; Moraes, A.S.; Oliveira, E.C.; et al. Vitamin D3 induces IDO+ tolerogenic DCs and enhances Treg, reducing the severity of EAE. CNS Neurosci. Ther. 2013, 19, 269–277. [Google Scholar] [CrossRef]
  185. Mansilla, M.J.; Sellès-Moreno, C.; Fàbregas-Puig, S.; Amoedo, J.; Navarro-Barriuso, J.; Teniente-Serra, A.; Grau-López, L.; Ramo-Tello, C.; Martínez-Cáceres, E.M. Beneficial effect of tolerogenic dendritic cells pulsed with MOG autoantigen in experimental autoimmune encephalomyelitis. CNS Neurosci. Ther. 2015, 21, 222–230. [Google Scholar] [CrossRef]
  186. Mansilla, M.J.; Contreras-Cardone, R.; Navarro-Barriuso, J.; Cools, N.; Berneman, Z.; Ramo-Tello, C.; Martínez-Cáceres, E.M. Cryopreserved vitamin D3-tolerogenic dendritic cells pulsed with autoantigens as a potential therapy for multiple sclerosis patients. J. Neuroinflamm. 2016, 13, 113. [Google Scholar] [CrossRef] [Green Version]
  187. Tacken, P.J.; de Vries, I.J.; Torensma, R.; Figdor, C.G. Dendritic-cell immunotherapy: From ex vivo loading to in vivo targeting. Nat. Rev. Immunol. 2007, 7, 790–802. [Google Scholar] [CrossRef] [PubMed]
  188. Unger, W.W.; van Kooyk, Y. ‘Dressed for success’ C-type lectin receptors for the delivery of glyco-vaccines to dendritic cells. Curr. Opin. Immunol. 2011, 23, 131–137. [Google Scholar] [CrossRef] [PubMed]
  189. Ponsaerts, P.; Van Tendeloo, V.F.; Berneman, Z.N. Cancer immunotherapy using RNA-loaded dendritic cells. Clin. Exp. Immunol. 2003, 134, 378–384. [Google Scholar] [CrossRef] [PubMed]
  190. Boudreau, J.E.; Bonehill, A.; Thielemans, K.; Wan, Y. Engineering dendritic cells to enhance cancer immunotherapy. Mol. Ther. J. Am. Soc. Gene Ther. 2011, 19, 841–853. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  191. Shurin, M.R.; Gregory, M.; Morris, J.C.; Malyguine, A.M. Genetically modified dendritic cells in cancer immunotherapy: A better tomorrow? Expert Opin. Biol. Ther. 2010, 10, 1539–1553. [Google Scholar] [CrossRef]
  192. Cathelin, D.; Nicolas, A.; Bouchot, A.; Fraszczak, J.; Labbe, J.; Bonnotte, B. Dendritic cell-tumor cell hybrids and immunotherapy: What’s next? Cytotherapy 2011, 13, 774–785. [Google Scholar] [CrossRef]
  193. Koido, S.; Hara, E.; Homma, S.; Ohkusa, T.; Gong, J.; Tajiri, H. Cancer immunotherapy by fusions of dendritic cells and tumor cells. Immunotherapy 2009, 1, 49–62. [Google Scholar] [CrossRef] [PubMed]
  194. Connolly, N.C.; Whiteside, T.L.; Wilson, C.; Kondragunta, V.; Rinaldo, C.R.; Riddler, S.A. Therapeutic immunization with human immunodeficiency virus type 1 (HIV-1) peptide-loaded dendritic cells is safe and induces immunogenicity in HIV-1-infected individuals. Clin. Vaccine Immunol. 2008, 15, 284–292. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  195. Brody, J.D.; Engleman, E.G. DC-based cancer vaccines: Lessons from clinical trials. Cytotherapy 2004, 6, 122–127. [Google Scholar] [CrossRef]
  196. Van Tendeloo, V.F.; Ponsaerts, P.; Lardon, F.; Nijs, G.; Lenjou, M.; Van Broeckhoven, C.; Van Bockstaele, D.R.; Berneman, Z.N. Highly efficient gene delivery by mRNA electroporation in human hematopoietic cells: Superiority to lipofection and passive pulsing of mRNA and to electroporation of plasmid cDNA for tumor antigen loading of dendritic cells. Blood 2001, 98, 49–56. [Google Scholar] [CrossRef] [PubMed]
  197. Boczkowski, D.; Nair, S.K.; Snyder, D.; Gilboa, E. Dendritic cells pulsed with RNA are potent antigen-presenting cells in vitro and in vivo. J. Exp. Med. 1996, 184, 465–472. [Google Scholar] [CrossRef] [Green Version]
  198. Kavanagh, D.G.; Kaufmann, D.E.; Sunderji, S.; Frahm, N.; Le Gall, S.; Boczkowski, D.; Rosenberg, E.S.; Stone, D.R.; Johnston, M.N.; Wagner, B.S.; et al. Expansion of HIV-specific CD4+ and CD8+ T cells by dendritic cells transfected with mRNA encoding cytoplasm- or lysosome-targeted Nef. Blood 2006, 107, 1963–1969. [Google Scholar] [CrossRef] [Green Version]
  199. Melhem, N.M.; Liu, X.D.; Boczkowski, D.; Gilboa, E.; Barratt-Boyes, S.M. Robust CD4+ and CD8+ T cell responses to SIV using mRNA-transfected DC expressing autologous viral Ag. Eur. J. Immunol. 2007, 37, 2164–2173. [Google Scholar] [CrossRef]
  200. Saeboe-Larssen, S.; Fossberg, E.; Gaudernack, G. mRNA-based electrotransfection of human dendritic cells and induction of cytotoxic T lymphocyte responses against the telomerase catalytic subunit (hTERT). J. Immunol. Methods 2002, 259, 191–203. [Google Scholar] [CrossRef]
  201. Strobel, I.; Berchtold, S.; Gotze, A.; Schulze, U.; Schuler, G.; Steinkasserer, A. Human dendritic cells transfected with eiTher. RNA or DNA encoding influenza matrix protein M1 differ in their ability to stimulate cytotoxic T lymphocytes. Gene Ther. 2000, 7, 2028–2035. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  202. Steinman, R.M.; Banchereau, J. Taking dendritic cells into medicine. Nature 2007, 449, 419–426. [Google Scholar] [CrossRef]
  203. Cabezon, R.; Benitez-Ribas, D. Therapeutic potential of tolerogenic dendritic cells in IBD: From animal models to clinical application. Clin. Dev. Immunol. 2013, 2013, 789814. [Google Scholar] [CrossRef]
  204. Wculek, S.K.; Cueto, F.J.; Mujal, A.M.; Melero, I.; Krummel, M.F.; Sancho, D. Dendritic cells in cancer immunology and immunotherapy. Nat. Rev. Immunol. 2020, 20, 7–24. [Google Scholar] [CrossRef]
  205. Santos, P.M.; Butterfield, L.H. Dendritic Cell-Based Cancer Vaccines. J. Immunol. 2018, 200, 443–449. [Google Scholar] [CrossRef] [PubMed]
  206. Giannoukakis, N.; Phillips, B.; Finegold, D.; Harnaha, J.; Trucco, M. Phase I (safety) study of autologous tolerogenic dendritic cells in type 1 diabetic patients. Diabetes Care 2011, 34, 2026–2032. [Google Scholar] [CrossRef] [Green Version]
  207. Benham, H.; Nel, H.J.; Law, S.C.; Mehdi, A.M.; Street, S.; Ramnoruth, N.; Pahau, H.; Lee, B.T.; Ng, J.; Brunck, M.E.; et al. Citrullinated peptide dendritic cell immunotherapy in HLA risk genotype-positive rheumatoid arthritis patients. Sci. Transl. Med. 2015, 7, 290ra287. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  208. Jauregui-Amezaga, A.; Cabezon, R.; Ramirez-Morros, A.; Espana, C.; Rimola, J.; Bru, C.; Pino-Donnay, S.; Gallego, M.; Masamunt, M.C.; Ordas, I.; et al. Intraperitoneal Administration of Autologous Tolerogenic Dendritic Cells for Refractory Crohn’s Disease: A Phase I Study. J. Crohns Colitis 2015, 9, 1071–1078. [Google Scholar] [CrossRef] [Green Version]
  209. Suwandi, J.S.; Toes, R.E.; Nikolic, T.; Roep, B.O. Inducing tissue specific tolerance in autoimmune disease with tolerogenic dendritic cells. Clin. Exp. Rheumatol. 2015, 33, S97–S103. [Google Scholar] [PubMed]
  210. Bell, G.M.; Anderson, A.E.; Diboll, J.; Reece, R.; Eltherington, O.; Harry, R.A.; Fouweather, T.; MacDonald, C.; Chadwick, T.; McColl, E.; et al. Autologous tolerogenic dendritic cells for rheumatoid and inflammatory arthritis. Ann. Rheum. Dis. 2017, 76, 227–234. [Google Scholar] [CrossRef] [PubMed]
  211. Zarkhin, V.; Kambham, N.; Li, L.; Kwok, S.; Hsieh, S.C.; Salvatierra, O.; Sarwal, M.M. Characterization of intra-graft B cells during renal allograft rejection. Kidney Int. 2008, 74, 664–673. [Google Scholar] [CrossRef] [Green Version]
  212. Zarkhin, V.; Chalasani, G.; Sarwal, M.M. The yin and yang of B cells in graft rejection and tolerance. Transplant. Rev. 2010, 24, 67–78. [Google Scholar] [CrossRef]
  213. Barnas, J.L.; Looney, R.J.; Anolik, J.H. B cell targeted therapies in autoimmune disease. Curr. Opin. Immunol. 2019, 61, 92–99. [Google Scholar] [CrossRef]
  214. Li, R.; Patterson, K.R.; Bar-Or, A. Reassessing B cell contributions in multiple sclerosis. Nat. Immunol. 2018. [Google Scholar] [CrossRef] [PubMed]
  215. Iwata, Y.; Matsushita, T.; Horikawa, M.; Dilillo, D.J.; Yanaba, K.; Venturi, G.M.; Szabolcs, P.M.; Bernstein, S.H.; Magro, C.M.; Williams, A.D.; et al. Characterization of a rare IL-10-competent B-cell subset in humans that parallels mouse regulatory B10 cells. Blood 2011, 117, 530–541. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  216. DiLillo, D.J.; Matsushita, T.; Tedder, T.F. B10 cells and regulatory B cells balance immune responses during inflammation, autoimmunity, and cancer. Ann. N. Y. Acad. Sci. 2010, 1183, 38–57. [Google Scholar] [CrossRef]
  217. Sun, J.B.; Czerkinsky, C.; Holmgren, J. B lymphocytes treated in vitro with antigen coupled to cholera toxin B subunit induce antigen-specific Foxp3(+) regulatory T cells and protect against experimental autoimmune encephalomyelitis. J. Immunol. 2012, 188, 1686–1697. [Google Scholar] [CrossRef] [Green Version]
  218. Su, Y.; Zhang, A.H.; Li, X.; Owusu-Boaitey, N.; Skupsky, J.; Scott, D.W. B cells "transduced" with TAT-fusion proteins can induce tolerance and protect mice from diabetes and EAE. Clin. Immunol. 2011, 140, 260–267. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  219. Pennati, A.; Ng, S.; Wu, Y.; Murphy, J.R.; Deng, J.; Rangaraju, S.; Asress, S.; Blanchfield, J.L.; Evavold, B.; Galipeau, J. Regulatory B Cells Induce Formation of IL-10-Expressing T Cells in Mice with Autoimmune Neuroinflammation. J. Neurosci. 2016, 36, 12598–12610. [Google Scholar] [CrossRef] [Green Version]
  220. Zhang, A.H.; Li, X.; Onabajo, O.O.; Su, Y.; Skupsky, J.; Thomas, J.W.; Scott, D.W. B-cell delivered gene therapy for tolerance induction: Role of autoantigen-specific B cells. J. Autoimmun. 2010, 35, 107–113. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  221. Calderon-Gomez, E.; Lampropoulou, V.; Shen, P.; Neves, P.; Roch, T.; Stervbo, U.; Rutz, S.; Kuhl, A.A.; Heppner, F.L.; Loddenkemper, C.; et al. Reprogrammed quiescent B cells provide an effective cellular therapy against chronic experimental autoimmune encephalomyelitis. Eur. J. Immunol. 2011, 41, 1696–1708. [Google Scholar] [CrossRef]
  222. Yanaba, K.; Bouaziz, J.D.; Haas, K.M.; Poe, J.C.; Fujimoto, M.; Tedder, T.F. A regulatory B cell subset with a unique CD1dhiCD5+ phenotype controls T cell-dependent inflammatory responses. Immunity 2008, 28, 639–650. [Google Scholar] [CrossRef] [Green Version]
  223. Matsushita, T.; Yanaba, K.; Bouaziz, J.D.; Fujimoto, M.; Tedder, T.F. Regulatory B cells inhibit EAE initiation in mice while oTher. B cells promote disease progression. J. Clin. Investig. 2008, 118, 3420–3430. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  224. Pennati, A.; Nylen, E.A.; Duncan, I.D.; Galipeau, J. Regulatory B Cells Normalize CNS Myeloid Cell Content in a Mouse Model of Multiple Sclerosis and Promote Oligodendrogenesis and Remyelination. J. Neurosci. 2020, 40, 5105–5115. [Google Scholar] [CrossRef]
  225. Caligiuri, M.A. Human natural killer cells. Blood 2008, 112, 461–469. [Google Scholar] [CrossRef]
  226. Freud, A.G.; Mundy-Bosse, B.L.; Yu, J.; Caligiuri, M.A. The Broad Spectrum of Human Natural Killer Cell Diversity. Immunity 2017, 47, 820–833. [Google Scholar] [CrossRef] [Green Version]
  227. Vivier, E.; Tomasello, E.; Baratin, M.; Walzer, T.; Ugolini, S. Functions of natural killer cells. Nat. Immunol. 2008, 9, 503–510. [Google Scholar] [CrossRef] [PubMed]
  228. Gianchecchi, E.; Delfino, D.V.; Fierabracci, A. NK cells in autoimmune diseases: Linking innate and adaptive immune responses. Autoimmun. Rev. 2018, 17, 142–154. [Google Scholar] [CrossRef]
  229. Mimpen, M.; Smolders, J.; Hupperts, R.; Damoiseaux, J. Natural killer cells in multiple sclerosis: A review. Immunol. Lett. 2020, 222, 1–11. [Google Scholar] [CrossRef] [PubMed]
  230. Netea, M.G.; Quintin, J.; Van Der Meer, J.W. Trained Immunity: A Memory for Innate Host Defense. Cell Host Microbe 2011, 9, 355–361. [Google Scholar] [CrossRef] [Green Version]
  231. Cohan, S.L.; Lucassen, E.B.; Romba, M.C.; Linch, S.N. Daclizumab: Mechanisms of Action, Therapeutic Efficacy, Adverse Events and Its Uncovering the Potential Role of Innate Immune System Recruitment as a Treatment Strategy for Relapsing Multiple Sclerosis. Biomedicines 2019, 7, 18. [Google Scholar] [CrossRef] [Green Version]
  232. Luessi, F.; Engel, S.; Spreer, A.; Bittner, S.; Zipp, F. GFAPα IgG-associated encephalitis upon daclizumab treatment of MS. Neurol. Neuroimmunol. Neuroinflammation 2018, 5, e481. [Google Scholar] [CrossRef] [Green Version]
  233. Gold, R.; Giovannoni, G.; Selmaj, K.; Havrdova, E.; Montalban, X.; Radue, E.W.; Stefoski, D.; Robinson, R.; Riester, K.; Rana, J.; et al. Daclizumab high-yield process in relapsing-remitting multiple sclerosis (SELECT): A randomised, double-blind, placebo-controlled trial. Lancet 2013, 381, 2167–2175. [Google Scholar] [CrossRef]
  234. Kappos, L.; Wiendl, H.; Selmaj, K.; Arnold, D.L.; Havrdova, E.; Boyko, A.; Kaufman, M.; Rose, J.; Greenberg, S.; Sweetser, M.; et al. Daclizumab HYP versus Interferon Beta-1a in Relapsing Multiple Sclerosis. N. Engl. J. Med. 2015, 373, 1418–1428. [Google Scholar] [CrossRef] [PubMed]
  235. The, L. End of the road for daclizumab in multiple sclerosis. Lancet 2018, 391, 1000. [Google Scholar] [CrossRef]
  236. Shimasaki, N.; Jain, A.; Campana, D. NK cells for cancer immunotherapy. Nat. Rev. Drug Discov. 2020, 19, 200–218. [Google Scholar] [CrossRef] [PubMed]
  237. Fang, F.; Xiao, W.; Tian, Z. NK cell-based immunotherapy for cancer. Semin Immunol. 2017, 31, 37–54. [Google Scholar] [CrossRef] [PubMed]
  238. Hegde, S.; Fox, L.; Wang, X.; Gumperz, J.E. Autoreactive natural killer T cells: Promoting immune protection and immune tolerance through varied interactions with myeloid antigen-presenting cells. Immunology 2010, 130, 471–483. [Google Scholar] [CrossRef]
  239. Pratschke, J.; Stauch, D.; Kotsch, K. Role of NK and NKT cells in solid organ transplantation. Transpl. Int. 2009, 22, 859–868. [Google Scholar] [CrossRef]
  240. Wu, L.; Van Kaer, L. Natural killer T cells and autoimmune disease. Curr. Mol. Med. 2009, 9, 4–14. [Google Scholar] [CrossRef]
  241. Kriegsmann, K.; Kriegsmann, M.; von Bergwelt-Baildon, M.; Cremer, M.; Witzens-Harig, M. NKT cells—New players in CAR cell immunotherapy? Eur. J. Haematol. 2018, 101, 750–757. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  242. Sakuishi, K.; Miyake, S.; Yamamura, T. Role of NK cells and invariant NKT cells in multiple sclerosis. Results Probl. Cell Differ. 2010, 51, 127–147. [Google Scholar] [CrossRef]
  243. Van Kaer, L.; Wu, L. Therapeutic Potential of Invariant Natural Killer T Cells in Autoimmunity. Front. Immunol. 2018, 9, 519. [Google Scholar] [CrossRef] [Green Version]
  244. Van Kaer, L.; Wu, L.; Parekh, V.V. Natural killer T cells in multiple sclerosis and its animal model, experimental autoimmune encephalomyelitis. Immunology 2015, 146, 1–10. [Google Scholar] [CrossRef] [Green Version]
  245. Exley, M.A.; Wilson, S.B.; Balk, S.P. Isolation and Functional Use of Human NKT Cells. Curr. Protoc. Immunol. 2017, 119, 14.11.11–14.11.20. [Google Scholar] [CrossRef] [PubMed]
  246. Ma, H.; Xia, C.Q. Phenotypic and Functional Diversities of Myeloid-Derived Suppressor Cells in Autoimmune Diseases. Mediators Inflamm. 2018, 2018, 4316584. [Google Scholar] [CrossRef]
  247. Wegner, A.; Verhagen, J.; Wraith, D.C. Myeloid-derived suppressor cells mediate tolerance induction in autoimmune disease. Immunology 2017, 151, 26–42. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  248. Veglia, F.; Perego, M.; Gabrilovich, D. Myeloid-derived suppressor cells coming of age. Nat. Immunol. 2018, 19, 108–119. [Google Scholar] [CrossRef] [PubMed]
  249. Bronte, V.; Brandau, S.; Chen, S.H.; Colombo, M.P.; Frey, A.B.; Greten, T.F.; Mandruzzato, S.; Murray, P.J.; Ochoa, A.; Ostrand-Rosenberg, S.; et al. Recommendations for myeloid-derived suppressor cell nomenclature and characterization standards. Nat. Commun. 2016, 7, 12150. [Google Scholar] [CrossRef] [Green Version]
  250. Iacobaeus, E.; Douagi, I.; Jitschin, R.; Marcusson-Stahl, M.; Andren, A.T.; Gavin, C.; Lefsihane, K.; Davies, L.C.; Mougiakakos, D.; Kadri, N.; et al. Phenotypic and functional alterations of myeloid-derived suppressor cells during the disease course of multiple sclerosis. Immunol. Cell Biol. 2018. [Google Scholar] [CrossRef]
  251. Casacuberta-Serra, S.; Costa, C.; Eixarch, H.; Mansilla, M.J.; Lopez-Estevez, S.; Martorell, L.; Pares, M.; Montalban, X.; Espejo, C.; Barquinero, J. Myeloid-derived suppressor cells expressing a self-antigen ameliorate experimental autoimmune encephalomyelitis. Exp. Neurol. 2016, 286, 50–60. [Google Scholar] [CrossRef] [PubMed]
  252. Miller, S.D.; Turley, D.M.; Podojil, J.R. Antigen-specific tolerance strategies for the prevention and treatment of autoimmune disease. Nat. Rev. Immunol. 2007, 7, 665–677. [Google Scholar] [CrossRef]
  253. Smith, C.E.; Miller, S.D. Multi-peptide coupled-cell tolerance ameliorates ongoing relapsing EAE associated with multiple pathogenic autoreactivities. J. Autoimmun. 2006, 27, 218–231. [Google Scholar] [CrossRef] [Green Version]
  254. Turley, D.M.; Miller, S.D. Peripheral tolerance induction using ethylenecarbodiimide-fixed APCs uses both direct and indirect mechanisms of antigen presentation for prevention of experimental autoimmune encephalomyelitis. J. Immunol. 2007, 178, 2212–2220. [Google Scholar] [CrossRef] [Green Version]
  255. Lutterotti, A.; Sospedra, M.; Martin, R. Antigen-specific therapies in MS—Current concepts and novel approaches. J. Neurol. Sci. 2008, 274, 18–22. [Google Scholar] [CrossRef]
  256. Pishesha, N.; Bilate, A.M.; Wibowo, M.C.; Huang, N.J.; Li, Z.; Deshycka, R.; Bousbaine, D.; Li, H.; Patterson, H.C.; Dougan, S.K.; et al. Engineered erythrocytes covalently linked to antigenic peptides can protect against autoimmune disease. Proc. Natl. Acad. Sci. USA 2017, 114, 3157–3162. [Google Scholar] [CrossRef] [Green Version]
  257. Lutterotti, A.; Ludersdorer, T.; Docampo, M.; Hohmann, M.; Moreno, C.S.; Hayward-Koennecke, H.; Pfender, N.; Schauer, K.; Jelcic, I.; Foege, M. Establish tolerence in MS with myelin-peptide coupled red blood cells-ETIMS (red) trial. Mult. Scler. J. 2018, 24, 275–276. [Google Scholar]
  258. Malik, N. Allogeneic versus autologous stem-cell therapy: A comparison of manufacturing costs and commercialization challenges. BioPharm Int. 2012, 25, 36–40. [Google Scholar]
  259. Snowden, J.A.; Saccardi, R.; Allez, M.; Ardizzone, S.; Arnold, R.; Cervera, R.; Denton, C.; Hawkey, C.; Labopin, M.; Mancardi, G.; et al. Haematopoietic SCT in severe autoimmune diseases: Updated guidelines of the European Group for Blood and Marrow Transplantation. Bone Marrow Transplant. 2012, 47, 770–790. [Google Scholar] [CrossRef] [Green Version]
  260. Majhail, N.S.; Farnia, S.H.; Carpenter, P.A.; Champlin, R.E.; Crawford, S.; Marks, D.I.; Omel, J.L.; Orchard, P.J.; Palmer, J.; Saber, W.; et al. Indications for Autologous and Allogeneic Hematopoietic Cell Transplantation: Guidelines from the American Society for Blood and Marrow Transplantation. Biol. Blood Marrow Transplant. 2015, 21, 1863–1869. [Google Scholar] [CrossRef] [Green Version]
  261. Morell, P.; Quarles, R.H. Characteristic Composition of Myelin. In Basic Neurochemistry: Molecular, Cellular and Medical Aspects, 6th ed.; Siegel, G.J., Agranoff, B.W., Albers, R.W., Fisher, S.K., Uhler, M.D., Eds.; Lippincott-Raven: Philadelphia, PA, USA, 1999. [Google Scholar]
  262. Hohlfeld, R.; Dornmair, K.; Meinl, E.; Wekerle, H. The search for the target antigens of multiple sclerosis, part 1: Autoreactive CD4+ T lymphocytes as pathogenic effectors and therapeutic targets. Lancet Neurol. 2015. [Google Scholar] [CrossRef]
  263. Rangachari, M.; Kuchroo, V.K. Using EAE to better understand principles of immune function and autoimmune pathology. J. Autoimmun. 2013, 45, 31–39. [Google Scholar] [CrossRef] [Green Version]
  264. Greer, J.M. Autoimmune T-cell reactivity to myelin proteolipids and glycolipids in multiple sclerosis. Mult. Scler. Int. 2013, 2013, 151427. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  265. Saez-Torres, I.; Brieva, L.; Espejo, C.; Barrau, M.A.; Montalban, X.; Martinez-Caceres, E.M. Specific proliferation towards myelin antigens in patients with multiple sclerosis during a relapse. Autoimmunity 2002, 35, 45–50. [Google Scholar] [CrossRef]
  266. Streeter, H.B.; Rigden, R.; Martin, K.F.; Scolding, N.J.; Wraith, D.C. Preclinical development and first-in-human study of ATX-MS-1467 for immunotherapy of MS. Neurol. Neuroimmunol. Neuroinflamm. 2015, 2, e93. [Google Scholar] [CrossRef] [Green Version]
  267. Walczak, A.; Siger, M.; Ciach, A.; Szczepanik, M.; Selmaj, K. Transdermal application of myelin peptides in multiple sclerosis treatment. JAMA Neurol. 2013, 70, 1105–1109. [Google Scholar] [CrossRef]
  268. Warren, K.G.; Catz, I. Administration of myelin basic protein synthetic peptides to multiple sclerosis patients. J. Neurol. Sci. 1995, 133, 85–94. [Google Scholar] [CrossRef]
  269. Weiner, H.L.; Mackin, G.A.; Matsui, M.; Orav, E.J.; Khoury, S.J.; Dawson, D.M.; Hafler, D.A. Double-blind pilot trial of oral tolerization with myelin antigens in multiple sclerosis. Science 1993, 259, 1321–1324. [Google Scholar] [CrossRef] [PubMed]
  270. Goebels, N.; Hofstetter, H.; Schmidt, S.; Brunner, C.; Wekerle, H.; Hohlfeld, R. Repertoire dynamics of autoreactive T cells in multiple sclerosis patients and healthy subjects: Epitope spreading versus clonal persistence. Brain 2000, 123 Pt 3, 508–518. [Google Scholar] [CrossRef] [Green Version]
  271. Tuohy, V.K.; Kinkel, R.P. Epitope spreading: A mechanism for progression of autoimmune disease. Arch. Immunol. Ther. Exp. 2000, 48, 347–351. [Google Scholar]
  272. Tuohy, V.K.; Yu, M.; Yin, L.; Kawczak, J.A.; Johnson, J.M.; Mathisen, P.M.; Weinstock-Guttman, B.; Kinkel, R.P. The epitope spreading cascade during progression of experimental autoimmune encephalomyelitis and multiple sclerosis. Immunol. Rev. 1998, 164, 93–100. [Google Scholar] [CrossRef]
  273. Anderton, S.M.; Viner, N.J.; Matharu, P.; Lowrey, P.A.; Wraith, D.C. Influence of a dominant cryptic epitope on autoimmune T cell tolerance. Nat. Immunol. 2002, 3, 175–181. [Google Scholar] [CrossRef]
  274. Kappos, L.; Radue, E.W.; O’Connor, P.; Polman, C.; Hohlfeld, R.; Calabresi, P.; Selmaj, K.; Agoropoulou, C.; Leyk, M.; Zhang-Auberson, L.; et al. A placebo-controlled trial of oral fingolimod in relapsing multiple sclerosis. N. Engl. J. Med. 2010, 362, 387–401. [Google Scholar] [CrossRef] [Green Version]
  275. Sallusto, F.; Lanzavecchia, A. The instructive role of dendritic cells on T-cell responses. Arthritis Res. 2002, 4 (Suppl. 3), S127–S132. [Google Scholar] [CrossRef]
  276. Steinman, R.M. Dendritic cells and the control of immunity: Enhancing the efficiency of antigen presentation. Mt. Sinai J. Med. 2001, 68, 160–166. [Google Scholar]
  277. Sagar, D.; Foss, C.; El Baz, R.; Pomper, M.G.; Khan, Z.K.; Jain, P. Mechanisms of dendritic cell trafficking across the blood-brain barrier. J. Neuroimmune Pharmacol. 2012, 7, 74–94. [Google Scholar] [CrossRef] [Green Version]
  278. Lopes Pinheiro, M.A.; Kooij, G.; Mizee, M.R.; Kamermans, A.; Enzmann, G.; Lyck, R.; Schwaninger, M.; Engelhardt, B.; de Vries, H.E. Immune cell trafficking across the barriers of the central nervous system in multiple sclerosis and stroke. Biochim. Biophys. Acta 2016, 1862, 461–471. [Google Scholar] [CrossRef]
  279. Sabado, R.L.; Balan, S.; Bhardwaj, N. Dendritic cell-based immunotherapy. Cell Res. 2017, 27, 74–95. [Google Scholar] [CrossRef] [Green Version]
  280. Mohammad, M.G.; Hassanpour, M.; Tsai, V.W.; Li, H.; Ruitenberg, M.J.; Booth, D.W.; Serrats, J.; Hart, P.H.; Symonds, G.P.; Sawchenko, P.E.; et al. Dendritic cells and multiple sclerosis: Disease, tolerance and therapy. Int. J. Mol. Sci. 2012, 14, 547–562. [Google Scholar] [CrossRef] [Green Version]
  281. Ballabh, P.; Braun, A.; Nedergaard, M. The blood-brain barrier: An overview: Structure, regulation, and clinical implications. Neurobiol. Dis. 2004, 16, 1–13. [Google Scholar] [CrossRef]
  282. de Vries, H.E.; Kuiper, J.; de Boer, A.G.; Van Berkel, T.J.; Breimer, D.D. The blood-brain barrier in neuroinflammatory diseases. Pharmacol. Rev. 1997, 49, 143–155. [Google Scholar]
  283. Pardridge, W.M. The blood-brain barrier: Bottleneck in brain drug development. NeuroRx 2005, 2, 3–14. [Google Scholar] [CrossRef]
  284. He, Q.; Liu, J.; Liang, J.; Liu, X.; Li, W.; Liu, Z.; Ding, Z.; Tuo, D. Towards Improvements for Penetrating the Blood-Brain Barrier-Recent Progress from a Material and Pharmaceutical Perspective. Cells 2018, 7, 24. [Google Scholar] [CrossRef] [Green Version]
  285. Teo, G.S.; Ankrum, J.A.; Martinelli, R.; Boetto, S.E.; Simms, K.; Sciuto, T.E.; Dvorak, A.M.; Karp, J.M.; Carman, C.V. Mesenchymal stem cells transmigrate between and directly through tumor necrosis factor-alpha-activated endothelial cells via both leukocyte-like and novel mechanisms. Stem Cells 2012, 30, 2472–2486. [Google Scholar] [CrossRef] [Green Version]
  286. Colton, C.A. Immune heterogeneity in neuroinflammation: Dendritic cells in the brain. J. Neuroimmune Pharmacol. 2013, 8, 145–162. [Google Scholar] [CrossRef]
  287. Ukena, S.N.; Höpting, M.; Velaga, S.; Ivanyi, P.; Grosse, J.; Baron, U.; Ganser, A.; Franzke, A. Isolation strategies of regulatory T cells for clinical trials: Phenotype, function, stability, and expansion capacity. Exp. Hematol. 2011, 39, 1152–1160. [Google Scholar] [CrossRef]
  288. Rice, C.M.; Kemp, K.; Wilkins, A.; Scolding, N.J. Cell therapy for multiple sclerosis: An evolving concept with implications for oTher. neurodegenerative diseases. Lancet 2013, 382, 1204–1213. [Google Scholar] [CrossRef]
  289. Liu, L.; Eckert, M.A.; Riazifar, H.; Kang, D.K.; Agalliu, D.; Zhao, W. From blood to the brain: Can systemically transplanted mesenchymal stem cells cross the blood-brain barrier? Stem Cells Int. 2013, 2013, 435093. [Google Scholar] [CrossRef]
  290. Sonar, S.A.; Lal, G. Differentiation and Transmigration of CD4 T Cells in Neuroinflammation and Autoimmunity. Front. Immunol. 2017, 8, 1695. [Google Scholar] [CrossRef] [Green Version]
  291. Meena, M.; Cools, N. On the road to new treatments for multiple sclerosis: Targeting dendritic cell migration into the central nervous system. Neural Regen Res. 2019, 14, 2088–2090. [Google Scholar] [CrossRef] [PubMed]
  292. Matsushita, T.; Kibayashi, T.; Katayama, T.; Yamashita, Y.; Suzuki, S.; Kawamata, J.; Honmou, O.; Minami, M.; Shimohama, S. Mesenchymal stem cells transmigrate across brain microvascular endothelial cell monolayers through transiently formed inter-endothelial gaps. Neurosci. Lett. 2011, 502, 41–45. [Google Scholar] [CrossRef]
  293. Schneider-Hohendorf, T.; Stenner, M.P.; Weidenfeller, C.; Zozulya, A.L.; Simon, O.J.; Schwab, N.; Wiendl, H. Regulatory T cells exhibit enhanced migratory characteristics, a feature impaired in patients with multiple sclerosis. Eur. J. Immunol. 2010, 40, 3581–3590. [Google Scholar] [CrossRef]
  294. Takeshita, Y.; Ransohoff, R.M. Inflammatory cell trafficking across the blood-brain barrier: Chemokine regulation and in vitro models. Immunol. Rev. 2012, 248, 228–239. [Google Scholar] [CrossRef] [Green Version]
  295. Chamberlain, G.; Smith, H.; Rainger, G.E.; Middleton, J. Mesenchymal stem cells exhibit firm adhesion, crawling, spreading and transmigration across aortic endothelial cells: Effects of chemokines and shear. PLoS ONE 2011, 6, e25663. [Google Scholar] [CrossRef]
  296. Ding, Y.; Xu, J.; Bromberg, J.S. Regulatory T cell migration during an immune response. Trends Immunol. 2012, 33, 174–180. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  297. Engelhardt, B.; Ransohoff, R.M. Capture, crawl, cross: The T cell code to breach the blood-brain barriers. Trends Immunol. 2012, 33, 579–589. [Google Scholar] [CrossRef] [PubMed]
  298. Worbs, T.; Hammerschmidt, S.I.; Förster, R. Dendritic cell migration in health and disease. Nat. Rev. Immunol. 2017, 17, 30–48. [Google Scholar] [CrossRef] [PubMed]
  299. Feger, U.; Luther, C.; Poeschel, S.; Melms, A.; Tolosa, E.; Wiendl, H. Increased frequency of CD4(+) CD25(+) regulatory T cells in the cerebrospinal fluid but not in the blood of multiple sclerosis patients. Clin. Exp. Immunol. 2007, 147, 412–418. [Google Scholar] [CrossRef] [PubMed]
  300. Zozulya, A.L.; Wiendl, H. The role of regulatory T cells in multiple sclerosis. Nat. Clin. Pract. Neurol. 2008, 4, 384–398. [Google Scholar] [CrossRef] [PubMed]
  301. Michel, L.; Berthelot, L.; Pettre, S.; Wiertlewski, S.; Lefrere, F.; Braudeau, C.; Brouard, S.; Soulillou, J.P.; Laplaud, D.A. Patients with relapsing-remitting multiple sclerosis have normal Treg function when cells expressing IL-7 receptor alpha-chain are excluded from the analysis. J. Clin. Investig. 2008, 118, 3411–3419. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  302. Wei, S.; Kryczek, I.; Zou, W. Regulatory T-cell compartmentalization and trafficking. Blood 2006, 108, 426–431. [Google Scholar] [CrossRef] [Green Version]
  303. Tiberio, L.; Del Prete, A.; Schioppa, T.; Sozio, F.; Bosisio, D.; Sozzani, S. Chemokine and chemotactic signals in dendritic cell migration. Cell. Mol. Immunol. 2018, 15, 346–352. [Google Scholar] [CrossRef]
  304. De Laere, M.; Derdelinckx, J.; Hassi, M.; Kerosalo, M.; Oravamäki, H.; Van den Bergh, J.; Berneman, Z.; Cools, N. Shuttling Tolerogenic Dendritic Cells across the Blood-Brain Barrier In Vitro via the Introduction of De Novo C-C Chemokine Receptor 5 Expression Using Messenger RNA Electroporation. Front. Immunol. 2017, 8, 1964. [Google Scholar] [CrossRef] [Green Version]
  305. Kim, J.E.; Kalimuthu, S.; Ahn, B.C. In vivo cell tracking with bioluminescence imaging. Nucl. Med. Mol. Imaging 2015, 49, 3–10. [Google Scholar] [CrossRef] [Green Version]
  306. Wang, H.; Cao, F.; De, A.; Cao, Y.; Contag, C.; Gambhir, S.S.; Wu, J.C.; Chen, X. Trafficking mesenchymal stem cell engraftment and differentiation in tumor-bearing mice by bioluminescence imaging. Stem Cells 2009, 27, 1548–1558. [Google Scholar] [CrossRef] [Green Version]
  307. Kleinovink, J.W.; Mezzanotte, L.; Zambito, G.; Fransen, M.F.; Cruz, L.J.; Verbeek, J.S.; Chan, A.; Ossendorp, F.; Löwik, C. A Dual-Color Bioluminescence Reporter Mouse for Simultaneous in vivo Imaging of T Cell Localization and Function. Front. Immunol. 2018, 9, 3097. [Google Scholar] [CrossRef] [PubMed]
  308. Maes, W.; Deroose, C.; Reumers, V.; Krylyshkina, O.; Gijsbers, R.; Baekelandt, V.; Ceuppens, J.; Debyser, Z.; Van Gool, S.W. In vivo bioluminescence imaging in an experimental mouse model for dendritic cell based immunotherapy against malignant glioma. J. Neuro-Oncol. 2009, 91, 127–139. [Google Scholar] [CrossRef] [PubMed]
  309. Ben-Hur, T. Cell therapy for multiple sclerosis. Neurotherapeutics 2011, 8, 625–642. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  310. Høglund, R.A.; Holmøy, T.; Harbo, H.F.; Maghazachi, A.A. A one year follow-up study of natural killer and dendritic cells activities in multiple sclerosis patients receiving glatiramer acetate (GA). PLoS ONE 2013, 8, e62237. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  311. Kivisäkk, P.; Francois, K.; Mbianda, J.; Gandhi, R.; Weiner, H.L.; Khoury, S.J. Effect of natalizumab treatment on circulating plasmacytoid dendritic cells: A cross-sectional observational study in patients with multiple sclerosis. PLoS ONE 2014, 9, e103716. [Google Scholar] [CrossRef] [Green Version]
  312. Quillien, V.; Moisan, A.; Carsin, A.; Lesimple, T.; Lefeuvre, C.; Adamski, H.; Bertho, N.; Devillers, A.; Leberre, C.; Toujas, L. Biodistribution of radiolabelled human dendritic cells injected by various routes. Eur. J. Nucl. Med. Mol. Imaging 2005, 32, 731–741. [Google Scholar] [CrossRef]
  313. Lesterhuis, W.J.; de Vries, I.J.; Schreibelt, G.; Lambeck, A.J.; Aarntzen, E.H.; Jacobs, J.F.; Scharenborg, N.M.; van de Rakt, M.W.; de Boer, A.J.; Croockewit, S.; et al. Route of administration modulates the induction of dendritic cell vaccine-induced antigen-specific T cells in advanced melanoma patients. Clin. Cancer Res. 2011, 17, 5725–5735. [Google Scholar] [CrossRef] [Green Version]
  314. Passerini, L.; Barzaghi, F.; Curto, R.; Sartirana, C.; Barera, G.; Tucci, F.; Albarello, L.; Mariani, A.; Testoni, P.A.; Bazzigaluppi, E.; et al. Treatment with rapamycin can restore regulatory T-cell function in IPEX patients. J. Allergy Clin. Immunol. 2020, 145, 1262–1271. [Google Scholar] [CrossRef]
  315. Stallone, G.; Pontrelli, P.; Infante, B.; Gigante, M.; Netti, G.S.; Ranieri, E.; Grandaliano, G.; Gesualdo, L. Rapamycin induces ILT3highILT4high dendritic cells promoting a new immunoregulatory pathway. Kidney Int. 2014, 85, 888–897. [Google Scholar] [CrossRef] [Green Version]
  316. Dai, L.; Zhang, R.; Wang, Z.; He, Y.; Bai, X.; Zhu, M.; Yu, Z.; Ruan, C.-g. Efficacy of immunomodulatory therapy with all-trans retinoid acid in adult patients with chronic immune thrombocytopenia. Thromb. Res. 2016, 140, 73–80. [Google Scholar] [CrossRef] [PubMed]
  317. Fruhwirth, G.O.; Kneilling, M.; de Vries, I.J.M.; Weigelin, B.; Srinivas, M.; Aarntzen, E. The Potential of In Vivo Imaging for Optimization of Molecular and Cellular Anti-cancer Immunotherapies. Mol. Imaging Biol. 2018, 20, 696–704. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  318. Zhou, Y.; Graves, J.S.; Simpson, S., Jr.; Charlesworth, J.C.; Mei, I.V.; Waubant, E.; Barcellos, L.F.; Belman, A.; Krupp, L.; Lucas, R.; et al. Genetic variation in the gene LRP2 increases relapse risk in multiple sclerosis. J. Neurol. Neurosurg. Psychiatry 2017, 88, 864–868. [Google Scholar] [CrossRef]
  319. Graves, J.S.; Barcellos, L.F.; Simpson, S.; Belman, A.; Lin, R.; Taylor, B.V.; Ponsonby, A.L.; Dwyer, T.; Krupp, L.; Waubant, E.; et al. The multiple sclerosis risk allele within the AHI1 gene is associated with relapses in children and adults. Mult. Scler. Relat. Disord. 2018, 19, 161–165. [Google Scholar] [CrossRef]
  320. Hilven, K.; Vandebergh, M.; Smets, I.; Mallants, K.; Goris, A.; Dubois, B. Genetic basis for relapse rate in multiple sclerosis: Association with LRP2 genetic variation. Mult. Scler. 2018. [Google Scholar] [CrossRef]
  321. Didonna, A.; Oksenberg, J.R. The Genetics of Multiple Sclerosis. In Multiple Sclerosis: Perspectives in Treatment and Pathogenesis; Zagon, I.S., McLaughlin, J.P.J., Eds.; Codon Publications: Brisbane, Australia, 2017. [Google Scholar] [CrossRef] [Green Version]
  322. Johnson, M.C.; Pierson, E.R.; Spieker, A.J.; Nielsen, A.S.; Posso, S.; Kita, M.; Buckner, J.H.; Goverman, J.M. Distinct T cell signatures define subsets of patients with multiple sclerosis. Neurol. Neuroimmunol. Neuroinflamm. 2016, 3, e278. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  323. Disanto, G.; Berlanga, A.J.; Handel, A.E.; Para, A.E.; Burrell, A.M.; Fries, A.; Handunnetthi, L.; De Luca, G.C.; Morahan, J.M. Heterogeneity in multiple sclerosis: Scratching the surface of a complex disease. Autoimmune Dis. 2010, 2011, 932351. [Google Scholar] [CrossRef] [Green Version]
  324. Dubuisson, N.; Puentes, F.; Giovannoni, G.; Gnanapavan, S. Science is 1% inspiration and 99% biomarkers. Mult. Scler. 2017, 23, 1442–1452. [Google Scholar] [CrossRef] [Green Version]
  325. Chalmer, T.A.; Baggesen, L.M.; Norgaard, M.; Koch-Henriksen, N.; Magyari, M.; Sorensen, P.S. Early versus later treatment start in multiple sclerosis: A register-based cohort study. Eur. J. Neurol. 2018. [Google Scholar] [CrossRef]
  326. Rae-Grant, A.; Day, G.S.; Marrie, R.A.; Rabinstein, A.; Cree, B.A.C.; Gronseth, G.S.; Haboubi, M.; Halper, J.; Hosey, J.P.; Jones, D.E.; et al. Practice guideline recommendations summary: Disease-modifying therapies for adults with multiple sclerosis: Report of the Guideline Development, Dissemination, and Implementation Subcommittee of the American Academy of Neurology. Neurology 2018, 90, 777–788. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  327. Comi, G.; Radaelli, M.; Soelberg Sorensen, P. Evolving concepts in the treatment of relapsing multiple sclerosis. Lancet 2017, 389, 1347–1356. [Google Scholar] [CrossRef]
  328. Willekens, B.; Wens, I.; Wouters, K.; Cras, P.; Cools, N. Safety and immunological proof-of-concept following treatment with tolerance-inducing cell products in patients with autoimmune diseases or receiving organ transplantation: A systematic review and meta-analysis of clinical trials. Autoimmun. Rev. 2021. [Google Scholar] [CrossRef] [PubMed]
  329. Dombrowski, Y.; O’Hagan, T.; Dittmer, M.; Penalva, R.; Mayoral, S.R.; Bankhead, P.; Fleville, S.; Eleftheriadis, G.; Zhao, C.; Naughton, M.; et al. Regulatory T cells promote myelin regeneration in the central nervous system. Nat. Neurosci. 2017, 20, 674–680. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  330. Miron, V.E. Beyond immunomodulation: The regenerative role for regulatory T cells in central nervous system remyelination. J. Cell Commun. Signal. 2017, 11, 191–192. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Figure 1. Autologous cell-based tolerance-inducing treatments in multiple sclerosis (MS). This schematic overview depicts the various modes of action implemented by cell-based tolerance-inducing treatments in MS. Additionally shown are the indirect tolerance-inducing strategies by means of inducing a regulatory phenotype in naïve T cells or by peptide-coupled fixed peripheral blood mononuclear cells and erythrocytes. Tolerance induction results in cytolysis, alteration in immune function and/or metabolic disruption of the target autoreactive T cells. The black arrows represent the functional influence. Abbreviations used: Breg: regulatory B cells; CTLA-4: cytotoxic T lymphocyte-associated antigen 4; HSC: haemopoietic stem cells; MHC: major histocompatibility complex; MSC: mesenchymal stromal cells; NKT: natural killer T cells; NK: natural killer cells; PBMC: peripheral blood mononuclear cells; RBC: erythrocytes; Treg: regulatory T cells; TCR: T cell receptor; tolDC: tolerogenic dendritic cells. Created with BioRender.com, accessed date 13 July 2021.
Figure 1. Autologous cell-based tolerance-inducing treatments in multiple sclerosis (MS). This schematic overview depicts the various modes of action implemented by cell-based tolerance-inducing treatments in MS. Additionally shown are the indirect tolerance-inducing strategies by means of inducing a regulatory phenotype in naïve T cells or by peptide-coupled fixed peripheral blood mononuclear cells and erythrocytes. Tolerance induction results in cytolysis, alteration in immune function and/or metabolic disruption of the target autoreactive T cells. The black arrows represent the functional influence. Abbreviations used: Breg: regulatory B cells; CTLA-4: cytotoxic T lymphocyte-associated antigen 4; HSC: haemopoietic stem cells; MHC: major histocompatibility complex; MSC: mesenchymal stromal cells; NKT: natural killer T cells; NK: natural killer cells; PBMC: peripheral blood mononuclear cells; RBC: erythrocytes; Treg: regulatory T cells; TCR: T cell receptor; tolDC: tolerogenic dendritic cells. Created with BioRender.com, accessed date 13 July 2021.
Ijms 22 07536 g001
Figure 2. Schematic overview of current cell-based tolerance-inducing treatments for multiple sclerosis (MS) in the clinic. Summary of the results on the feasibility, tolerability, safety and efficiency of cell-based tolerance-inducing treatments that are currently being investigated in different clinical trials is given. Abbreviations used: HSC: haemopoietic stem cells; MSC: mesenchymal stromal cells; PBMC: peripheral blood mononuclear cells; RBC: erythrocytes; Treg: regulatory T cells; tolDC: tolerogenic dendritic cells. Created with BioRender.com, accessed date 13 July 2021.
Figure 2. Schematic overview of current cell-based tolerance-inducing treatments for multiple sclerosis (MS) in the clinic. Summary of the results on the feasibility, tolerability, safety and efficiency of cell-based tolerance-inducing treatments that are currently being investigated in different clinical trials is given. Abbreviations used: HSC: haemopoietic stem cells; MSC: mesenchymal stromal cells; PBMC: peripheral blood mononuclear cells; RBC: erythrocytes; Treg: regulatory T cells; tolDC: tolerogenic dendritic cells. Created with BioRender.com, accessed date 13 July 2021.
Ijms 22 07536 g002
Table 1. Clinical trials in multiple sclerosis (MS) patients. All clinical trials using haematopoietic stem cells (HSC), mesenchymal stem cells (MSC), regulatory T cells (Treg), tolerogenic dendritic cells (tolDC), peptide-coupled peripheral blood mononuclear cells (PBMC) and peptide-coupled erythrocytes (RBC) in MS. A search was conducted in ClinicalTrials.gov on the 16th of June 2021.
Table 1. Clinical trials in multiple sclerosis (MS) patients. All clinical trials using haematopoietic stem cells (HSC), mesenchymal stem cells (MSC), regulatory T cells (Treg), tolerogenic dendritic cells (tolDC), peptide-coupled peripheral blood mononuclear cells (PBMC) and peptide-coupled erythrocytes (RBC) in MS. A search was conducted in ClinicalTrials.gov on the 16th of June 2021.
IDPhaseDesignStatusCell TypeRouteAdministration SchemeRef.
HSCNCT00278655IISingle group assignment, open labelTerminatedAutologous haematopoietic stem cell transplantationNot providedSingle infusionN/A
NCT01099930IISingle group assignment, open labelCompletedAutologous haematopoietic stem cell transplantationIntravenousSingle infusion[40]
NCT00342134IINot providedCompletedAutologous haematopoietic stem cell transplantationIntravenousSingle infusionN/A
NCT00014755INot providedCompletedSyngeneic or autologous haematopoietic stem cell transplantationNot providedSingle infusion[36]
NCT00288626IISingle group assignment, open labelCompletedAutologous haematopoietic stem cell transplantationNot providedSingle infusion[41]
NCT00040482IISingle group assignment, open labelCompletedAutologous haematopoietic stem cell transplantationNot providedSingle infusionN/A
NCT01679041IISingle group assignment, open labelTerminatedAutologous haematopoietic stem cell transplantationNot providedSingle infusionN/A
NCT00017628INot providedCompletedAutologous haematopoietic stem cell transplantationNot providedSingle infusionN/A
NCT00273364IIParallel assignment, open labelCompletedAutologous haematopoietic stem cell transplantationNot providedSingle infusion[43]
NCT00497952I/IISingle group assignment, open labelActive, not recruitingAllogenic haematopoietic stem cell transplantationIntravenousSingle infusionN/A
NCT02674217N/ASingle group assignment, open labelActive, enrolling by invitationAutologous haematopoietic stem cell transplantationNot providedSingle infusion[45]
NCT03113162ISingle group assignment, open labelActive, recruitingAutologous haematopoietic stem cell transplantationIntravenousSingle infusionN/A
NCT03477500IIIParallel assignment, open labelActive, recruitingAutologous haematopoietic stem cell transplantationNot providedSingle infusionN/A
NCT03342638IIIParallel assignment, open labelTerminatedAutologous haematopoietic stem cell transplantationIntravenousSingle infusionN/A
NCT04047628IIIParallel assignment, open labelActive, recruitingAutologous haematopoietic stem cell transplantationNot providedSingle infusionN/A
MSCNCT01377870I/IIRandomised, double-blind, placebo-controlledCompletedAutologous bone marrow-derived mesenchymal stem cellsIntravenousSingle infusionN/A
NCT02326935IOpen-labelTerminatedAutologous adipose-derived mesenchymal cellsIntravenousSingle infusionN/A
NCT01895439I/IIaOpen-labelCompletedAutologous bone marrow-derived mesenchymal stem cellsIntrathecalNot providedN/A
NCT02034188I/IIOpen-labelCompletedUmbilical cord-derived mesenchymal stem cellsIntravenous7 doses[46]
NCT01606215I/IIPlacebo-controlled crossover studyCompletedAutologous bone marrow-derived mesenchymal stem cellsIntravenousSingle infusion[47]
NCT02035514I/IICrossover designCompletedAutologous bone marrow-derived mesenchymal stem cellsIntravenousSingle infusion[47]
NCT01228266IIRandomised double-blind, placebo-controlled crossover studyTerminatedAutologous mesenchymal stem cell transplantationIntravenousSingle infusion[48]
NCT00395200I/IIaOpen-labelCompletedAutologous bone marrow-derived mesenchymal stem cellsIntravenousSingle infusion[49]
NCT02418351I/IIOpen-label, non-randomisedTerminatedAutologous bone marrow-derived mononuclear stem cellsIntravenousSingle infusionN/A
NCT00813969IOpen-labelRecruitment completedAutologous mesenchymal stem cellMSC transplantationSingle infusion[50]
NCT02418325I/IIOpen-label, non-randomisedTerminatedAllogeneic human umbilical cord tissue-derived mesenchymal stem cellsIntravenousSingle infusionN/A
NCT01056471I/IITriple-blind, randomised, placebo-controlledRecruitment completedAutologous mesenchymal stem cells from adipose tissueIntravenousSingle infusion[51]
NCT03069170IOpen-labelActiveAutologous bone marrow-derived mesenchymal stem cellsIntravenous/intrathecalSingle infusionN/A
NCT02403947I//INot providedActiveAutologous mesenchymal stem cell transplantationIntravenousNot provided[47]
NCT03326505I/IIRandomised, single-blindCompletedUmbilical cord-derived mesenchymal stem cellsIntrathecalSingle infusion[52]
NCT01745783I/IIMulticentre, randomised, crossover, double-blind, placebo-controlledActive, recruitingAutologous bone marrow-derived mesenchymal stem cellsIntravenousNot provided[47]
NCT02495766I/IIRandomised, cross-over, placebo-controlledCompletedCryopreserved autologous adult bone-marrow mesenchymal stromal cellsIntravenousSingle infusionN/A
NCT02239393IIRandomised, double-blind, cross-over, placebo-controlledTerminatedAutologous mesenchymal stem cell transplantationIntravenousSingle infusion[47]
NCT01815632IIBlinded, randomised, cross-over designUnknownAutologous bone marrow-derived cellular therapyIntravenousSingle infusion[53]
NCT01854957I/IIDouble-blinded, randomised, cross-over designUnknownAutologous mesenchymal stem cellsIntravenousSingle infusion[47]
NCT01730547I/IIDouble-blinded, randomised, cross-over designUnknownAutologous mesenchymal stromal cellsIntravenousNot provided[47]
NCT02166021IIRandomised, cross-over, placebo-controlledCompletedAutologous mesenchymal bone marrow stem cellsIntravenous/intrathecalDouble infusion[54]
NCT00781872I/IISingle group assignment, open labelCompletedAutologous bone marrow derived mesenchymal stem cellsIntravenous/intrathecalSingle infusion[55]
NCT01932593IISingle group assignment, double-blindedCompletedAutologous bone marrow cellsIntravenousReinfusion[56]
NCT01364246I/IISingle group assignment, open labelUnknownUmbilical cord mesenchymal stem cellsNot providedNot providedN/A
TregEudraCT 2014-004320-22Ib/IIaParallel assignment, open labelCompletedPolyclonal CD4+CD25hiCD127FoxP3+ TregsIntravenous/intrathecalSingle infusion[57]
tolDCNCT02283671IbSingle group assignment, open labelCompletedDexamethasone-tolDC loaded with a pool of myelin peptidesIntravenousDose-escalation, 3 injections: bi-weekly[58]
NCT02618902I/IIaParallel assignment, open labelActive, not recruitingVitD3-tolDCs loaded with a pool of myelin peptidesIntradermalDose-escalation, 6 injections: 4 bi-weekly and 2 monthly[59]
NCT02903537I/IIaParallel assignment, open labelRecruitingVitD3-tolDCs loaded with a pool of myelin peptidesIntranodalDose-escalation, 6 injections: 4 bi-weekly and 2 monthly[59]
Peptide-coupled PBMCNCT01414634I/IIaParallel assignment, open labelCompletedMyelin-peptide coupled autologous PBMCIntravenousDose-escalation, single infusion[60]
Peptide-coupled RBCETIMSREDIbParallel assignment, open labelCompletedMyelin-peptide coupled erythrocytesIntravenousDose-escalation, single infusion[61]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Wens, I.; Janssens, I.; Derdelinckx, J.; Meena, M.; Willekens, B.; Cools, N. Made to Measure: Patient-Tailored Treatment of Multiple Sclerosis Using Cell-Based Therapies. Int. J. Mol. Sci. 2021, 22, 7536. https://doi.org/10.3390/ijms22147536

AMA Style

Wens I, Janssens I, Derdelinckx J, Meena M, Willekens B, Cools N. Made to Measure: Patient-Tailored Treatment of Multiple Sclerosis Using Cell-Based Therapies. International Journal of Molecular Sciences. 2021; 22(14):7536. https://doi.org/10.3390/ijms22147536

Chicago/Turabian Style

Wens, Inez, Ibo Janssens, Judith Derdelinckx, Megha Meena, Barbara Willekens, and Nathalie Cools. 2021. "Made to Measure: Patient-Tailored Treatment of Multiple Sclerosis Using Cell-Based Therapies" International Journal of Molecular Sciences 22, no. 14: 7536. https://doi.org/10.3390/ijms22147536

APA Style

Wens, I., Janssens, I., Derdelinckx, J., Meena, M., Willekens, B., & Cools, N. (2021). Made to Measure: Patient-Tailored Treatment of Multiple Sclerosis Using Cell-Based Therapies. International Journal of Molecular Sciences, 22(14), 7536. https://doi.org/10.3390/ijms22147536

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop